fix: add missing import for backend.server.v2.llm.routes

Was removed in earlier commit but still used in include_router.
Caused AttributeError on server startup.

.claude/skills/backend-check/SKILL.md

@@ -0,0 +1,17 @@
+---
+name: backend-check
+description: Run the full backend formatting, linting, and test suite. Ensures code quality before commits and PRs. TRIGGER when backend Python code has been modified and needs validation.
+user-invocable: true
+metadata:
+  author: autogpt-team
+  version: "1.0.0"
+---
+
+# Backend Check
+
+## Steps
+
+1. **Format**: `poetry run format` — runs formatting AND linting. NEVER run ruff/black/isort individually
+2. **Fix** any remaining errors manually, re-run until clean
+3. **Test**: `poetry run test` (runs DB setup + pytest). For specific files: `poetry run pytest -s -vvv <test_files>`
+4. **Snapshots** (if needed): `poetry run pytest path/to/test.py --snapshot-update` — review with `git diff`

.claude/skills/code-style/SKILL.md

@@ -0,0 +1,35 @@
+---
+name: code-style
+description: Python code style preferences for the AutoGPT backend. Apply when writing or reviewing Python code. TRIGGER when writing new Python code, reviewing PRs, or refactoring backend code.
+user-invocable: false
+metadata:
+  author: autogpt-team
+  version: "1.0.0"
+---
+
+# Code Style
+
+## Imports
+
+- **Top-level only** — no local/inner imports. Move all imports to the top of the file.
+
+## Typing
+
+- **No duck typing** — avoid `hasattr`, `getattr`, `isinstance` for type dispatch. Use proper typed interfaces, unions, or protocols.
+- **Pydantic models** over dataclass, namedtuple, or raw dict for structured data.
+- **No linter suppressors** — avoid `# type: ignore`, `# noqa`, `# pyright: ignore` etc. 99% of the time the right fix is fixing the type/code, not silencing the tool.
+
+## Code Structure
+
+- **List comprehensions** over manual loop-and-append.
+- **Early return** — guard clauses first, avoid deep nesting.
+- **Flatten inline** — prefer short, concise expressions. Reduce `if/else` chains with direct returns or ternaries when readable.
+- **Modular functions** — break complex logic into small, focused functions rather than long blocks with nested conditionals.
+
+## Review Checklist
+
+Before finishing, always ask:
+- Can any function be split into smaller pieces?
+- Is there unnecessary nesting that an early return would eliminate?
+- Can any loop be a comprehension?
+- Is there a simpler way to express this logic?

.claude/skills/frontend-check/SKILL.md

@@ -0,0 +1,16 @@
+---
+name: frontend-check
+description: Run the full frontend formatting, linting, and type checking suite. Ensures code quality before commits and PRs. TRIGGER when frontend TypeScript/React code has been modified and needs validation.
+user-invocable: true
+metadata:
+  author: autogpt-team
+  version: "1.0.0"
+---
+
+# Frontend Check
+
+## Steps (in order)
+
+1. **Format**: `pnpm format` — NEVER run individual formatters
+2. **Lint**: `pnpm lint` — fix errors, re-run until clean
+3. **Types**: `pnpm types` — if it keeps failing after multiple attempts, stop and ask the user

.claude/skills/new-block/SKILL.md

@@ -0,0 +1,29 @@
+---
+name: new-block
+description: Create a new backend block following the Block SDK Guide. Guides through provider configuration, schema definition, authentication, and testing. TRIGGER when user asks to create a new block, add a new integration, or build a new node for the graph editor.
+user-invocable: true
+metadata:
+  author: autogpt-team
+  version: "1.0.0"
+---
+
+# New Block Creation
+
+Read `docs/platform/block-sdk-guide.md` first for the full guide.
+
+## Steps
+
+1. **Provider config** (if external service): create `_config.py` with `ProviderBuilder`
+2. **Block file** in `backend/blocks/` (from `autogpt_platform/backend/`):
+   - Generate a UUID once with `uuid.uuid4()`, then **hard-code that string** as `id` (IDs must be stable across imports)
+   - `Input(BlockSchema)` and `Output(BlockSchema)` classes
+   - `async def run` that `yield`s output fields
+3. **Files**: use `store_media_file()` with `"for_block_output"` for outputs
+4. **Test**: `poetry run pytest 'backend/blocks/test/test_block.py::test_available_blocks[MyBlock]' -xvs`
+5. **Format**: `poetry run format`
+
+## Rules
+
+- Analyze interfaces: do inputs/outputs connect well with other blocks in a graph?
+- Use top-level imports, avoid duck typing
+- Always use `for_block_output` for block outputs

.claude/skills/openapi-regen/SKILL.md

@@ -0,0 +1,28 @@
+---
+name: openapi-regen
+description: Regenerate the OpenAPI spec and frontend API client. Starts the backend REST server, fetches the spec, and regenerates the typed frontend hooks. TRIGGER when API routes change, new endpoints are added, or frontend API types are stale.
+user-invocable: true
+metadata:
+  author: autogpt-team
+  version: "1.0.0"
+---
+
+# OpenAPI Spec Regeneration
+
+## Steps
+
+1. **Run end-to-end** in a single shell block (so `REST_PID` persists):
+   ```bash
+   cd autogpt_platform/backend && poetry run rest &
+   REST_PID=$!
+   WAIT=0; until curl -sf http://localhost:8006/health > /dev/null 2>&1; do sleep 1; WAIT=$((WAIT+1)); [ $WAIT -ge 60 ] && echo "Timed out" && kill $REST_PID && exit 1; done
+   cd ../frontend && pnpm generate:api:force
+   kill $REST_PID
+   pnpm types && pnpm lint && pnpm format
+   ```
+
+## Rules
+
+- Always use `pnpm generate:api:force` (not `pnpm generate:api`)
+- Don't manually edit files in `src/app/api/__generated__/`
+- Generated hooks follow: `use{Method}{Version}{OperationName}`

.claude/skills/pr-create/SKILL.md

@@ -0,0 +1,31 @@
+---
+name: pr-create
+description: Create a pull request for the current branch. TRIGGER when user asks to create a PR, open a pull request, push changes for review, or submit work for merging.
+user-invocable: true
+metadata:
+  author: autogpt-team
+  version: "1.0.0"
+---
+
+# Create Pull Request
+
+## Steps
+
+1. **Check for existing PR**: `gh pr view --json url -q .url 2>/dev/null` — if a PR already exists, output its URL and stop
+2. **Understand changes**: `git status`, `git diff dev...HEAD`, `git log dev..HEAD --oneline`
+3. **Read PR template**: `.github/PULL_REQUEST_TEMPLATE.md`
+4. **Draft PR title**: Use conventional commits format (see CLAUDE.md for types and scopes)
+5. **Fill out PR template** as the body — be thorough in the Changes section
+6. **Format first** (if relevant changes exist):
+   - Backend: `cd autogpt_platform/backend && poetry run format`
+   - Frontend: `cd autogpt_platform/frontend && pnpm format`
+   - Fix any lint errors, then commit formatting changes before pushing
+7. **Push**: `git push -u origin HEAD`
+8. **Create PR**: `gh pr create --base dev`
+9. **Output** the PR URL
+
+## Rules
+
+- Always target `dev` branch
+- Do NOT run tests — CI will handle that
+- Use the PR template from `.github/PULL_REQUEST_TEMPLATE.md`

.claude/skills/pr-review/SKILL.md

@@ -0,0 +1,51 @@
+---
+name: pr-review
+description: Address all open PR review comments systematically. Fetches comments, addresses each one, reacts +1/-1, and replies when clarification is needed. Keeps iterating until all comments are addressed and CI is green. TRIGGER when user shares a PR URL, asks to address review comments, fix PR feedback, or respond to reviewer comments.
+user-invocable: true
+metadata:
+  author: autogpt-team
+  version: "1.0.0"
+---
+
+# PR Review Comment Workflow
+
+## Steps
+
+1. **Find PR**: `gh pr list --head $(git branch --show-current) --repo Significant-Gravitas/AutoGPT`
+2. **Fetch comments** (all three sources):
+   - `gh api repos/Significant-Gravitas/AutoGPT/pulls/{N}/reviews` (top-level reviews)
+   - `gh api repos/Significant-Gravitas/AutoGPT/pulls/{N}/comments` (inline review comments)
+   - `gh api repos/Significant-Gravitas/AutoGPT/issues/{N}/comments` (PR conversation comments)
+3. **Skip** comments already reacted to by PR author
+4. **For each unreacted comment**:
+   - Read referenced code, make the fix (or reply if you disagree/need info)
+   - **Inline review comments** (`pulls/{N}/comments`):
+     - React: `gh api repos/.../pulls/comments/{ID}/reactions -f content="+1"` (or `-1`)
+     - Reply: `gh api repos/.../pulls/{N}/comments/{ID}/replies -f body="..."`
+   - **PR conversation comments** (`issues/{N}/comments`):
+     - React: `gh api repos/.../issues/comments/{ID}/reactions -f content="+1"` (or `-1`)
+     - No threaded replies — post a new issue comment if needed
+   - **Top-level reviews**: no reaction API — address in code, reply via issue comment if needed
+5. **Include autogpt-reviewer bot fixes** too
+6. **Format**: `cd autogpt_platform/backend && poetry run format`, `cd autogpt_platform/frontend && pnpm format`
+7. **Commit & push**
+8. **Re-fetch comments** immediately — address any new unreacted ones before waiting on CI
+9. **Stay productive while CI runs** — don't idle. In priority order:
+   - Run any pending local tests (`poetry run pytest`, e2e, etc.) and fix failures
+   - Address any remaining comments
+   - Only poll `gh pr checks {N}` as the last resort when there's truly nothing left to do
+10. **If CI fails** — fix, go back to step 6
+11. **Re-fetch comments again** after CI is green — address anything that appeared while CI was running
+12. **Done** only when: all comments reacted AND CI is green.
+
+## CRITICAL: Do Not Stop
+
+**Loop is: address → format → commit → push → re-check comments → run local tests → wait CI → re-check comments → repeat.**
+
+Never idle. If CI is running and you have nothing to address, run local tests. Waiting on CI is the last resort.
+
+## Rules
+
+- One todo per comment
+- For inline review comments: reply on existing threads. For PR conversation comments: post a new issue comment (API doesn't support threaded replies)
+- React to every comment: +1 addressed, -1 disagreed (with explanation)

.claude/skills/worktree-setup/SKILL.md

@@ -0,0 +1,45 @@
+---
+name: worktree-setup
+description: Set up a new git worktree for parallel development. Creates the worktree, copies .env files, installs dependencies, generates Prisma client, and optionally starts the app (with port conflict resolution) or runs tests. TRIGGER when user asks to set up a worktree, work on a branch in isolation, or needs a separate environment for a branch or PR.
+user-invocable: true
+metadata:
+  author: autogpt-team
+  version: "1.0.0"
+---
+
+# Worktree Setup
+
+## Preferred: Use Branchlet
+
+The repo has a `.branchlet.json` config — it handles env file copying, dependency installation, and Prisma generation automatically.
+
+```bash
+npm install -g branchlet                                      # install once
+branchlet create -n <name> -s <source-branch> -b <new-branch>
+branchlet list --json   # list all worktrees
+```
+
+## Manual Fallback
+
+If branchlet isn't available:
+
+1. `git worktree add ../<RepoName><N> <branch-name>`
+2. Copy `.env` files: `backend/.env`, `frontend/.env`, `autogpt_platform/.env`, `db/docker/.env`
+3. Install deps:
+   - `cd autogpt_platform/backend && poetry install && poetry run prisma generate`
+   - `cd autogpt_platform/frontend && pnpm install`
+
+## Running the App
+
+Free ports first — backend uses: 8001, 8002, 8003, 8005, 8006, 8007, 8008.
+
+```bash
+for port in 8001 8002 8003 8005 8006 8007 8008; do
+  lsof -ti :$port | xargs kill -9 2>/dev/null || true
+done
+cd <worktree>/autogpt_platform/backend && poetry run app
+```
+
+## CoPilot Testing Gotcha
+
+SDK mode spawns a Claude subprocess — **won't work inside Claude Code**. Set `CHAT_USE_CLAUDE_AGENT_SDK=false` in `backend/.env` to use baseline mode.

autogpt_platform/backend/backend/api/conn_manager.py

@@ -122,6 +122,24 @@ class ConnectionManager:
 
         return len(connections)
 
+    async def broadcast_to_all(self, *, method: WSMethod, data: dict) -> int:
+        """Broadcast a message to all active websocket connections."""
+        message = WSMessage(
+            method=method,
+            data=data,
+        ).model_dump_json()
+
+        connections = tuple(self.active_connections)
+        if not connections:
+            return 0
+
+        await asyncio.gather(
+            *(connection.send_text(message) for connection in connections),
+            return_exceptions=True,
+        )
+
+        return len(connections)
+
     async def _subscribe(self, channel_key: str, websocket: WebSocket) -> str:
         if channel_key not in self.subscriptions:
             self.subscriptions[channel_key] = set()

autogpt_platform/backend/backend/api/external/v1/routes.py

@@ -1,7 +1,7 @@
 import logging
 import urllib.parse
 from collections import defaultdict
-from typing import Annotated, Any, Literal, Optional, Sequence
+from typing import Annotated, Any, Optional, Sequence
 
 from fastapi import APIRouter, Body, HTTPException, Security
 from prisma.enums import AgentExecutionStatus, APIKeyPermission
@@ -9,9 +9,10 @@ from pydantic import BaseModel, Field
 from typing_extensions import TypedDict
 
 import backend.api.features.store.cache as store_cache
+import backend.api.features.store.db as store_db
 import backend.api.features.store.model as store_model
 import backend.blocks
-from backend.api.external.middleware import require_permission
+from backend.api.external.middleware import require_auth, require_permission
 from backend.data import execution as execution_db
 from backend.data import graph as graph_db
 from backend.data import user as user_db
@@ -230,13 +231,13 @@ async def get_graph_execution_results(
 @v1_router.get(
     path="/store/agents",
     tags=["store"],
-    dependencies=[Security(require_permission(APIKeyPermission.READ_STORE))],
+    dependencies=[Security(require_auth)],  # data is public; auth required as anti-DDoS
     response_model=store_model.StoreAgentsResponse,
 )
 async def get_store_agents(
     featured: bool = False,
     creator: str | None = None,
-    sorted_by: Literal["rating", "runs", "name", "updated_at"] | None = None,
+    sorted_by: store_db.StoreAgentsSortOptions | None = None,
     search_query: str | None = None,
     category: str | None = None,
     page: int = 1,
@@ -278,7 +279,7 @@ async def get_store_agents(
 @v1_router.get(
     path="/store/agents/{username}/{agent_name}",
     tags=["store"],
-    dependencies=[Security(require_permission(APIKeyPermission.READ_STORE))],
+    dependencies=[Security(require_auth)],  # data is public; auth required as anti-DDoS
     response_model=store_model.StoreAgentDetails,
 )
 async def get_store_agent(
@@ -306,13 +307,13 @@ async def get_store_agent(
 @v1_router.get(
     path="/store/creators",
     tags=["store"],
-    dependencies=[Security(require_permission(APIKeyPermission.READ_STORE))],
+    dependencies=[Security(require_auth)],  # data is public; auth required as anti-DDoS
     response_model=store_model.CreatorsResponse,
 )
 async def get_store_creators(
     featured: bool = False,
     search_query: str | None = None,
-    sorted_by: Literal["agent_rating", "agent_runs", "num_agents"] | None = None,
+    sorted_by: store_db.StoreCreatorsSortOptions | None = None,
     page: int = 1,
     page_size: int = 20,
 ) -> store_model.CreatorsResponse:
@@ -348,7 +349,7 @@ async def get_store_creators(
 @v1_router.get(
     path="/store/creators/{username}",
     tags=["store"],
-    dependencies=[Security(require_permission(APIKeyPermission.READ_STORE))],
+    dependencies=[Security(require_auth)],  # data is public; auth required as anti-DDoS
     response_model=store_model.CreatorDetails,
 )
 async def get_store_creator(

autogpt_platform/backend/backend/api/features/admin/execution_analytics_routes.py

@@ -8,6 +8,7 @@ from fastapi import APIRouter, HTTPException, Security
 from pydantic import BaseModel, Field
 
 from backend.blocks.llm import LlmModel
+from backend.data import llm_registry
 from backend.data.analytics import (
     AccuracyTrendsResponse,
     get_accuracy_trends_and_alerts,
@@ -18,6 +19,7 @@ from backend.data.execution import (
     get_graph_executions,
     update_graph_execution_stats,
 )
+from backend.server.v2.llm import db as llm_db
 from backend.data.model import GraphExecutionStats
 from backend.executor.activity_status_generator import (
     DEFAULT_SYSTEM_PROMPT,
@@ -176,30 +178,55 @@ async def get_execution_analytics_config(
         # Return with provider prefix for clarity
         return f"{provider_name}: {model_name}"
 
-    # Include all LlmModel values (no more filtering by hardcoded list)
-    recommended_model = LlmModel.GPT4O_MINI.value
-    for model in LlmModel:
+    # Get all models from the registry (dynamic, not hardcoded enum)
+    # Get the recommended model from the database (configurable via admin UI)
+    recommended_model_slug = await llm_db.get_recommended_model_slug()
+
+    # Build the available models list
+    first_enabled_slug = None
+    for registry_model in llm_registry.iter_dynamic_models():
+        # Only include enabled models in the list
+        if not registry_model.is_enabled:
+            continue
+
+        # Track first enabled model as fallback
+        if first_enabled_slug is None:
+            first_enabled_slug = registry_model.slug
+
+        model = LlmModel(registry_model.slug)
         label = generate_model_label(model)
         # Add "(Recommended)" suffix to the recommended model
-        if model.value == recommended_model:
+        if registry_model.slug == recommended_model_slug:
             label += " (Recommended)"
 
         available_models.append(
             ModelInfo(
-                value=model.value,
+                value=registry_model.slug,
                 label=label,
-                provider=model.provider,
+                provider=registry_model.metadata.provider,
             )
         )
 
     # Sort models by provider and name for better UX
     available_models.sort(key=lambda x: (x.provider, x.label))
 
+    # Handle case where no models are available
+    if not available_models:
+        logger.warning(
+            "No enabled LLM models found in registry. "
+            "Ensure models are configured and enabled in the LLM Registry."
+        )
+        # Return empty list - frontend will handle empty state appropriately
+        # Self-hosters should run database migrations to seed default models
+
+    # Use the DB recommended model, or fallback to first enabled model
+    final_recommended = recommended_model_slug or first_enabled_slug or ""
+
     return ExecutionAnalyticsConfig(
         available_models=available_models,
         default_system_prompt=DEFAULT_SYSTEM_PROMPT,
         default_user_prompt=DEFAULT_USER_PROMPT,
-        recommended_model=recommended_model,
+        recommended_model=final_recommended,
     )
 
 

autogpt_platform/backend/backend/api/features/admin/llm_routes.py

@@ -0,0 +1,599 @@
+import logging
+
+import autogpt_libs.auth
+import fastapi
+
+from backend.api.features.builder import db as builder_db
+from backend.api.features.v1 import _get_cached_blocks
+from backend.blocks._base import BlockSchema
+from backend.data import llm_registry
+from backend.data.block_cost_config import refresh_llm_costs
+from backend.data.llm_registry import publish_registry_refresh_notification
+from backend.data.llm_registry.registry import _fetch_registry_from_db
+from backend.server.v2.llm import db as llm_db
+from backend.server.v2.llm import model as llm_model
+
+logger = logging.getLogger(__name__)
+
+router = fastapi.APIRouter(
+    tags=["llm", "admin"],
+    dependencies=[fastapi.Security(autogpt_libs.auth.requires_admin_user)],
+)
+
+
+async def _refresh_runtime_state() -> None:
+    """Refresh the LLM registry and clear all related caches to ensure real-time updates."""
+    logger.info("Refreshing LLM registry runtime state...")
+    try:
+        _fetch_registry_from_db.cache_clear()
+        logger.debug("Cleared Redis cache for LLM registry")
+
+        # Refresh registry from database
+        await llm_registry.refresh_llm_registry()
+        await refresh_llm_costs()
+
+        # Clear block schema caches so they're regenerated with updated model options
+        BlockSchema.clear_all_schema_caches()
+        logger.info("Cleared all block schema caches")
+
+        # Clear the /blocks endpoint cache so frontend gets updated schemas
+        try:
+            _get_cached_blocks.cache_clear()
+            logger.info("Cleared /blocks endpoint cache")
+        except Exception as e:
+            logger.warning("Failed to clear /blocks cache: %s", e)
+
+        # Clear the v2 builder caches
+        try:
+            builder_db._get_all_providers.cache_clear()
+            logger.info("Cleared v2 builder providers cache")
+            builder_db._build_cached_search_results.cache_clear()
+            logger.info("Cleared v2 builder search results cache")
+            builder_db._get_llm_models.cache_clear()
+            logger.info("Cleared v2 builder LLM models cache")
+        except Exception as e:
+            logger.debug("Could not clear v2 builder cache: %s", e)
+
+        # Fetch fresh data for notification (now contains updated data from DB)
+        models_data = await _fetch_registry_from_db()
+
+        await publish_registry_refresh_notification(models_data=models_data)
+        logger.info(
+            "Published registry refresh notification with %d models", len(models_data)
+        )
+    except Exception as exc:
+        logger.exception(
+            "LLM runtime state refresh failed; caches may be stale: %s", exc
+        )
+
+
+@router.get(
+    "/providers",
+    summary="List LLM providers",
+    response_model=llm_model.LlmProvidersResponse,
+)
+async def list_llm_providers(include_models: bool = True):
+    providers = await llm_db.list_providers(include_models=include_models)
+    return llm_model.LlmProvidersResponse(providers=providers)
+
+
+@router.post(
+    "/providers",
+    summary="Create LLM provider",
+    response_model=llm_model.LlmProvider,
+)
+async def create_llm_provider(request: llm_model.UpsertLlmProviderRequest):
+    provider = await llm_db.upsert_provider(request=request)
+    await _refresh_runtime_state()
+    return provider
+
+
+@router.patch(
+    "/providers/{provider_id}",
+    summary="Update LLM provider",
+    response_model=llm_model.LlmProvider,
+)
+async def update_llm_provider(
+    provider_id: str,
+    request: llm_model.UpsertLlmProviderRequest,
+):
+    provider = await llm_db.upsert_provider(request=request, provider_id=provider_id)
+    await _refresh_runtime_state()
+    return provider
+
+
+@router.delete(
+    "/providers/{provider_id}",
+    summary="Delete LLM provider",
+    response_model=dict,
+)
+async def delete_llm_provider(provider_id: str):
+    """
+    Delete an LLM provider.
+
+    A provider can only be deleted if it has no associated models.
+    Delete all models from the provider first before deleting the provider.
+    """
+    try:
+        await llm_db.delete_provider(provider_id)
+        await _refresh_runtime_state()
+        logger.info("Deleted LLM provider '%s'", provider_id)
+        return {"success": True, "message": "Provider deleted successfully"}
+    except ValueError as e:
+        logger.warning("Failed to delete provider '%s': %s", provider_id, e)
+        raise fastapi.HTTPException(status_code=400, detail=str(e))
+    except Exception as e:
+        logger.exception("Failed to delete provider '%s': %s", provider_id, e)
+        raise fastapi.HTTPException(status_code=500, detail=str(e))
+
+
+@router.get(
+    "/models",
+    summary="List LLM models",
+    response_model=llm_model.LlmModelsResponse,
+)
+async def list_llm_models(
+    provider_id: str | None = fastapi.Query(default=None),
+    page: int = fastapi.Query(default=1, ge=1, description="Page number (1-indexed)"),
+    page_size: int = fastapi.Query(
+        default=50, ge=1, le=100, description="Number of models per page"
+    ),
+):
+    return await llm_db.list_models(
+        provider_id=provider_id, page=page, page_size=page_size
+    )
+
+
+@router.post(
+    "/models",
+    summary="Create LLM model",
+    response_model=llm_model.LlmModel,
+)
+async def create_llm_model(request: llm_model.CreateLlmModelRequest):
+    model = await llm_db.create_model(request=request)
+    await _refresh_runtime_state()
+    return model
+
+
+@router.patch(
+    "/models/{model_id}",
+    summary="Update LLM model",
+    response_model=llm_model.LlmModel,
+)
+async def update_llm_model(
+    model_id: str,
+    request: llm_model.UpdateLlmModelRequest,
+):
+    model = await llm_db.update_model(model_id=model_id, request=request)
+    await _refresh_runtime_state()
+    return model
+
+
+@router.patch(
+    "/models/{model_id}/toggle",
+    summary="Toggle LLM model availability",
+    response_model=llm_model.ToggleLlmModelResponse,
+)
+async def toggle_llm_model(
+    model_id: str,
+    request: llm_model.ToggleLlmModelRequest,
+):
+    """
+    Toggle a model's enabled status, optionally migrating workflows when disabling.
+
+    If disabling a model and `migrate_to_slug` is provided, all workflows using
+    this model will be migrated to the specified replacement model before disabling.
+    A migration record is created which can be reverted later using the revert endpoint.
+
+    Optional fields:
+    - `migration_reason`: Reason for the migration (e.g., "Provider outage")
+    - `custom_credit_cost`: Custom pricing override for billing during migration
+    """
+    try:
+        result = await llm_db.toggle_model(
+            model_id=model_id,
+            is_enabled=request.is_enabled,
+            migrate_to_slug=request.migrate_to_slug,
+            migration_reason=request.migration_reason,
+            custom_credit_cost=request.custom_credit_cost,
+        )
+        await _refresh_runtime_state()
+        if result.nodes_migrated > 0:
+            logger.info(
+                "Toggled model '%s' to %s and migrated %d nodes to '%s' (migration_id=%s)",
+                result.model.slug,
+                "enabled" if request.is_enabled else "disabled",
+                result.nodes_migrated,
+                result.migrated_to_slug,
+                result.migration_id,
+            )
+        return result
+    except ValueError as exc:
+        logger.warning("Model toggle validation failed: %s", exc)
+        raise fastapi.HTTPException(status_code=400, detail=str(exc)) from exc
+    except Exception as exc:
+        logger.exception("Failed to toggle LLM model %s: %s", model_id, exc)
+        raise fastapi.HTTPException(
+            status_code=500,
+            detail="Failed to toggle model availability",
+        ) from exc
+
+
+@router.get(
+    "/models/{model_id}/usage",
+    summary="Get model usage count",
+    response_model=llm_model.LlmModelUsageResponse,
+)
+async def get_llm_model_usage(model_id: str):
+    """Get the number of workflow nodes using this model."""
+    try:
+        return await llm_db.get_model_usage(model_id=model_id)
+    except ValueError as exc:
+        raise fastapi.HTTPException(status_code=404, detail=str(exc)) from exc
+    except Exception as exc:
+        logger.exception("Failed to get model usage %s: %s", model_id, exc)
+        raise fastapi.HTTPException(
+            status_code=500,
+            detail="Failed to get model usage",
+        ) from exc
+
+
+@router.delete(
+    "/models/{model_id}",
+    summary="Delete LLM model and migrate workflows",
+    response_model=llm_model.DeleteLlmModelResponse,
+)
+async def delete_llm_model(
+    model_id: str,
+    replacement_model_slug: str | None = fastapi.Query(
+        default=None,
+        description="Slug of the model to migrate existing workflows to (required only if workflows use this model)",
+    ),
+):
+    """
+    Delete a model and optionally migrate workflows using it to a replacement model.
+
+    If no workflows are using this model, it can be deleted without providing a
+    replacement. If workflows exist, replacement_model_slug is required.
+
+    This endpoint:
+    1. Counts how many workflow nodes use the model being deleted
+    2. If nodes exist, validates the replacement model and migrates them
+    3. Deletes the model record
+    4. Refreshes all caches and notifies executors
+
+    Example: DELETE /api/llm/admin/models/{id}?replacement_model_slug=gpt-4o
+    Example (no usage): DELETE /api/llm/admin/models/{id}
+    """
+    try:
+        result = await llm_db.delete_model(
+            model_id=model_id, replacement_model_slug=replacement_model_slug
+        )
+        await _refresh_runtime_state()
+        logger.info(
+            "Deleted model '%s' and migrated %d nodes to '%s'",
+            result.deleted_model_slug,
+            result.nodes_migrated,
+            result.replacement_model_slug,
+        )
+        return result
+    except ValueError as exc:
+        # Validation errors (model not found, replacement invalid, etc.)
+        logger.warning("Model deletion validation failed: %s", exc)
+        raise fastapi.HTTPException(status_code=400, detail=str(exc)) from exc
+    except Exception as exc:
+        logger.exception("Failed to delete LLM model %s: %s", model_id, exc)
+        raise fastapi.HTTPException(
+            status_code=500,
+            detail="Failed to delete model and migrate workflows",
+        ) from exc
+
+
+# ============================================================================
+# Migration Management Endpoints
+# ============================================================================
+
+
+@router.get(
+    "/migrations",
+    summary="List model migrations",
+    response_model=llm_model.LlmMigrationsResponse,
+)
+async def list_llm_migrations(
+    include_reverted: bool = fastapi.Query(
+        default=False, description="Include reverted migrations in the list"
+    ),
+):
+    """
+    List all model migrations.
+
+    Migrations are created when disabling a model with the migrate_to_slug option.
+    They can be reverted to restore the original model configuration.
+    """
+    try:
+        migrations = await llm_db.list_migrations(include_reverted=include_reverted)
+        return llm_model.LlmMigrationsResponse(migrations=migrations)
+    except Exception as exc:
+        logger.exception("Failed to list migrations: %s", exc)
+        raise fastapi.HTTPException(
+            status_code=500,
+            detail="Failed to list migrations",
+        ) from exc
+
+
+@router.get(
+    "/migrations/{migration_id}",
+    summary="Get migration details",
+    response_model=llm_model.LlmModelMigration,
+)
+async def get_llm_migration(migration_id: str):
+    """Get details of a specific migration."""
+    try:
+        migration = await llm_db.get_migration(migration_id)
+        if not migration:
+            raise fastapi.HTTPException(
+                status_code=404, detail=f"Migration '{migration_id}' not found"
+            )
+        return migration
+    except fastapi.HTTPException:
+        raise
+    except Exception as exc:
+        logger.exception("Failed to get migration %s: %s", migration_id, exc)
+        raise fastapi.HTTPException(
+            status_code=500,
+            detail="Failed to get migration",
+        ) from exc
+
+
+@router.post(
+    "/migrations/{migration_id}/revert",
+    summary="Revert a model migration",
+    response_model=llm_model.RevertMigrationResponse,
+)
+async def revert_llm_migration(
+    migration_id: str,
+    request: llm_model.RevertMigrationRequest | None = None,
+):
+    """
+    Revert a model migration, restoring affected workflows to their original model.
+
+    This only reverts the specific nodes that were part of the migration.
+    The source model must exist for the revert to succeed.
+
+    Options:
+    - `re_enable_source_model`: Whether to re-enable the source model if disabled (default: True)
+
+    Response includes:
+    - `nodes_reverted`: Number of nodes successfully reverted
+    - `nodes_already_changed`: Number of nodes that were modified since migration (not reverted)
+    - `source_model_re_enabled`: Whether the source model was re-enabled
+
+    Requirements:
+    - Migration must not already be reverted
+    - Source model must exist
+    """
+    try:
+        re_enable = request.re_enable_source_model if request else True
+        result = await llm_db.revert_migration(
+            migration_id,
+            re_enable_source_model=re_enable,
+        )
+        await _refresh_runtime_state()
+        logger.info(
+            "Reverted migration '%s': %d nodes restored from '%s' to '%s' "
+            "(%d already changed, source re-enabled=%s)",
+            migration_id,
+            result.nodes_reverted,
+            result.target_model_slug,
+            result.source_model_slug,
+            result.nodes_already_changed,
+            result.source_model_re_enabled,
+        )
+        return result
+    except ValueError as exc:
+        logger.warning("Migration revert validation failed: %s", exc)
+        raise fastapi.HTTPException(status_code=400, detail=str(exc)) from exc
+    except Exception as exc:
+        logger.exception("Failed to revert migration %s: %s", migration_id, exc)
+        raise fastapi.HTTPException(
+            status_code=500,
+            detail="Failed to revert migration",
+        ) from exc
+
+
+# ============================================================================
+# Creator Management Endpoints
+# ============================================================================
+
+
+@router.get(
+    "/creators",
+    summary="List model creators",
+    response_model=llm_model.LlmCreatorsResponse,
+)
+async def list_llm_creators():
+    """
+    List all model creators.
+
+    Creators are organizations that create/train models (e.g., OpenAI, Meta, Anthropic).
+    This is distinct from providers who host/serve the models (e.g., OpenRouter).
+    """
+    try:
+        creators = await llm_db.list_creators()
+        return llm_model.LlmCreatorsResponse(creators=creators)
+    except Exception as exc:
+        logger.exception("Failed to list creators: %s", exc)
+        raise fastapi.HTTPException(
+            status_code=500,
+            detail="Failed to list creators",
+        ) from exc
+
+
+@router.get(
+    "/creators/{creator_id}",
+    summary="Get creator details",
+    response_model=llm_model.LlmModelCreator,
+)
+async def get_llm_creator(creator_id: str):
+    """Get details of a specific model creator."""
+    try:
+        creator = await llm_db.get_creator(creator_id)
+        if not creator:
+            raise fastapi.HTTPException(
+                status_code=404, detail=f"Creator '{creator_id}' not found"
+            )
+        return creator
+    except fastapi.HTTPException:
+        raise
+    except Exception as exc:
+        logger.exception("Failed to get creator %s: %s", creator_id, exc)
+        raise fastapi.HTTPException(
+            status_code=500,
+            detail="Failed to get creator",
+        ) from exc
+
+
+@router.post(
+    "/creators",
+    summary="Create model creator",
+    response_model=llm_model.LlmModelCreator,
+)
+async def create_llm_creator(request: llm_model.UpsertLlmCreatorRequest):
+    """
+    Create a new model creator.
+
+    A creator represents an organization that creates/trains AI models,
+    such as OpenAI, Anthropic, Meta, or Google.
+    """
+    try:
+        creator = await llm_db.upsert_creator(request=request)
+        await _refresh_runtime_state()
+        logger.info("Created model creator '%s' (%s)", creator.display_name, creator.id)
+        return creator
+    except Exception as exc:
+        logger.exception("Failed to create creator: %s", exc)
+        raise fastapi.HTTPException(
+            status_code=500,
+            detail="Failed to create creator",
+        ) from exc
+
+
+@router.patch(
+    "/creators/{creator_id}",
+    summary="Update model creator",
+    response_model=llm_model.LlmModelCreator,
+)
+async def update_llm_creator(
+    creator_id: str,
+    request: llm_model.UpsertLlmCreatorRequest,
+):
+    """Update an existing model creator."""
+    try:
+        creator = await llm_db.upsert_creator(request=request, creator_id=creator_id)
+        await _refresh_runtime_state()
+        logger.info("Updated model creator '%s' (%s)", creator.display_name, creator_id)
+        return creator
+    except Exception as exc:
+        logger.exception("Failed to update creator %s: %s", creator_id, exc)
+        raise fastapi.HTTPException(
+            status_code=500,
+            detail="Failed to update creator",
+        ) from exc
+
+
+@router.delete(
+    "/creators/{creator_id}",
+    summary="Delete model creator",
+    response_model=dict,
+)
+async def delete_llm_creator(creator_id: str):
+    """
+    Delete a model creator.
+
+    This will remove the creator association from all models that reference it
+    (sets creatorId to NULL), but will not delete the models themselves.
+    """
+    try:
+        await llm_db.delete_creator(creator_id)
+        await _refresh_runtime_state()
+        logger.info("Deleted model creator '%s'", creator_id)
+        return {"success": True, "message": f"Creator '{creator_id}' deleted"}
+    except ValueError as exc:
+        logger.warning("Creator deletion validation failed: %s", exc)
+        raise fastapi.HTTPException(status_code=404, detail=str(exc)) from exc
+    except Exception as exc:
+        logger.exception("Failed to delete creator %s: %s", creator_id, exc)
+        raise fastapi.HTTPException(
+            status_code=500,
+            detail="Failed to delete creator",
+        ) from exc
+
+
+# ============================================================================
+# Recommended Model Endpoints
+# ============================================================================
+
+
+@router.get(
+    "/recommended-model",
+    summary="Get recommended model",
+    response_model=llm_model.RecommendedModelResponse,
+)
+async def get_recommended_model():
+    """
+    Get the currently recommended LLM model.
+
+    The recommended model is shown to users as the default/suggested option
+    in model selection dropdowns.
+    """
+    try:
+        model = await llm_db.get_recommended_model()
+        return llm_model.RecommendedModelResponse(
+            model=model,
+            slug=model.slug if model else None,
+        )
+    except Exception as exc:
+        logger.exception("Failed to get recommended model: %s", exc)
+        raise fastapi.HTTPException(
+            status_code=500,
+            detail="Failed to get recommended model",
+        ) from exc
+
+
+@router.post(
+    "/recommended-model",
+    summary="Set recommended model",
+    response_model=llm_model.SetRecommendedModelResponse,
+)
+async def set_recommended_model(request: llm_model.SetRecommendedModelRequest):
+    """
+    Set a model as the recommended model.
+
+    This clears the recommended flag from any other model and sets it on
+    the specified model. The model must be enabled to be set as recommended.
+
+    The recommended model is displayed to users as the default/suggested
+    option in model selection dropdowns throughout the platform.
+    """
+    try:
+        model, previous_slug = await llm_db.set_recommended_model(request.model_id)
+        await _refresh_runtime_state()
+        logger.info(
+            "Set recommended model to '%s' (previous: %s)",
+            model.slug,
+            previous_slug or "none",
+        )
+        return llm_model.SetRecommendedModelResponse(
+            model=model,
+            previous_recommended_slug=previous_slug,
+            message=f"Model '{model.display_name}' is now the recommended model",
+        )
+    except ValueError as exc:
+        logger.warning("Set recommended model validation failed: %s", exc)
+        raise fastapi.HTTPException(status_code=400, detail=str(exc)) from exc
+    except Exception as exc:
+        logger.exception("Failed to set recommended model: %s", exc)
+        raise fastapi.HTTPException(
+            status_code=500,
+            detail="Failed to set recommended model",
+        ) from exc

autogpt_platform/backend/backend/api/features/admin/llm_routes_test.py

@@ -0,0 +1,491 @@
+import json
+from unittest.mock import AsyncMock
+
+import fastapi
+import fastapi.testclient
+import pytest
+import pytest_mock
+from autogpt_libs.auth.jwt_utils import get_jwt_payload
+from pytest_snapshot.plugin import Snapshot
+
+import backend.api.features.admin.llm_routes as llm_routes
+from backend.server.v2.llm import model as llm_model
+from backend.util.models import Pagination
+
+app = fastapi.FastAPI()
+app.include_router(llm_routes.router, prefix="/admin/llm")
+
+client = fastapi.testclient.TestClient(app)
+
+
+@pytest.fixture(autouse=True)
+def setup_app_admin_auth(mock_jwt_admin):
+    """Setup admin auth overrides for all tests in this module"""
+    app.dependency_overrides[get_jwt_payload] = mock_jwt_admin["get_jwt_payload"]
+    yield
+    app.dependency_overrides.clear()
+
+
+def test_list_llm_providers_success(
+    mocker: pytest_mock.MockFixture,
+    configured_snapshot: Snapshot,
+) -> None:
+    """Test successful listing of LLM providers"""
+    # Mock the database function
+    mock_providers = [
+        {
+            "id": "provider-1",
+            "name": "openai",
+            "display_name": "OpenAI",
+            "description": "OpenAI LLM provider",
+            "supports_tools": True,
+            "supports_json_output": True,
+            "supports_reasoning": False,
+            "supports_parallel_tool": True,
+            "metadata": {},
+            "models": [],
+        },
+        {
+            "id": "provider-2",
+            "name": "anthropic",
+            "display_name": "Anthropic",
+            "description": "Anthropic LLM provider",
+            "supports_tools": True,
+            "supports_json_output": True,
+            "supports_reasoning": False,
+            "supports_parallel_tool": True,
+            "metadata": {},
+            "models": [],
+        },
+    ]
+
+    mocker.patch(
+        "backend.api.features.admin.llm_routes.llm_db.list_providers",
+        new=AsyncMock(return_value=mock_providers),
+    )
+
+    response = client.get("/admin/llm/providers")
+
+    assert response.status_code == 200
+    response_data = response.json()
+    assert len(response_data["providers"]) == 2
+    assert response_data["providers"][0]["name"] == "openai"
+
+    # Snapshot test the response (must be string)
+    configured_snapshot.assert_match(
+        json.dumps(response_data, indent=2, sort_keys=True),
+        "list_llm_providers_success.json",
+    )
+
+
+def test_list_llm_models_success(
+    mocker: pytest_mock.MockFixture,
+    configured_snapshot: Snapshot,
+) -> None:
+    """Test successful listing of LLM models with pagination"""
+    # Mock the database function - now returns LlmModelsResponse
+    mock_model = llm_model.LlmModel(
+        id="model-1",
+        slug="gpt-4o",
+        display_name="GPT-4o",
+        description="GPT-4 Optimized",
+        provider_id="provider-1",
+        context_window=128000,
+        max_output_tokens=16384,
+        is_enabled=True,
+        capabilities={},
+        metadata={},
+        costs=[
+            llm_model.LlmModelCost(
+                id="cost-1",
+                credit_cost=10,
+                credential_provider="openai",
+                metadata={},
+            )
+        ],
+    )
+
+    mock_response = llm_model.LlmModelsResponse(
+        models=[mock_model],
+        pagination=Pagination(
+            total_items=1,
+            total_pages=1,
+            current_page=1,
+            page_size=50,
+        ),
+    )
+
+    mocker.patch(
+        "backend.api.features.admin.llm_routes.llm_db.list_models",
+        new=AsyncMock(return_value=mock_response),
+    )
+
+    response = client.get("/admin/llm/models")
+
+    assert response.status_code == 200
+    response_data = response.json()
+    assert len(response_data["models"]) == 1
+    assert response_data["models"][0]["slug"] == "gpt-4o"
+    assert response_data["pagination"]["total_items"] == 1
+    assert response_data["pagination"]["page_size"] == 50
+
+    # Snapshot test the response (must be string)
+    configured_snapshot.assert_match(
+        json.dumps(response_data, indent=2, sort_keys=True),
+        "list_llm_models_success.json",
+    )
+
+
+def test_create_llm_provider_success(
+    mocker: pytest_mock.MockFixture,
+    configured_snapshot: Snapshot,
+) -> None:
+    """Test successful creation of LLM provider"""
+    mock_provider = {
+        "id": "new-provider-id",
+        "name": "groq",
+        "display_name": "Groq",
+        "description": "Groq LLM provider",
+        "supports_tools": True,
+        "supports_json_output": True,
+        "supports_reasoning": False,
+        "supports_parallel_tool": False,
+        "metadata": {},
+    }
+
+    mocker.patch(
+        "backend.api.features.admin.llm_routes.llm_db.upsert_provider",
+        new=AsyncMock(return_value=mock_provider),
+    )
+
+    mock_refresh = mocker.patch(
+        "backend.api.features.admin.llm_routes._refresh_runtime_state",
+        new=AsyncMock(),
+    )
+
+    request_data = {
+        "name": "groq",
+        "display_name": "Groq",
+        "description": "Groq LLM provider",
+        "supports_tools": True,
+        "supports_json_output": True,
+        "supports_reasoning": False,
+        "supports_parallel_tool": False,
+        "metadata": {},
+    }
+
+    response = client.post("/admin/llm/providers", json=request_data)
+
+    assert response.status_code == 200
+    response_data = response.json()
+    assert response_data["name"] == "groq"
+    assert response_data["display_name"] == "Groq"
+
+    # Verify refresh was called
+    mock_refresh.assert_called_once()
+
+    # Snapshot test the response (must be string)
+    configured_snapshot.assert_match(
+        json.dumps(response_data, indent=2, sort_keys=True),
+        "create_llm_provider_success.json",
+    )
+
+
+def test_create_llm_model_success(
+    mocker: pytest_mock.MockFixture,
+    configured_snapshot: Snapshot,
+) -> None:
+    """Test successful creation of LLM model"""
+    mock_model = {
+        "id": "new-model-id",
+        "slug": "gpt-4.1-mini",
+        "display_name": "GPT-4.1 Mini",
+        "description": "Latest GPT-4.1 Mini model",
+        "provider_id": "provider-1",
+        "context_window": 128000,
+        "max_output_tokens": 16384,
+        "is_enabled": True,
+        "capabilities": {},
+        "metadata": {},
+        "costs": [
+            {
+                "id": "cost-id",
+                "credit_cost": 5,
+                "credential_provider": "openai",
+                "metadata": {},
+            }
+        ],
+    }
+
+    mocker.patch(
+        "backend.api.features.admin.llm_routes.llm_db.create_model",
+        new=AsyncMock(return_value=mock_model),
+    )
+
+    mock_refresh = mocker.patch(
+        "backend.api.features.admin.llm_routes._refresh_runtime_state",
+        new=AsyncMock(),
+    )
+
+    request_data = {
+        "slug": "gpt-4.1-mini",
+        "display_name": "GPT-4.1 Mini",
+        "description": "Latest GPT-4.1 Mini model",
+        "provider_id": "provider-1",
+        "context_window": 128000,
+        "max_output_tokens": 16384,
+        "is_enabled": True,
+        "capabilities": {},
+        "metadata": {},
+        "costs": [
+            {
+                "credit_cost": 5,
+                "credential_provider": "openai",
+                "metadata": {},
+            }
+        ],
+    }
+
+    response = client.post("/admin/llm/models", json=request_data)
+
+    assert response.status_code == 200
+    response_data = response.json()
+    assert response_data["slug"] == "gpt-4.1-mini"
+    assert response_data["is_enabled"] is True
+
+    # Verify refresh was called
+    mock_refresh.assert_called_once()
+
+    # Snapshot test the response (must be string)
+    configured_snapshot.assert_match(
+        json.dumps(response_data, indent=2, sort_keys=True),
+        "create_llm_model_success.json",
+    )
+
+
+def test_update_llm_model_success(
+    mocker: pytest_mock.MockFixture,
+    configured_snapshot: Snapshot,
+) -> None:
+    """Test successful update of LLM model"""
+    mock_model = {
+        "id": "model-1",
+        "slug": "gpt-4o",
+        "display_name": "GPT-4o Updated",
+        "description": "Updated description",
+        "provider_id": "provider-1",
+        "context_window": 256000,
+        "max_output_tokens": 32768,
+        "is_enabled": True,
+        "capabilities": {},
+        "metadata": {},
+        "costs": [
+            {
+                "id": "cost-1",
+                "credit_cost": 15,
+                "credential_provider": "openai",
+                "metadata": {},
+            }
+        ],
+    }
+
+    mocker.patch(
+        "backend.api.features.admin.llm_routes.llm_db.update_model",
+        new=AsyncMock(return_value=mock_model),
+    )
+
+    mock_refresh = mocker.patch(
+        "backend.api.features.admin.llm_routes._refresh_runtime_state",
+        new=AsyncMock(),
+    )
+
+    request_data = {
+        "display_name": "GPT-4o Updated",
+        "description": "Updated description",
+        "context_window": 256000,
+        "max_output_tokens": 32768,
+    }
+
+    response = client.patch("/admin/llm/models/model-1", json=request_data)
+
+    assert response.status_code == 200
+    response_data = response.json()
+    assert response_data["display_name"] == "GPT-4o Updated"
+    assert response_data["context_window"] == 256000
+
+    # Verify refresh was called
+    mock_refresh.assert_called_once()
+
+    # Snapshot test the response (must be string)
+    configured_snapshot.assert_match(
+        json.dumps(response_data, indent=2, sort_keys=True),
+        "update_llm_model_success.json",
+    )
+
+
+def test_toggle_llm_model_success(
+    mocker: pytest_mock.MockFixture,
+    configured_snapshot: Snapshot,
+) -> None:
+    """Test successful toggling of LLM model enabled status"""
+    # Create a proper mock model object
+    mock_model = llm_model.LlmModel(
+        id="model-1",
+        slug="gpt-4o",
+        display_name="GPT-4o",
+        description="GPT-4 Optimized",
+        provider_id="provider-1",
+        context_window=128000,
+        max_output_tokens=16384,
+        is_enabled=False,
+        capabilities={},
+        metadata={},
+        costs=[],
+    )
+
+    # Create a proper ToggleLlmModelResponse
+    mock_response = llm_model.ToggleLlmModelResponse(
+        model=mock_model,
+        nodes_migrated=0,
+        migrated_to_slug=None,
+        migration_id=None,
+    )
+
+    mocker.patch(
+        "backend.api.features.admin.llm_routes.llm_db.toggle_model",
+        new=AsyncMock(return_value=mock_response),
+    )
+
+    mock_refresh = mocker.patch(
+        "backend.api.features.admin.llm_routes._refresh_runtime_state",
+        new=AsyncMock(),
+    )
+
+    request_data = {"is_enabled": False}
+
+    response = client.patch("/admin/llm/models/model-1/toggle", json=request_data)
+
+    assert response.status_code == 200
+    response_data = response.json()
+    assert response_data["model"]["is_enabled"] is False
+
+    # Verify refresh was called
+    mock_refresh.assert_called_once()
+
+    # Snapshot test the response (must be string)
+    configured_snapshot.assert_match(
+        json.dumps(response_data, indent=2, sort_keys=True),
+        "toggle_llm_model_success.json",
+    )
+
+
+def test_delete_llm_model_success(
+    mocker: pytest_mock.MockFixture,
+    configured_snapshot: Snapshot,
+) -> None:
+    """Test successful deletion of LLM model with migration"""
+    # Create a proper DeleteLlmModelResponse
+    mock_response = llm_model.DeleteLlmModelResponse(
+        deleted_model_slug="gpt-3.5-turbo",
+        deleted_model_display_name="GPT-3.5 Turbo",
+        replacement_model_slug="gpt-4o-mini",
+        nodes_migrated=42,
+        message="Successfully deleted model 'GPT-3.5 Turbo' (gpt-3.5-turbo) "
+        "and migrated 42 workflow node(s) to 'gpt-4o-mini'.",
+    )
+
+    mocker.patch(
+        "backend.api.features.admin.llm_routes.llm_db.delete_model",
+        new=AsyncMock(return_value=mock_response),
+    )
+
+    mock_refresh = mocker.patch(
+        "backend.api.features.admin.llm_routes._refresh_runtime_state",
+        new=AsyncMock(),
+    )
+
+    response = client.delete(
+        "/admin/llm/models/model-1?replacement_model_slug=gpt-4o-mini"
+    )
+
+    assert response.status_code == 200
+    response_data = response.json()
+    assert response_data["deleted_model_slug"] == "gpt-3.5-turbo"
+    assert response_data["nodes_migrated"] == 42
+    assert response_data["replacement_model_slug"] == "gpt-4o-mini"
+
+    # Verify refresh was called
+    mock_refresh.assert_called_once()
+
+    # Snapshot test the response (must be string)
+    configured_snapshot.assert_match(
+        json.dumps(response_data, indent=2, sort_keys=True),
+        "delete_llm_model_success.json",
+    )
+
+
+def test_delete_llm_model_validation_error(
+    mocker: pytest_mock.MockFixture,
+) -> None:
+    """Test deletion fails with proper error when validation fails"""
+    mocker.patch(
+        "backend.api.features.admin.llm_routes.llm_db.delete_model",
+        new=AsyncMock(side_effect=ValueError("Replacement model 'invalid' not found")),
+    )
+
+    response = client.delete("/admin/llm/models/model-1?replacement_model_slug=invalid")
+
+    assert response.status_code == 400
+    assert "Replacement model 'invalid' not found" in response.json()["detail"]
+
+
+def test_delete_llm_model_no_replacement_with_usage(
+    mocker: pytest_mock.MockFixture,
+) -> None:
+    """Test deletion fails when nodes exist but no replacement is provided"""
+    mocker.patch(
+        "backend.api.features.admin.llm_routes.llm_db.delete_model",
+        new=AsyncMock(
+            side_effect=ValueError(
+                "Cannot delete model 'test-model': 5 workflow node(s) are using it. "
+                "Please provide a replacement_model_slug to migrate them."
+            )
+        ),
+    )
+
+    response = client.delete("/admin/llm/models/model-1")
+
+    assert response.status_code == 400
+    assert "workflow node(s) are using it" in response.json()["detail"]
+
+
+def test_delete_llm_model_no_replacement_no_usage(
+    mocker: pytest_mock.MockFixture,
+) -> None:
+    """Test deletion succeeds when no nodes use the model and no replacement is provided"""
+    mock_response = llm_model.DeleteLlmModelResponse(
+        deleted_model_slug="unused-model",
+        deleted_model_display_name="Unused Model",
+        replacement_model_slug=None,
+        nodes_migrated=0,
+        message="Successfully deleted model 'Unused Model' (unused-model). No workflows were using this model.",
+    )
+
+    mocker.patch(
+        "backend.api.features.admin.llm_routes.llm_db.delete_model",
+        new=AsyncMock(return_value=mock_response),
+    )
+
+    mock_refresh = mocker.patch(
+        "backend.api.features.admin.llm_routes._refresh_runtime_state",
+        new=AsyncMock(),
+    )
+
+    response = client.delete("/admin/llm/models/model-1")
+
+    assert response.status_code == 200
+    response_data = response.json()
+    assert response_data["deleted_model_slug"] == "unused-model"
+    assert response_data["nodes_migrated"] == 0
+    assert response_data["replacement_model_slug"] is None
+    mock_refresh.assert_called_once()

autogpt_platform/backend/backend/api/features/admin/store_admin_routes.py

@@ -24,14 +24,13 @@ router = fastapi.APIRouter(
 @router.get(
     "/listings",
     summary="Get Admin Listings History",
-    response_model=store_model.StoreListingsWithVersionsResponse,
 )
 async def get_admin_listings_with_versions(
     status: typing.Optional[prisma.enums.SubmissionStatus] = None,
     search: typing.Optional[str] = None,
     page: int = 1,
     page_size: int = 20,
-):
+) -> store_model.StoreListingsWithVersionsAdminViewResponse:
     """
     Get store listings with their version history for admins.
 
@@ -45,36 +44,26 @@ async def get_admin_listings_with_versions(
         page_size: Number of items per page
 
     Returns:
-        StoreListingsWithVersionsResponse with listings and their versions
+        Paginated listings with their versions
     """
-    try:
-        listings = await store_db.get_admin_listings_with_versions(
-            status=status,
-            search_query=search,
-            page=page,
-            page_size=page_size,
-        )
-        return listings
-    except Exception as e:
-        logger.exception("Error getting admin listings with versions: %s", e)
-        return fastapi.responses.JSONResponse(
-            status_code=500,
-            content={
-                "detail": "An error occurred while retrieving listings with versions"
-            },
-        )
+    listings = await store_db.get_admin_listings_with_versions(
+        status=status,
+        search_query=search,
+        page=page,
+        page_size=page_size,
+    )
+    return listings
 
 
 @router.post(
     "/submissions/{store_listing_version_id}/review",
     summary="Review Store Submission",
-    response_model=store_model.StoreSubmission,
 )
 async def review_submission(
     store_listing_version_id: str,
     request: store_model.ReviewSubmissionRequest,
     user_id: str = fastapi.Security(autogpt_libs.auth.get_user_id),
-):
+) -> store_model.StoreSubmissionAdminView:
     """
     Review a store listing submission.
 
@@ -84,31 +73,24 @@ async def review_submission(
         user_id: Authenticated admin user performing the review
 
     Returns:
-        StoreSubmission with updated review information
+        StoreSubmissionAdminView with updated review information
     """
-    try:
-        already_approved = await store_db.check_submission_already_approved(
-            store_listing_version_id=store_listing_version_id,
-        )
-        submission = await store_db.review_store_submission(
-            store_listing_version_id=store_listing_version_id,
-            is_approved=request.is_approved,
-            external_comments=request.comments,
-            internal_comments=request.internal_comments or "",
-            reviewer_id=user_id,
-        )
+    already_approved = await store_db.check_submission_already_approved(
+        store_listing_version_id=store_listing_version_id,
+    )
+    submission = await store_db.review_store_submission(
+        store_listing_version_id=store_listing_version_id,
+        is_approved=request.is_approved,
+        external_comments=request.comments,
+        internal_comments=request.internal_comments or "",
+        reviewer_id=user_id,
+    )
 
-        state_changed = already_approved != request.is_approved
-        # Clear caches when the request is approved as it updates what is shown on the store
-        if state_changed:
-            store_cache.clear_all_caches()
-        return submission
-    except Exception as e:
-        logger.exception("Error reviewing submission: %s", e)
-        return fastapi.responses.JSONResponse(
-            status_code=500,
-            content={"detail": "An error occurred while reviewing the submission"},
-        )
+    state_changed = already_approved != request.is_approved
+    # Clear caches whenever approval state changes, since store visibility can change
+    if state_changed:
+        store_cache.clear_all_caches()
+    return submission
 
 
 @router.get(

autogpt_platform/backend/backend/api/features/builder/db.py

@@ -1,6 +1,7 @@
 import logging
 from dataclasses import dataclass
 from difflib import SequenceMatcher
+from functools import lru_cache
 from typing import Any, Sequence, get_args, get_origin
 
 import prisma
@@ -21,6 +22,7 @@ from backend.blocks._base import (
     BlockType,
 )
 from backend.blocks.llm import LlmModel
+from backend.data.llm_registry import get_all_model_slugs_for_validation
 from backend.integrations.providers import ProviderName
 from backend.util.cache import cached
 from backend.util.models import Pagination
@@ -37,7 +39,20 @@ from .model import (
 )
 
 logger = logging.getLogger(__name__)
-llm_models = [name.name.lower().replace("_", " ") for name in LlmModel]
+
+
+@lru_cache(maxsize=1)
+def _get_llm_models() -> tuple[str, ...]:
+    """Get LLM model names for search matching from the registry.
+
+    Cached to avoid rebuilding on every search call.
+    Cache is cleared when registry is refreshed via _refresh_runtime_state.
+    Returns tuple for hashability (required by lru_cache).
+    """
+    return tuple(
+        slug.lower().replace("-", " ") for slug in get_all_model_slugs_for_validation()
+    )
+
 
 MAX_LIBRARY_AGENT_RESULTS = 100
 MAX_MARKETPLACE_AGENT_RESULTS = 100
@@ -656,8 +671,10 @@ def _contains_type(annotation: Any, target: type) -> bool:
 def _matches_llm_model(schema_cls: type[BlockSchema], query: str) -> bool:
     for field in schema_cls.model_fields.values():
         if _contains_type(field.annotation, LlmModel):
-            # Check if query matches any value in llm_models
-            if any(query in name for name in llm_models):
+            # Normalize query same as model slugs (lowercase, hyphens to spaces)
+            normalized_model_query = query.lower().replace("-", " ")
+            # Check if query matches any value in llm_models from registry
+            if any(normalized_model_query in name for name in _get_llm_models()):
                 return True
     return False
 

autogpt_platform/backend/backend/api/features/chat/routes.py

@@ -11,7 +11,7 @@ from autogpt_libs import auth
 from fastapi import APIRouter, Depends, HTTPException, Query, Response, Security
 from fastapi.responses import StreamingResponse
 from prisma.models import UserWorkspaceFile
-from pydantic import BaseModel, Field
+from pydantic import BaseModel, Field, field_validator
 
 from backend.copilot import service as chat_service
 from backend.copilot import stream_registry
@@ -25,8 +25,10 @@ from backend.copilot.model import (
     delete_chat_session,
     get_chat_session,
     get_user_sessions,
+    update_session_title,
 )
 from backend.copilot.response_model import StreamError, StreamFinish, StreamHeartbeat
+from backend.copilot.tools.e2b_sandbox import kill_sandbox
 from backend.copilot.tools.models import (
     AgentDetailsResponse,
     AgentOutputResponse,
@@ -141,6 +143,20 @@ class CancelSessionResponse(BaseModel):
     reason: str | None = None
 
 
+class UpdateSessionTitleRequest(BaseModel):
+    """Request model for updating a session's title."""
+
+    title: str
+
+    @field_validator("title")
+    @classmethod
+    def title_must_not_be_blank(cls, v: str) -> str:
+        stripped = v.strip()
+        if not stripped:
+            raise ValueError("Title must not be blank")
+        return stripped
+
+
 # ========== Routes ==========
 
 
@@ -250,12 +266,12 @@ async def delete_session(
         )
 
     # Best-effort cleanup of the E2B sandbox (if any).
-    config = ChatConfig()
-    if config.use_e2b_sandbox and config.e2b_api_key:
-        from backend.copilot.tools.e2b_sandbox import kill_sandbox
-
+    # sandbox_id is in Redis; kill_sandbox() fetches it from there.
+    e2b_cfg = ChatConfig()
+    if e2b_cfg.e2b_active:
+        assert e2b_cfg.e2b_api_key  # guaranteed by e2b_active check
         try:
-            await kill_sandbox(session_id, config.e2b_api_key)
+            await kill_sandbox(session_id, e2b_cfg.e2b_api_key)
         except Exception:
             logger.warning(
                 "[E2B] Failed to kill sandbox for session %s", session_id[:12]
@@ -264,6 +280,43 @@ async def delete_session(
     return Response(status_code=204)
 
 
+@router.patch(
+    "/sessions/{session_id}/title",
+    summary="Update session title",
+    dependencies=[Security(auth.requires_user)],
+    status_code=200,
+    responses={404: {"description": "Session not found or access denied"}},
+)
+async def update_session_title_route(
+    session_id: str,
+    request: UpdateSessionTitleRequest,
+    user_id: Annotated[str, Security(auth.get_user_id)],
+) -> dict:
+    """
+    Update the title of a chat session.
+
+    Allows the user to rename their chat session.
+
+    Args:
+        session_id: The session ID to update.
+        request: Request body containing the new title.
+        user_id: The authenticated user's ID.
+
+    Returns:
+        dict: Status of the update.
+
+    Raises:
+        HTTPException: 404 if session not found or not owned by user.
+    """
+    success = await update_session_title(session_id, user_id, request.title)
+    if not success:
+        raise HTTPException(
+            status_code=404,
+            detail=f"Session {session_id} not found or access denied",
+        )
+    return {"status": "ok"}
+
+
 @router.get(
     "/sessions/{session_id}",
 )
@@ -753,7 +806,6 @@ async def resume_session_stream(
 @router.patch(
     "/sessions/{session_id}/assign-user",
     dependencies=[Security(auth.requires_user)],
-    status_code=200,
 )
 async def session_assign_user(
     session_id: str,

autogpt_platform/backend/backend/api/features/chat/routes_test.py

@@ -1,4 +1,6 @@
-"""Tests for chat route file_ids validation and enrichment."""
+"""Tests for chat API routes: session title update and file attachment validation."""
+
+from unittest.mock import AsyncMock
 
 import fastapi
 import fastapi.testclient
@@ -17,6 +19,7 @@ TEST_USER_ID = "3e53486c-cf57-477e-ba2a-cb02dc828e1a"
 
 @pytest.fixture(autouse=True)
 def setup_app_auth(mock_jwt_user):
+    """Setup auth overrides for all tests in this module"""
     from autogpt_libs.auth.jwt_utils import get_jwt_payload
 
     app.dependency_overrides[get_jwt_payload] = mock_jwt_user["get_jwt_payload"]
@@ -24,7 +27,95 @@ def setup_app_auth(mock_jwt_user):
     app.dependency_overrides.clear()
 
 
-# ---- file_ids Pydantic validation (B1) ----
+def _mock_update_session_title(
+    mocker: pytest_mock.MockerFixture, *, success: bool = True
+):
+    """Mock update_session_title."""
+    return mocker.patch(
+        "backend.api.features.chat.routes.update_session_title",
+        new_callable=AsyncMock,
+        return_value=success,
+    )
+
+
+# ─── Update title: success ─────────────────────────────────────────────
+
+
+def test_update_title_success(
+    mocker: pytest_mock.MockerFixture,
+    test_user_id: str,
+) -> None:
+    mock_update = _mock_update_session_title(mocker, success=True)
+
+    response = client.patch(
+        "/sessions/sess-1/title",
+        json={"title": "My project"},
+    )
+
+    assert response.status_code == 200
+    assert response.json() == {"status": "ok"}
+    mock_update.assert_called_once_with("sess-1", test_user_id, "My project")
+
+
+def test_update_title_trims_whitespace(
+    mocker: pytest_mock.MockerFixture,
+    test_user_id: str,
+) -> None:
+    mock_update = _mock_update_session_title(mocker, success=True)
+
+    response = client.patch(
+        "/sessions/sess-1/title",
+        json={"title": "  trimmed  "},
+    )
+
+    assert response.status_code == 200
+    mock_update.assert_called_once_with("sess-1", test_user_id, "trimmed")
+
+
+# ─── Update title: blank / whitespace-only → 422 ──────────────────────
+
+
+def test_update_title_blank_rejected(
+    test_user_id: str,
+) -> None:
+    """Whitespace-only titles must be rejected before hitting the DB."""
+    response = client.patch(
+        "/sessions/sess-1/title",
+        json={"title": "   "},
+    )
+
+    assert response.status_code == 422
+
+
+def test_update_title_empty_rejected(
+    test_user_id: str,
+) -> None:
+    response = client.patch(
+        "/sessions/sess-1/title",
+        json={"title": ""},
+    )
+
+    assert response.status_code == 422
+
+
+# ─── Update title: session not found or wrong user → 404 ──────────────
+
+
+def test_update_title_not_found(
+    mocker: pytest_mock.MockerFixture,
+    test_user_id: str,
+) -> None:
+    _mock_update_session_title(mocker, success=False)
+
+    response = client.patch(
+        "/sessions/sess-1/title",
+        json={"title": "New name"},
+    )
+
+    assert response.status_code == 404
+
+
+# ─── file_ids Pydantic validation ─────────────────────────────────────
 
 
 def test_stream_chat_rejects_too_many_file_ids():
@@ -92,7 +183,7 @@ def test_stream_chat_accepts_20_file_ids(mocker: pytest_mock.MockFixture):
     assert response.status_code == 200
 
 
-# ---- UUID format filtering ----
+# ─── UUID format filtering ─────────────────────────────────────────────
 
 
 def test_file_ids_filters_invalid_uuids(mocker: pytest_mock.MockFixture):
@@ -131,7 +222,7 @@ def test_file_ids_filters_invalid_uuids(mocker: pytest_mock.MockFixture):
     assert call_kwargs["where"]["id"]["in"] == [valid_id]
 
 
-# ---- Cross-workspace file_ids ----
+# ─── Cross-workspace file_ids ─────────────────────────────────────────
 
 
 def test_file_ids_scoped_to_workspace(mocker: pytest_mock.MockFixture):

autogpt_platform/backend/backend/api/features/library/db.py

@@ -8,7 +8,6 @@ import prisma.errors
 import prisma.models
 import prisma.types
 
-import backend.api.features.store.exceptions as store_exceptions
 import backend.api.features.store.image_gen as store_image_gen
 import backend.api.features.store.media as store_media
 import backend.data.graph as graph_db
@@ -251,7 +250,7 @@ async def get_library_agent(id: str, user_id: str) -> library_model.LibraryAgent
         The requested LibraryAgent.
 
     Raises:
-        AgentNotFoundError: If the specified agent does not exist.
+        NotFoundError: If the specified agent does not exist.
         DatabaseError: If there's an error during retrieval.
     """
     library_agent = await prisma.models.LibraryAgent.prisma().find_first(
@@ -398,6 +397,7 @@ async def create_library_agent(
     hitl_safe_mode: bool = True,
     sensitive_action_safe_mode: bool = False,
     create_library_agents_for_sub_graphs: bool = True,
+    folder_id: str | None = None,
 ) -> list[library_model.LibraryAgent]:
     """
     Adds an agent to the user's library (LibraryAgent table).
@@ -414,12 +414,18 @@ async def create_library_agent(
         If the graph has sub-graphs, the parent graph will always be the first entry in the list.
 
     Raises:
-        AgentNotFoundError: If the specified agent does not exist.
+        NotFoundError: If the specified agent does not exist.
         DatabaseError: If there's an error during creation or if image generation fails.
     """
     logger.info(
         f"Creating library agent for graph #{graph.id} v{graph.version}; user:<redacted>"
     )
+
+    # Authorization: FK only checks existence, not ownership.
+    # Verify the folder belongs to this user to prevent cross-user nesting.
+    if folder_id:
+        await get_folder(folder_id, user_id)
+
     graph_entries = (
         [graph, *graph.sub_graphs] if create_library_agents_for_sub_graphs else [graph]
     )
@@ -432,7 +438,6 @@ async def create_library_agent(
                         isCreatedByUser=(user_id == user_id),
                         useGraphIsActiveVersion=True,
                         User={"connect": {"id": user_id}},
-                        # Creator={"connect": {"id": user_id}},
                         AgentGraph={
                             "connect": {
                                 "graphVersionId": {
@@ -448,6 +453,11 @@ async def create_library_agent(
                                 sensitive_action_safe_mode=sensitive_action_safe_mode,
                             ).model_dump()
                         ),
+                        **(
+                            {"Folder": {"connect": {"id": folder_id}}}
+                            if folder_id and graph_entry is graph
+                            else {}
+                        ),
                     ),
                     include=library_agent_include(
                         user_id, include_nodes=False, include_executions=False
@@ -529,6 +539,7 @@ async def update_agent_version_in_library(
 async def create_graph_in_library(
     graph: graph_db.Graph,
     user_id: str,
+    folder_id: str | None = None,
 ) -> tuple[graph_db.GraphModel, library_model.LibraryAgent]:
     """Create a new graph and add it to the user's library."""
     graph.version = 1
@@ -542,6 +553,7 @@ async def create_graph_in_library(
         user_id=user_id,
         sensitive_action_safe_mode=True,
         create_library_agents_for_sub_graphs=False,
+        folder_id=folder_id,
     )
 
     if created_graph.is_active:
@@ -817,7 +829,7 @@ async def add_store_agent_to_library(
         The newly created LibraryAgent if successfully added, the existing corresponding one if any.
 
     Raises:
-        AgentNotFoundError: If the store listing or associated agent is not found.
+        NotFoundError: If the store listing or associated agent is not found.
         DatabaseError: If there's an issue creating the LibraryAgent record.
     """
     logger.debug(
@@ -832,7 +844,7 @@ async def add_store_agent_to_library(
     )
     if not store_listing_version or not store_listing_version.AgentGraph:
         logger.warning(f"Store listing version not found: {store_listing_version_id}")
-        raise store_exceptions.AgentNotFoundError(
+        raise NotFoundError(
             f"Store listing version {store_listing_version_id} not found or invalid"
         )
 
@@ -846,7 +858,7 @@ async def add_store_agent_to_library(
         include_subgraphs=False,
     )
     if not graph_model:
-        raise store_exceptions.AgentNotFoundError(
+        raise NotFoundError(
             f"Graph #{graph.id} v{graph.version} not found or accessible"
         )
 
@@ -1481,6 +1493,67 @@ async def bulk_move_agents_to_folder(
     return [library_model.LibraryAgent.from_db(agent) for agent in agents]
 
 
+def collect_tree_ids(
+    nodes: list[library_model.LibraryFolderTree],
+    visited: set[str] | None = None,
+) -> list[str]:
+    """Collect all folder IDs from a folder tree."""
+    if visited is None:
+        visited = set()
+    ids: list[str] = []
+    for n in nodes:
+        if n.id in visited:
+            continue
+        visited.add(n.id)
+        ids.append(n.id)
+        ids.extend(collect_tree_ids(n.children, visited))
+    return ids
+
+
+async def get_folder_agent_summaries(
+    user_id: str, folder_id: str
+) -> list[dict[str, str | None]]:
+    """Get a lightweight list of agents in a folder (id, name, description)."""
+    all_agents: list[library_model.LibraryAgent] = []
+    for page in itertools.count(1):
+        resp = await list_library_agents(
+            user_id=user_id, folder_id=folder_id, page=page
+        )
+        all_agents.extend(resp.agents)
+        if page >= resp.pagination.total_pages:
+            break
+    return [
+        {"id": a.id, "name": a.name, "description": a.description} for a in all_agents
+    ]
+
+
+async def get_root_agent_summaries(
+    user_id: str,
+) -> list[dict[str, str | None]]:
+    """Get a lightweight list of root-level agents (folderId IS NULL)."""
+    all_agents: list[library_model.LibraryAgent] = []
+    for page in itertools.count(1):
+        resp = await list_library_agents(
+            user_id=user_id, include_root_only=True, page=page
+        )
+        all_agents.extend(resp.agents)
+        if page >= resp.pagination.total_pages:
+            break
+    return [
+        {"id": a.id, "name": a.name, "description": a.description} for a in all_agents
+    ]
+
+
+async def get_folder_agents_map(
+    user_id: str, folder_ids: list[str]
+) -> dict[str, list[dict[str, str | None]]]:
+    """Get agent summaries for multiple folders concurrently."""
+    results = await asyncio.gather(
+        *(get_folder_agent_summaries(user_id, fid) for fid in folder_ids)
+    )
+    return dict(zip(folder_ids, results))
+
+
 ##############################################
 ########### Presets DB Functions #############
 ##############################################

autogpt_platform/backend/backend/api/features/library/db_test.py

@@ -4,7 +4,6 @@ import prisma.enums
 import prisma.models
 import pytest
 
-import backend.api.features.store.exceptions
 from backend.data.db import connect
 from backend.data.includes import library_agent_include
 
@@ -218,7 +217,7 @@ async def test_add_agent_to_library_not_found(mocker):
     )
 
     # Call function and verify exception
-    with pytest.raises(backend.api.features.store.exceptions.AgentNotFoundError):
+    with pytest.raises(db.NotFoundError):
         await db.add_store_agent_to_library("version123", "test-user")
 
     # Verify mock called correctly

autogpt_platform/backend/backend/api/features/store/cache.py

@@ -1,5 +1,3 @@
-from typing import Literal
-
 from backend.util.cache import cached
 
 from . import db as store_db
@@ -23,7 +21,7 @@ def clear_all_caches():
 async def _get_cached_store_agents(
     featured: bool,
     creator: str | None,
-    sorted_by: Literal["rating", "runs", "name", "updated_at"] | None,
+    sorted_by: store_db.StoreAgentsSortOptions | None,
     search_query: str | None,
     category: str | None,
     page: int,
@@ -57,7 +55,7 @@ async def _get_cached_agent_details(
 async def _get_cached_store_creators(
     featured: bool,
     search_query: str | None,
-    sorted_by: Literal["agent_rating", "agent_runs", "num_agents"] | None,
+    sorted_by: store_db.StoreCreatorsSortOptions | None,
     page: int,
     page_size: int,
 ):
@@ -75,4 +73,4 @@ async def _get_cached_store_creators(
 @cached(maxsize=100, ttl_seconds=300, shared_cache=True)
 async def _get_cached_creator_details(username: str):
     """Cached helper to get creator details."""
-    return await store_db.get_store_creator_details(username=username.lower())
+    return await store_db.get_store_creator(username=username.lower())

autogpt_platform/backend/backend/api/features/store/db_test.py

@@ -26,7 +26,7 @@ async def test_get_store_agents(mocker):
     mock_agents = [
         prisma.models.StoreAgent(
             listing_id="test-id",
-            storeListingVersionId="version123",
+            listing_version_id="version123",
             slug="test-agent",
             agent_name="Test Agent",
             agent_video=None,
@@ -40,11 +40,11 @@ async def test_get_store_agents(mocker):
             runs=10,
             rating=4.5,
             versions=["1.0"],
-            agentGraphVersions=["1"],
-            agentGraphId="test-graph-id",
+            graph_id="test-graph-id",
+            graph_versions=["1"],
             updated_at=datetime.now(),
             is_available=False,
-            useForOnboarding=False,
+            use_for_onboarding=False,
         )
     ]
 
@@ -68,10 +68,10 @@ async def test_get_store_agents(mocker):
 
 @pytest.mark.asyncio(loop_scope="session")
 async def test_get_store_agent_details(mocker):
-    # Mock data
+    # Mock data - StoreAgent view already contains the active version data
     mock_agent = prisma.models.StoreAgent(
         listing_id="test-id",
-        storeListingVersionId="version123",
+        listing_version_id="version123",
         slug="test-agent",
         agent_name="Test Agent",
         agent_video="video.mp4",
@@ -85,102 +85,38 @@ async def test_get_store_agent_details(mocker):
         runs=10,
         rating=4.5,
         versions=["1.0"],
-        agentGraphVersions=["1"],
-        agentGraphId="test-graph-id",
-        updated_at=datetime.now(),
-        is_available=False,
-        useForOnboarding=False,
-    )
-
-    # Mock active version agent (what we want to return for active version)
-    mock_active_agent = prisma.models.StoreAgent(
-        listing_id="test-id",
-        storeListingVersionId="active-version-id",
-        slug="test-agent",
-        agent_name="Test Agent Active",
-        agent_video="active_video.mp4",
-        agent_image=["active_image.jpg"],
-        featured=False,
-        creator_username="creator",
-        creator_avatar="avatar.jpg",
-        sub_heading="Test heading active",
-        description="Test description active",
-        categories=["test"],
-        runs=15,
-        rating=4.8,
-        versions=["1.0", "2.0"],
-        agentGraphVersions=["1", "2"],
-        agentGraphId="test-graph-id-active",
+        graph_id="test-graph-id",
+        graph_versions=["1"],
         updated_at=datetime.now(),
         is_available=True,
-        useForOnboarding=False,
+        use_for_onboarding=False,
     )
 
-    # Create a mock StoreListing result
-    mock_store_listing = mocker.MagicMock()
-    mock_store_listing.activeVersionId = "active-version-id"
-    mock_store_listing.hasApprovedVersion = True
-    mock_store_listing.ActiveVersion = mocker.MagicMock()
-    mock_store_listing.ActiveVersion.recommendedScheduleCron = None
-
-    # Mock StoreAgent prisma call - need to handle multiple calls
+    # Mock StoreAgent prisma call
     mock_store_agent = mocker.patch("prisma.models.StoreAgent.prisma")
-
-    # Set up side_effect to return different results for different calls
-    def mock_find_first_side_effect(*args, **kwargs):
-        where_clause = kwargs.get("where", {})
-        if "storeListingVersionId" in where_clause:
-            # Second call for active version
-            return mock_active_agent
-        else:
-            # First call for initial lookup
-            return mock_agent
-
-    mock_store_agent.return_value.find_first = mocker.AsyncMock(
-        side_effect=mock_find_first_side_effect
-    )
-
-    # Mock Profile prisma call
-    mock_profile = mocker.MagicMock()
-    mock_profile.userId = "user-id-123"
-    mock_profile_db = mocker.patch("prisma.models.Profile.prisma")
-    mock_profile_db.return_value.find_first = mocker.AsyncMock(
-        return_value=mock_profile
-    )
-
-    # Mock StoreListing prisma call
-    mock_store_listing_db = mocker.patch("prisma.models.StoreListing.prisma")
-    mock_store_listing_db.return_value.find_first = mocker.AsyncMock(
-        return_value=mock_store_listing
-    )
+    mock_store_agent.return_value.find_first = mocker.AsyncMock(return_value=mock_agent)
 
     # Call function
     result = await db.get_store_agent_details("creator", "test-agent")
 
-    # Verify results - should use active version data
+    # Verify results - constructed from the StoreAgent view
     assert result.slug == "test-agent"
-    assert result.agent_name == "Test Agent Active"  # From active version
-    assert result.active_version_id == "active-version-id"
+    assert result.agent_name == "Test Agent"
+    assert result.active_version_id == "version123"
     assert result.has_approved_version is True
-    assert (
-        result.store_listing_version_id == "active-version-id"
-    )  # Should be active version ID
+    assert result.store_listing_version_id == "version123"
+    assert result.graph_id == "test-graph-id"
+    assert result.runs == 10
+    assert result.rating == 4.5
 
-    # Verify mocks called correctly - now expecting 2 calls
-    assert mock_store_agent.return_value.find_first.call_count == 2
-
-    # Check the specific calls
-    calls = mock_store_agent.return_value.find_first.call_args_list
-    assert calls[0] == mocker.call(
+    # Verify single StoreAgent lookup
+    mock_store_agent.return_value.find_first.assert_called_once_with(
         where={"creator_username": "creator", "slug": "test-agent"}
     )
-    assert calls[1] == mocker.call(where={"storeListingVersionId": "active-version-id"})
-
-    mock_store_listing_db.return_value.find_first.assert_called_once()
 
 
 @pytest.mark.asyncio(loop_scope="session")
-async def test_get_store_creator_details(mocker):
+async def test_get_store_creator(mocker):
     # Mock data
     mock_creator_data = prisma.models.Creator(
         name="Test Creator",
@@ -202,7 +138,7 @@ async def test_get_store_creator_details(mocker):
     mock_creator.return_value.find_unique.return_value = mock_creator_data
 
     # Call function
-    result = await db.get_store_creator_details("creator")
+    result = await db.get_store_creator("creator")
 
     # Verify results
     assert result.username == "creator"
@@ -218,61 +154,110 @@ async def test_get_store_creator_details(mocker):
 
 @pytest.mark.asyncio(loop_scope="session")
 async def test_create_store_submission(mocker):
-    # Mock data
+    now = datetime.now()
+
+    # Mock agent graph (with no pending submissions) and user with profile
+    mock_profile = prisma.models.Profile(
+        id="profile-id",
+        userId="user-id",
+        name="Test User",
+        username="testuser",
+        description="Test",
+        isFeatured=False,
+        links=[],
+        createdAt=now,
+        updatedAt=now,
+    )
+    mock_user = prisma.models.User(
+        id="user-id",
+        email="test@example.com",
+        createdAt=now,
+        updatedAt=now,
+        Profile=[mock_profile],
+        emailVerified=True,
+        metadata="{}",  # type: ignore[reportArgumentType]
+        integrations="",
+        maxEmailsPerDay=1,
+        notifyOnAgentRun=True,
+        notifyOnZeroBalance=True,
+        notifyOnLowBalance=True,
+        notifyOnBlockExecutionFailed=True,
+        notifyOnContinuousAgentError=True,
+        notifyOnDailySummary=True,
+        notifyOnWeeklySummary=True,
+        notifyOnMonthlySummary=True,
+        notifyOnAgentApproved=True,
+        notifyOnAgentRejected=True,
+        timezone="Europe/Delft",
+    )
     mock_agent = prisma.models.AgentGraph(
         id="agent-id",
         version=1,
         userId="user-id",
-        createdAt=datetime.now(),
+        createdAt=now,
         isActive=True,
+        StoreListingVersions=[],
+        User=mock_user,
     )
 
-    mock_listing = prisma.models.StoreListing(
+    # Mock the created StoreListingVersion (returned by create)
+    mock_store_listing_obj = prisma.models.StoreListing(
         id="listing-id",
-        createdAt=datetime.now(),
-        updatedAt=datetime.now(),
+        createdAt=now,
+        updatedAt=now,
         isDeleted=False,
         hasApprovedVersion=False,
         slug="test-agent",
         agentGraphId="agent-id",
-        agentGraphVersion=1,
         owningUserId="user-id",
-        Versions=[
-            prisma.models.StoreListingVersion(
-                id="version-id",
-                agentGraphId="agent-id",
-                agentGraphVersion=1,
-                name="Test Agent",
-                description="Test description",
-                createdAt=datetime.now(),
-                updatedAt=datetime.now(),
-                subHeading="Test heading",
-                imageUrls=["image.jpg"],
-                categories=["test"],
-                isFeatured=False,
-                isDeleted=False,
-                version=1,
-                storeListingId="listing-id",
-                submissionStatus=prisma.enums.SubmissionStatus.PENDING,
-                isAvailable=True,
-            )
-        ],
         useForOnboarding=False,
     )
+    mock_version = prisma.models.StoreListingVersion(
+        id="version-id",
+        agentGraphId="agent-id",
+        agentGraphVersion=1,
+        name="Test Agent",
+        description="Test description",
+        createdAt=now,
+        updatedAt=now,
+        subHeading="",
+        imageUrls=[],
+        categories=[],
+        isFeatured=False,
+        isDeleted=False,
+        version=1,
+        storeListingId="listing-id",
+        submissionStatus=prisma.enums.SubmissionStatus.PENDING,
+        isAvailable=True,
+        submittedAt=now,
+        StoreListing=mock_store_listing_obj,
+    )
 
     # Mock prisma calls
     mock_agent_graph = mocker.patch("prisma.models.AgentGraph.prisma")
     mock_agent_graph.return_value.find_first = mocker.AsyncMock(return_value=mock_agent)
 
-    mock_store_listing = mocker.patch("prisma.models.StoreListing.prisma")
-    mock_store_listing.return_value.find_first = mocker.AsyncMock(return_value=None)
-    mock_store_listing.return_value.create = mocker.AsyncMock(return_value=mock_listing)
+    # Mock transaction context manager
+    mock_tx = mocker.MagicMock()
+    mocker.patch(
+        "backend.api.features.store.db.transaction",
+        return_value=mocker.AsyncMock(
+            __aenter__=mocker.AsyncMock(return_value=mock_tx),
+            __aexit__=mocker.AsyncMock(return_value=False),
+        ),
+    )
+
+    mock_sl = mocker.patch("prisma.models.StoreListing.prisma")
+    mock_sl.return_value.find_unique = mocker.AsyncMock(return_value=None)
+
+    mock_slv = mocker.patch("prisma.models.StoreListingVersion.prisma")
+    mock_slv.return_value.create = mocker.AsyncMock(return_value=mock_version)
 
     # Call function
     result = await db.create_store_submission(
         user_id="user-id",
-        agent_id="agent-id",
-        agent_version=1,
+        graph_id="agent-id",
+        graph_version=1,
         slug="test-agent",
         name="Test Agent",
         description="Test description",
@@ -281,11 +266,11 @@ async def test_create_store_submission(mocker):
     # Verify results
     assert result.name == "Test Agent"
     assert result.description == "Test description"
-    assert result.store_listing_version_id == "version-id"
+    assert result.listing_version_id == "version-id"
 
     # Verify mocks called correctly
     mock_agent_graph.return_value.find_first.assert_called_once()
-    mock_store_listing.return_value.create.assert_called_once()
+    mock_slv.return_value.create.assert_called_once()
 
 
 @pytest.mark.asyncio(loop_scope="session")
@@ -318,7 +303,6 @@ async def test_update_profile(mocker):
         description="Test description",
         links=["link1"],
         avatar_url="avatar.jpg",
-        is_featured=False,
     )
 
     # Call function
@@ -389,7 +373,7 @@ async def test_get_store_agents_with_search_and_filters_parameterized():
         creators=["creator1'; DROP TABLE Users; --", "creator2"],
         category="AI'; DELETE FROM StoreAgent; --",
         featured=True,
-        sorted_by="rating",
+        sorted_by=db.StoreAgentsSortOptions.RATING,
         page=1,
         page_size=20,
     )

autogpt_platform/backend/backend/api/features/store/exceptions.py

@@ -57,12 +57,6 @@ class StoreError(ValueError):
     pass
 
 
-class AgentNotFoundError(NotFoundError):
-    """Raised when an agent is not found"""
-
-    pass
-
-
 class CreatorNotFoundError(NotFoundError):
     """Raised when a creator is not found"""
 

autogpt_platform/backend/backend/api/features/store/hybrid_search.py

@@ -568,7 +568,7 @@ async def hybrid_search(
             SELECT uce."contentId" as "storeListingVersionId"
             FROM {{schema_prefix}}"UnifiedContentEmbedding" uce
             INNER JOIN {{schema_prefix}}"StoreAgent" sa
-                ON uce."contentId" = sa."storeListingVersionId"
+                ON uce."contentId" = sa.listing_version_id
             WHERE uce."contentType" = 'STORE_AGENT'::{{schema_prefix}}"ContentType"
             AND uce."userId" IS NULL
             AND uce.search @@ plainto_tsquery('english', {query_param})
@@ -582,7 +582,7 @@ async def hybrid_search(
                 SELECT uce."contentId", uce.embedding
                 FROM {{schema_prefix}}"UnifiedContentEmbedding" uce
                 INNER JOIN {{schema_prefix}}"StoreAgent" sa
-                    ON uce."contentId" = sa."storeListingVersionId"
+                    ON uce."contentId" = sa.listing_version_id
                 WHERE uce."contentType" = 'STORE_AGENT'::{{schema_prefix}}"ContentType"
                 AND uce."userId" IS NULL
                 AND {where_clause}
@@ -605,7 +605,7 @@ async def hybrid_search(
                 sa.featured,
                 sa.is_available,
                 sa.updated_at,
-                sa."agentGraphId",
+                sa.graph_id,
                 -- Searchable text for BM25 reranking
                 COALESCE(sa.agent_name, '') || ' ' || COALESCE(sa.sub_heading, '') || ' ' || COALESCE(sa.description, '') as searchable_text,
                 -- Semantic score
@@ -627,9 +627,9 @@ async def hybrid_search(
                 sa.runs as popularity_raw
             FROM candidates c
             INNER JOIN {{schema_prefix}}"StoreAgent" sa
-                ON c."storeListingVersionId" = sa."storeListingVersionId"
+                ON c."storeListingVersionId" = sa.listing_version_id
             INNER JOIN {{schema_prefix}}"UnifiedContentEmbedding" uce
-                ON sa."storeListingVersionId" = uce."contentId"
+                ON sa.listing_version_id = uce."contentId"
                 AND uce."contentType" = 'STORE_AGENT'::{{schema_prefix}}"ContentType"
         ),
         max_vals AS (
@@ -665,7 +665,7 @@ async def hybrid_search(
                 featured,
                 is_available,
                 updated_at,
-                "agentGraphId",
+                graph_id,
                 searchable_text,
                 semantic_score,
                 lexical_score,

autogpt_platform/backend/backend/api/features/store/model.py

@@ -1,11 +1,14 @@
 import datetime
-from typing import List
+from typing import TYPE_CHECKING, List, Self
 
 import prisma.enums
 import pydantic
 
 from backend.util.models import Pagination
 
+if TYPE_CHECKING:
+    import prisma.models
+
 
 class ChangelogEntry(pydantic.BaseModel):
     version: str
@@ -13,9 +16,9 @@ class ChangelogEntry(pydantic.BaseModel):
     date: datetime.datetime
 
 
-class MyAgent(pydantic.BaseModel):
-    agent_id: str
-    agent_version: int
+class MyUnpublishedAgent(pydantic.BaseModel):
+    graph_id: str
+    graph_version: int
     agent_name: str
     agent_image: str | None = None
     description: str
@@ -23,8 +26,8 @@ class MyAgent(pydantic.BaseModel):
     recommended_schedule_cron: str | None = None
 
 
-class MyAgentsResponse(pydantic.BaseModel):
-    agents: list[MyAgent]
+class MyUnpublishedAgentsResponse(pydantic.BaseModel):
+    agents: list[MyUnpublishedAgent]
     pagination: Pagination
 
 
@@ -40,6 +43,21 @@ class StoreAgent(pydantic.BaseModel):
     rating: float
     agent_graph_id: str
 
+    @classmethod
+    def from_db(cls, agent: "prisma.models.StoreAgent") -> "StoreAgent":
+        return cls(
+            slug=agent.slug,
+            agent_name=agent.agent_name,
+            agent_image=agent.agent_image[0] if agent.agent_image else "",
+            creator=agent.creator_username or "Needs Profile",
+            creator_avatar=agent.creator_avatar or "",
+            sub_heading=agent.sub_heading,
+            description=agent.description,
+            runs=agent.runs,
+            rating=agent.rating,
+            agent_graph_id=agent.graph_id,
+        )
+
 
 class StoreAgentsResponse(pydantic.BaseModel):
     agents: list[StoreAgent]
@@ -62,81 +80,192 @@ class StoreAgentDetails(pydantic.BaseModel):
     runs: int
     rating: float
     versions: list[str]
-    agentGraphVersions: list[str]
-    agentGraphId: str
+    graph_id: str
+    graph_versions: list[str]
     last_updated: datetime.datetime
     recommended_schedule_cron: str | None = None
 
-    active_version_id: str | None = None
-    has_approved_version: bool = False
+    active_version_id: str
+    has_approved_version: bool
 
     # Optional changelog data when include_changelog=True
     changelog: list[ChangelogEntry] | None = None
 
-
-class Creator(pydantic.BaseModel):
-    name: str
-    username: str
-    description: str
-    avatar_url: str
-    num_agents: int
-    agent_rating: float
-    agent_runs: int
-    is_featured: bool
-
-
-class CreatorsResponse(pydantic.BaseModel):
-    creators: List[Creator]
-    pagination: Pagination
-
-
-class CreatorDetails(pydantic.BaseModel):
-    name: str
-    username: str
-    description: str
-    links: list[str]
-    avatar_url: str
-    agent_rating: float
-    agent_runs: int
-    top_categories: list[str]
+    @classmethod
+    def from_db(cls, agent: "prisma.models.StoreAgent") -> "StoreAgentDetails":
+        return cls(
+            store_listing_version_id=agent.listing_version_id,
+            slug=agent.slug,
+            agent_name=agent.agent_name,
+            agent_video=agent.agent_video or "",
+            agent_output_demo=agent.agent_output_demo or "",
+            agent_image=agent.agent_image,
+            creator=agent.creator_username or "",
+            creator_avatar=agent.creator_avatar or "",
+            sub_heading=agent.sub_heading,
+            description=agent.description,
+            categories=agent.categories,
+            runs=agent.runs,
+            rating=agent.rating,
+            versions=agent.versions,
+            graph_id=agent.graph_id,
+            graph_versions=agent.graph_versions,
+            last_updated=agent.updated_at,
+            recommended_schedule_cron=agent.recommended_schedule_cron,
+            active_version_id=agent.listing_version_id,
+            has_approved_version=True,  # StoreAgent view only has approved agents
+        )
 
 
 class Profile(pydantic.BaseModel):
-    name: str
+    """Marketplace user profile (only attributes that the user can update)"""
+
     username: str
+    name: str
     description: str
+    avatar_url: str | None
     links: list[str]
-    avatar_url: str
-    is_featured: bool = False
+
+
+class ProfileDetails(Profile):
+    """Marketplace user profile (including read-only fields)"""
+
+    is_featured: bool
+
+    @classmethod
+    def from_db(cls, profile: "prisma.models.Profile") -> "ProfileDetails":
+        return cls(
+            name=profile.name,
+            username=profile.username,
+            avatar_url=profile.avatarUrl,
+            description=profile.description,
+            links=profile.links,
+            is_featured=profile.isFeatured,
+        )
+
+
+class CreatorDetails(ProfileDetails):
+    """Marketplace creator profile details, including aggregated stats"""
+
+    num_agents: int
+    agent_runs: int
+    agent_rating: float
+    top_categories: list[str]
+
+    @classmethod
+    def from_db(cls, creator: "prisma.models.Creator") -> "CreatorDetails":  # type: ignore[override]
+        return cls(
+            name=creator.name,
+            username=creator.username,
+            avatar_url=creator.avatar_url,
+            description=creator.description,
+            links=creator.links,
+            is_featured=creator.is_featured,
+            num_agents=creator.num_agents,
+            agent_runs=creator.agent_runs,
+            agent_rating=creator.agent_rating,
+            top_categories=creator.top_categories,
+        )
+
+
+class CreatorsResponse(pydantic.BaseModel):
+    creators: List[CreatorDetails]
+    pagination: Pagination
 
 
 class StoreSubmission(pydantic.BaseModel):
+    # From StoreListing:
     listing_id: str
-    agent_id: str
-    agent_version: int
+    user_id: str
+    slug: str
+
+    # From StoreListingVersion:
+    listing_version_id: str
+    listing_version: int
+    graph_id: str
+    graph_version: int
     name: str
     sub_heading: str
-    slug: str
     description: str
-    instructions: str | None = None
+    instructions: str | None
+    categories: list[str]
     image_urls: list[str]
-    date_submitted: datetime.datetime
-    status: prisma.enums.SubmissionStatus
-    runs: int
-    rating: float
-    store_listing_version_id: str | None = None
-    version: int | None = None  # Actual version number from the database
+    video_url: str | None
+    agent_output_demo_url: str | None
 
+    submitted_at: datetime.datetime | None
+    changes_summary: str | None
+    status: prisma.enums.SubmissionStatus
+    reviewed_at: datetime.datetime | None = None
     reviewer_id: str | None = None
     review_comments: str | None = None  # External comments visible to creator
-    internal_comments: str | None = None  # Private notes for admin use only
-    reviewed_at: datetime.datetime | None = None
-    changes_summary: str | None = None
 
-    # Additional fields for editing
-    video_url: str | None = None
-    agent_output_demo_url: str | None = None
-    categories: list[str] = []
+    # Aggregated from AgentGraphExecutions and StoreListingReviews:
+    run_count: int = 0
+    review_count: int = 0
+    review_avg_rating: float = 0.0
+
+    @classmethod
+    def from_db(cls, _sub: "prisma.models.StoreSubmission") -> Self:
+        """Construct from the StoreSubmission Prisma view."""
+        return cls(
+            listing_id=_sub.listing_id,
+            user_id=_sub.user_id,
+            slug=_sub.slug,
+            listing_version_id=_sub.listing_version_id,
+            listing_version=_sub.listing_version,
+            graph_id=_sub.graph_id,
+            graph_version=_sub.graph_version,
+            name=_sub.name,
+            sub_heading=_sub.sub_heading,
+            description=_sub.description,
+            instructions=_sub.instructions,
+            categories=_sub.categories,
+            image_urls=_sub.image_urls,
+            video_url=_sub.video_url,
+            agent_output_demo_url=_sub.agent_output_demo_url,
+            submitted_at=_sub.submitted_at,
+            changes_summary=_sub.changes_summary,
+            status=_sub.status,
+            reviewed_at=_sub.reviewed_at,
+            reviewer_id=_sub.reviewer_id,
+            review_comments=_sub.review_comments,
+            run_count=_sub.run_count,
+            review_count=_sub.review_count,
+            review_avg_rating=_sub.review_avg_rating,
+        )
+
+    @classmethod
+    def from_listing_version(cls, _lv: "prisma.models.StoreListingVersion") -> Self:
+        """
+        Construct from the StoreListingVersion Prisma model (with StoreListing included)
+        """
+        if not (_l := _lv.StoreListing):
+            raise ValueError("StoreListingVersion must have included StoreListing")
+
+        return cls(
+            listing_id=_l.id,
+            user_id=_l.owningUserId,
+            slug=_l.slug,
+            listing_version_id=_lv.id,
+            listing_version=_lv.version,
+            graph_id=_lv.agentGraphId,
+            graph_version=_lv.agentGraphVersion,
+            name=_lv.name,
+            sub_heading=_lv.subHeading,
+            description=_lv.description,
+            instructions=_lv.instructions,
+            categories=_lv.categories,
+            image_urls=_lv.imageUrls,
+            video_url=_lv.videoUrl,
+            agent_output_demo_url=_lv.agentOutputDemoUrl,
+            submitted_at=_lv.submittedAt,
+            changes_summary=_lv.changesSummary,
+            status=_lv.submissionStatus,
+            reviewed_at=_lv.reviewedAt,
+            reviewer_id=_lv.reviewerId,
+            review_comments=_lv.reviewComments,
+        )
 
 
 class StoreSubmissionsResponse(pydantic.BaseModel):
@@ -144,33 +273,12 @@ class StoreSubmissionsResponse(pydantic.BaseModel):
     pagination: Pagination
 
 
-class StoreListingWithVersions(pydantic.BaseModel):
-    """A store listing with its version history"""
-
-    listing_id: str
-    slug: str
-    agent_id: str
-    agent_version: int
-    active_version_id: str | None = None
-    has_approved_version: bool = False
-    creator_email: str | None = None
-    latest_version: StoreSubmission | None = None
-    versions: list[StoreSubmission] = []
-
-
-class StoreListingsWithVersionsResponse(pydantic.BaseModel):
-    """Response model for listings with version history"""
-
-    listings: list[StoreListingWithVersions]
-    pagination: Pagination
-
-
 class StoreSubmissionRequest(pydantic.BaseModel):
-    agent_id: str = pydantic.Field(
-        ..., min_length=1, description="Agent ID cannot be empty"
+    graph_id: str = pydantic.Field(
+        ..., min_length=1, description="Graph ID cannot be empty"
     )
-    agent_version: int = pydantic.Field(
-        ..., gt=0, description="Agent version must be greater than 0"
+    graph_version: int = pydantic.Field(
+        ..., gt=0, description="Graph version must be greater than 0"
     )
     slug: str
     name: str
@@ -198,12 +306,42 @@ class StoreSubmissionEditRequest(pydantic.BaseModel):
     recommended_schedule_cron: str | None = None
 
 
-class ProfileDetails(pydantic.BaseModel):
-    name: str
-    username: str
-    description: str
-    links: list[str]
-    avatar_url: str | None = None
+class StoreSubmissionAdminView(StoreSubmission):
+    internal_comments: str | None  # Private admin notes
+
+    @classmethod
+    def from_db(cls, _sub: "prisma.models.StoreSubmission") -> Self:
+        return cls(
+            **StoreSubmission.from_db(_sub).model_dump(),
+            internal_comments=_sub.internal_comments,
+        )
+
+    @classmethod
+    def from_listing_version(cls, _lv: "prisma.models.StoreListingVersion") -> Self:
+        return cls(
+            **StoreSubmission.from_listing_version(_lv).model_dump(),
+            internal_comments=_lv.internalComments,
+        )
+
+
+class StoreListingWithVersionsAdminView(pydantic.BaseModel):
+    """A store listing with its version history"""
+
+    listing_id: str
+    graph_id: str
+    slug: str
+    active_listing_version_id: str | None = None
+    has_approved_version: bool = False
+    creator_email: str | None = None
+    latest_version: StoreSubmissionAdminView | None = None
+    versions: list[StoreSubmissionAdminView] = []
+
+
+class StoreListingsWithVersionsAdminViewResponse(pydantic.BaseModel):
+    """Response model for listings with version history"""
+
+    listings: list[StoreListingWithVersionsAdminView]
+    pagination: Pagination
 
 
 class StoreReview(pydantic.BaseModel):

autogpt_platform/backend/backend/api/features/store/model_test.py

@@ -1,203 +0,0 @@
-import datetime
-
-import prisma.enums
-
-from . import model as store_model
-
-
-def test_pagination():
-    pagination = store_model.Pagination(
-        total_items=100, total_pages=5, current_page=2, page_size=20
-    )
-    assert pagination.total_items == 100
-    assert pagination.total_pages == 5
-    assert pagination.current_page == 2
-    assert pagination.page_size == 20
-
-
-def test_store_agent():
-    agent = store_model.StoreAgent(
-        slug="test-agent",
-        agent_name="Test Agent",
-        agent_image="test.jpg",
-        creator="creator1",
-        creator_avatar="avatar.jpg",
-        sub_heading="Test subheading",
-        description="Test description",
-        runs=50,
-        rating=4.5,
-        agent_graph_id="test-graph-id",
-    )
-    assert agent.slug == "test-agent"
-    assert agent.agent_name == "Test Agent"
-    assert agent.runs == 50
-    assert agent.rating == 4.5
-    assert agent.agent_graph_id == "test-graph-id"
-
-
-def test_store_agents_response():
-    response = store_model.StoreAgentsResponse(
-        agents=[
-            store_model.StoreAgent(
-                slug="test-agent",
-                agent_name="Test Agent",
-                agent_image="test.jpg",
-                creator="creator1",
-                creator_avatar="avatar.jpg",
-                sub_heading="Test subheading",
-                description="Test description",
-                runs=50,
-                rating=4.5,
-                agent_graph_id="test-graph-id",
-            )
-        ],
-        pagination=store_model.Pagination(
-            total_items=1, total_pages=1, current_page=1, page_size=20
-        ),
-    )
-    assert len(response.agents) == 1
-    assert response.pagination.total_items == 1
-
-
-def test_store_agent_details():
-    details = store_model.StoreAgentDetails(
-        store_listing_version_id="version123",
-        slug="test-agent",
-        agent_name="Test Agent",
-        agent_video="video.mp4",
-        agent_output_demo="demo.mp4",
-        agent_image=["image1.jpg", "image2.jpg"],
-        creator="creator1",
-        creator_avatar="avatar.jpg",
-        sub_heading="Test subheading",
-        description="Test description",
-        categories=["cat1", "cat2"],
-        runs=50,
-        rating=4.5,
-        versions=["1.0", "2.0"],
-        agentGraphVersions=["1", "2"],
-        agentGraphId="test-graph-id",
-        last_updated=datetime.datetime.now(),
-    )
-    assert details.slug == "test-agent"
-    assert len(details.agent_image) == 2
-    assert len(details.categories) == 2
-    assert len(details.versions) == 2
-
-
-def test_creator():
-    creator = store_model.Creator(
-        agent_rating=4.8,
-        agent_runs=1000,
-        name="Test Creator",
-        username="creator1",
-        description="Test description",
-        avatar_url="avatar.jpg",
-        num_agents=5,
-        is_featured=False,
-    )
-    assert creator.name == "Test Creator"
-    assert creator.num_agents == 5
-
-
-def test_creators_response():
-    response = store_model.CreatorsResponse(
-        creators=[
-            store_model.Creator(
-                agent_rating=4.8,
-                agent_runs=1000,
-                name="Test Creator",
-                username="creator1",
-                description="Test description",
-                avatar_url="avatar.jpg",
-                num_agents=5,
-                is_featured=False,
-            )
-        ],
-        pagination=store_model.Pagination(
-            total_items=1, total_pages=1, current_page=1, page_size=20
-        ),
-    )
-    assert len(response.creators) == 1
-    assert response.pagination.total_items == 1
-
-
-def test_creator_details():
-    details = store_model.CreatorDetails(
-        name="Test Creator",
-        username="creator1",
-        description="Test description",
-        links=["link1.com", "link2.com"],
-        avatar_url="avatar.jpg",
-        agent_rating=4.8,
-        agent_runs=1000,
-        top_categories=["cat1", "cat2"],
-    )
-    assert details.name == "Test Creator"
-    assert len(details.links) == 2
-    assert details.agent_rating == 4.8
-    assert len(details.top_categories) == 2
-
-
-def test_store_submission():
-    submission = store_model.StoreSubmission(
-        listing_id="listing123",
-        agent_id="agent123",
-        agent_version=1,
-        sub_heading="Test subheading",
-        name="Test Agent",
-        slug="test-agent",
-        description="Test description",
-        image_urls=["image1.jpg", "image2.jpg"],
-        date_submitted=datetime.datetime(2023, 1, 1),
-        status=prisma.enums.SubmissionStatus.PENDING,
-        runs=50,
-        rating=4.5,
-    )
-    assert submission.name == "Test Agent"
-    assert len(submission.image_urls) == 2
-    assert submission.status == prisma.enums.SubmissionStatus.PENDING
-
-
-def test_store_submissions_response():
-    response = store_model.StoreSubmissionsResponse(
-        submissions=[
-            store_model.StoreSubmission(
-                listing_id="listing123",
-                agent_id="agent123",
-                agent_version=1,
-                sub_heading="Test subheading",
-                name="Test Agent",
-                slug="test-agent",
-                description="Test description",
-                image_urls=["image1.jpg"],
-                date_submitted=datetime.datetime(2023, 1, 1),
-                status=prisma.enums.SubmissionStatus.PENDING,
-                runs=50,
-                rating=4.5,
-            )
-        ],
-        pagination=store_model.Pagination(
-            total_items=1, total_pages=1, current_page=1, page_size=20
-        ),
-    )
-    assert len(response.submissions) == 1
-    assert response.pagination.total_items == 1
-
-
-def test_store_submission_request():
-    request = store_model.StoreSubmissionRequest(
-        agent_id="agent123",
-        agent_version=1,
-        slug="test-agent",
-        name="Test Agent",
-        sub_heading="Test subheading",
-        video_url="video.mp4",
-        image_urls=["image1.jpg", "image2.jpg"],
-        description="Test description",
-        categories=["cat1", "cat2"],
-    )
-    assert request.agent_id == "agent123"
-    assert request.agent_version == 1
-    assert len(request.image_urls) == 2
-    assert len(request.categories) == 2

autogpt_platform/backend/backend/api/features/store/routes.py

@@ -1,16 +1,17 @@
 import logging
 import tempfile
-import typing
 import urllib.parse
-from typing import Literal
 
 import autogpt_libs.auth
 import fastapi
 import fastapi.responses
 import prisma.enums
+from fastapi import Query, Security
+from pydantic import BaseModel
 
 import backend.data.graph
 import backend.util.json
+from backend.util.exceptions import NotFoundError
 from backend.util.models import Pagination
 
 from . import cache as store_cache
@@ -34,22 +35,15 @@ router = fastapi.APIRouter()
     "/profile",
     summary="Get user profile",
     tags=["store", "private"],
-    dependencies=[fastapi.Security(autogpt_libs.auth.requires_user)],
-    response_model=store_model.ProfileDetails,
+    dependencies=[Security(autogpt_libs.auth.requires_user)],
 )
 async def get_profile(
-    user_id: str = fastapi.Security(autogpt_libs.auth.get_user_id),
-):
-    """
-    Get the profile details for the authenticated user.
-    Cached for 1 hour per user.
-    """
+    user_id: str = Security(autogpt_libs.auth.get_user_id),
+) -> store_model.ProfileDetails:
+    """Get the profile details for the authenticated user."""
     profile = await store_db.get_user_profile(user_id)
     if profile is None:
-        return fastapi.responses.JSONResponse(
-            status_code=404,
-            content={"detail": "Profile not found"},
-        )
+        raise NotFoundError("User does not have a profile yet")
     return profile
 
 
@@ -57,98 +51,17 @@ async def get_profile(
     "/profile",
     summary="Update user profile",
     tags=["store", "private"],
-    dependencies=[fastapi.Security(autogpt_libs.auth.requires_user)],
-    response_model=store_model.CreatorDetails,
+    dependencies=[Security(autogpt_libs.auth.requires_user)],
 )
 async def update_or_create_profile(
     profile: store_model.Profile,
-    user_id: str = fastapi.Security(autogpt_libs.auth.get_user_id),
-):
-    """
-    Update the store profile for the authenticated user.
-
-    Args:
-        profile (Profile): The updated profile details
-        user_id (str): ID of the authenticated user
-
-    Returns:
-        CreatorDetails: The updated profile
-
-    Raises:
-        HTTPException: If there is an error updating the profile
-    """
+    user_id: str = Security(autogpt_libs.auth.get_user_id),
+) -> store_model.ProfileDetails:
+    """Update the store profile for the authenticated user."""
     updated_profile = await store_db.update_profile(user_id=user_id, profile=profile)
     return updated_profile
 
 
-##############################################
-############### Agent Endpoints ##############
-##############################################
-
-
-@router.get(
-    "/agents",
-    summary="List store agents",
-    tags=["store", "public"],
-    response_model=store_model.StoreAgentsResponse,
-)
-async def get_agents(
-    featured: bool = False,
-    creator: str | None = None,
-    sorted_by: Literal["rating", "runs", "name", "updated_at"] | None = None,
-    search_query: str | None = None,
-    category: str | None = None,
-    page: int = 1,
-    page_size: int = 20,
-):
-    """
-    Get a paginated list of agents from the store with optional filtering and sorting.
-
-    Args:
-        featured (bool, optional): Filter to only show featured agents. Defaults to False.
-        creator (str | None, optional): Filter agents by creator username. Defaults to None.
-        sorted_by (str | None, optional): Sort agents by "runs" or "rating". Defaults to None.
-        search_query (str | None, optional): Search agents by name, subheading and description. Defaults to None.
-        category (str | None, optional): Filter agents by category. Defaults to None.
-        page (int, optional): Page number for pagination. Defaults to 1.
-        page_size (int, optional): Number of agents per page. Defaults to 20.
-
-    Returns:
-        StoreAgentsResponse: Paginated list of agents matching the filters
-
-    Raises:
-        HTTPException: If page or page_size are less than 1
-
-    Used for:
-    - Home Page Featured Agents
-    - Home Page Top Agents
-    - Search Results
-    - Agent Details - Other Agents By Creator
-    - Agent Details - Similar Agents
-    - Creator Details - Agents By Creator
-    """
-    if page < 1:
-        raise fastapi.HTTPException(
-            status_code=422, detail="Page must be greater than 0"
-        )
-
-    if page_size < 1:
-        raise fastapi.HTTPException(
-            status_code=422, detail="Page size must be greater than 0"
-        )
-
-    agents = await store_cache._get_cached_store_agents(
-        featured=featured,
-        creator=creator,
-        sorted_by=sorted_by,
-        search_query=search_query,
-        category=category,
-        page=page,
-        page_size=page_size,
-    )
-    return agents
-
-
 ##############################################
 ############### Search Endpoints #############
 ##############################################
@@ -158,60 +71,30 @@ async def get_agents(
     "/search",
     summary="Unified search across all content types",
     tags=["store", "public"],
-    response_model=store_model.UnifiedSearchResponse,
 )
 async def unified_search(
     query: str,
-    content_types: list[str] | None = fastapi.Query(
+    content_types: list[prisma.enums.ContentType] | None = Query(
         default=None,
-        description="Content types to search: STORE_AGENT, BLOCK, DOCUMENTATION. If not specified, searches all.",
+        description="Content types to search. If not specified, searches all.",
     ),
-    page: int = 1,
-    page_size: int = 20,
-    user_id: str | None = fastapi.Security(
+    page: int = Query(ge=1, default=1),
+    page_size: int = Query(ge=1, default=20),
+    user_id: str | None = Security(
         autogpt_libs.auth.get_optional_user_id, use_cache=False
     ),
-):
+) -> store_model.UnifiedSearchResponse:
     """
-    Search across all content types (store agents, blocks, documentation) using hybrid search.
+    Search across all content types (marketplace agents, blocks, documentation)
+    using hybrid search.
 
     Combines semantic (embedding-based) and lexical (text-based) search for best results.
-
-    Args:
-        query: The search query string
-        content_types: Optional list of content types to filter by (STORE_AGENT, BLOCK, DOCUMENTATION)
-        page: Page number for pagination (default 1)
-        page_size: Number of results per page (default 20)
-        user_id: Optional authenticated user ID (for user-scoped content in future)
-
-    Returns:
-        UnifiedSearchResponse: Paginated list of search results with relevance scores
     """
-    if page < 1:
-        raise fastapi.HTTPException(
-            status_code=422, detail="Page must be greater than 0"
-        )
-
-    if page_size < 1:
-        raise fastapi.HTTPException(
-            status_code=422, detail="Page size must be greater than 0"
-        )
-
-    # Convert string content types to enum
-    content_type_enums: list[prisma.enums.ContentType] | None = None
-    if content_types:
-        try:
-            content_type_enums = [prisma.enums.ContentType(ct) for ct in content_types]
-        except ValueError as e:
-            raise fastapi.HTTPException(
-                status_code=422,
-                detail=f"Invalid content type. Valid values: STORE_AGENT, BLOCK, DOCUMENTATION. Error: {e}",
-            )
 
     # Perform unified hybrid search
     results, total = await store_hybrid_search.unified_hybrid_search(
         query=query,
-        content_types=content_type_enums,
+        content_types=content_types,
         user_id=user_id,
         page=page,
         page_size=page_size,
@@ -245,22 +128,69 @@ async def unified_search(
     )
 
 
+##############################################
+############### Agent Endpoints ##############
+##############################################
+
+
+@router.get(
+    "/agents",
+    summary="List store agents",
+    tags=["store", "public"],
+)
+async def get_agents(
+    featured: bool = Query(
+        default=False, description="Filter to only show featured agents"
+    ),
+    creator: str | None = Query(
+        default=None, description="Filter agents by creator username"
+    ),
+    category: str | None = Query(default=None, description="Filter agents by category"),
+    search_query: str | None = Query(
+        default=None, description="Literal + semantic search on names and descriptions"
+    ),
+    sorted_by: store_db.StoreAgentsSortOptions | None = Query(
+        default=None,
+        description="Property to sort results by. Ignored if search_query is provided.",
+    ),
+    page: int = Query(ge=1, default=1),
+    page_size: int = Query(ge=1, default=20),
+) -> store_model.StoreAgentsResponse:
+    """
+    Get a paginated list of agents from the marketplace,
+    with optional filtering and sorting.
+
+    Used for:
+    - Home Page Featured Agents
+    - Home Page Top Agents
+    - Search Results
+    - Agent Details - Other Agents By Creator
+    - Agent Details - Similar Agents
+    - Creator Details - Agents By Creator
+    """
+    agents = await store_cache._get_cached_store_agents(
+        featured=featured,
+        creator=creator,
+        sorted_by=sorted_by,
+        search_query=search_query,
+        category=category,
+        page=page,
+        page_size=page_size,
+    )
+    return agents
+
+
 @router.get(
     "/agents/{username}/{agent_name}",
     summary="Get specific agent",
     tags=["store", "public"],
-    response_model=store_model.StoreAgentDetails,
 )
-async def get_agent(
+async def get_agent_by_name(
     username: str,
     agent_name: str,
-    include_changelog: bool = fastapi.Query(default=False),
-):
-    """
-    This is only used on the AgentDetails Page.
-
-    It returns the store listing agents details.
-    """
+    include_changelog: bool = Query(default=False),
+) -> store_model.StoreAgentDetails:
+    """Get details of a marketplace agent"""
     username = urllib.parse.unquote(username).lower()
     # URL decode the agent name since it comes from the URL path
     agent_name = urllib.parse.unquote(agent_name).lower()
@@ -270,76 +200,82 @@ async def get_agent(
     return agent
 
 
-@router.get(
-    "/graph/{store_listing_version_id}",
-    summary="Get agent graph",
-    tags=["store"],
-    dependencies=[fastapi.Security(autogpt_libs.auth.requires_user)],
-)
-async def get_graph_meta_by_store_listing_version_id(
-    store_listing_version_id: str,
-) -> backend.data.graph.GraphModelWithoutNodes:
-    """
-    Get Agent Graph from Store Listing Version ID.
-    """
-    graph = await store_db.get_available_graph(store_listing_version_id)
-    return graph
-
-
-@router.get(
-    "/agents/{store_listing_version_id}",
-    summary="Get agent by version",
-    tags=["store"],
-    dependencies=[fastapi.Security(autogpt_libs.auth.requires_user)],
-    response_model=store_model.StoreAgentDetails,
-)
-async def get_store_agent(store_listing_version_id: str):
-    """
-    Get Store Agent Details from Store Listing Version ID.
-    """
-    agent = await store_db.get_store_agent_by_version_id(store_listing_version_id)
-
-    return agent
-
-
 @router.post(
     "/agents/{username}/{agent_name}/review",
     summary="Create agent review",
     tags=["store"],
-    dependencies=[fastapi.Security(autogpt_libs.auth.requires_user)],
-    response_model=store_model.StoreReview,
+    dependencies=[Security(autogpt_libs.auth.requires_user)],
 )
-async def create_review(
+async def post_user_review_for_agent(
     username: str,
     agent_name: str,
     review: store_model.StoreReviewCreate,
-    user_id: str = fastapi.Security(autogpt_libs.auth.get_user_id),
-):
-    """
-    Create a review for a store agent.
-
-    Args:
-        username: Creator's username
-        agent_name: Name/slug of the agent
-        review: Review details including score and optional comments
-        user_id: ID of authenticated user creating the review
-
-    Returns:
-        The created review
-    """
+    user_id: str = Security(autogpt_libs.auth.get_user_id),
+) -> store_model.StoreReview:
+    """Post a user review on a marketplace agent listing"""
     username = urllib.parse.unquote(username).lower()
     agent_name = urllib.parse.unquote(agent_name).lower()
-    # Create the review
+
     created_review = await store_db.create_store_review(
         user_id=user_id,
         store_listing_version_id=review.store_listing_version_id,
         score=review.score,
         comments=review.comments,
     )
-
     return created_review
 
 
+@router.get(
+    "/listings/versions/{store_listing_version_id}",
+    summary="Get agent by version",
+    tags=["store"],
+    dependencies=[Security(autogpt_libs.auth.requires_user)],
+)
+async def get_agent_by_listing_version(
+    store_listing_version_id: str,
+) -> store_model.StoreAgentDetails:
+    agent = await store_db.get_store_agent_by_version_id(store_listing_version_id)
+    return agent
+
+
+@router.get(
+    "/listings/versions/{store_listing_version_id}/graph",
+    summary="Get agent graph",
+    tags=["store"],
+    dependencies=[Security(autogpt_libs.auth.requires_user)],
+)
+async def get_graph_meta_by_store_listing_version_id(
+    store_listing_version_id: str,
+) -> backend.data.graph.GraphModelWithoutNodes:
+    """Get outline of graph belonging to a specific marketplace listing version"""
+    graph = await store_db.get_available_graph(store_listing_version_id)
+    return graph
+
+
+@router.get(
+    "/listings/versions/{store_listing_version_id}/graph/download",
+    summary="Download agent file",
+    tags=["store", "public"],
+)
+async def download_agent_file(
+    store_listing_version_id: str,
+) -> fastapi.responses.FileResponse:
+    """Download agent graph file for a specific marketplace listing version"""
+    graph_data = await store_db.get_agent(store_listing_version_id)
+    file_name = f"agent_{graph_data.id}_v{graph_data.version or 'latest'}.json"
+
+    # Sending graph as a stream (similar to marketplace v1)
+    with tempfile.NamedTemporaryFile(
+        mode="w", suffix=".json", delete=False
+    ) as tmp_file:
+        tmp_file.write(backend.util.json.dumps(graph_data))
+        tmp_file.flush()
+
+        return fastapi.responses.FileResponse(
+            tmp_file.name, filename=file_name, media_type="application/json"
+        )
+
+
 ##############################################
 ############# Creator Endpoints #############
 ##############################################
@@ -349,37 +285,19 @@ async def create_review(
     "/creators",
     summary="List store creators",
     tags=["store", "public"],
-    response_model=store_model.CreatorsResponse,
 )
 async def get_creators(
-    featured: bool = False,
-    search_query: str | None = None,
-    sorted_by: Literal["agent_rating", "agent_runs", "num_agents"] | None = None,
-    page: int = 1,
-    page_size: int = 20,
-):
-    """
-    This is needed for:
-    - Home Page Featured Creators
-    - Search Results Page
-
-    ---
-
-    To support this functionality we need:
-    - featured: bool - to limit the list to just featured agents
-    - search_query: str - vector search based on the creators profile description.
-    - sorted_by: [agent_rating, agent_runs] -
-    """
-    if page < 1:
-        raise fastapi.HTTPException(
-            status_code=422, detail="Page must be greater than 0"
-        )
-
-    if page_size < 1:
-        raise fastapi.HTTPException(
-            status_code=422, detail="Page size must be greater than 0"
-        )
-
+    featured: bool = Query(
+        default=False, description="Filter to only show featured creators"
+    ),
+    search_query: str | None = Query(
+        default=None, description="Literal + semantic search on names and descriptions"
+    ),
+    sorted_by: store_db.StoreCreatorsSortOptions | None = None,
+    page: int = Query(ge=1, default=1),
+    page_size: int = Query(ge=1, default=20),
+) -> store_model.CreatorsResponse:
+    """List or search marketplace creators"""
     creators = await store_cache._get_cached_store_creators(
         featured=featured,
         search_query=search_query,
@@ -391,18 +309,13 @@ async def get_creators(
 
 
 @router.get(
-    "/creator/{username}",
+    "/creators/{username}",
     summary="Get creator details",
+    operation_id="getV2GetCreatorDetails",
     tags=["store", "public"],
-    response_model=store_model.CreatorDetails,
 )
-async def get_creator(
-    username: str,
-):
-    """
-    Get the details of a creator.
-    - Creator Details Page
-    """
+async def get_creator(username: str) -> store_model.CreatorDetails:
+    """Get details on a marketplace creator"""
     username = urllib.parse.unquote(username).lower()
     creator = await store_cache._get_cached_creator_details(username=username)
     return creator
@@ -414,20 +327,17 @@ async def get_creator(
 
 
 @router.get(
-    "/myagents",
+    "/my-unpublished-agents",
     summary="Get my agents",
     tags=["store", "private"],
-    dependencies=[fastapi.Security(autogpt_libs.auth.requires_user)],
-    response_model=store_model.MyAgentsResponse,
+    dependencies=[Security(autogpt_libs.auth.requires_user)],
 )
-async def get_my_agents(
-    user_id: str = fastapi.Security(autogpt_libs.auth.get_user_id),
-    page: typing.Annotated[int, fastapi.Query(ge=1)] = 1,
-    page_size: typing.Annotated[int, fastapi.Query(ge=1)] = 20,
-):
-    """
-    Get user's own agents.
-    """
+async def get_my_unpublished_agents(
+    user_id: str = Security(autogpt_libs.auth.get_user_id),
+    page: int = Query(ge=1, default=1),
+    page_size: int = Query(ge=1, default=20),
+) -> store_model.MyUnpublishedAgentsResponse:
+    """List the authenticated user's unpublished agents"""
     agents = await store_db.get_my_agents(user_id, page=page, page_size=page_size)
     return agents
 
@@ -436,28 +346,17 @@ async def get_my_agents(
     "/submissions/{submission_id}",
     summary="Delete store submission",
     tags=["store", "private"],
-    dependencies=[fastapi.Security(autogpt_libs.auth.requires_user)],
-    response_model=bool,
+    dependencies=[Security(autogpt_libs.auth.requires_user)],
 )
 async def delete_submission(
     submission_id: str,
-    user_id: str = fastapi.Security(autogpt_libs.auth.get_user_id),
-):
-    """
-    Delete a store listing submission.
-
-    Args:
-        user_id (str): ID of the authenticated user
-        submission_id (str): ID of the submission to be deleted
-
-    Returns:
-        bool: True if the submission was successfully deleted, False otherwise
-    """
+    user_id: str = Security(autogpt_libs.auth.get_user_id),
+) -> bool:
+    """Delete a marketplace listing submission"""
     result = await store_db.delete_store_submission(
         user_id=user_id,
         submission_id=submission_id,
     )
-
     return result
 
 
@@ -465,37 +364,14 @@ async def delete_submission(
     "/submissions",
     summary="List my submissions",
     tags=["store", "private"],
-    dependencies=[fastapi.Security(autogpt_libs.auth.requires_user)],
-    response_model=store_model.StoreSubmissionsResponse,
+    dependencies=[Security(autogpt_libs.auth.requires_user)],
 )
 async def get_submissions(
-    user_id: str = fastapi.Security(autogpt_libs.auth.get_user_id),
-    page: int = 1,
-    page_size: int = 20,
-):
-    """
-    Get a paginated list of store submissions for the authenticated user.
-
-    Args:
-        user_id (str): ID of the authenticated user
-        page (int, optional): Page number for pagination. Defaults to 1.
-        page_size (int, optional): Number of submissions per page. Defaults to 20.
-
-    Returns:
-        StoreListingsResponse: Paginated list of store submissions
-
-    Raises:
-        HTTPException: If page or page_size are less than 1
-    """
-    if page < 1:
-        raise fastapi.HTTPException(
-            status_code=422, detail="Page must be greater than 0"
-        )
-
-    if page_size < 1:
-        raise fastapi.HTTPException(
-            status_code=422, detail="Page size must be greater than 0"
-        )
+    user_id: str = Security(autogpt_libs.auth.get_user_id),
+    page: int = Query(ge=1, default=1),
+    page_size: int = Query(ge=1, default=20),
+) -> store_model.StoreSubmissionsResponse:
+    """List the authenticated user's marketplace listing submissions"""
     listings = await store_db.get_store_submissions(
         user_id=user_id,
         page=page,
@@ -508,30 +384,17 @@ async def get_submissions(
     "/submissions",
     summary="Create store submission",
     tags=["store", "private"],
-    dependencies=[fastapi.Security(autogpt_libs.auth.requires_user)],
-    response_model=store_model.StoreSubmission,
+    dependencies=[Security(autogpt_libs.auth.requires_user)],
 )
 async def create_submission(
     submission_request: store_model.StoreSubmissionRequest,
-    user_id: str = fastapi.Security(autogpt_libs.auth.get_user_id),
-):
-    """
-    Create a new store listing submission.
-
-    Args:
-        submission_request (StoreSubmissionRequest): The submission details
-        user_id (str): ID of the authenticated user submitting the listing
-
-    Returns:
-        StoreSubmission: The created store submission
-
-    Raises:
-        HTTPException: If there is an error creating the submission
-    """
+    user_id: str = Security(autogpt_libs.auth.get_user_id),
+) -> store_model.StoreSubmission:
+    """Submit a new marketplace listing for review"""
     result = await store_db.create_store_submission(
         user_id=user_id,
-        agent_id=submission_request.agent_id,
-        agent_version=submission_request.agent_version,
+        graph_id=submission_request.graph_id,
+        graph_version=submission_request.graph_version,
         slug=submission_request.slug,
         name=submission_request.name,
         video_url=submission_request.video_url,
@@ -544,7 +407,6 @@ async def create_submission(
         changes_summary=submission_request.changes_summary or "Initial Submission",
         recommended_schedule_cron=submission_request.recommended_schedule_cron,
     )
-
     return result
 
 
@@ -552,28 +414,14 @@ async def create_submission(
     "/submissions/{store_listing_version_id}",
     summary="Edit store submission",
     tags=["store", "private"],
-    dependencies=[fastapi.Security(autogpt_libs.auth.requires_user)],
-    response_model=store_model.StoreSubmission,
+    dependencies=[Security(autogpt_libs.auth.requires_user)],
 )
 async def edit_submission(
     store_listing_version_id: str,
     submission_request: store_model.StoreSubmissionEditRequest,
-    user_id: str = fastapi.Security(autogpt_libs.auth.get_user_id),
-):
-    """
-    Edit an existing store listing submission.
-
-    Args:
-        store_listing_version_id (str): ID of the store listing version to edit
-        submission_request (StoreSubmissionRequest): The updated submission details
-        user_id (str): ID of the authenticated user editing the listing
-
-    Returns:
-        StoreSubmission: The updated store submission
-
-    Raises:
-        HTTPException: If there is an error editing the submission
-    """
+    user_id: str = Security(autogpt_libs.auth.get_user_id),
+) -> store_model.StoreSubmission:
+    """Update a pending marketplace listing submission"""
     result = await store_db.edit_store_submission(
         user_id=user_id,
         store_listing_version_id=store_listing_version_id,
@@ -588,7 +436,6 @@ async def edit_submission(
         changes_summary=submission_request.changes_summary,
         recommended_schedule_cron=submission_request.recommended_schedule_cron,
     )
-
     return result
 
 
@@ -596,115 +443,61 @@ async def edit_submission(
     "/submissions/media",
     summary="Upload submission media",
     tags=["store", "private"],
-    dependencies=[fastapi.Security(autogpt_libs.auth.requires_user)],
+    dependencies=[Security(autogpt_libs.auth.requires_user)],
 )
 async def upload_submission_media(
     file: fastapi.UploadFile,
-    user_id: str = fastapi.Security(autogpt_libs.auth.get_user_id),
-):
-    """
-    Upload media (images/videos) for a store listing submission.
-
-    Args:
-        file (UploadFile): The media file to upload
-        user_id (str): ID of the authenticated user uploading the media
-
-    Returns:
-        str: URL of the uploaded media file
-
-    Raises:
-        HTTPException: If there is an error uploading the media
-    """
+    user_id: str = Security(autogpt_libs.auth.get_user_id),
+) -> str:
+    """Upload media for a marketplace listing submission"""
     media_url = await store_media.upload_media(user_id=user_id, file=file)
     return media_url
 
 
+class ImageURLResponse(BaseModel):
+    image_url: str
+
+
 @router.post(
     "/submissions/generate_image",
     summary="Generate submission image",
     tags=["store", "private"],
-    dependencies=[fastapi.Security(autogpt_libs.auth.requires_user)],
+    dependencies=[Security(autogpt_libs.auth.requires_user)],
 )
 async def generate_image(
-    agent_id: str,
-    user_id: str = fastapi.Security(autogpt_libs.auth.get_user_id),
-) -> fastapi.responses.Response:
+    graph_id: str,
+    user_id: str = Security(autogpt_libs.auth.get_user_id),
+) -> ImageURLResponse:
     """
-    Generate an image for a store listing submission.
-
-    Args:
-        agent_id (str): ID of the agent to generate an image for
-        user_id (str): ID of the authenticated user
-
-    Returns:
-        JSONResponse: JSON containing the URL of the generated image
+    Generate an image for a marketplace listing submission based on the properties
+    of a given graph.
     """
-    agent = await backend.data.graph.get_graph(
-        graph_id=agent_id, version=None, user_id=user_id
+    graph = await backend.data.graph.get_graph(
+        graph_id=graph_id, version=None, user_id=user_id
     )
 
-    if not agent:
-        raise fastapi.HTTPException(
-            status_code=404, detail=f"Agent with ID {agent_id} not found"
-        )
+    if not graph:
+        raise NotFoundError(f"Agent graph #{graph_id} not found")
     # Use .jpeg here since we are generating JPEG images
-    filename = f"agent_{agent_id}.jpeg"
+    filename = f"agent_{graph_id}.jpeg"
 
     existing_url = await store_media.check_media_exists(user_id, filename)
     if existing_url:
-        logger.info(f"Using existing image for agent {agent_id}")
-        return fastapi.responses.JSONResponse(content={"image_url": existing_url})
+        logger.info(f"Using existing image for agent graph {graph_id}")
+        return ImageURLResponse(image_url=existing_url)
     # Generate agent image as JPEG
-    image = await store_image_gen.generate_agent_image(agent=agent)
+    image = await store_image_gen.generate_agent_image(agent=graph)
 
     # Create UploadFile with the correct filename and content_type
     image_file = fastapi.UploadFile(
         file=image,
         filename=filename,
     )
-
     image_url = await store_media.upload_media(
         user_id=user_id, file=image_file, use_file_name=True
     )
 
-    return fastapi.responses.JSONResponse(content={"image_url": image_url})
-
-
-@router.get(
-    "/download/agents/{store_listing_version_id}",
-    summary="Download agent file",
-    tags=["store", "public"],
-)
-async def download_agent_file(
-    store_listing_version_id: str = fastapi.Path(
-        ..., description="The ID of the agent to download"
-    ),
-) -> fastapi.responses.FileResponse:
-    """
-    Download the agent file by streaming its content.
-
-    Args:
-        store_listing_version_id (str): The ID of the agent to download
-
-    Returns:
-        StreamingResponse: A streaming response containing the agent's graph data.
-
-    Raises:
-        HTTPException: If the agent is not found or an unexpected error occurs.
-    """
-    graph_data = await store_db.get_agent(store_listing_version_id)
-    file_name = f"agent_{graph_data.id}_v{graph_data.version or 'latest'}.json"
-
-    # Sending graph as a stream (similar to marketplace v1)
-    with tempfile.NamedTemporaryFile(
-        mode="w", suffix=".json", delete=False
-    ) as tmp_file:
-        tmp_file.write(backend.util.json.dumps(graph_data))
-        tmp_file.flush()
-
-        return fastapi.responses.FileResponse(
-            tmp_file.name, filename=file_name, media_type="application/json"
-        )
+    return ImageURLResponse(image_url=image_url)
 
 
 ##############################################

autogpt_platform/backend/backend/api/features/store/routes_test.py

@@ -8,6 +8,8 @@ import pytest
 import pytest_mock
 from pytest_snapshot.plugin import Snapshot
 
+from backend.api.features.store.db import StoreAgentsSortOptions
+
 from . import model as store_model
 from . import routes as store_routes
 
@@ -196,7 +198,7 @@ def test_get_agents_sorted(
     mock_db_call.assert_called_once_with(
         featured=False,
         creators=None,
-        sorted_by="runs",
+        sorted_by=StoreAgentsSortOptions.RUNS,
         search_query=None,
         category=None,
         page=1,
@@ -380,9 +382,11 @@ def test_get_agent_details(
         runs=100,
         rating=4.5,
         versions=["1.0.0", "1.1.0"],
-        agentGraphVersions=["1", "2"],
-        agentGraphId="test-graph-id",
+        graph_versions=["1", "2"],
+        graph_id="test-graph-id",
         last_updated=FIXED_NOW,
+        active_version_id="test-version-id",
+        has_approved_version=True,
     )
     mock_db_call = mocker.patch("backend.api.features.store.db.get_store_agent_details")
     mock_db_call.return_value = mocked_value
@@ -435,15 +439,17 @@ def test_get_creators_pagination(
 ) -> None:
     mocked_value = store_model.CreatorsResponse(
         creators=[
-            store_model.Creator(
+            store_model.CreatorDetails(
                 name=f"Creator {i}",
                 username=f"creator{i}",
-                description=f"Creator {i} description",
                 avatar_url=f"avatar{i}.jpg",
-                num_agents=1,
-                agent_rating=4.5,
-                agent_runs=100,
+                description=f"Creator {i} description",
+                links=[f"user{i}.link.com"],
                 is_featured=False,
+                num_agents=1,
+                agent_runs=100,
+                agent_rating=4.5,
+                top_categories=["cat1", "cat2", "cat3"],
             )
             for i in range(5)
         ],
@@ -496,19 +502,19 @@ def test_get_creator_details(
     mocked_value = store_model.CreatorDetails(
         name="Test User",
         username="creator1",
+        avatar_url="avatar.jpg",
         description="Test creator description",
         links=["link1.com", "link2.com"],
-        avatar_url="avatar.jpg",
-        agent_rating=4.8,
+        is_featured=True,
+        num_agents=5,
         agent_runs=1000,
+        agent_rating=4.8,
         top_categories=["category1", "category2"],
     )
-    mock_db_call = mocker.patch(
-        "backend.api.features.store.db.get_store_creator_details"
-    )
+    mock_db_call = mocker.patch("backend.api.features.store.db.get_store_creator")
     mock_db_call.return_value = mocked_value
 
-    response = client.get("/creator/creator1")
+    response = client.get("/creators/creator1")
     assert response.status_code == 200
 
     data = store_model.CreatorDetails.model_validate(response.json())
@@ -528,19 +534,26 @@ def test_get_submissions_success(
         submissions=[
             store_model.StoreSubmission(
                 listing_id="test-listing-id",
-                name="Test Agent",
-                description="Test agent description",
-                image_urls=["test.jpg"],
-                date_submitted=FIXED_NOW,
-                status=prisma.enums.SubmissionStatus.APPROVED,
-                runs=50,
-                rating=4.2,
-                agent_id="test-agent-id",
-                agent_version=1,
-                sub_heading="Test agent subheading",
+                user_id="test-user-id",
                 slug="test-agent",
-                video_url="test.mp4",
+                listing_version_id="test-version-id",
+                listing_version=1,
+                graph_id="test-agent-id",
+                graph_version=1,
+                name="Test Agent",
+                sub_heading="Test agent subheading",
+                description="Test agent description",
+                instructions="Click the button!",
                 categories=["test-category"],
+                image_urls=["test.jpg"],
+                video_url="test.mp4",
+                agent_output_demo_url="demo_video.mp4",
+                submitted_at=FIXED_NOW,
+                changes_summary="Initial Submission",
+                status=prisma.enums.SubmissionStatus.APPROVED,
+                run_count=50,
+                review_count=5,
+                review_avg_rating=4.2,
             )
         ],
         pagination=store_model.Pagination(

autogpt_platform/backend/backend/api/features/store/test_cache_delete.py

@@ -11,6 +11,7 @@ import pytest
 from backend.util.models import Pagination
 
 from . import cache as store_cache
+from .db import StoreAgentsSortOptions
 from .model import StoreAgent, StoreAgentsResponse
 
 
@@ -215,7 +216,7 @@ class TestCacheDeletion:
             await store_cache._get_cached_store_agents(
                 featured=True,
                 creator="testuser",
-                sorted_by="rating",
+                sorted_by=StoreAgentsSortOptions.RATING,
                 search_query="AI assistant",
                 category="productivity",
                 page=2,
@@ -227,7 +228,7 @@ class TestCacheDeletion:
             deleted = store_cache._get_cached_store_agents.cache_delete(
                 featured=True,
                 creator="testuser",
-                sorted_by="rating",
+                sorted_by=StoreAgentsSortOptions.RATING,
                 search_query="AI assistant",
                 category="productivity",
                 page=2,
@@ -239,7 +240,7 @@ class TestCacheDeletion:
             deleted = store_cache._get_cached_store_agents.cache_delete(
                 featured=True,
                 creator="testuser",
-                sorted_by="rating",
+                sorted_by=StoreAgentsSortOptions.RATING,
                 search_query="AI assistant",
                 category="productivity",
                 page=2,

autogpt_platform/backend/backend/api/features/v1.py

@@ -449,7 +449,6 @@ async def execute_graph_block(
 async def upload_file(
     user_id: Annotated[str, Security(get_user_id)],
     file: UploadFile = File(...),
-    provider: str = "gcs",
     expiration_hours: int = 24,
 ) -> UploadFileResponse:
     """
@@ -512,7 +511,6 @@ async def upload_file(
     storage_path = await cloud_storage.store_file(
         content=content,
         filename=file_name,
-        provider=provider,
         expiration_hours=expiration_hours,
         user_id=user_id,
     )

autogpt_platform/backend/backend/api/features/v1_test.py

@@ -515,7 +515,6 @@ async def test_upload_file_success(test_user_id: str):
         result = await upload_file(
             file=upload_file_mock,
             user_id=test_user_id,
-            provider="gcs",
             expiration_hours=24,
         )
 
@@ -533,7 +532,6 @@ async def test_upload_file_success(test_user_id: str):
         mock_handler.store_file.assert_called_once_with(
             content=file_content,
             filename="test.txt",
-            provider="gcs",
             expiration_hours=24,
             user_id=test_user_id,
         )

autogpt_platform/backend/backend/api/rest_api.py

@@ -18,6 +18,7 @@ from prisma.errors import PrismaError
 
 import backend.api.features.admin.credit_admin_routes
 import backend.api.features.admin.execution_analytics_routes
+import backend.api.features.admin.llm_routes
 import backend.api.features.admin.store_admin_routes
 import backend.api.features.builder
 import backend.api.features.builder.routes
@@ -39,13 +40,15 @@ import backend.data.db
 import backend.data.graph
 import backend.data.user
 import backend.integrations.webhooks.utils
+import backend.server.v2.llm.routes
 import backend.util.service
 import backend.util.settings
 from backend.api.features.library.exceptions import (
     FolderAlreadyExistsError,
     FolderValidationError,
 )
-from backend.blocks.llm import DEFAULT_LLM_MODEL
+from backend.data import llm_registry
+from backend.data.block_cost_config import refresh_llm_costs
 from backend.data.model import Credentials
 from backend.integrations.providers import ProviderName
 from backend.monitoring.instrumentation import instrument_fastapi
@@ -55,6 +58,7 @@ from backend.util.exceptions import (
     MissingConfigError,
     NotAuthorizedError,
     NotFoundError,
+    PreconditionFailed,
 )
 from backend.util.feature_flag import initialize_launchdarkly, shutdown_launchdarkly
 from backend.util.service import UnhealthyServiceError
@@ -116,11 +120,30 @@ async def lifespan_context(app: fastapi.FastAPI):
 
     AutoRegistry.patch_integrations()
 
+    # Refresh LLM registry before initializing blocks so blocks can use registry data
+    try:
+        await llm_registry.refresh_llm_registry()
+        await refresh_llm_costs()
+    except Exception as e:
+        logger.warning(f"Failed to refresh LLM registry/costs at startup: {e}")
+
+    # Clear block schema caches so they're regenerated with updated discriminator_mapping
+    from backend.blocks._base import BlockSchema
+
+    BlockSchema.clear_all_schema_caches()
+
     await backend.data.block.initialize_blocks()
 
     await backend.data.user.migrate_and_encrypt_user_integrations()
     await backend.data.graph.fix_llm_provider_credentials()
-    await backend.data.graph.migrate_llm_models(DEFAULT_LLM_MODEL)
+    # migrate_llm_models uses registry default model
+    from backend.blocks.llm import LlmModel
+
+    default_model_slug = llm_registry.get_default_model_slug()
+    if default_model_slug:
+        await backend.data.graph.migrate_llm_models(LlmModel(default_model_slug))
+    else:
+        logger.warning("Skipping LLM model migration: no default model available")
     await backend.integrations.webhooks.utils.migrate_legacy_triggered_graphs()
 
     with launch_darkly_context():
@@ -275,6 +298,7 @@ app.add_exception_handler(RequestValidationError, validation_error_handler)
 app.add_exception_handler(pydantic.ValidationError, validation_error_handler)
 app.add_exception_handler(MissingConfigError, handle_internal_http_error(503))
 app.add_exception_handler(ValueError, handle_internal_http_error(400))
+app.add_exception_handler(PreconditionFailed, handle_internal_http_error(428))
 app.add_exception_handler(Exception, handle_internal_http_error(500))
 
 app.include_router(backend.api.features.v1.v1_router, tags=["v1"], prefix="/api")
@@ -314,6 +338,16 @@ app.include_router(
     tags=["v2", "executions", "review"],
     prefix="/api/review",
 )
+app.include_router(
+    backend.api.features.admin.llm_routes.router,
+    tags=["v2"],
+    prefix="/api/llm/admin",
+)
+app.include_router(
+    backend.server.v2.llm.routes.router,
+    tags=["v2"],
+    prefix="/api/llm",
+)
 app.include_router(
     backend.api.features.library.routes.router, tags=["v2"], prefix="/api/library"
 )

autogpt_platform/backend/backend/api/ws_api.py

@@ -79,7 +79,42 @@ async def event_broadcaster(manager: ConnectionManager):
                     payload=notification.payload,
                 )
 
-        await asyncio.gather(execution_worker(), notification_worker())
+        async def registry_refresh_worker():
+            """Listen for LLM registry refresh notifications and broadcast to all clients."""
+            from backend.data.llm_registry import REGISTRY_REFRESH_CHANNEL
+            from backend.data.redis_client import connect_async
+
+            redis = await connect_async()
+            pubsub = redis.pubsub()
+            try:
+                await pubsub.subscribe(REGISTRY_REFRESH_CHANNEL)
+                logger.info(
+                    "Subscribed to LLM registry refresh notifications for WebSocket broadcast"
+                )
+
+                async for message in pubsub.listen():
+                    if (
+                        message["type"] == "message"
+                        and message["channel"] == REGISTRY_REFRESH_CHANNEL
+                    ):
+                        logger.info(
+                            "Broadcasting LLM registry refresh to all WebSocket clients"
+                        )
+                        await manager.broadcast_to_all(
+                            method=WSMethod.NOTIFICATION,
+                            data={
+                                "type": "LLM_REGISTRY_REFRESH",
+                                "event": "registry_updated",
+                            },
+                        )
+            finally:
+                await pubsub.close()
+
+        await asyncio.gather(
+            execution_worker(),
+            notification_worker(),
+            registry_refresh_worker(),
+        )
     finally:
         # Ensure PubSub connections are closed on any exit to prevent leaks
         await execution_bus.close()

autogpt_platform/backend/backend/blocks/_base.py

@@ -134,7 +134,26 @@ class BlockInfo(BaseModel):
 
 
 class BlockSchema(BaseModel):
-    cached_jsonschema: ClassVar[dict[str, Any]]
+    cached_jsonschema: ClassVar[dict[str, Any] | None] = None
+
+    @classmethod
+    def clear_schema_cache(cls) -> None:
+        """Clear the cached JSON schema for this class."""
+        # Use None instead of {} because {} is truthy and would prevent regeneration
+        cls.cached_jsonschema = None  # type: ignore
+
+    @staticmethod
+    def clear_all_schema_caches() -> None:
+        """Clear cached JSON schemas for all BlockSchema subclasses."""
+
+        def clear_recursive(cls: type) -> None:
+            """Recursively clear cache for class and all subclasses."""
+            if hasattr(cls, "clear_schema_cache"):
+                cls.clear_schema_cache()
+            for subclass in cls.__subclasses__():
+                clear_recursive(subclass)
+
+        clear_recursive(BlockSchema)
 
     @classmethod
     def jsonschema(cls) -> dict[str, Any]:
@@ -225,7 +244,8 @@ class BlockSchema(BaseModel):
         super().__pydantic_init_subclass__(**kwargs)
 
         # Reset cached JSON schema to prevent inheriting it from parent class
-        cls.cached_jsonschema = {}
+        # Use None instead of {} because {} is truthy and would prevent regeneration
+        cls.cached_jsonschema = None
 
         credentials_fields = cls.get_credentials_fields()
 
@@ -418,6 +438,8 @@ class BlockWebhookConfig(BlockManualWebhookConfig):
 
 
 class Block(ABC, Generic[BlockSchemaInputType, BlockSchemaOutputType]):
+    _optimized_description: ClassVar[str | None] = None
+
     def __init__(
         self,
         id: str = "",
@@ -470,6 +492,8 @@ class Block(ABC, Generic[BlockSchemaInputType, BlockSchemaOutputType]):
         self.block_type = block_type
         self.webhook_config = webhook_config
         self.is_sensitive_action = is_sensitive_action
+        # Read from ClassVar set by initialize_blocks()
+        self.optimized_description: str | None = type(self)._optimized_description
         self.execution_stats: "NodeExecutionStats" = NodeExecutionStats()
 
         if self.webhook_config:

autogpt_platform/backend/backend/blocks/ai_condition.py

@@ -7,7 +7,6 @@ from backend.blocks._base import (
     BlockSchemaOutput,
 )
 from backend.blocks.llm import (
-    DEFAULT_LLM_MODEL,
     TEST_CREDENTIALS,
     TEST_CREDENTIALS_INPUT,
     AIBlockBase,
@@ -16,6 +15,7 @@ from backend.blocks.llm import (
     LlmModel,
     LLMResponse,
     llm_call,
+    llm_model_schema_extra,
 )
 from backend.data.model import APIKeyCredentials, NodeExecutionStats, SchemaField
 
@@ -50,9 +50,10 @@ class AIConditionBlock(AIBlockBase):
         )
         model: LlmModel = SchemaField(
             title="LLM Model",
-            default=DEFAULT_LLM_MODEL,
+            default_factory=LlmModel.default,
             description="The language model to use for evaluating the condition.",
             advanced=False,
+            json_schema_extra=llm_model_schema_extra(),
         )
         credentials: AICredentials = AICredentialsField()
 
@@ -82,7 +83,7 @@ class AIConditionBlock(AIBlockBase):
                 "condition": "the input is an email address",
                 "yes_value": "Valid email",
                 "no_value": "Not an email",
-                "model": DEFAULT_LLM_MODEL,
+                "model": LlmModel.default(),
                 "credentials": TEST_CREDENTIALS_INPUT,
             },
             test_credentials=TEST_CREDENTIALS,

autogpt_platform/backend/backend/blocks/code_executor.py

@@ -142,7 +142,7 @@ class BaseE2BExecutorMixin:
                 start_timestamp = ts_result.stdout.strip() if ts_result.stdout else None
 
             # Execute the code
-            execution = await sandbox.run_code(
+            execution = await sandbox.run_code(  # type: ignore[attr-defined]
                 code,
                 language=language.value,
                 on_error=lambda e: sandbox.kill(),  # Kill the sandbox on error

autogpt_platform/backend/backend/blocks/perplexity.py

@@ -21,6 +21,7 @@ from backend.data.model import (
     SchemaField,
 )
 from backend.integrations.providers import ProviderName
+from backend.util.clients import OPENROUTER_BASE_URL
 from backend.util.logging import TruncatedLogger
 
 logger = TruncatedLogger(logging.getLogger(__name__), "[Perplexity-Block]")
@@ -136,7 +137,7 @@ class PerplexityBlock(Block):
     ) -> dict[str, Any]:
         """Call Perplexity via OpenRouter and extract annotations."""
         client = openai.AsyncOpenAI(
-            base_url="https://openrouter.ai/api/v1",
+            base_url=OPENROUTER_BASE_URL,
             api_key=credentials.api_key.get_secret_value(),
         )
 

autogpt_platform/backend/backend/blocks/smart_decision_maker.py

@@ -226,9 +226,10 @@ class SmartDecisionMakerBlock(Block):
         )
         model: llm.LlmModel = SchemaField(
             title="LLM Model",
-            default=llm.DEFAULT_LLM_MODEL,
+            default_factory=llm.LlmModel.default,
             description="The language model to use for answering the prompt.",
             advanced=False,
+            json_schema_extra=llm.llm_model_schema_extra(),
         )
         credentials: llm.AICredentials = llm.AICredentialsField()
         multiple_tool_calls: bool = SchemaField(

autogpt_platform/backend/backend/blocks/stagehand/blocks.py

@@ -10,13 +10,13 @@ import stagehand.main
 from stagehand import Stagehand
 
 from backend.blocks.llm import (
-    MODEL_METADATA,
     AICredentials,
     AICredentialsField,
     LlmModel,
     ModelMetadata,
 )
 from backend.blocks.stagehand._config import stagehand as stagehand_provider
+from backend.data import llm_registry
 from backend.sdk import (
     APIKeyCredentials,
     Block,
@@ -83,7 +83,8 @@ class StagehandRecommendedLlmModel(str, Enum):
     GPT41_MINI = "gpt-4.1-mini-2025-04-14"
 
     # Anthropic
-    CLAUDE_4_5_SONNET = "claude-sonnet-4-5-20250929"
+    CLAUDE_4_5_SONNET = "claude-sonnet-4-5-20250929"  # Keep for backwards compat
+    CLAUDE_4_6_SONNET = "claude-sonnet-4-6"
 
     @property
     def provider_name(self) -> str:
@@ -91,7 +92,7 @@ class StagehandRecommendedLlmModel(str, Enum):
         Returns the provider name for the model in the required format for Stagehand:
         provider/model_name
         """
-        model_metadata = MODEL_METADATA[LlmModel(self.value)]
+        model_metadata = self.metadata
         model_name = self.value
 
         if len(model_name.split("/")) == 1 and not self.value.startswith(
@@ -102,24 +103,28 @@ class StagehandRecommendedLlmModel(str, Enum):
             ), "Logic failed and open_router provider attempted to be prepended to model name! in stagehand/_config.py"
             model_name = f"{model_metadata.provider}/{model_name}"
 
-        logger.error(f"Model name: {model_name}")
+        logger.debug(f"Model name: {model_name}")
         return model_name
 
     @property
     def provider(self) -> str:
-        return MODEL_METADATA[LlmModel(self.value)].provider
+        return self.metadata.provider
 
     @property
     def metadata(self) -> ModelMetadata:
-        return MODEL_METADATA[LlmModel(self.value)]
+        metadata = llm_registry.get_llm_model_metadata(self.value)
+        if metadata:
+            return metadata
+        # Fallback to LlmModel enum if registry lookup fails
+        return LlmModel(self.value).metadata
 
     @property
     def context_window(self) -> int:
-        return MODEL_METADATA[LlmModel(self.value)].context_window
+        return self.metadata.context_window
 
     @property
     def max_output_tokens(self) -> int | None:
-        return MODEL_METADATA[LlmModel(self.value)].max_output_tokens
+        return self.metadata.max_output_tokens
 
 
 class StagehandObserveBlock(Block):
@@ -137,7 +142,7 @@ class StagehandObserveBlock(Block):
         model: StagehandRecommendedLlmModel = SchemaField(
             title="LLM Model",
             description="LLM to use for Stagehand (provider is inferred)",
-            default=StagehandRecommendedLlmModel.CLAUDE_4_5_SONNET,
+            default=StagehandRecommendedLlmModel.CLAUDE_4_6_SONNET,
             advanced=False,
         )
         model_credentials: AICredentials = AICredentialsField()
@@ -227,7 +232,7 @@ class StagehandActBlock(Block):
         model: StagehandRecommendedLlmModel = SchemaField(
             title="LLM Model",
             description="LLM to use for Stagehand (provider is inferred)",
-            default=StagehandRecommendedLlmModel.CLAUDE_4_5_SONNET,
+            default=StagehandRecommendedLlmModel.CLAUDE_4_6_SONNET,
             advanced=False,
         )
         model_credentials: AICredentials = AICredentialsField()
@@ -324,7 +329,7 @@ class StagehandExtractBlock(Block):
         model: StagehandRecommendedLlmModel = SchemaField(
             title="LLM Model",
             description="LLM to use for Stagehand (provider is inferred)",
-            default=StagehandRecommendedLlmModel.CLAUDE_4_5_SONNET,
+            default=StagehandRecommendedLlmModel.CLAUDE_4_6_SONNET,
             advanced=False,
         )
         model_credentials: AICredentials = AICredentialsField()

autogpt_platform/backend/backend/blocks/system/store_operations.py

@@ -1,8 +1,8 @@
 import logging
-from typing import Literal
 
 from pydantic import BaseModel
 
+from backend.api.features.store.db import StoreAgentsSortOptions
 from backend.blocks._base import (
     Block,
     BlockCategory,
@@ -176,8 +176,8 @@ class SearchStoreAgentsBlock(Block):
         category: str | None = SchemaField(
             description="Filter by category", default=None
         )
-        sort_by: Literal["rating", "runs", "name", "updated_at"] = SchemaField(
-            description="How to sort the results", default="rating"
+        sort_by: StoreAgentsSortOptions = SchemaField(
+            description="How to sort the results", default=StoreAgentsSortOptions.RATING
         )
         limit: int = SchemaField(
             description="Maximum number of results to return", default=10, ge=1, le=100
@@ -278,7 +278,7 @@ class SearchStoreAgentsBlock(Block):
         self,
         query: str | None = None,
         category: str | None = None,
-        sort_by: Literal["rating", "runs", "name", "updated_at"] = "rating",
+        sort_by: StoreAgentsSortOptions = StoreAgentsSortOptions.RATING,
         limit: int = 10,
     ) -> SearchAgentsResponse:
         """

autogpt_platform/backend/backend/blocks/test/test_store_operations.py

@@ -2,6 +2,7 @@ from unittest.mock import MagicMock
 
 import pytest
 
+from backend.api.features.store.db import StoreAgentsSortOptions
 from backend.blocks.system.library_operations import (
     AddToLibraryFromStoreBlock,
     LibraryAgent,
@@ -121,7 +122,10 @@ async def test_search_store_agents_block(mocker):
     )
 
     input_data = block.Input(
-        query="test", category="productivity", sort_by="rating", limit=10
+        query="test",
+        category="productivity",
+        sort_by=StoreAgentsSortOptions.RATING,  # type: ignore[reportArgumentType]
+        limit=10,
     )
 
     outputs = {}

autogpt_platform/backend/backend/copilot/baseline/service.py

@@ -22,6 +22,7 @@ from backend.copilot.model import (
     update_session_title,
     upsert_chat_session,
 )
+from backend.copilot.prompting import get_baseline_supplement
 from backend.copilot.response_model import (
     StreamBaseResponse,
     StreamError,
@@ -62,8 +63,8 @@ async def _update_title_async(
     """Generate and persist a session title in the background."""
     try:
         title = await _generate_session_title(message, user_id, session_id)
-        if title:
-            await update_session_title(session_id, title)
+        if title and user_id:
+            await update_session_title(session_id, user_id, title, only_if_empty=True)
     except Exception as e:
         logger.warning("[Baseline] Failed to update session title: %s", e)
 
@@ -176,14 +177,17 @@ async def stream_chat_completion_baseline(
     # changes from concurrent chats updating business understanding.
     is_first_turn = len(session.messages) <= 1
     if is_first_turn:
-        system_prompt, _ = await _build_system_prompt(
+        base_system_prompt, _ = await _build_system_prompt(
             user_id, has_conversation_history=False
         )
     else:
-        system_prompt, _ = await _build_system_prompt(
+        base_system_prompt, _ = await _build_system_prompt(
             user_id=None, has_conversation_history=True
         )
 
+    # Append tool documentation and technical notes
+    system_prompt = base_system_prompt + get_baseline_supplement()
+
     # Compress context if approaching the model's token limit
     messages_for_context = await _compress_session_messages(session.messages)
 

autogpt_platform/backend/backend/copilot/config.py

@@ -1,10 +1,13 @@
 """Configuration management for chat system."""
 
 import os
+from typing import Literal
 
 from pydantic import Field, field_validator
 from pydantic_settings import BaseSettings
 
+from backend.util.clients import OPENROUTER_BASE_URL
+
 
 class ChatConfig(BaseSettings):
     """Configuration for the chat system."""
@@ -19,7 +22,7 @@ class ChatConfig(BaseSettings):
     )
     api_key: str | None = Field(default=None, description="OpenAI API key")
     base_url: str | None = Field(
-        default="https://openrouter.ai/api/v1",
+        default=OPENROUTER_BASE_URL,
         description="Base URL for API (e.g., for OpenRouter)",
     )
 
@@ -112,9 +115,37 @@ class ChatConfig(BaseSettings):
         description="E2B sandbox template to use for copilot sessions.",
     )
     e2b_sandbox_timeout: int = Field(
-        default=43200,  # 12 hours — same as session_ttl
-        description="E2B sandbox keepalive timeout in seconds.",
+        default=10800,  # 3 hours — wall-clock timeout, not idle; explicit pause is primary
+        description="E2B sandbox running-time timeout (seconds). "
+        "E2B timeout is wall-clock (not idle). Explicit per-turn pause is the primary "
+        "mechanism; this is the safety net.",
     )
+    e2b_sandbox_on_timeout: Literal["kill", "pause"] = Field(
+        default="pause",
+        description="E2B lifecycle action on timeout: 'pause' (default, free) or 'kill'.",
+    )
+
+    @property
+    def e2b_active(self) -> bool:
+        """True when E2B is enabled and the API key is present.
+
+        Single source of truth for "should we use E2B right now?".
+        Prefer this over combining ``use_e2b_sandbox`` and ``e2b_api_key``
+        separately at call sites.
+        """
+        return self.use_e2b_sandbox and bool(self.e2b_api_key)
+
+    @property
+    def active_e2b_api_key(self) -> str | None:
+        """Return the E2B API key when E2B is enabled and configured, else None.
+
+        Combines the ``use_e2b_sandbox`` flag check and key presence into one.
+        Use in callers::
+
+            if api_key := config.active_e2b_api_key:
+                # E2B is active; api_key is narrowed to str
+        """
+        return self.e2b_api_key if self.e2b_active else None
 
     @field_validator("use_e2b_sandbox", mode="before")
     @classmethod
@@ -164,7 +195,7 @@ class ChatConfig(BaseSettings):
             if not v:
                 v = os.getenv("OPENAI_BASE_URL")
             if not v:
-                v = "https://openrouter.ai/api/v1"
+                v = OPENROUTER_BASE_URL
         return v
 
     @field_validator("use_claude_agent_sdk", mode="before")

autogpt_platform/backend/backend/copilot/config_test.py

@@ -0,0 +1,38 @@
+"""Unit tests for ChatConfig."""
+
+import pytest
+
+from .config import ChatConfig
+
+# Env vars that the ChatConfig validators read — must be cleared so they don't
+# override the explicit constructor values we pass in each test.
+_E2B_ENV_VARS = (
+    "CHAT_USE_E2B_SANDBOX",
+    "CHAT_E2B_API_KEY",
+    "E2B_API_KEY",
+)
+
+
+@pytest.fixture(autouse=True)
+def _clean_e2b_env(monkeypatch: pytest.MonkeyPatch) -> None:
+    for var in _E2B_ENV_VARS:
+        monkeypatch.delenv(var, raising=False)
+
+
+class TestE2BActive:
+    """Tests for the e2b_active property — single source of truth for E2B usage."""
+
+    def test_both_enabled_and_key_present_returns_true(self):
+        """e2b_active is True when use_e2b_sandbox=True and e2b_api_key is set."""
+        cfg = ChatConfig(use_e2b_sandbox=True, e2b_api_key="test-key")
+        assert cfg.e2b_active is True
+
+    def test_enabled_but_missing_key_returns_false(self):
+        """e2b_active is False when use_e2b_sandbox=True but e2b_api_key is absent."""
+        cfg = ChatConfig(use_e2b_sandbox=True, e2b_api_key=None)
+        assert cfg.e2b_active is False
+
+    def test_disabled_returns_false(self):
+        """e2b_active is False when use_e2b_sandbox=False regardless of key."""
+        cfg = ChatConfig(use_e2b_sandbox=False, e2b_api_key="test-key")
+        assert cfg.e2b_active is False

autogpt_platform/backend/backend/copilot/context.py

@@ -0,0 +1,115 @@
+"""Shared execution context for copilot SDK tool handlers.
+
+All context variables and their accessors live here so that
+``tool_adapter``, ``file_ref``, and ``e2b_file_tools`` can import them
+without creating circular dependencies.
+"""
+
+import os
+import re
+from contextvars import ContextVar
+from typing import TYPE_CHECKING
+
+from backend.copilot.model import ChatSession
+
+if TYPE_CHECKING:
+    from e2b import AsyncSandbox
+
+# Allowed base directory for the Read tool.
+_SDK_PROJECTS_DIR = os.path.realpath(os.path.expanduser("~/.claude/projects"))
+
+# Encoded project-directory name for the current session (e.g.
+# "-private-tmp-copilot-<uuid>").  Set by set_execution_context() so path
+# validation can scope tool-results reads to the current session.
+_current_project_dir: ContextVar[str] = ContextVar("_current_project_dir", default="")
+
+_current_user_id: ContextVar[str | None] = ContextVar("current_user_id", default=None)
+_current_session: ContextVar[ChatSession | None] = ContextVar(
+    "current_session", default=None
+)
+_current_sandbox: ContextVar["AsyncSandbox | None"] = ContextVar(
+    "_current_sandbox", default=None
+)
+_current_sdk_cwd: ContextVar[str] = ContextVar("_current_sdk_cwd", default="")
+
+
+def _encode_cwd_for_cli(cwd: str) -> str:
+    """Encode a working directory path the same way the Claude CLI does."""
+    return re.sub(r"[^a-zA-Z0-9]", "-", os.path.realpath(cwd))
+
+
+def set_execution_context(
+    user_id: str | None,
+    session: ChatSession,
+    sandbox: "AsyncSandbox | None" = None,
+    sdk_cwd: str | None = None,
+) -> None:
+    """Set per-turn context variables used by file-resolution tool handlers."""
+    _current_user_id.set(user_id)
+    _current_session.set(session)
+    _current_sandbox.set(sandbox)
+    _current_sdk_cwd.set(sdk_cwd or "")
+    _current_project_dir.set(_encode_cwd_for_cli(sdk_cwd) if sdk_cwd else "")
+
+
+def get_execution_context() -> tuple[str | None, ChatSession | None]:
+    """Return the current (user_id, session) pair for the active request."""
+    return _current_user_id.get(), _current_session.get()
+
+
+def get_current_sandbox() -> "AsyncSandbox | None":
+    """Return the E2B sandbox for the current session, or None if not active."""
+    return _current_sandbox.get()
+
+
+def get_sdk_cwd() -> str:
+    """Return the SDK working directory for the current session (empty string if unset)."""
+    return _current_sdk_cwd.get()
+
+
+E2B_WORKDIR = "/home/user"
+
+
+def resolve_sandbox_path(path: str) -> str:
+    """Normalise *path* to an absolute sandbox path under ``/home/user``.
+
+    Raises :class:`ValueError` if the resolved path escapes the sandbox.
+    """
+    candidate = path if os.path.isabs(path) else os.path.join(E2B_WORKDIR, path)
+    normalized = os.path.normpath(candidate)
+    if normalized != E2B_WORKDIR and not normalized.startswith(E2B_WORKDIR + "/"):
+        raise ValueError(f"Path must be within {E2B_WORKDIR}: {path}")
+    return normalized
+
+
+def is_allowed_local_path(path: str, sdk_cwd: str | None = None) -> bool:
+    """Return True if *path* is within an allowed host-filesystem location.
+
+    Allowed:
+    - Files under *sdk_cwd* (``/tmp/copilot-<session>/``)
+    - Files under ``~/.claude/projects/<encoded-cwd>/tool-results/`` (SDK tool-results)
+    """
+    if not path:
+        return False
+
+    if path.startswith("~"):
+        resolved = os.path.realpath(os.path.expanduser(path))
+    elif not os.path.isabs(path) and sdk_cwd:
+        resolved = os.path.realpath(os.path.join(sdk_cwd, path))
+    else:
+        resolved = os.path.realpath(path)
+
+    if sdk_cwd:
+        norm_cwd = os.path.realpath(sdk_cwd)
+        if resolved == norm_cwd or resolved.startswith(norm_cwd + os.sep):
+            return True
+
+    encoded = _current_project_dir.get("")
+    if encoded:
+        tool_results_dir = os.path.join(_SDK_PROJECTS_DIR, encoded, "tool-results")
+        if resolved == tool_results_dir or resolved.startswith(
+            tool_results_dir + os.sep
+        ):
+            return True
+
+    return False

autogpt_platform/backend/backend/copilot/context_test.py

@@ -0,0 +1,163 @@
+"""Tests for context.py — execution context variables and path helpers."""
+
+from __future__ import annotations
+
+import os
+import tempfile
+from unittest.mock import MagicMock
+
+import pytest
+
+from backend.copilot.context import (
+    _SDK_PROJECTS_DIR,
+    _current_project_dir,
+    get_current_sandbox,
+    get_execution_context,
+    get_sdk_cwd,
+    is_allowed_local_path,
+    resolve_sandbox_path,
+    set_execution_context,
+)
+
+
+def _make_session() -> MagicMock:
+    s = MagicMock()
+    s.session_id = "test-session"
+    return s
+
+
+# ---------------------------------------------------------------------------
+# Context variable getters
+# ---------------------------------------------------------------------------
+
+
+def test_get_execution_context_defaults():
+    """get_execution_context returns (None, session) when user_id is not set."""
+    set_execution_context(None, _make_session())
+    user_id, session = get_execution_context()
+    assert user_id is None
+    assert session is not None
+
+
+def test_set_and_get_execution_context():
+    """set_execution_context stores user_id and session."""
+    mock_session = _make_session()
+    set_execution_context("user-abc", mock_session)
+    user_id, session = get_execution_context()
+    assert user_id == "user-abc"
+    assert session is mock_session
+
+
+def test_get_current_sandbox_none_by_default():
+    """get_current_sandbox returns None when no sandbox is set."""
+    set_execution_context("u1", _make_session(), sandbox=None)
+    assert get_current_sandbox() is None
+
+
+def test_get_current_sandbox_returns_set_value():
+    """get_current_sandbox returns the sandbox set via set_execution_context."""
+    mock_sandbox = MagicMock()
+    set_execution_context("u1", _make_session(), sandbox=mock_sandbox)
+    assert get_current_sandbox() is mock_sandbox
+
+
+def test_get_sdk_cwd_empty_when_not_set():
+    """get_sdk_cwd returns empty string when sdk_cwd is not set."""
+    set_execution_context("u1", _make_session(), sdk_cwd=None)
+    assert get_sdk_cwd() == ""
+
+
+def test_get_sdk_cwd_returns_set_value():
+    """get_sdk_cwd returns the value set via set_execution_context."""
+    set_execution_context("u1", _make_session(), sdk_cwd="/tmp/copilot-test")
+    assert get_sdk_cwd() == "/tmp/copilot-test"
+
+
+# ---------------------------------------------------------------------------
+# is_allowed_local_path
+# ---------------------------------------------------------------------------
+
+
+def test_is_allowed_local_path_empty():
+    assert not is_allowed_local_path("")
+
+
+def test_is_allowed_local_path_inside_sdk_cwd():
+    with tempfile.TemporaryDirectory() as cwd:
+        path = os.path.join(cwd, "file.txt")
+        assert is_allowed_local_path(path, cwd)
+
+
+def test_is_allowed_local_path_sdk_cwd_itself():
+    with tempfile.TemporaryDirectory() as cwd:
+        assert is_allowed_local_path(cwd, cwd)
+
+
+def test_is_allowed_local_path_outside_sdk_cwd():
+    with tempfile.TemporaryDirectory() as cwd:
+        assert not is_allowed_local_path("/etc/passwd", cwd)
+
+
+def test_is_allowed_local_path_no_sdk_cwd_no_project_dir():
+    """Without sdk_cwd or project_dir, all paths are rejected."""
+    _current_project_dir.set("")
+    assert not is_allowed_local_path("/tmp/some-file.txt", sdk_cwd=None)
+
+
+def test_is_allowed_local_path_tool_results_dir():
+    """Files under the tool-results directory for the current project are allowed."""
+    encoded = "test-encoded-dir"
+    tool_results_dir = os.path.join(_SDK_PROJECTS_DIR, encoded, "tool-results")
+    path = os.path.join(tool_results_dir, "output.txt")
+
+    _current_project_dir.set(encoded)
+    try:
+        assert is_allowed_local_path(path, sdk_cwd=None)
+    finally:
+        _current_project_dir.set("")
+
+
+def test_is_allowed_local_path_sibling_of_tool_results_is_rejected():
+    """A path adjacent to tool-results/ but not inside it is rejected."""
+    encoded = "test-encoded-dir"
+    sibling_path = os.path.join(_SDK_PROJECTS_DIR, encoded, "other-dir", "file.txt")
+
+    _current_project_dir.set(encoded)
+    try:
+        assert not is_allowed_local_path(sibling_path, sdk_cwd=None)
+    finally:
+        _current_project_dir.set("")
+
+
+# ---------------------------------------------------------------------------
+# resolve_sandbox_path
+# ---------------------------------------------------------------------------
+
+
+def test_resolve_sandbox_path_absolute_valid():
+    assert (
+        resolve_sandbox_path("/home/user/project/main.py")
+        == "/home/user/project/main.py"
+    )
+
+
+def test_resolve_sandbox_path_relative():
+    assert resolve_sandbox_path("project/main.py") == "/home/user/project/main.py"
+
+
+def test_resolve_sandbox_path_workdir_itself():
+    assert resolve_sandbox_path("/home/user") == "/home/user"
+
+
+def test_resolve_sandbox_path_normalizes_dots():
+    assert resolve_sandbox_path("/home/user/a/../b") == "/home/user/b"
+
+
+def test_resolve_sandbox_path_escape_raises():
+    with pytest.raises(ValueError, match="/home/user"):
+        resolve_sandbox_path("/home/user/../../etc/passwd")
+
+
+def test_resolve_sandbox_path_absolute_outside_raises():
+    with pytest.raises(ValueError, match="/home/user"):
+        resolve_sandbox_path("/etc/passwd")

autogpt_platform/backend/backend/copilot/db.py

@@ -81,6 +81,35 @@ async def update_chat_session(
     return ChatSession.from_db(session) if session else None
 
 
+async def update_chat_session_title(
+    session_id: str,
+    user_id: str,
+    title: str,
+    *,
+    only_if_empty: bool = False,
+) -> bool:
+    """Update the title of a chat session, scoped to the owning user.
+
+    Always filters by (session_id, user_id) so callers cannot mutate another
+    user's session even when they know the session_id.
+
+    Args:
+        only_if_empty: When True, uses an atomic ``UPDATE WHERE title IS NULL``
+            guard so auto-generated titles never overwrite a user-set title.
+
+    Returns True if a row was updated, False otherwise (session not found,
+    wrong user, or — when only_if_empty — title was already set).
+    """
+    where: ChatSessionWhereInput = {"id": session_id, "userId": user_id}
+    if only_if_empty:
+        where["title"] = None
+    result = await PrismaChatSession.prisma().update_many(
+        where=where,
+        data={"title": title, "updatedAt": datetime.now(UTC)},
+    )
+    return result > 0
+
+
 async def add_chat_message(
     session_id: str,
     role: str,

autogpt_platform/backend/backend/copilot/model.py

@@ -469,8 +469,16 @@ async def upsert_chat_session(
             )
             db_error = e
 
-        # Save to cache (best-effort, even if DB failed)
+        # Save to cache (best-effort, even if DB failed).
+        # Title updates (update_session_title) run *outside* this lock because
+        # they only touch the title field, not messages.  So a concurrent rename
+        # or auto-title may have written a newer title to Redis while this
+        # upsert was in progress.  Always prefer the cached title to avoid
+        # overwriting it with the stale in-memory copy.
         try:
+            existing_cached = await _get_session_from_cache(session.session_id)
+            if existing_cached and existing_cached.title:
+                session = session.model_copy(update={"title": existing_cached.title})
             await cache_chat_session(session)
         except Exception as e:
             # If DB succeeded but cache failed, raise cache error
@@ -685,30 +693,48 @@ async def delete_chat_session(session_id: str, user_id: str | None = None) -> bo
     return True
 
 
-async def update_session_title(session_id: str, title: str) -> bool:
-    """Update only the title of a chat session.
+async def update_session_title(
+    session_id: str,
+    user_id: str,
+    title: str,
+    *,
+    only_if_empty: bool = False,
+) -> bool:
+    """Update the title of a chat session, scoped to the owning user.
 
-    This is a lightweight operation that doesn't touch messages, avoiding
-    race conditions with concurrent message updates. Use this for background
-    title generation instead of upsert_chat_session.
+    Lightweight operation that doesn't touch messages, avoiding race conditions
+    with concurrent message updates.
 
     Args:
         session_id: The session ID to update.
+        user_id: Owning user — the DB query filters on this.
         title: The new title to set.
+        only_if_empty: When True, uses an atomic ``UPDATE WHERE title IS NULL``
+            so auto-generated titles never overwrite a user-set title.
 
     Returns:
-        True if updated successfully, False otherwise.
+        True if updated successfully, False otherwise (not found, wrong user,
+        or — when only_if_empty — title was already set).
     """
     try:
-        result = await chat_db().update_chat_session(session_id=session_id, title=title)
-        if result is None:
-            logger.warning(f"Session {session_id} not found for title update")
+        updated = await chat_db().update_chat_session_title(
+            session_id, user_id, title, only_if_empty=only_if_empty
+        )
+        if not updated:
             return False
 
-        # Invalidate the cache so the next access reloads from DB with the
-        # updated title. This avoids a read-modify-write on the full session
-        # blob, which could overwrite concurrent message updates.
-        await invalidate_session_cache(session_id)
+        # Update title in cache if it exists (instead of invalidating).
+        # This prevents race conditions where cache invalidation causes
+        # the frontend to see stale DB data while streaming is still in progress.
+        try:
+            cached = await _get_session_from_cache(session_id)
+            if cached:
+                cached.title = title
+                await cache_chat_session(cached)
+        except Exception as e:
+            logger.warning(
+                f"Cache title update failed for session {session_id} (non-critical): {e}"
+            )
 
         return True
     except Exception as e:

autogpt_platform/backend/backend/copilot/optimize_blocks.py

@@ -0,0 +1,138 @@
+"""Scheduler job to generate LLM-optimized block descriptions.
+
+Runs periodically to rewrite block descriptions into concise, actionable
+summaries that help the copilot LLM pick the right blocks during agent
+generation.
+"""
+
+import asyncio
+import logging
+
+from backend.blocks import get_blocks
+from backend.util.clients import get_database_manager_client, get_openai_client
+
+logger = logging.getLogger(__name__)
+
+SYSTEM_PROMPT = (
+    "You are a technical writer for an automation platform. "
+    "Rewrite the following block description to be concise (under 50 words), "
+    "informative, and actionable. Focus on what the block does and when to "
+    "use it. Output ONLY the rewritten description, nothing else. "
+    "Do not use markdown formatting."
+)
+
+# Rate-limit delay between sequential LLM calls (seconds)
+_RATE_LIMIT_DELAY = 0.5
+# Maximum tokens for optimized description generation
+_MAX_DESCRIPTION_TOKENS = 150
+# Model for generating optimized descriptions (fast, cheap)
+_MODEL = "gpt-4o-mini"
+
+
+async def _optimize_descriptions(blocks: list[dict[str, str]]) -> dict[str, str]:
+    """Call the shared OpenAI client to rewrite each block description."""
+    client = get_openai_client()
+    if client is None:
+        logger.error(
+            "No OpenAI client configured, skipping block description optimization"
+        )
+        return {}
+
+    results: dict[str, str] = {}
+    for block in blocks:
+        block_id = block["id"]
+        block_name = block["name"]
+        description = block["description"]
+
+        try:
+            response = await client.chat.completions.create(
+                model=_MODEL,
+                messages=[
+                    {"role": "system", "content": SYSTEM_PROMPT},
+                    {
+                        "role": "user",
+                        "content": f"Block name: {block_name}\nDescription: {description}",
+                    },
+                ],
+                max_tokens=_MAX_DESCRIPTION_TOKENS,
+            )
+            optimized = (response.choices[0].message.content or "").strip()
+            if optimized:
+                results[block_id] = optimized
+                logger.debug("Optimized description for %s", block_name)
+            else:
+                logger.warning("Empty response for block %s", block_name)
+        except Exception:
+            logger.warning(
+                "Failed to optimize description for %s", block_name, exc_info=True
+            )
+
+        await asyncio.sleep(_RATE_LIMIT_DELAY)
+
+    return results
+
+
+def optimize_block_descriptions() -> dict[str, int]:
+    """Generate optimized descriptions for blocks that don't have one yet.
+
+    Uses the shared OpenAI client to rewrite block descriptions into concise
+    summaries suitable for agent generation prompts.
+
+    Returns:
+        Dict with counts: processed, success, failed, skipped.
+    """
+    db_client = get_database_manager_client()
+
+    blocks = db_client.get_blocks_needing_optimization()
+    if not blocks:
+        logger.info("All blocks already have optimized descriptions")
+        return {"processed": 0, "success": 0, "failed": 0, "skipped": 0}
+
+    logger.info("Found %d blocks needing optimized descriptions", len(blocks))
+
+    non_empty = [b for b in blocks if b.get("description", "").strip()]
+    skipped = len(blocks) - len(non_empty)
+
+    new_descriptions = asyncio.run(_optimize_descriptions(non_empty))
+
+    stats = {
+        "processed": len(non_empty),
+        "success": len(new_descriptions),
+        "failed": len(non_empty) - len(new_descriptions),
+        "skipped": skipped,
+    }
+
+    logger.info(
+        "Block description optimization complete: "
+        "%d/%d succeeded, %d failed, %d skipped",
+        stats["success"],
+        stats["processed"],
+        stats["failed"],
+        stats["skipped"],
+    )
+
+    if new_descriptions:
+        for block_id, optimized in new_descriptions.items():
+            db_client.update_block_optimized_description(block_id, optimized)
+
+        # Update in-memory descriptions first so the cache rebuilds with fresh data.
+        try:
+            block_classes = get_blocks()
+            for block_id, optimized in new_descriptions.items():
+                if block_id in block_classes:
+                    block_classes[block_id]._optimized_description = optimized
+            logger.info(
+                "Updated %d in-memory block descriptions", len(new_descriptions)
+            )
+        except Exception:
+            logger.warning(
+                "Could not update in-memory block descriptions", exc_info=True
+            )
+
+        from backend.copilot.tools.agent_generator.blocks import (
+            reset_block_caches,  # local to avoid circular import
+        )
+
+        reset_block_caches()
+
+    return stats

autogpt_platform/backend/backend/copilot/optimize_blocks_test.py

@@ -0,0 +1,91 @@
+"""Unit tests for optimize_blocks._optimize_descriptions."""
+
+import asyncio
+from unittest.mock import AsyncMock, MagicMock, patch
+
+from backend.copilot.optimize_blocks import _RATE_LIMIT_DELAY, _optimize_descriptions
+
+
+def _make_client_response(text: str) -> MagicMock:
+    """Build a minimal mock that looks like an OpenAI ChatCompletion response."""
+    choice = MagicMock()
+    choice.message.content = text
+    response = MagicMock()
+    response.choices = [choice]
+    return response
+
+
+def _run(coro):
+    return asyncio.get_event_loop().run_until_complete(coro)
+
+
+class TestOptimizeDescriptions:
+    """Tests for _optimize_descriptions async function."""
+
+    def test_returns_empty_when_no_client(self):
+        with patch(
+            "backend.copilot.optimize_blocks.get_openai_client", return_value=None
+        ):
+            result = _run(
+                _optimize_descriptions([{"id": "b1", "name": "B", "description": "d"}])
+            )
+        assert result == {}
+
+    def test_success_single_block(self):
+        client = MagicMock()
+        client.chat.completions.create = AsyncMock(
+            return_value=_make_client_response("Short desc.")
+        )
+        blocks = [{"id": "b1", "name": "MyBlock", "description": "A block."}]
+
+        with (
+            patch(
+                "backend.copilot.optimize_blocks.get_openai_client", return_value=client
+            ),
+            patch(
+                "backend.copilot.optimize_blocks.asyncio.sleep", new_callable=AsyncMock
+            ),
+        ):
+            result = _run(_optimize_descriptions(blocks))
+
+        assert result == {"b1": "Short desc."}
+        client.chat.completions.create.assert_called_once()
+
+    def test_skips_block_on_exception(self):
+        client = MagicMock()
+        client.chat.completions.create = AsyncMock(side_effect=Exception("API error"))
+        blocks = [{"id": "b1", "name": "MyBlock", "description": "A block."}]
+
+        with (
+            patch(
+                "backend.copilot.optimize_blocks.get_openai_client", return_value=client
+            ),
+            patch(
+                "backend.copilot.optimize_blocks.asyncio.sleep", new_callable=AsyncMock
+            ),
+        ):
+            result = _run(_optimize_descriptions(blocks))
+
+        assert result == {}
+
+    def test_sleeps_between_blocks(self):
+        client = MagicMock()
+        client.chat.completions.create = AsyncMock(
+            return_value=_make_client_response("desc")
+        )
+        blocks = [
+            {"id": "b1", "name": "B1", "description": "d1"},
+            {"id": "b2", "name": "B2", "description": "d2"},
+        ]
+        sleep_mock = AsyncMock()
+
+        with (
+            patch(
+                "backend.copilot.optimize_blocks.get_openai_client", return_value=client
+            ),
+            patch("backend.copilot.optimize_blocks.asyncio.sleep", sleep_mock),
+        ):
+            _run(_optimize_descriptions(blocks))
+
+        assert sleep_mock.call_count == 2
+        sleep_mock.assert_called_with(_RATE_LIMIT_DELAY)

autogpt_platform/backend/backend/copilot/prompt_constants.py

@@ -1,29 +0,0 @@
-"""Prompt constants for CoPilot - workflow guidance and supplementary documentation.
-
-This module contains workflow patterns and guidance that supplement the main system prompt.
-These are appended dynamically to the prompt along with auto-generated tool documentation.
-"""
-
-# Workflow guidance for key tool patterns
-# This is appended after the auto-generated tool list to provide usage patterns
-KEY_WORKFLOWS = """
-
-## KEY WORKFLOWS
-
-### MCP Integration Workflow
-When using `run_mcp_tool`:
-1. **Known servers** (use directly): Notion (https://mcp.notion.com/mcp), Linear (https://mcp.linear.app/mcp), Stripe (https://mcp.stripe.com), Intercom (https://mcp.intercom.com/mcp), Cloudflare (https://mcp.cloudflare.com/mcp), Atlassian (https://mcp.atlassian.com/mcp)
-2. **Unknown servers**: Use `web_search("{{service}} MCP server URL")` to find the endpoint
-3. **Discovery**: Call `run_mcp_tool(server_url)` to see available tools
-4. **Execution**: Call `run_mcp_tool(server_url, tool_name, tool_arguments)`
-5. **Authentication**: If credentials needed, user will be prompted. When they confirm, retry immediately with same arguments.
-
-### Agent Creation Workflow
-When using `create_agent`:
-1. Always check `find_library_agent` first for existing solutions
-2. Call `create_agent` with description
-3. **If `suggested_goal` returned**: Present to user, ask for confirmation, call again with suggested goal if accepted
-4. **If `clarifying_questions` returned**: After user answers, call again with original description AND answers in `context` parameter
-
-### Folder Management
-Use folder tools (`create_folder`, `list_folders`, `move_agents_to_folder`) to organize agents in the user's library for better discoverability."""

autogpt_platform/backend/backend/copilot/prompting.py

@@ -0,0 +1,218 @@
+"""Centralized prompt building logic for CoPilot.
+
+This module contains all prompt construction functions and constants,
+handling the distinction between:
+- SDK mode vs Baseline mode (tool documentation needs)
+- Local mode vs E2B mode (storage/filesystem differences)
+"""
+
+from backend.copilot.tools import TOOL_REGISTRY
+
+# Shared technical notes that apply to both SDK and baseline modes
+_SHARED_TOOL_NOTES = """\
+
+### Sharing files with the user
+After saving a file to the persistent workspace with `write_workspace_file`,
+share it with the user by embedding the `download_url` from the response in
+your message as a Markdown link or image:
+
+- **Any file** — shows as a clickable download link:
+  `[report.csv](workspace://file_id#text/csv)`
+- **Image** — renders inline in chat:
+  `![chart](workspace://file_id#image/png)`
+- **Video** — renders inline in chat with player controls:
+  `![recording](workspace://file_id#video/mp4)`
+
+The `download_url` field in the `write_workspace_file` response is already
+in the correct format — paste it directly after the `(` in the Markdown.
+
+### Passing file content to tools — @@agptfile: references
+Instead of copying large file contents into a tool argument, pass a file
+reference and the platform will load the content for you.
+
+Syntax: `@@agptfile:<uri>[<start>-<end>]`
+
+- `<uri>` **must** start with `workspace://` or `/` (absolute path):
+  - `workspace://<file_id>` — workspace file by ID
+  - `workspace:///<path>` — workspace file by virtual path
+  - `/absolute/local/path` — ephemeral or sdk_cwd file
+  - E2B sandbox absolute path (e.g. `/home/user/script.py`)
+- `[<start>-<end>]` is an optional 1-indexed inclusive line range.
+- URIs that do not start with `workspace://` or `/` are **not** expanded.
+
+Examples:
+```
+@@agptfile:workspace://abc123
+@@agptfile:workspace://abc123[10-50]
+@@agptfile:workspace:///reports/q1.md
+@@agptfile:/tmp/copilot-<session>/output.py[1-80]
+@@agptfile:/home/user/script.py
+```
+
+You can embed a reference inside any string argument, or use it as the entire
+value.  Multiple references in one argument are all expanded.
+
+
+### Sub-agent tasks
+- When using the Task tool, NEVER set `run_in_background` to true.
+  All tasks must run in the foreground.
+"""
+
+
+# Environment-specific supplement templates
+def _build_storage_supplement(
+    working_dir: str,
+    sandbox_type: str,
+    storage_system_1_name: str,
+    storage_system_1_characteristics: list[str],
+    storage_system_1_persistence: list[str],
+    file_move_name_1_to_2: str,
+    file_move_name_2_to_1: str,
+) -> str:
+    """Build storage/filesystem supplement for a specific environment.
+
+    Template function handles all formatting (bullets, indentation, markdown).
+    Callers provide clean data as lists of strings.
+
+    Args:
+        working_dir: Working directory path
+        sandbox_type: Description of bash_exec sandbox
+        storage_system_1_name: Name of primary storage (ephemeral or cloud)
+        storage_system_1_characteristics: List of characteristic descriptions
+        storage_system_1_persistence: List of persistence behavior descriptions
+        file_move_name_1_to_2: Direction label for primary→persistent
+        file_move_name_2_to_1: Direction label for persistent→primary
+    """
+    # Format lists as bullet points with proper indentation
+    characteristics = "\n".join(f"   - {c}" for c in storage_system_1_characteristics)
+    persistence = "\n".join(f"   - {p}" for p in storage_system_1_persistence)
+
+    return f"""
+
+## Tool notes
+
+### Shell commands
+- The SDK built-in Bash tool is NOT available.  Use the `bash_exec` MCP tool
+  for shell commands — it runs {sandbox_type}.
+
+### Working directory
+- Your working directory is: `{working_dir}`
+- All SDK file tools AND `bash_exec` operate on the same filesystem
+- Use relative paths or absolute paths under `{working_dir}` for all file operations
+
+### Two storage systems — CRITICAL to understand
+
+1. **{storage_system_1_name}** (`{working_dir}`):
+{characteristics}
+{persistence}
+
+2. **Persistent workspace** (cloud storage):
+   - Files here **survive across sessions indefinitely**
+
+### Moving files between storages
+- **{file_move_name_1_to_2}**: Copy to persistent workspace
+- **{file_move_name_2_to_1}**: Download for processing
+
+### File persistence
+Important files (code, configs, outputs) should be saved to workspace to ensure they persist.
+{_SHARED_TOOL_NOTES}"""
+
+
+# Pre-built supplements for common environments
+def _get_local_storage_supplement(cwd: str) -> str:
+    """Local ephemeral storage (files lost between turns)."""
+    return _build_storage_supplement(
+        working_dir=cwd,
+        sandbox_type="in a network-isolated sandbox",
+        storage_system_1_name="Ephemeral working directory",
+        storage_system_1_characteristics=[
+            "Shared by SDK Read/Write/Edit/Glob/Grep tools AND `bash_exec`",
+        ],
+        storage_system_1_persistence=[
+            "Files here are **lost between turns** — do NOT rely on them persisting",
+            "Use for temporary work: running scripts, processing data, etc.",
+        ],
+        file_move_name_1_to_2="Ephemeral → Persistent",
+        file_move_name_2_to_1="Persistent → Ephemeral",
+    )
+
+
+def _get_cloud_sandbox_supplement() -> str:
+    """Cloud persistent sandbox (files survive across turns in session)."""
+    return _build_storage_supplement(
+        working_dir="/home/user",
+        sandbox_type="in a cloud sandbox with full internet access",
+        storage_system_1_name="Cloud sandbox",
+        storage_system_1_characteristics=[
+            "Shared by all file tools AND `bash_exec` — same filesystem",
+            "Full Linux environment with internet access",
+        ],
+        storage_system_1_persistence=[
+            "Files **persist across turns** within the current session",
+            "Lost when the session expires (12 h inactivity)",
+        ],
+        file_move_name_1_to_2="Sandbox → Persistent",
+        file_move_name_2_to_1="Persistent → Sandbox",
+    )
+
+
+def _generate_tool_documentation() -> str:
+    """Auto-generate tool documentation from TOOL_REGISTRY.
+
+    NOTE: This is ONLY used in baseline mode (direct OpenAI API).
+    SDK mode doesn't need it since Claude gets tool schemas automatically.
+
+    This generates a complete list of available tools with their descriptions,
+    ensuring the documentation stays in sync with the actual tool implementations.
+    All workflow guidance is now embedded in individual tool descriptions.
+
+    Only documents tools that are available in the current environment
+    (checked via tool.is_available property).
+    """
+    docs = "\n## AVAILABLE TOOLS\n\n"
+
+    # Sort tools alphabetically for consistent output
+    # Filter by is_available to match get_available_tools() behavior
+    for name in sorted(TOOL_REGISTRY.keys()):
+        tool = TOOL_REGISTRY[name]
+        if not tool.is_available:
+            continue
+        schema = tool.as_openai_tool()
+        desc = schema["function"].get("description", "No description available")
+        # Format as bullet list with tool name in code style
+        docs += f"- **`{name}`**: {desc}\n"
+
+    return docs
+
+
+def get_sdk_supplement(use_e2b: bool, cwd: str = "") -> str:
+    """Get the supplement for SDK mode (Claude Agent SDK).
+
+    SDK mode does NOT include tool documentation because Claude automatically
+    receives tool schemas from the SDK. Only includes technical notes about
+    storage systems and execution environment.
+
+    Args:
+        use_e2b: Whether E2B cloud sandbox is being used
+        cwd: Current working directory (only used in local_storage mode)
+
+    Returns:
+        The supplement string to append to the system prompt
+    """
+    if use_e2b:
+        return _get_cloud_sandbox_supplement()
+    return _get_local_storage_supplement(cwd)
+
+
+def get_baseline_supplement() -> str:
+    """Get the supplement for baseline mode (direct OpenAI API).
+
+    Baseline mode INCLUDES auto-generated tool documentation because the
+    direct API doesn't automatically provide tool schemas to Claude.
+    Also includes shared technical notes (but NOT SDK-specific environment details).
+
+    Returns:
+        The supplement string to append to the system prompt
+    """
+    tool_docs = _generate_tool_documentation()
+    return tool_docs + _SHARED_TOOL_NOTES

autogpt_platform/backend/backend/copilot/sdk/agent_generation_guide.md

@@ -0,0 +1,155 @@
+## Agent Generation Guide
+
+You can create, edit, and customize agents directly. You ARE the brain —
+generate the agent JSON yourself using block schemas, then validate and save.
+
+### Workflow for Creating/Editing Agents
+
+1. **Discover blocks**: Call `find_block(query, include_schemas=true)` to
+   search for relevant blocks. This returns block IDs, names, descriptions,
+   and full input/output schemas.
+2. **Find library agents**: Call `find_library_agent` to discover reusable
+   agents that can be composed as sub-agents via `AgentExecutorBlock`.
+3. **Generate JSON**: Build the agent JSON using block schemas:
+   - Use block IDs from step 1 as `block_id` in nodes
+   - Wire outputs to inputs using links
+   - Set design-time config in `input_default`
+   - Use `AgentInputBlock` for values the user provides at runtime
+4. **Write to workspace**: Save the JSON to a workspace file so the user
+   can review it: `write_workspace_file(filename="agent.json", content=...)`
+5. **Validate**: Call `validate_agent_graph` with the agent JSON to check
+   for errors
+6. **Fix if needed**: Call `fix_agent_graph` to auto-fix common issues,
+   or fix manually based on the error descriptions. Iterate until valid.
+7. **Save**: Call `create_agent` (new) or `edit_agent` (existing) with
+   the final `agent_json`
+
+### Agent JSON Structure
+
+```json
+{
+  "id": "<UUID v4>",        // auto-generated if omitted
+  "version": 1,
+  "is_active": true,
+  "name": "Agent Name",
+  "description": "What the agent does",
+  "nodes": [
+    {
+      "id": "<UUID v4>",
+      "block_id": "<block UUID from find_block>",
+      "input_default": {
+        "field_name": "design-time value"
+      },
+      "metadata": {
+        "position": {"x": 0, "y": 0},
+        "customized_name": "Optional display name"
+      }
+    }
+  ],
+  "links": [
+    {
+      "id": "<UUID v4>",
+      "source_id": "<source node UUID>",
+      "source_name": "output_field_name",
+      "sink_id": "<sink node UUID>",
+      "sink_name": "input_field_name",
+      "is_static": false
+    }
+  ]
+}
+```
+
+### REQUIRED: AgentInputBlock and AgentOutputBlock
+
+Every agent MUST include at least one AgentInputBlock and one AgentOutputBlock.
+These define the agent's interface — what it accepts and what it produces.
+
+**AgentInputBlock** (ID: `c0a8e994-ebf1-4a9c-a4d8-89d09c86741b`):
+- Defines a user-facing input field on the agent
+- Required `input_default` fields: `name` (str), `value` (default: null)
+- Optional: `title`, `description`, `placeholder_values` (for dropdowns)
+- Output: `result` — the user-provided value at runtime
+- Create one AgentInputBlock per distinct input the agent needs
+
+**AgentOutputBlock** (ID: `363ae599-353e-4804-937e-b2ee3cef3da4`):
+- Defines a user-facing output displayed after the agent runs
+- Required `input_default` fields: `name` (str)
+- The `value` input should be linked from another block's output
+- Optional: `title`, `description`, `format` (Jinja2 template)
+- Create one AgentOutputBlock per distinct result to show the user
+
+Without these blocks, the agent has no interface and the user cannot provide
+inputs or see outputs. NEVER skip them.
+
+### Key Rules
+
+- **Name & description**: Include `name` and `description` in the agent JSON
+  when creating a new agent, or when editing and the agent's purpose changed.
+  Without these the agent gets a generic default name.
+- **Design-time vs runtime**: `input_default` = values known at build time.
+  For user-provided values, create an `AgentInputBlock` node and link its
+  output to the consuming block's input.
+- **Credentials**: Do NOT require credentials upfront. Users configure
+  credentials later in the platform UI after the agent is saved.
+- **Node spacing**: Position nodes with at least 800 X-units between them.
+- **Nested properties**: Use `parentField_#_childField` notation in link
+  sink_name/source_name to access nested object fields.
+- **is_static links**: Set `is_static: true` when the link carries a
+  design-time constant (matches a field in inputSchema with a default).
+- **ConditionBlock**: Needs a `StoreValueBlock` wired to its `value2` input.
+- **Prompt templates**: Use `{{variable}}` (double curly braces) for
+  literal braces in prompt strings — single `{` and `}` are for
+  template variables.
+- **AgentExecutorBlock**: When composing sub-agents, set `graph_id` and
+  `graph_version` in input_default, and wire inputs/outputs to match
+  the sub-agent's schema.
+
+### Using Sub-Agents (AgentExecutorBlock)
+
+To compose agents using other agents as sub-agents:
+1. Call `find_library_agent` to find the sub-agent — the response includes
+   `graph_id`, `graph_version`, `input_schema`, and `output_schema`
+2. Create an `AgentExecutorBlock` node (ID: `e189baac-8c20-45a1-94a7-55177ea42565`)
+3. Set `input_default`:
+   - `graph_id`: from the library agent's `graph_id`
+   - `graph_version`: from the library agent's `graph_version`
+   - `input_schema`: from the library agent's `input_schema` (JSON Schema)
+   - `output_schema`: from the library agent's `output_schema` (JSON Schema)
+   - `user_id`: leave as `""` (filled at runtime)
+   - `inputs`: `{}` (populated by links at runtime)
+4. Wire inputs: link to sink names matching the sub-agent's `input_schema`
+   property names (e.g., if input_schema has a `"url"` property, use
+   `"url"` as the sink_name)
+5. Wire outputs: link from source names matching the sub-agent's
+   `output_schema` property names
+6. Pass `library_agent_ids` to `create_agent`/`customize_agent` with
+   the library agent IDs used, so the fixer can validate schemas
+
+### Using MCP Tools (MCPToolBlock)
+
+To use an MCP (Model Context Protocol) tool as a node in the agent:
+1. The user must specify which MCP server URL and tool name they want
+2. Create an `MCPToolBlock` node (ID: `a0a4b1c2-d3e4-4f56-a7b8-c9d0e1f2a3b4`)
+3. Set `input_default`:
+   - `server_url`: the MCP server URL (e.g. `"https://mcp.example.com/sse"`)
+   - `selected_tool`: the tool name on that server
+   - `tool_input_schema`: JSON Schema for the tool's inputs
+   - `tool_arguments`: `{}` (populated by links or hardcoded values)
+4. The block requires MCP credentials — the user configures these in the
+   platform UI after the agent is saved
+5. Wire inputs using the tool argument field name directly as the sink_name
+   (e.g., `query`, NOT `tool_arguments_#_query`). The execution engine
+   automatically collects top-level fields matching tool_input_schema into
+   tool_arguments.
+6. Output: `result` (the tool's return value) and `error` (error message)
+
+### Example: Simple AI Text Processor
+
+A minimal agent with input, processing, and output:
+- Node 1: `AgentInputBlock` (ID: `c0a8e994-ebf1-4a9c-a4d8-89d09c86741b`,
+  input_default: {"name": "user_text", "title": "Text to process"},
+  output: "result")
+- Node 2: `AITextGeneratorBlock` (input: "prompt" linked from Node 1's "result")
+- Node 3: `AgentOutputBlock` (ID: `363ae599-353e-4804-937e-b2ee3cef3da4`,
+  input_default: {"name": "summary", "title": "Summary"},
+  input: "value" linked from Node 2's output)

autogpt_platform/backend/backend/copilot/sdk/e2b_file_tools.py

@@ -8,8 +8,6 @@ SDK-internal paths (``~/.claude/projects/…/tool-results/``) are handled
 by the separate ``Read`` MCP tool registered in ``tool_adapter.py``.
 """
 
-from __future__ import annotations
-
 import itertools
 import json
 import logging
@@ -17,36 +15,23 @@ import os
 import shlex
 from typing import Any, Callable
 
-from backend.copilot.tools.e2b_sandbox import E2B_WORKDIR
+from backend.copilot.context import (
+    E2B_WORKDIR,
+    get_current_sandbox,
+    get_sdk_cwd,
+    is_allowed_local_path,
+    resolve_sandbox_path,
+)
 
 logger = logging.getLogger(__name__)
 
 
-# Lazy imports to break circular dependency with tool_adapter.
-
-
-def _get_sandbox():  # type: ignore[return]
-    from .tool_adapter import get_current_sandbox  # noqa: E402
-
+def _get_sandbox():
     return get_current_sandbox()
 
 
 def _is_allowed_local(path: str) -> bool:
-    from .tool_adapter import is_allowed_local_path  # noqa: E402
-
-    return is_allowed_local_path(path)
-
-
-def _resolve_remote(path: str) -> str:
-    """Normalise *path* to an absolute sandbox path under ``/home/user``.
-
-    Raises :class:`ValueError` if the resolved path escapes the sandbox.
-    """
-    candidate = path if os.path.isabs(path) else os.path.join(E2B_WORKDIR, path)
-    normalized = os.path.normpath(candidate)
-    if normalized != E2B_WORKDIR and not normalized.startswith(E2B_WORKDIR + "/"):
-        raise ValueError(f"Path must be within {E2B_WORKDIR}: {path}")
-    return normalized
+    return is_allowed_local_path(path, get_sdk_cwd())
 
 
 def _mcp(text: str, *, error: bool = False) -> dict[str, Any]:
@@ -63,7 +48,7 @@ def _get_sandbox_and_path(
     if sandbox is None:
         return _mcp("No E2B sandbox available", error=True)
     try:
-        remote = _resolve_remote(file_path)
+        remote = resolve_sandbox_path(file_path)
     except ValueError as exc:
         return _mcp(str(exc), error=True)
     return sandbox, remote
@@ -73,6 +58,7 @@ def _get_sandbox_and_path(
 
 
 async def _handle_read_file(args: dict[str, Any]) -> dict[str, Any]:
+    """Read lines from a sandbox file, falling back to the local host for SDK-internal paths."""
     file_path: str = args.get("file_path", "")
     offset: int = max(0, int(args.get("offset", 0)))
     limit: int = max(1, int(args.get("limit", 2000)))
@@ -104,6 +90,7 @@ async def _handle_read_file(args: dict[str, Any]) -> dict[str, Any]:
 
 
 async def _handle_write_file(args: dict[str, Any]) -> dict[str, Any]:
+    """Write content to a sandbox file, creating parent directories as needed."""
     file_path: str = args.get("file_path", "")
     content: str = args.get("content", "")
 
@@ -127,6 +114,7 @@ async def _handle_write_file(args: dict[str, Any]) -> dict[str, Any]:
 
 
 async def _handle_edit_file(args: dict[str, Any]) -> dict[str, Any]:
+    """Replace a substring in a sandbox file, with optional replace-all support."""
     file_path: str = args.get("file_path", "")
     old_string: str = args.get("old_string", "")
     new_string: str = args.get("new_string", "")
@@ -172,6 +160,7 @@ async def _handle_edit_file(args: dict[str, Any]) -> dict[str, Any]:
 
 
 async def _handle_glob(args: dict[str, Any]) -> dict[str, Any]:
+    """Find files matching a name pattern inside the sandbox using ``find``."""
     pattern: str = args.get("pattern", "")
     path: str = args.get("path", "")
 
@@ -183,7 +172,7 @@ async def _handle_glob(args: dict[str, Any]) -> dict[str, Any]:
         return _mcp("No E2B sandbox available", error=True)
 
     try:
-        search_dir = _resolve_remote(path) if path else E2B_WORKDIR
+        search_dir = resolve_sandbox_path(path) if path else E2B_WORKDIR
     except ValueError as exc:
         return _mcp(str(exc), error=True)
 
@@ -198,6 +187,7 @@ async def _handle_glob(args: dict[str, Any]) -> dict[str, Any]:
 
 
 async def _handle_grep(args: dict[str, Any]) -> dict[str, Any]:
+    """Search file contents by regex inside the sandbox using ``grep -rn``."""
     pattern: str = args.get("pattern", "")
     path: str = args.get("path", "")
     include: str = args.get("include", "")
@@ -210,7 +200,7 @@ async def _handle_grep(args: dict[str, Any]) -> dict[str, Any]:
         return _mcp("No E2B sandbox available", error=True)
 
     try:
-        search_dir = _resolve_remote(path) if path else E2B_WORKDIR
+        search_dir = resolve_sandbox_path(path) if path else E2B_WORKDIR
     except ValueError as exc:
         return _mcp(str(exc), error=True)
 
@@ -238,7 +228,7 @@ def _read_local(file_path: str, offset: int, limit: int) -> dict[str, Any]:
         return _mcp(f"Path not allowed: {file_path}", error=True)
     expanded = os.path.realpath(os.path.expanduser(file_path))
     try:
-        with open(expanded) as fh:
+        with open(expanded, encoding="utf-8", errors="replace") as fh:
             selected = list(itertools.islice(fh, offset, offset + limit))
         numbered = "".join(
             f"{i + offset + 1:>6}\t{line}" for i, line in enumerate(selected)

autogpt_platform/backend/backend/copilot/sdk/e2b_file_tools_test.py

@@ -7,59 +7,60 @@ import os
 
 import pytest
 
-from .e2b_file_tools import _read_local, _resolve_remote
-from .tool_adapter import _current_project_dir
+from backend.copilot.context import _current_project_dir
+
+from .e2b_file_tools import _read_local, resolve_sandbox_path
 
 _SDK_PROJECTS_DIR = os.path.realpath(os.path.expanduser("~/.claude/projects"))
 
 
 # ---------------------------------------------------------------------------
-# _resolve_remote — sandbox path normalisation & boundary enforcement
+# resolve_sandbox_path — sandbox path normalisation & boundary enforcement
 # ---------------------------------------------------------------------------
 
 
-class TestResolveRemote:
+class TestResolveSandboxPath:
     def test_relative_path_resolved(self):
-        assert _resolve_remote("src/main.py") == "/home/user/src/main.py"
+        assert resolve_sandbox_path("src/main.py") == "/home/user/src/main.py"
 
     def test_absolute_within_sandbox(self):
-        assert _resolve_remote("/home/user/file.txt") == "/home/user/file.txt"
+        assert resolve_sandbox_path("/home/user/file.txt") == "/home/user/file.txt"
 
     def test_workdir_itself(self):
-        assert _resolve_remote("/home/user") == "/home/user"
+        assert resolve_sandbox_path("/home/user") == "/home/user"
 
     def test_relative_dotslash(self):
-        assert _resolve_remote("./README.md") == "/home/user/README.md"
+        assert resolve_sandbox_path("./README.md") == "/home/user/README.md"
 
     def test_traversal_blocked(self):
         with pytest.raises(ValueError, match="must be within /home/user"):
-            _resolve_remote("../../etc/passwd")
+            resolve_sandbox_path("../../etc/passwd")
 
     def test_absolute_traversal_blocked(self):
         with pytest.raises(ValueError, match="must be within /home/user"):
-            _resolve_remote("/home/user/../../etc/passwd")
+            resolve_sandbox_path("/home/user/../../etc/passwd")
 
     def test_absolute_outside_sandbox_blocked(self):
         with pytest.raises(ValueError, match="must be within /home/user"):
-            _resolve_remote("/etc/passwd")
+            resolve_sandbox_path("/etc/passwd")
 
     def test_root_blocked(self):
         with pytest.raises(ValueError, match="must be within /home/user"):
-            _resolve_remote("/")
+            resolve_sandbox_path("/")
 
     def test_home_other_user_blocked(self):
         with pytest.raises(ValueError, match="must be within /home/user"):
-            _resolve_remote("/home/other/file.txt")
+            resolve_sandbox_path("/home/other/file.txt")
 
     def test_deep_nested_allowed(self):
-        assert _resolve_remote("a/b/c/d/e.txt") == "/home/user/a/b/c/d/e.txt"
+        assert resolve_sandbox_path("a/b/c/d/e.txt") == "/home/user/a/b/c/d/e.txt"
 
     def test_trailing_slash_normalised(self):
-        assert _resolve_remote("src/") == "/home/user/src"
+        assert resolve_sandbox_path("src/") == "/home/user/src"
 
     def test_double_dots_within_sandbox_ok(self):
         """Path that resolves back within /home/user is allowed."""
-        assert _resolve_remote("a/b/../c.txt") == "/home/user/a/c.txt"
+        assert resolve_sandbox_path("a/b/../c.txt") == "/home/user/a/c.txt"
 
 
 # ---------------------------------------------------------------------------

autogpt_platform/backend/backend/copilot/sdk/file_ref.py

@@ -0,0 +1,281 @@
+"""File reference protocol for tool call inputs.
+
+Allows the LLM to pass a file reference instead of embedding large content
+inline.  The processor expands ``@@agptfile:<uri>[<start>-<end>]`` tokens in tool
+arguments before the tool is executed.
+
+Protocol
+--------
+
+    @@agptfile:<uri>[<start>-<end>]
+
+``<uri>`` (required)
+    - ``workspace://<file_id>`` — workspace file by ID
+    - ``workspace://<file_id>#<mime>`` — same, MIME hint is ignored for reads
+    - ``workspace:///<path>`` — workspace file by virtual path
+    - ``/absolute/local/path`` — ephemeral or sdk_cwd file (validated by
+      :func:`~backend.copilot.sdk.tool_adapter.is_allowed_local_path`)
+    - Any absolute path that resolves inside the E2B sandbox
+      (``/home/user/...``) when a sandbox is active
+
+``[<start>-<end>]`` (optional)
+    Line range, 1-indexed inclusive.  Examples: ``[1-100]``, ``[50-200]``.
+    Omit to read the entire file.
+
+Examples
+--------
+    @@agptfile:workspace://abc123
+    @@agptfile:workspace://abc123[10-50]
+    @@agptfile:workspace:///reports/q1.md
+    @@agptfile:/tmp/copilot-<session>/output.py[1-80]
+    @@agptfile:/home/user/script.sh
+"""
+
+import itertools
+import logging
+import os
+import re
+from dataclasses import dataclass
+from typing import Any
+
+from backend.copilot.context import (
+    get_current_sandbox,
+    get_sdk_cwd,
+    is_allowed_local_path,
+    resolve_sandbox_path,
+)
+from backend.copilot.model import ChatSession
+from backend.copilot.tools.workspace_files import get_manager
+from backend.util.file import parse_workspace_uri
+
+
+class FileRefExpansionError(Exception):
+    """Raised when a ``@@agptfile:`` reference in tool call args fails to resolve.
+
+    Separating this from inline substitution lets callers (e.g. the MCP tool
+    wrapper) block tool execution and surface a helpful error to the model
+    rather than passing an ``[file-ref error: …]`` string as actual input.
+    """
+
+
+logger = logging.getLogger(__name__)
+
+FILE_REF_PREFIX = "@@agptfile:"
+
+# Matches:  @@agptfile:<uri>[start-end]?
+#   Group 1 – URI; must start with '/' (absolute path) or 'workspace://'
+#   Group 2 – start line (optional)
+#   Group 3 – end line (optional)
+_FILE_REF_RE = re.compile(
+    re.escape(FILE_REF_PREFIX) + r"((?:workspace://|/)[^\[\s]*)(?:\[(\d+)-(\d+)\])?"
+)
+
+# Maximum characters returned for a single file reference expansion.
+_MAX_EXPAND_CHARS = 200_000
+# Maximum total characters across all @@agptfile: expansions in one string.
+_MAX_TOTAL_EXPAND_CHARS = 1_000_000
+
+
+@dataclass
+class FileRef:
+    uri: str
+    start_line: int | None  # 1-indexed, inclusive
+    end_line: int | None  # 1-indexed, inclusive
+
+
+def parse_file_ref(text: str) -> FileRef | None:
+    """Return a :class:`FileRef` if *text* is a bare file reference token.
+
+    A "bare token" means the entire string matches the ``@@agptfile:...`` pattern
+    (after stripping whitespace).  Use :func:`expand_file_refs_in_string` to
+    expand references embedded in larger strings.
+    """
+    m = _FILE_REF_RE.fullmatch(text.strip())
+    if not m:
+        return None
+    start = int(m.group(2)) if m.group(2) else None
+    end = int(m.group(3)) if m.group(3) else None
+    if start is not None and start < 1:
+        return None
+    if end is not None and end < 1:
+        return None
+    if start is not None and end is not None and end < start:
+        return None
+    return FileRef(uri=m.group(1), start_line=start, end_line=end)
+
+
+def _apply_line_range(text: str, start: int | None, end: int | None) -> str:
+    """Slice *text* to the requested 1-indexed line range (inclusive)."""
+    if start is None and end is None:
+        return text
+    lines = text.splitlines(keepends=True)
+    s = (start - 1) if start is not None else 0
+    e = end if end is not None else len(lines)
+    selected = list(itertools.islice(lines, s, e))
+    return "".join(selected)
+
+
+async def read_file_bytes(
+    uri: str,
+    user_id: str | None,
+    session: ChatSession,
+) -> bytes:
+    """Resolve *uri* to raw bytes using workspace, local, or E2B path logic.
+
+    Raises :class:`ValueError` if the URI cannot be resolved.
+    """
+    # Strip MIME fragment (e.g. workspace://id#mime) before dispatching.
+    plain = uri.split("#")[0] if uri.startswith("workspace://") else uri
+
+    if plain.startswith("workspace://"):
+        if not user_id:
+            raise ValueError("workspace:// file references require authentication")
+        manager = await get_manager(user_id, session.session_id)
+        ws = parse_workspace_uri(plain)
+        try:
+            return await (
+                manager.read_file(ws.file_ref)
+                if ws.is_path
+                else manager.read_file_by_id(ws.file_ref)
+            )
+        except FileNotFoundError:
+            raise ValueError(f"File not found: {plain}")
+        except Exception as exc:
+            raise ValueError(f"Failed to read {plain}: {exc}") from exc
+
+    if is_allowed_local_path(plain, get_sdk_cwd()):
+        resolved = os.path.realpath(os.path.expanduser(plain))
+        try:
+            with open(resolved, "rb") as fh:
+                return fh.read()
+        except FileNotFoundError:
+            raise ValueError(f"File not found: {plain}")
+        except Exception as exc:
+            raise ValueError(f"Failed to read {plain}: {exc}") from exc
+
+    sandbox = get_current_sandbox()
+    if sandbox is not None:
+        try:
+            remote = resolve_sandbox_path(plain)
+        except ValueError as exc:
+            raise ValueError(
+                f"Path is not allowed (not in workspace, sdk_cwd, or sandbox): {plain}"
+            ) from exc
+        try:
+            return bytes(await sandbox.files.read(remote, format="bytes"))
+        except Exception as exc:
+            raise ValueError(f"Failed to read from sandbox: {plain}: {exc}") from exc
+
+    raise ValueError(
+        f"Path is not allowed (not in workspace, sdk_cwd, or sandbox): {plain}"
+    )
+
+
+async def resolve_file_ref(
+    ref: FileRef,
+    user_id: str | None,
+    session: ChatSession,
+) -> str:
+    """Resolve a :class:`FileRef` to its text content."""
+    raw = await read_file_bytes(ref.uri, user_id, session)
+    return _apply_line_range(
+        raw.decode("utf-8", errors="replace"), ref.start_line, ref.end_line
+    )
+
+
+async def expand_file_refs_in_string(
+    text: str,
+    user_id: str | None,
+    session: "ChatSession",
+    *,
+    raise_on_error: bool = False,
+) -> str:
+    """Expand all ``@@agptfile:...`` tokens in *text*, returning the substituted string.
+
+    Non-reference text is passed through unchanged.
+
+    If *raise_on_error* is ``False`` (default), expansion errors are surfaced
+    inline as ``[file-ref error: <message>]`` — useful for display/log contexts
+    where partial expansion is acceptable.
+
+    If *raise_on_error* is ``True``, any resolution failure raises
+    :class:`FileRefExpansionError` immediately so the caller can block the
+    operation and surface a clean error to the model.
+    """
+    if FILE_REF_PREFIX not in text:
+        return text
+
+    result: list[str] = []
+    last_end = 0
+    total_chars = 0
+    for m in _FILE_REF_RE.finditer(text):
+        result.append(text[last_end : m.start()])
+        start = int(m.group(2)) if m.group(2) else None
+        end = int(m.group(3)) if m.group(3) else None
+        if (start is not None and start < 1) or (end is not None and end < 1):
+            msg = f"line numbers must be >= 1: {m.group(0)}"
+            if raise_on_error:
+                raise FileRefExpansionError(msg)
+            result.append(f"[file-ref error: {msg}]")
+            last_end = m.end()
+            continue
+        if start is not None and end is not None and end < start:
+            msg = f"end line must be >= start line: {m.group(0)}"
+            if raise_on_error:
+                raise FileRefExpansionError(msg)
+            result.append(f"[file-ref error: {msg}]")
+            last_end = m.end()
+            continue
+        ref = FileRef(uri=m.group(1), start_line=start, end_line=end)
+        try:
+            content = await resolve_file_ref(ref, user_id, session)
+            if len(content) > _MAX_EXPAND_CHARS:
+                content = content[:_MAX_EXPAND_CHARS] + "\n... [truncated]"
+            remaining = _MAX_TOTAL_EXPAND_CHARS - total_chars
+            if remaining <= 0:
+                content = "[file-ref budget exhausted: total expansion limit reached]"
+            elif len(content) > remaining:
+                content = content[:remaining] + "\n... [total budget exhausted]"
+            total_chars += len(content)
+            result.append(content)
+        except ValueError as exc:
+            logger.warning("file-ref expansion failed for %r: %s", m.group(0), exc)
+            if raise_on_error:
+                raise FileRefExpansionError(str(exc)) from exc
+            result.append(f"[file-ref error: {exc}]")
+        last_end = m.end()
+
+    result.append(text[last_end:])
+    return "".join(result)
+
+
+async def expand_file_refs_in_args(
+    args: dict[str, Any],
+    user_id: str | None,
+    session: "ChatSession",
+) -> dict[str, Any]:
+    """Recursively expand ``@@agptfile:...`` references in tool call arguments.
+
+    String values are expanded in-place.  Nested dicts and lists are
+    traversed.  Non-string scalars are returned unchanged.
+
+    Raises :class:`FileRefExpansionError` if any reference fails to resolve,
+    so the tool is *not* executed with an error string as its input.  The
+    caller (the MCP tool wrapper) should convert this into an MCP error
+    response that lets the model correct the reference before retrying.
+    """
+    if not args:
+        return args
+
+    async def _expand(value: Any) -> Any:
+        if isinstance(value, str):
+            return await expand_file_refs_in_string(
+                value, user_id, session, raise_on_error=True
+            )
+        if isinstance(value, dict):
+            return {k: await _expand(v) for k, v in value.items()}
+        if isinstance(value, list):
+            return [await _expand(item) for item in value]
+        return value
+
+    return {k: await _expand(v) for k, v in args.items()}

autogpt_platform/backend/backend/copilot/sdk/file_ref_integration_test.py

@@ -0,0 +1,328 @@
+"""Integration tests for @@agptfile: reference expansion in tool calls.
+
+These tests verify the end-to-end behaviour of the file reference protocol:
+- Parsing @@agptfile: tokens from tool arguments
+- Resolving local-filesystem paths (sdk_cwd / ephemeral)
+- Expanding references inside the tool-call pipeline (_execute_tool_sync)
+- The extended Read tool handler (workspace:// pass-through via session context)
+
+No real LLM or database is required; workspace reads are stubbed where needed.
+"""
+
+from __future__ import annotations
+
+import os
+import tempfile
+from unittest.mock import AsyncMock, MagicMock, patch
+
+import pytest
+
+from backend.copilot.sdk.file_ref import (
+    FileRef,
+    expand_file_refs_in_args,
+    expand_file_refs_in_string,
+    read_file_bytes,
+    resolve_file_ref,
+)
+from backend.copilot.sdk.tool_adapter import _read_file_handler
+
+# ---------------------------------------------------------------------------
+# Helpers
+# ---------------------------------------------------------------------------
+
+
+def _make_session(session_id: str = "integ-sess") -> MagicMock:
+    s = MagicMock()
+    s.session_id = session_id
+    return s
+
+
+# ---------------------------------------------------------------------------
+# Local-file resolution (sdk_cwd)
+# ---------------------------------------------------------------------------
+
+
+@pytest.mark.asyncio
+async def test_resolve_file_ref_local_path():
+    """resolve_file_ref reads a real local file when it's within sdk_cwd."""
+    with tempfile.TemporaryDirectory() as sdk_cwd:
+        # Write a test file inside sdk_cwd
+        test_file = os.path.join(sdk_cwd, "hello.txt")
+        with open(test_file, "w") as f:
+            f.write("line1\nline2\nline3\n")
+
+        session = _make_session()
+        with patch("backend.copilot.context._current_sdk_cwd") as mock_cwd_var:
+            mock_cwd_var.get.return_value = sdk_cwd
+
+            ref = FileRef(uri=test_file, start_line=None, end_line=None)
+            content = await resolve_file_ref(ref, user_id="u1", session=session)
+
+        assert content == "line1\nline2\nline3\n"
+
+
+@pytest.mark.asyncio
+async def test_resolve_file_ref_local_path_with_line_range():
+    """resolve_file_ref respects line ranges for local files."""
+    with tempfile.TemporaryDirectory() as sdk_cwd:
+        test_file = os.path.join(sdk_cwd, "multi.txt")
+        lines = [f"line{i}\n" for i in range(1, 11)]  # line1 … line10
+        with open(test_file, "w") as f:
+            f.writelines(lines)
+
+        session = _make_session()
+        with patch("backend.copilot.context._current_sdk_cwd") as mock_cwd_var:
+            mock_cwd_var.get.return_value = sdk_cwd
+
+            ref = FileRef(uri=test_file, start_line=3, end_line=5)
+            content = await resolve_file_ref(ref, user_id="u1", session=session)
+
+        assert content == "line3\nline4\nline5\n"
+
+
+@pytest.mark.asyncio
+async def test_resolve_file_ref_rejects_path_outside_sdk_cwd():
+    """resolve_file_ref raises ValueError for paths outside sdk_cwd."""
+    with tempfile.TemporaryDirectory() as sdk_cwd:
+        with patch("backend.copilot.context._current_sdk_cwd") as mock_cwd_var, patch(
+            "backend.copilot.context._current_sandbox"
+        ) as mock_sandbox_var:
+            mock_cwd_var.get.return_value = sdk_cwd
+            mock_sandbox_var.get.return_value = None
+
+            ref = FileRef(uri="/etc/passwd", start_line=None, end_line=None)
+            with pytest.raises(ValueError, match="not allowed"):
+                await resolve_file_ref(ref, user_id="u1", session=_make_session())
+
+
+# ---------------------------------------------------------------------------
+# expand_file_refs_in_string — integration with real files
+# ---------------------------------------------------------------------------
+
+
+@pytest.mark.asyncio
+async def test_expand_string_with_real_file():
+    """expand_file_refs_in_string replaces @@agptfile: token with actual content."""
+    with tempfile.TemporaryDirectory() as sdk_cwd:
+        test_file = os.path.join(sdk_cwd, "data.txt")
+        with open(test_file, "w") as f:
+            f.write("hello world\n")
+
+        with patch("backend.copilot.context._current_sdk_cwd") as mock_cwd_var:
+            mock_cwd_var.get.return_value = sdk_cwd
+
+            result = await expand_file_refs_in_string(
+                f"Content: @@agptfile:{test_file}",
+                user_id="u1",
+                session=_make_session(),
+            )
+
+        assert result == "Content: hello world\n"
+
+
+@pytest.mark.asyncio
+async def test_expand_string_missing_file_is_surfaced_inline():
+    """Missing file ref yields [file-ref error: …] inline rather than raising."""
+    with tempfile.TemporaryDirectory() as sdk_cwd:
+        missing = os.path.join(sdk_cwd, "does_not_exist.txt")
+
+        with patch("backend.copilot.context._current_sdk_cwd") as mock_cwd_var:
+            mock_cwd_var.get.return_value = sdk_cwd
+
+            result = await expand_file_refs_in_string(
+                f"@@agptfile:{missing}",
+                user_id="u1",
+                session=_make_session(),
+            )
+
+        assert "[file-ref error:" in result
+        assert "not found" in result.lower() or "not allowed" in result.lower()
+
+
+# ---------------------------------------------------------------------------
+# expand_file_refs_in_args — dict traversal with real files
+# ---------------------------------------------------------------------------
+
+
+@pytest.mark.asyncio
+async def test_expand_args_replaces_file_ref_in_nested_dict():
+    """Nested @@agptfile: references in args are fully expanded."""
+    with tempfile.TemporaryDirectory() as sdk_cwd:
+        file_a = os.path.join(sdk_cwd, "a.txt")
+        file_b = os.path.join(sdk_cwd, "b.txt")
+        with open(file_a, "w") as f:
+            f.write("AAA")
+        with open(file_b, "w") as f:
+            f.write("BBB")
+
+        with patch("backend.copilot.context._current_sdk_cwd") as mock_cwd_var:
+            mock_cwd_var.get.return_value = sdk_cwd
+
+            result = await expand_file_refs_in_args(
+                {
+                    "outer": {
+                        "content_a": f"@@agptfile:{file_a}",
+                        "content_b": f"start @@agptfile:{file_b} end",
+                    },
+                    "count": 42,
+                },
+                user_id="u1",
+                session=_make_session(),
+            )
+
+        assert result["outer"]["content_a"] == "AAA"
+        assert result["outer"]["content_b"] == "start BBB end"
+        assert result["count"] == 42
+
+
+# ---------------------------------------------------------------------------
+# _read_file_handler — extended to accept workspace:// and local paths
+# ---------------------------------------------------------------------------
+
+
+@pytest.mark.asyncio
+async def test_read_file_handler_local_file():
+    """_read_file_handler reads a local file when it's within sdk_cwd."""
+    with tempfile.TemporaryDirectory() as sdk_cwd:
+        test_file = os.path.join(sdk_cwd, "read_test.txt")
+        lines = [f"L{i}\n" for i in range(1, 6)]
+        with open(test_file, "w") as f:
+            f.writelines(lines)
+
+        with patch("backend.copilot.context._current_sdk_cwd") as mock_cwd_var, patch(
+            "backend.copilot.context._current_project_dir"
+        ) as mock_proj_var, patch(
+            "backend.copilot.sdk.tool_adapter.get_execution_context",
+            return_value=("user-1", _make_session()),
+        ):
+            mock_cwd_var.get.return_value = sdk_cwd
+            mock_proj_var.get.return_value = ""
+
+            result = await _read_file_handler(
+                {"file_path": test_file, "offset": 0, "limit": 5}
+            )
+
+        assert not result["isError"]
+        text = result["content"][0]["text"]
+        assert "L1" in text
+        assert "L5" in text
+
+
+@pytest.mark.asyncio
+async def test_read_file_handler_workspace_uri():
+    """_read_file_handler handles workspace:// URIs via the workspace manager."""
+    mock_session = _make_session()
+    mock_manager = AsyncMock()
+    mock_manager.read_file_by_id.return_value = b"workspace file content\nline two\n"
+
+    with patch(
+        "backend.copilot.sdk.tool_adapter.get_execution_context",
+        return_value=("user-1", mock_session),
+    ), patch(
+        "backend.copilot.sdk.file_ref.get_manager",
+        new=AsyncMock(return_value=mock_manager),
+    ):
+        result = await _read_file_handler(
+            {"file_path": "workspace://file-id-abc", "offset": 0, "limit": 10}
+        )
+
+    assert not result["isError"], result["content"][0]["text"]
+    text = result["content"][0]["text"]
+    assert "workspace file content" in text
+    assert "line two" in text
+
+
+@pytest.mark.asyncio
+async def test_read_file_handler_workspace_uri_no_session():
+    """_read_file_handler returns error when workspace:// is used without session."""
+    with patch(
+        "backend.copilot.sdk.tool_adapter.get_execution_context",
+        return_value=(None, None),
+    ):
+        result = await _read_file_handler({"file_path": "workspace://some-id"})
+
+    assert result["isError"]
+    assert "session" in result["content"][0]["text"].lower()
+
+
+@pytest.mark.asyncio
+async def test_read_file_handler_access_denied():
+    """_read_file_handler rejects paths outside allowed locations."""
+    with patch("backend.copilot.context._current_sdk_cwd") as mock_cwd, patch(
+        "backend.copilot.context._current_sandbox"
+    ) as mock_sandbox, patch(
+        "backend.copilot.sdk.tool_adapter.get_execution_context",
+        return_value=("user-1", _make_session()),
+    ):
+        mock_cwd.get.return_value = "/tmp/safe-dir"
+        mock_sandbox.get.return_value = None
+
+        result = await _read_file_handler({"file_path": "/etc/passwd"})
+
+    assert result["isError"]
+    assert "not allowed" in result["content"][0]["text"].lower()
+
+
+# ---------------------------------------------------------------------------
+# read_file_bytes — workspace:///path (virtual path) and E2B sandbox branch
+# ---------------------------------------------------------------------------
+
+
+@pytest.mark.asyncio
+async def test_read_file_bytes_workspace_virtual_path():
+    """workspace:///path resolves via manager.read_file (is_path=True path)."""
+    session = _make_session()
+    mock_manager = AsyncMock()
+    mock_manager.read_file.return_value = b"virtual path content"
+
+    with patch(
+        "backend.copilot.sdk.file_ref.get_manager",
+        new=AsyncMock(return_value=mock_manager),
+    ):
+        result = await read_file_bytes("workspace:///reports/q1.md", "user-1", session)
+
+    assert result == b"virtual path content"
+    mock_manager.read_file.assert_awaited_once_with("/reports/q1.md")
+
+
+@pytest.mark.asyncio
+async def test_read_file_bytes_e2b_sandbox_branch():
+    """read_file_bytes reads from the E2B sandbox when a sandbox is active."""
+    session = _make_session()
+    mock_sandbox = AsyncMock()
+    mock_sandbox.files.read.return_value = bytearray(b"sandbox content")
+
+    with patch("backend.copilot.context._current_sdk_cwd") as mock_cwd, patch(
+        "backend.copilot.context._current_sandbox"
+    ) as mock_sandbox_var, patch(
+        "backend.copilot.context._current_project_dir"
+    ) as mock_proj:
+        mock_cwd.get.return_value = ""
+        mock_sandbox_var.get.return_value = mock_sandbox
+        mock_proj.get.return_value = ""
+
+        result = await read_file_bytes("/home/user/script.sh", None, session)
+
+    assert result == b"sandbox content"
+    mock_sandbox.files.read.assert_awaited_once_with(
+        "/home/user/script.sh", format="bytes"
+    )
+
+
+@pytest.mark.asyncio
+async def test_read_file_bytes_e2b_path_escapes_sandbox_raises():
+    """read_file_bytes raises ValueError for paths that escape the sandbox root."""
+    session = _make_session()
+    mock_sandbox = AsyncMock()
+
+    with patch("backend.copilot.context._current_sdk_cwd") as mock_cwd, patch(
+        "backend.copilot.context._current_sandbox"
+    ) as mock_sandbox_var, patch(
+        "backend.copilot.context._current_project_dir"
+    ) as mock_proj:
+        mock_cwd.get.return_value = ""
+        mock_sandbox_var.get.return_value = mock_sandbox
+        mock_proj.get.return_value = ""
+
+        with pytest.raises(ValueError, match="not allowed"):
+            await read_file_bytes("/etc/passwd", None, session)

autogpt_platform/backend/backend/copilot/sdk/file_ref_test.py

@@ -0,0 +1,382 @@
+"""Tests for the @@agptfile: reference protocol (file_ref.py)."""
+
+from __future__ import annotations
+
+from unittest.mock import AsyncMock, MagicMock, patch
+
+import pytest
+
+from backend.copilot.sdk.file_ref import (
+    _MAX_EXPAND_CHARS,
+    FileRef,
+    FileRefExpansionError,
+    _apply_line_range,
+    expand_file_refs_in_args,
+    expand_file_refs_in_string,
+    parse_file_ref,
+)
+
+# ---------------------------------------------------------------------------
+# parse_file_ref
+# ---------------------------------------------------------------------------
+
+
+def test_parse_file_ref_workspace_id():
+    ref = parse_file_ref("@@agptfile:workspace://abc123")
+    assert ref == FileRef(uri="workspace://abc123", start_line=None, end_line=None)
+
+
+def test_parse_file_ref_workspace_id_with_mime():
+    ref = parse_file_ref("@@agptfile:workspace://abc123#text/plain")
+    assert ref is not None
+    assert ref.uri == "workspace://abc123#text/plain"
+    assert ref.start_line is None
+
+
+def test_parse_file_ref_workspace_path():
+    ref = parse_file_ref("@@agptfile:workspace:///reports/q1.md")
+    assert ref is not None
+    assert ref.uri == "workspace:///reports/q1.md"
+
+
+def test_parse_file_ref_with_line_range():
+    ref = parse_file_ref("@@agptfile:workspace://abc123[10-50]")
+    assert ref == FileRef(uri="workspace://abc123", start_line=10, end_line=50)
+
+
+def test_parse_file_ref_local_path():
+    ref = parse_file_ref("@@agptfile:/tmp/copilot-session/output.py[1-100]")
+    assert ref is not None
+    assert ref.uri == "/tmp/copilot-session/output.py"
+    assert ref.start_line == 1
+    assert ref.end_line == 100
+
+
+def test_parse_file_ref_no_match():
+    assert parse_file_ref("just a normal string") is None
+    assert parse_file_ref("workspace://abc123") is None  # missing @@agptfile: prefix
+    assert (
+        parse_file_ref("@@agptfile:workspace://abc123 extra") is None
+    )  # not full match
+
+
+def test_parse_file_ref_strips_whitespace():
+    ref = parse_file_ref("  @@agptfile:workspace://abc123  ")
+    assert ref is not None
+    assert ref.uri == "workspace://abc123"
+
+
+def test_parse_file_ref_invalid_range_zero_start():
+    assert parse_file_ref("@@agptfile:workspace://abc123[0-5]") is None
+
+
+def test_parse_file_ref_invalid_range_end_less_than_start():
+    assert parse_file_ref("@@agptfile:workspace://abc123[10-5]") is None
+
+
+def test_parse_file_ref_invalid_range_zero_end():
+    assert parse_file_ref("@@agptfile:workspace://abc123[1-0]") is None
+
+
+# ---------------------------------------------------------------------------
+# _apply_line_range
+# ---------------------------------------------------------------------------
+
+
+TEXT = "line1\nline2\nline3\nline4\nline5\n"
+
+
+def test_apply_line_range_no_range():
+    assert _apply_line_range(TEXT, None, None) == TEXT
+
+
+def test_apply_line_range_start_only():
+    result = _apply_line_range(TEXT, 3, None)
+    assert result == "line3\nline4\nline5\n"
+
+
+def test_apply_line_range_full():
+    result = _apply_line_range(TEXT, 2, 4)
+    assert result == "line2\nline3\nline4\n"
+
+
+def test_apply_line_range_single_line():
+    result = _apply_line_range(TEXT, 2, 2)
+    assert result == "line2\n"
+
+
+def test_apply_line_range_beyond_eof():
+    result = _apply_line_range(TEXT, 4, 999)
+    assert result == "line4\nline5\n"
+
+
+# ---------------------------------------------------------------------------
+# expand_file_refs_in_string
+# ---------------------------------------------------------------------------
+
+
+def _make_session(session_id: str = "sess-1") -> MagicMock:
+    session = MagicMock()
+    session.session_id = session_id
+    return session
+
+
+async def _resolve_always(ref: FileRef, _user_id: str | None, _session: object) -> str:
+    """Stub resolver that returns the URI and range as a descriptive string."""
+    if ref.start_line is not None:
+        return f"content:{ref.uri}[{ref.start_line}-{ref.end_line}]"
+    return f"content:{ref.uri}"
+
+
+@pytest.mark.asyncio
+async def test_expand_no_refs():
+    result = await expand_file_refs_in_string(
+        "no references here", user_id="u1", session=_make_session()
+    )
+    assert result == "no references here"
+
+
+@pytest.mark.asyncio
+async def test_expand_single_ref():
+    with patch(
+        "backend.copilot.sdk.file_ref.resolve_file_ref",
+        new=AsyncMock(side_effect=_resolve_always),
+    ):
+        result = await expand_file_refs_in_string(
+            "@@agptfile:workspace://abc123",
+            user_id="u1",
+            session=_make_session(),
+        )
+    assert result == "content:workspace://abc123"
+
+
+@pytest.mark.asyncio
+async def test_expand_ref_with_range():
+    with patch(
+        "backend.copilot.sdk.file_ref.resolve_file_ref",
+        new=AsyncMock(side_effect=_resolve_always),
+    ):
+        result = await expand_file_refs_in_string(
+            "@@agptfile:workspace://abc123[10-50]",
+            user_id="u1",
+            session=_make_session(),
+        )
+    assert result == "content:workspace://abc123[10-50]"
+
+
+@pytest.mark.asyncio
+async def test_expand_ref_embedded_in_text():
+    with patch(
+        "backend.copilot.sdk.file_ref.resolve_file_ref",
+        new=AsyncMock(side_effect=_resolve_always),
+    ):
+        result = await expand_file_refs_in_string(
+            "Here is the file: @@agptfile:workspace://abc123 — done",
+            user_id="u1",
+            session=_make_session(),
+        )
+    assert result == "Here is the file: content:workspace://abc123 — done"
+
+
+@pytest.mark.asyncio
+async def test_expand_multiple_refs():
+    with patch(
+        "backend.copilot.sdk.file_ref.resolve_file_ref",
+        new=AsyncMock(side_effect=_resolve_always),
+    ):
+        result = await expand_file_refs_in_string(
+            "@@agptfile:workspace://file1 and @@agptfile:workspace://file2[1-5]",
+            user_id="u1",
+            session=_make_session(),
+        )
+    assert result == "content:workspace://file1 and content:workspace://file2[1-5]"
+
+
+@pytest.mark.asyncio
+async def test_expand_invalid_range_zero_start_surfaces_inline():
+    """expand_file_refs_in_string surfaces [file-ref error: ...] for zero-start ranges."""
+    result = await expand_file_refs_in_string(
+        "@@agptfile:workspace://abc123[0-5]",
+        user_id="u1",
+        session=_make_session(),
+    )
+    assert "[file-ref error:" in result
+    assert "line numbers must be >= 1" in result
+
+
+@pytest.mark.asyncio
+async def test_expand_invalid_range_end_less_than_start_surfaces_inline():
+    """expand_file_refs_in_string surfaces [file-ref error: ...] when end < start."""
+    result = await expand_file_refs_in_string(
+        "prefix @@agptfile:workspace://abc123[10-5] suffix",
+        user_id="u1",
+        session=_make_session(),
+    )
+    assert "[file-ref error:" in result
+    assert "end line must be >= start line" in result
+    assert "prefix" in result
+    assert "suffix" in result
+
+
+@pytest.mark.asyncio
+async def test_expand_ref_error_surfaces_inline():
+    async def _raise(*args, **kwargs):  # noqa: ARG001
+        raise ValueError("file not found")
+
+    with patch(
+        "backend.copilot.sdk.file_ref.resolve_file_ref",
+        new=AsyncMock(side_effect=_raise),
+    ):
+        result = await expand_file_refs_in_string(
+            "@@agptfile:workspace://bad",
+            user_id="u1",
+            session=_make_session(),
+        )
+    assert "[file-ref error:" in result
+    assert "file not found" in result
+
+
+# ---------------------------------------------------------------------------
+# expand_file_refs_in_args
+# ---------------------------------------------------------------------------
+
+
+@pytest.mark.asyncio
+async def test_expand_args_flat():
+    with patch(
+        "backend.copilot.sdk.file_ref.resolve_file_ref",
+        new=AsyncMock(side_effect=_resolve_always),
+    ):
+        result = await expand_file_refs_in_args(
+            {"content": "@@agptfile:workspace://abc123", "other": 42},
+            user_id="u1",
+            session=_make_session(),
+        )
+    assert result["content"] == "content:workspace://abc123"
+    assert result["other"] == 42
+
+
+@pytest.mark.asyncio
+async def test_expand_args_nested_dict():
+    with patch(
+        "backend.copilot.sdk.file_ref.resolve_file_ref",
+        new=AsyncMock(side_effect=_resolve_always),
+    ):
+        result = await expand_file_refs_in_args(
+            {"outer": {"inner": "@@agptfile:workspace://nested"}},
+            user_id="u1",
+            session=_make_session(),
+        )
+    assert result["outer"]["inner"] == "content:workspace://nested"
+
+
+@pytest.mark.asyncio
+async def test_expand_args_list():
+    with patch(
+        "backend.copilot.sdk.file_ref.resolve_file_ref",
+        new=AsyncMock(side_effect=_resolve_always),
+    ):
+        result = await expand_file_refs_in_args(
+            {
+                "items": [
+                    "@@agptfile:workspace://a",
+                    "plain",
+                    "@@agptfile:workspace://b[1-3]",
+                ]
+            },
+            user_id="u1",
+            session=_make_session(),
+        )
+    assert result["items"] == [
+        "content:workspace://a",
+        "plain",
+        "content:workspace://b[1-3]",
+    ]
+
+
+@pytest.mark.asyncio
+async def test_expand_args_empty():
+    result = await expand_file_refs_in_args({}, user_id="u1", session=_make_session())
+    assert result == {}
+
+
+@pytest.mark.asyncio
+async def test_expand_args_no_refs():
+    result = await expand_file_refs_in_args(
+        {"key": "no refs here", "num": 1},
+        user_id="u1",
+        session=_make_session(),
+    )
+    assert result == {"key": "no refs here", "num": 1}
+
+
+@pytest.mark.asyncio
+async def test_expand_args_raises_on_file_ref_error():
+    """expand_file_refs_in_args raises FileRefExpansionError instead of passing
+    the inline error string to the tool, blocking tool execution."""
+
+    async def _raise(*args, **kwargs):  # noqa: ARG001
+        raise ValueError("path does not exist")
+
+    with patch(
+        "backend.copilot.sdk.file_ref.resolve_file_ref",
+        new=AsyncMock(side_effect=_raise),
+    ):
+        with pytest.raises(FileRefExpansionError) as exc_info:
+            await expand_file_refs_in_args(
+                {"prompt": "@@agptfile:/home/user/missing.txt"},
+                user_id="u1",
+                session=_make_session(),
+            )
+    assert "path does not exist" in str(exc_info.value)
+
+
+# ---------------------------------------------------------------------------
+# Per-file truncation and aggregate budget
+# ---------------------------------------------------------------------------
+
+
+@pytest.mark.asyncio
+async def test_expand_per_file_truncation():
+    """Content exceeding _MAX_EXPAND_CHARS is truncated with a marker."""
+    oversized = "x" * (_MAX_EXPAND_CHARS + 100)
+
+    async def _resolve_oversized(ref: FileRef, _uid: str | None, _s: object) -> str:
+        return oversized
+
+    with patch(
+        "backend.copilot.sdk.file_ref.resolve_file_ref",
+        new=AsyncMock(side_effect=_resolve_oversized),
+    ):
+        result = await expand_file_refs_in_string(
+            "@@agptfile:workspace://big-file",
+            user_id="u1",
+            session=_make_session(),
+        )
+
+    assert len(result) <= _MAX_EXPAND_CHARS + len("\n... [truncated]") + 10
+    assert "[truncated]" in result
+
+
+@pytest.mark.asyncio
+async def test_expand_aggregate_budget_exhausted():
+    """When the aggregate budget is exhausted, later refs get the budget message."""
+    # Each file returns just under 300K; after ~4 files the 1M budget is used.
+    big_chunk = "y" * 300_000
+
+    async def _resolve_big(ref: FileRef, _uid: str | None, _s: object) -> str:
+        return big_chunk
+
+    with patch(
+        "backend.copilot.sdk.file_ref.resolve_file_ref",
+        new=AsyncMock(side_effect=_resolve_big),
+    ):
+        # 5 refs @ 300K each = 1.5M → last ref(s) should hit the aggregate limit
+        refs = " ".join(f"@@agptfile:workspace://f{i}" for i in range(5))
+        result = await expand_file_refs_in_string(
+            refs,
+            user_id="u1",
+            session=_make_session(),
+        )
+
+    assert "budget exhausted" in result

autogpt_platform/backend/backend/copilot/sdk/mcp_tool_guide.md

@@ -0,0 +1,28 @@
+## MCP Tool Guide
+
+### Workflow
+
+`run_mcp_tool` follows a two-step pattern:
+
+1. **Discover** — call with only `server_url` to list available tools on the server.
+2. **Execute** — call again with `server_url`, `tool_name`, and `tool_arguments` to run a tool.
+
+### Known hosted MCP servers
+
+Use these URLs directly without asking the user:
+
+| Service | URL |
+|---|---|
+| Notion | `https://mcp.notion.com/mcp` |
+| Linear | `https://mcp.linear.app/mcp` |
+| Stripe | `https://mcp.stripe.com` |
+| Intercom | `https://mcp.intercom.com/mcp` |
+| Cloudflare | `https://mcp.cloudflare.com/mcp` |
+| Atlassian / Jira | `https://mcp.atlassian.com/mcp` |
+
+For other services, search the MCP registry at https://registry.modelcontextprotocol.io/.
+
+### Authentication
+
+If the server requires credentials, a `SetupRequirementsResponse` is returned with an OAuth
+login prompt. Once the user completes the flow and confirms, retry the same call immediately.

autogpt_platform/backend/backend/copilot/sdk/response_adapter_test.py

@@ -536,10 +536,12 @@ async def test_wait_for_stash_signaled():
     result = await wait_for_stash(timeout=1.0)
 
     assert result is True
-    assert _pto.get({}).get("WebSearch") == ["result data"]
+    pto = _pto.get()
+    assert pto is not None
+    assert pto.get("WebSearch") == ["result data"]
 
     # Cleanup
-    _pto.set({})  # type: ignore[arg-type]
+    _pto.set({})
     _stash_event.set(None)
 
 
@@ -554,7 +556,7 @@ async def test_wait_for_stash_timeout():
     assert result is False
 
     # Cleanup
-    _pto.set({})  # type: ignore[arg-type]
+    _pto.set({})
     _stash_event.set(None)
 
 
@@ -573,10 +575,12 @@ async def test_wait_for_stash_already_stashed():
     assert result is True
 
     # But the stash itself is populated
-    assert _pto.get({}).get("Read") == ["file contents"]
+    pto = _pto.get()
+    assert pto is not None
+    assert pto.get("Read") == ["file contents"]
 
     # Cleanup
-    _pto.set({})  # type: ignore[arg-type]
+    _pto.set({})
     _stash_event.set(None)
 
 

autogpt_platform/backend/backend/copilot/sdk/security_hooks.py

@@ -10,12 +10,13 @@ import re
 from collections.abc import Callable
 from typing import Any, cast
 
+from backend.copilot.context import is_allowed_local_path
+
 from .tool_adapter import (
     BLOCKED_TOOLS,
     DANGEROUS_PATTERNS,
     MCP_TOOL_PREFIX,
     WORKSPACE_SCOPED_TOOLS,
-    is_allowed_local_path,
     stash_pending_tool_output,
 )
 

autogpt_platform/backend/backend/copilot/sdk/security_hooks_test.py

@@ -9,8 +9,9 @@ import os
 
 import pytest
 
+from backend.copilot.context import _current_project_dir
+
 from .security_hooks import _validate_tool_access, _validate_user_isolation
-from .service import _is_tool_error_or_denial
 
 SDK_CWD = "/tmp/copilot-abc123"
 
@@ -120,8 +121,6 @@ def test_read_no_cwd_denies_absolute():
 
 
 def test_read_tool_results_allowed():
-    from .tool_adapter import _current_project_dir
-
     home = os.path.expanduser("~")
     path = f"{home}/.claude/projects/-tmp-copilot-abc123/tool-results/12345.txt"
     # is_allowed_local_path requires the session's encoded cwd to be set
@@ -133,16 +132,14 @@ def test_read_tool_results_allowed():
         _current_project_dir.reset(token)
 
 
-def test_read_claude_projects_session_dir_allowed():
-    """Files within the current session's project dir are allowed."""
-    from .tool_adapter import _current_project_dir
-
+def test_read_claude_projects_settings_json_denied():
+    """SDK-internal artifacts like settings.json are NOT accessible — only tool-results/ is."""
     home = os.path.expanduser("~")
     path = f"{home}/.claude/projects/-tmp-copilot-abc123/settings.json"
     token = _current_project_dir.set("-tmp-copilot-abc123")
     try:
         result = _validate_tool_access("Read", {"file_path": path}, sdk_cwd=SDK_CWD)
-        assert not _is_denied(result)
+        assert _is_denied(result)
     finally:
         _current_project_dir.reset(token)
 
@@ -357,76 +354,3 @@ async def test_task_slot_released_on_failure(_hooks):
         context={},
     )
     assert not _is_denied(result)
-
-
-# -- _is_tool_error_or_denial ------------------------------------------------
-
-
-class TestIsToolErrorOrDenial:
-    def test_none_content(self):
-        assert _is_tool_error_or_denial(None) is False
-
-    def test_empty_content(self):
-        assert _is_tool_error_or_denial("") is False
-
-    def test_benign_output(self):
-        assert _is_tool_error_or_denial("All good, no issues.") is False
-
-    def test_security_marker(self):
-        assert _is_tool_error_or_denial("[SECURITY] Tool access blocked") is True
-
-    def test_cannot_be_bypassed(self):
-        assert _is_tool_error_or_denial("This restriction cannot be bypassed.") is True
-
-    def test_not_allowed(self):
-        assert _is_tool_error_or_denial("Operation not allowed in sandbox") is True
-
-    def test_background_task_denial(self):
-        assert (
-            _is_tool_error_or_denial(
-                "Background task execution is not supported. "
-                "Run tasks in the foreground instead."
-            )
-            is True
-        )
-
-    def test_subtask_limit_denial(self):
-        assert (
-            _is_tool_error_or_denial(
-                "Maximum 2 concurrent sub-tasks. "
-                "Wait for running sub-tasks to finish, "
-                "or continue in the main conversation."
-            )
-            is True
-        )
-
-    def test_denied_marker(self):
-        assert (
-            _is_tool_error_or_denial("Access denied: insufficient privileges") is True
-        )
-
-    def test_blocked_marker(self):
-        assert _is_tool_error_or_denial("Request blocked by security policy") is True
-
-    def test_failed_marker(self):
-        assert _is_tool_error_or_denial("Failed to execute tool: timeout") is True
-
-    def test_mcp_iserror(self):
-        assert _is_tool_error_or_denial('{"isError": true, "content": []}') is True
-
-    def test_benign_error_in_value(self):
-        """Content like '0 errors found' should not trigger — 'error' was removed."""
-        assert _is_tool_error_or_denial("0 errors found") is False
-
-    def test_benign_permission_field(self):
-        """Schema descriptions mentioning 'permission' should not trigger."""
-        assert (
-            _is_tool_error_or_denial(
-                '{"fields": [{"name": "permission_level", "type": "int"}]}'
-            )
-            is False
-        )
-
-    def test_benign_not_found_in_listing(self):
-        """File listing containing 'not found' in filenames should not trigger."""
-        assert _is_tool_error_or_denial("readme.md\nfile-not-found-handler.py") is False

autogpt_platform/backend/backend/copilot/sdk/service.py

@@ -44,7 +44,7 @@ from ..model import (
     update_session_title,
     upsert_chat_session,
 )
-from ..prompt_constants import KEY_WORKFLOWS
+from ..prompting import get_sdk_supplement
 from ..response_model import (
     StreamBaseResponse,
     StreamError,
@@ -60,8 +60,7 @@ from ..service import (
     _generate_session_title,
     _is_langfuse_configured,
 )
-from ..tools import TOOL_REGISTRY
-from ..tools.e2b_sandbox import get_or_create_sandbox
+from ..tools.e2b_sandbox import get_or_create_sandbox, pause_sandbox_direct
 from ..tools.sandbox import WORKSPACE_PREFIX, make_session_path
 from ..tools.workspace_files import get_manager
 from ..tracking import track_user_message
@@ -148,169 +147,6 @@ _SDK_CWD_PREFIX = WORKSPACE_PREFIX
 _HEARTBEAT_INTERVAL = 10.0  # seconds
 
 
-# Appended to the system prompt to inform the agent about available tools.
-# The SDK built-in Bash is NOT available — use mcp__copilot__bash_exec instead,
-# which has kernel-level network isolation (unshare --net).
-def _generate_tool_documentation() -> str:
-    """Auto-generate tool documentation from TOOL_REGISTRY.
-
-    This generates a complete list of available tools with their descriptions,
-    ensuring the documentation stays in sync with the actual tool implementations.
-    """
-    docs = "\n## AVAILABLE TOOLS\n\n"
-
-    # Sort tools alphabetically for consistent output
-    for name in sorted(TOOL_REGISTRY.keys()):
-        tool = TOOL_REGISTRY[name]
-        schema = tool.as_openai_tool()
-        desc = schema["function"].get("description", "No description available")
-        # Format as bullet list with tool name in code style
-        docs += f"- **`{name}`**: {desc}\n"
-
-    # Add workflow guidance for key tools
-    docs += KEY_WORKFLOWS
-
-    return docs
-
-
-_SHARED_TOOL_NOTES = """\
-
-### Web search and research
-- **`web_search(query)`** — Search the web for current information (uses Claude's
-  native web search). Use this when you need up-to-date information, facts,
-  statistics, or current events that are beyond your knowledge cutoff.
-- **`web_fetch(url)`** — Retrieve and analyze content from a specific URL.
-  Use this when you have a specific URL to read (documentation, articles, etc.).
-
-### Sharing files with the user
-After saving a file to the persistent workspace with `write_workspace_file`,
-share it with the user by embedding the `download_url` from the response in
-your message as a Markdown link or image:
-
-- **Any file** — shows as a clickable download link:
-  `[report.csv](workspace://file_id#text/csv)`
-- **Image** — renders inline in chat:
-  `![chart](workspace://file_id#image/png)`
-- **Video** — renders inline in chat with player controls:
-  `![recording](workspace://file_id#video/mp4)`
-
-The `download_url` field in the `write_workspace_file` response is already
-in the correct format — paste it directly after the `(` in the Markdown.
-
-### Long-running tools
-Long-running tools (create_agent, edit_agent, etc.) are handled
-asynchronously.  You will receive an immediate response; the actual result
-is delivered to the user via a background stream.
-
-### Large tool outputs
-When a tool output exceeds the display limit, it is automatically saved to
-the persistent workspace.  The truncated output includes a
-`<tool-output-truncated>` tag with the workspace path.  Use
-`read_workspace_file(path="...", offset=N, length=50000)` to retrieve
-additional sections.
-
-### Sub-agent tasks
-- When using the Task tool, NEVER set `run_in_background` to true.
-  All tasks must run in the foreground.
-"""
-
-
-_LOCAL_TOOL_SUPPLEMENT = (
-    """
-
-## Tool notes
-
-### Shell commands
-- The SDK built-in Bash tool is NOT available.  Use the `bash_exec` MCP tool
-  for shell commands — it runs in a network-isolated sandbox.
-
-### Working directory
-- Your working directory is: `{cwd}`
-- All SDK Read/Write/Edit/Glob/Grep tools AND `bash_exec` operate inside this
-  directory.  This is the ONLY writable path — do not attempt to read or write
-  anywhere else on the filesystem.
-- Use relative paths or absolute paths under `{cwd}` for all file operations.
-
-### Two storage systems — CRITICAL to understand
-
-1. **Ephemeral working directory** (`{cwd}`):
-   - Shared by SDK Read/Write/Edit/Glob/Grep tools AND `bash_exec`
-   - Files here are **lost between turns** — do NOT rely on them persisting
-   - Use for temporary work: running scripts, processing data, etc.
-
-2. **Persistent workspace** (cloud storage):
-   - Files here **survive across turns and sessions**
-   - Use `write_workspace_file` to save important files (code, outputs, configs)
-   - Use `read_workspace_file` to retrieve previously saved files
-   - Use `list_workspace_files` to see what files you've saved before
-   - Call `list_workspace_files(include_all_sessions=True)` to see files from
-     all sessions
-
-### Moving files between ephemeral and persistent storage
-- **Ephemeral → Persistent**: Use `write_workspace_file` with either:
-  - `content` param (plain text) — for text files
-  - `source_path` param — to copy any file directly from the ephemeral dir
-- **Persistent → Ephemeral**: Use `read_workspace_file` with `save_to_path`
-  param to download a workspace file to the ephemeral dir for processing
-
-### File persistence workflow
-When you create or modify important files (code, configs, outputs), you MUST:
-1. Save them using `write_workspace_file` so they persist
-2. At the start of a new turn, call `list_workspace_files` to see what files
-   are available from previous turns
-"""
-    + _SHARED_TOOL_NOTES
-)
-
-
-_E2B_TOOL_SUPPLEMENT = (
-    """
-
-## Tool notes
-
-### Shell commands
-- The SDK built-in Bash tool is NOT available.  Use the `bash_exec` MCP tool
-  for shell commands — it runs in a cloud sandbox with full internet access.
-
-### Working directory
-- Your working directory is: `/home/user` (cloud sandbox)
-- All file tools (`read_file`, `write_file`, `edit_file`, `glob`, `grep`)
-  AND `bash_exec` operate on the **same cloud sandbox filesystem**.
-- Files created by `bash_exec` are immediately visible to `read_file` and
-  vice-versa — they share one filesystem.
-- Use relative paths (resolved from `/home/user`) or absolute paths.
-
-### Two storage systems — CRITICAL to understand
-
-1. **Cloud sandbox** (`/home/user`):
-   - Shared by all file tools AND `bash_exec` — same filesystem
-   - Files **persist across turns** within the current session
-   - Full Linux environment with internet access
-   - Lost when the session expires (12 h inactivity)
-
-2. **Persistent workspace** (cloud storage):
-   - Files here **survive across sessions indefinitely**
-   - Use `write_workspace_file` to save important files permanently
-   - Use `read_workspace_file` to retrieve previously saved files
-   - Use `list_workspace_files` to see what files you've saved before
-   - Call `list_workspace_files(include_all_sessions=True)` to see files from
-     all sessions
-
-### Moving files between sandbox and persistent storage
-- **Sandbox → Persistent**: Use `write_workspace_file` with `source_path`
-  to copy from the sandbox to permanent storage
-- **Persistent → Sandbox**: Use `read_workspace_file` with `save_to_path`
-  to download into the sandbox for processing
-
-### File persistence workflow
-Important files that must survive beyond this session should be saved with
-`write_workspace_file`.  Sandbox files persist across turns but are lost
-when the session expires.
-"""
-    + _SHARED_TOOL_NOTES
-)
-
-
 STREAM_LOCK_PREFIX = "copilot:stream:lock:"
 
 
@@ -491,13 +327,14 @@ def _format_sdk_content_blocks(blocks: list) -> list[dict[str, Any]]:
                 }
             )
         elif isinstance(block, ToolResultBlock):
-            result.append(
-                {
-                    "type": "tool_result",
-                    "tool_use_id": block.tool_use_id,
-                    "content": block.content,
-                }
-            )
+            tool_result_entry: dict[str, Any] = {
+                "type": "tool_result",
+                "tool_use_id": block.tool_use_id,
+                "content": block.content,
+            }
+            if block.is_error:
+                tool_result_entry["is_error"] = True
+            result.append(tool_result_entry)
         elif isinstance(block, ThinkingBlock):
             result.append(
                 {
@@ -619,31 +456,6 @@ def _format_conversation_context(messages: list[ChatMessage]) -> str | None:
     return "<conversation_history>\n" + "\n".join(lines) + "\n</conversation_history>"
 
 
-def _is_tool_error_or_denial(content: str | None) -> bool:
-    """Check if a tool message content indicates an error or denial.
-
-    Currently unused — ``_format_conversation_context`` includes all tool
-    results.  Kept as a utility for future selective filtering.
-    """
-    if not content:
-        return False
-    lower = content.lower()
-    return any(
-        marker in lower
-        for marker in (
-            "[security]",
-            "cannot be bypassed",
-            "not allowed",
-            "not supported",  # background-task denial
-            "maximum",  # subtask-limit denial
-            "denied",
-            "blocked",
-            "failed to",  # internal tool execution failures
-            '"iserror": true',  # MCP protocol error flag
-        )
-    )
-
-
 async def _build_query_message(
     current_message: str,
     session: ChatSession,
@@ -947,28 +759,29 @@ async def stream_chat_completion_sdk(
 
         async def _setup_e2b():
             """Set up E2B sandbox if configured, return sandbox or None."""
-            if config.use_e2b_sandbox and not config.e2b_api_key:
-                logger.warning(
-                    "[E2B] [%s] E2B sandbox enabled but no API key configured "
-                    "(CHAT_E2B_API_KEY / E2B_API_KEY) — falling back to bubblewrap",
-                    session_id[:12],
-                )
-                return None
-            if config.use_e2b_sandbox and config.e2b_api_key:
-                try:
-                    return await get_or_create_sandbox(
-                        session_id,
-                        api_key=config.e2b_api_key,
-                        template=config.e2b_sandbox_template,
-                        timeout=config.e2b_sandbox_timeout,
-                    )
-                except Exception as e2b_err:
-                    logger.error(
-                        "[E2B] [%s] Setup failed: %s",
+            if not (e2b_api_key := config.active_e2b_api_key):
+                if config.use_e2b_sandbox:
+                    logger.warning(
+                        "[E2B] [%s] E2B sandbox enabled but no API key configured "
+                        "(CHAT_E2B_API_KEY / E2B_API_KEY) — falling back to bubblewrap",
                         session_id[:12],
-                        e2b_err,
-                        exc_info=True,
                     )
+                return None
+            try:
+                return await get_or_create_sandbox(
+                    session_id,
+                    api_key=e2b_api_key,
+                    template=config.e2b_sandbox_template,
+                    timeout=config.e2b_sandbox_timeout,
+                    on_timeout=config.e2b_sandbox_on_timeout,
+                )
+            except Exception as e2b_err:
+                logger.error(
+                    "[E2B] [%s] Setup failed: %s",
+                    session_id[:12],
+                    e2b_err,
+                    exc_info=True,
+                )
             return None
 
         async def _fetch_transcript():
@@ -996,18 +809,10 @@ async def stream_chat_completion_sdk(
         )
 
         use_e2b = e2b_sandbox is not None
-        # Generate tool documentation and append appropriate supplement
-        tool_docs = _generate_tool_documentation()
-        system_prompt = (
-            base_system_prompt
-            + tool_docs
-            + (
-                _E2B_TOOL_SUPPLEMENT
-                if use_e2b
-                else _LOCAL_TOOL_SUPPLEMENT.format(cwd=sdk_cwd)
-            )
+        # Append appropriate supplement (Claude gets tool schemas automatically)
+        system_prompt = base_system_prompt + get_sdk_supplement(
+            use_e2b=use_e2b, cwd=sdk_cwd
         )
-
         # Process transcript download result
         transcript_msg_count = 0
         if dl:
@@ -1072,6 +877,11 @@ async def stream_chat_completion_sdk(
 
         allowed = get_copilot_tool_names(use_e2b=use_e2b)
         disallowed = get_sdk_disallowed_tools(use_e2b=use_e2b)
+
+        def _on_stderr(line: str) -> None:
+            sid = session_id[:12] if session_id else "?"
+            logger.info("[SDK] [%s] CLI stderr: %s", sid, line.rstrip())
+
         sdk_options_kwargs: dict[str, Any] = {
             "system_prompt": system_prompt,
             "mcp_servers": {"copilot": mcp_server},
@@ -1080,6 +890,7 @@ async def stream_chat_completion_sdk(
             "hooks": security_hooks,
             "cwd": sdk_cwd,
             "max_buffer_size": config.claude_agent_max_buffer_size,
+            "stderr": _on_stderr,
         }
         if sdk_model:
             sdk_options_kwargs["model"] = sdk_model
@@ -1170,19 +981,18 @@ async def stream_chat_completion_sdk(
                     json.dumps(user_msg) + "\n"
                 )
                 # Capture user message in transcript (multimodal)
-                transcript_builder.add_user_message(content=content_blocks)
+                transcript_builder.append_user(content=content_blocks)
             else:
                 await client.query(query_message, session_id=session_id)
                 # Capture actual user message in transcript (not the engineered query)
                 # query_message may include context wrappers, but transcript needs raw input
-                transcript_builder.add_user_message(content=current_message)
+                transcript_builder.append_user(content=current_message)
 
             assistant_response = ChatMessage(role="assistant", content="")
             accumulated_tool_calls: list[dict[str, Any]] = []
             has_appended_assistant = False
             has_tool_results = False
             ended_with_stream_error = False
-
             # Use an explicit async iterator with non-cancelling heartbeats.
             # CRITICAL: we must NOT cancel __anext__() mid-flight — doing so
             # (via asyncio.timeout or wait_for) corrupts the SDK's internal
@@ -1253,13 +1063,17 @@ async def stream_chat_completion_sdk(
                         len(adapter.resolved_tool_calls),
                     )
 
-                    # Capture SDK messages in transcript
-                    if isinstance(sdk_msg, AssistantMessage):
-                        content_blocks = _format_sdk_content_blocks(sdk_msg.content)
-                        model_name = getattr(sdk_msg, "model", "")
-                        transcript_builder.add_assistant_message(
-                            content_blocks=content_blocks,
-                            model=model_name,
+                    # Log AssistantMessage API errors (e.g. invalid_request)
+                    # so we can debug Anthropic API 400s surfaced by the CLI.
+                    sdk_error = getattr(sdk_msg, "error", None)
+                    if isinstance(sdk_msg, AssistantMessage) and sdk_error:
+                        logger.error(
+                            "[SDK] [%s] AssistantMessage has error=%s, "
+                            "content_blocks=%d, content_preview=%s",
+                            session_id[:12],
+                            sdk_error,
+                            len(sdk_msg.content),
+                            str(sdk_msg.content)[:500],
                         )
 
                     # Race-condition fix: SDK hooks (PostToolUse) are
@@ -1392,33 +1206,37 @@ async def stream_chat_completion_sdk(
                                 has_appended_assistant = True
 
                         elif isinstance(response, StreamToolOutputAvailable):
-                            tool_result_content = (
+                            content = (
                                 response.output
                                 if isinstance(response.output, str)
-                                else str(response.output)
+                                else json.dumps(response.output, ensure_ascii=False)
                             )
                             session.messages.append(
                                 ChatMessage(
                                     role="tool",
-                                    content=tool_result_content,
+                                    content=content,
                                     tool_call_id=response.toolCallId,
                                 )
                             )
-                            # Capture tool result in transcript as user message with tool_result content
-                            transcript_builder.add_user_message(
-                                content=[
-                                    {
-                                        "type": "tool_result",
-                                        "tool_use_id": response.toolCallId,
-                                        "content": tool_result_content,
-                                    }
-                                ]
+                            transcript_builder.append_tool_result(
+                                tool_use_id=response.toolCallId,
+                                content=content,
                             )
                             has_tool_results = True
 
                         elif isinstance(response, StreamFinish):
                             stream_completed = True
 
+                    # Append assistant entry AFTER convert_message so that
+                    # any stashed tool results from the previous turn are
+                    # recorded first, preserving the required API order:
+                    # assistant(tool_use) → tool_result → assistant(text).
+                    if isinstance(sdk_msg, AssistantMessage):
+                        transcript_builder.append_assistant(
+                            content_blocks=_format_sdk_content_blocks(sdk_msg.content),
+                            model=sdk_msg.model,
+                        )
+
             except asyncio.CancelledError:
                 # Task/generator was cancelled (e.g. client disconnect,
                 # server shutdown).  Log and let the safety-net / finally
@@ -1467,6 +1285,15 @@ async def stream_chat_completion_sdk(
                             type(response).__name__,
                             getattr(response, "toolName", "N/A"),
                         )
+                    if isinstance(response, StreamToolOutputAvailable):
+                        transcript_builder.append_tool_result(
+                            tool_use_id=response.toolCallId,
+                            content=(
+                                response.output
+                                if isinstance(response.output, str)
+                                else json.dumps(response.output, ensure_ascii=False)
+                            ),
+                        )
                     yield response
 
             # If the stream ended without a ResultMessage, the SDK
@@ -1583,6 +1410,17 @@ async def stream_chat_completion_sdk(
                     exc_info=True,
                 )
 
+        # --- Pause E2B sandbox to stop billing between turns ---
+        # Fire-and-forget: pausing is best-effort and must not block the
+        # response or the transcript upload.  The task is anchored to
+        # _background_tasks to prevent garbage collection.
+        # Use pause_sandbox_direct to skip the Redis lookup and reconnect
+        # round-trip — e2b_sandbox is the live object from this turn.
+        if e2b_sandbox is not None:
+            task = asyncio.create_task(pause_sandbox_direct(e2b_sandbox, session_id))
+            _background_tasks.add(task)
+            task.add_done_callback(_background_tasks.discard)
+
         # --- Upload transcript for next-turn --resume ---
         # This MUST run in finally so the transcript is uploaded even when
         # the streaming loop raises an exception.
@@ -1645,7 +1483,7 @@ async def _update_title_async(
             message, user_id=user_id, session_id=session_id
         )
         if title and user_id:
-            await update_session_title(session_id, title)
+            await update_session_title(session_id, user_id, title, only_if_empty=True)
             logger.debug(f"[SDK] Generated title for {session_id}: {title}")
     except Exception as e:
         logger.warning(f"[SDK] Failed to update session title: {e}")

autogpt_platform/backend/backend/copilot/sdk/service_test.py

@@ -1,13 +1,14 @@
 """Tests for SDK service helpers."""
 
+import asyncio
 import base64
 import os
 from dataclasses import dataclass
-from unittest.mock import AsyncMock, patch
+from unittest.mock import AsyncMock, MagicMock, patch
 
 import pytest
 
-from .service import _generate_tool_documentation, _prepare_file_attachments
+from .service import _prepare_file_attachments
 
 
 @dataclass
@@ -147,92 +148,143 @@ class TestPrepareFileAttachments:
         assert len(result.image_blocks) == 1
 
 
-class TestGenerateToolDocumentation:
-    """Tests for auto-generated tool documentation from TOOL_REGISTRY."""
+class TestPromptSupplement:
+    """Tests for centralized prompt supplement generation."""
 
-    def test_generate_tool_documentation_structure(self):
-        """Test that tool documentation has expected structure."""
-        docs = _generate_tool_documentation()
+    def test_sdk_supplement_excludes_tool_docs(self):
+        """SDK mode should NOT include tool documentation (Claude gets schemas automatically)."""
+        from backend.copilot.prompting import get_sdk_supplement
 
-        # Check main sections exist
-        assert "## AVAILABLE TOOLS" in docs
-        assert "## KEY WORKFLOWS" in docs
+        # Test both local and E2B modes
+        local_supplement = get_sdk_supplement(use_e2b=False, cwd="/tmp/test")
+        e2b_supplement = get_sdk_supplement(use_e2b=True, cwd="")
 
-        # Verify no duplicate sections
-        assert docs.count("## AVAILABLE TOOLS") == 1
-        assert docs.count("## KEY WORKFLOWS") == 1
+        # Should NOT have tool list section
+        assert "## AVAILABLE TOOLS" not in local_supplement
+        assert "## AVAILABLE TOOLS" not in e2b_supplement
 
-    def test_tool_documentation_includes_key_tools(self):
-        """Test that documentation includes essential copilot tools."""
-        docs = _generate_tool_documentation()
+        # Should still have technical notes
+        assert "## Tool notes" in local_supplement
+        assert "## Tool notes" in e2b_supplement
 
-        # Core agent workflow tools
+    def test_baseline_supplement_includes_tool_docs(self):
+        """Baseline mode MUST include tool documentation (direct API needs it)."""
+        from backend.copilot.prompting import get_baseline_supplement
+
+        supplement = get_baseline_supplement()
+
+        # MUST have tool list section
+        assert "## AVAILABLE TOOLS" in supplement
+
+        # Should NOT have environment-specific notes (SDK-only)
+        assert "## Tool notes" not in supplement
+
+    def test_baseline_supplement_includes_key_tools(self):
+        """Baseline supplement should document all essential tools."""
+        from backend.copilot.prompting import get_baseline_supplement
+        from backend.copilot.tools import TOOL_REGISTRY
+
+        docs = get_baseline_supplement()
+
+        # Core agent workflow tools (always available)
         assert "`create_agent`" in docs
         assert "`run_agent`" in docs
         assert "`find_library_agent`" in docs
         assert "`edit_agent`" in docs
 
-        # MCP integration
+        # MCP integration (always available)
         assert "`run_mcp_tool`" in docs
 
-        # Browser automation
-        assert "`browser_navigate`" in docs
-
-        # Folder management
+        # Folder management (always available)
         assert "`create_folder`" in docs
 
-    def test_tool_documentation_format(self):
-        """Test that each tool follows bullet list format."""
-        docs = _generate_tool_documentation()
+        # Browser tools only if available (Playwright may not be installed in CI)
+        if (
+            TOOL_REGISTRY.get("browser_navigate")
+            and TOOL_REGISTRY["browser_navigate"].is_available
+        ):
+            assert "`browser_navigate`" in docs
 
-        lines = docs.split("\n")
-        tool_lines = [line for line in lines if line.strip().startswith("- **`")]
+    def test_baseline_supplement_includes_workflows(self):
+        """Baseline supplement should include workflow guidance in tool descriptions."""
+        from backend.copilot.prompting import get_baseline_supplement
 
-        # Should have multiple tools (at least 20 from TOOL_REGISTRY)
-        assert len(tool_lines) >= 20
+        docs = get_baseline_supplement()
 
-        # Each tool line should have proper markdown format
-        for line in tool_lines:
-            assert line.startswith("- **`"), f"Bad format: {line}"
-            assert "`**:" in line, f"Missing description separator: {line}"
+        # Workflows are now in individual tool descriptions (not separate sections)
+        # Check that key workflow concepts appear in tool descriptions
+        assert "agent_json" in docs or "find_block" in docs
+        assert "run_mcp_tool" in docs
 
-    def test_tool_documentation_includes_workflows(self):
-        """Test that key workflow patterns are documented."""
-        docs = _generate_tool_documentation()
-
-        # Check workflow sections
-        assert "MCP Integration Workflow" in docs
-        assert "Agent Creation Workflow" in docs
-        assert "Folder Management" in docs
-
-        # Check workflow details
-        assert "suggested_goal" in docs  # Agent creation feedback loop
-        assert "clarifying_questions" in docs  # Agent creation feedback loop
-        assert "run_mcp_tool(server_url)" in docs  # MCP discovery pattern
-
-    def test_tool_documentation_completeness(self):
-        """Test that all tools from TOOL_REGISTRY appear in documentation."""
+    def test_baseline_supplement_completeness(self):
+        """All available tools from TOOL_REGISTRY should appear in baseline supplement."""
+        from backend.copilot.prompting import get_baseline_supplement
         from backend.copilot.tools import TOOL_REGISTRY
 
-        docs = _generate_tool_documentation()
+        docs = get_baseline_supplement()
 
-        # Verify each registered tool is documented
-        for tool_name in TOOL_REGISTRY.keys():
+        # Verify each available registered tool is documented
+        # (matches _generate_tool_documentation which filters by is_available)
+        for tool_name, tool in TOOL_REGISTRY.items():
+            if not tool.is_available:
+                continue
             assert (
                 f"`{tool_name}`" in docs
-            ), f"Tool '{tool_name}' missing from auto-generated documentation"
+            ), f"Tool '{tool_name}' missing from baseline supplement"
 
-    def test_tool_documentation_no_duplicate_tools(self):
-        """Test that no tool appears multiple times in the list."""
+    def test_pause_task_scheduled_before_transcript_upload(self):
+        """Pause is scheduled as a background task before transcript upload begins.
+
+        The finally block in stream_response_sdk does:
+          (1) asyncio.create_task(pause_sandbox_direct(...))  — fire-and-forget
+          (2) await asyncio.shield(upload_transcript(...))    — awaited
+
+        Scheduling pause via create_task before awaiting upload ensures:
+        - Pause never blocks transcript upload (billing stops concurrently)
+        - On E2B timeout, pause silently fails; upload proceeds unaffected
+        """
+        call_order: list[str] = []
+
+        async def _mock_pause(sandbox, session_id):
+            call_order.append("pause")
+
+        async def _mock_upload(**kwargs):
+            call_order.append("upload")
+
+        async def _simulate_teardown():
+            """Mirror the service.py finally block teardown sequence."""
+            sandbox = MagicMock()
+
+            # (1) Schedule pause — mirrors lines ~1427-1429 in service.py
+            task = asyncio.create_task(_mock_pause(sandbox, "test-sess"))
+
+            # (2) Await transcript upload — mirrors lines ~1460-1468 in service.py
+            # Yielding to the event loop here lets the pause task start concurrently.
+            await _mock_upload(
+                user_id="u", session_id="test-sess", content="x", message_count=1
+            )
+            await task
+
+        asyncio.run(_simulate_teardown())
+
+        # Both must run; pause is scheduled before upload starts
+        assert "pause" in call_order
+        assert "upload" in call_order
+        # create_task schedules pause, then upload is awaited — pause runs
+        # concurrently during upload's first yield. The ordering guarantee is
+        # that create_task is CALLED before upload is AWAITED (see source order).
+
+    def test_baseline_supplement_no_duplicate_tools(self):
+        """No tool should appear multiple times in baseline supplement."""
+        from backend.copilot.prompting import get_baseline_supplement
         from backend.copilot.tools import TOOL_REGISTRY
 
-        docs = _generate_tool_documentation()
+        docs = get_baseline_supplement()
 
-        # Extract the tools section (before KEY WORKFLOWS)
-        tools_section = docs.split("## KEY WORKFLOWS")[0]
-
-        # Count occurrences of each tool
-        for tool_name in TOOL_REGISTRY.keys():
+        # Count occurrences of each available tool in the entire supplement
+        for tool_name, tool in TOOL_REGISTRY.items():
+            if not tool.is_available:
+                continue
             # Count how many times this tool appears as a bullet point
-            count = tools_section.count(f"- **`{tool_name}`**")
+            count = docs.count(f"- **`{tool_name}`**")
             assert count == 1, f"Tool '{tool_name}' appears {count} times (should be 1)"

autogpt_platform/backend/backend/copilot/sdk/tool_adapter.py

@@ -9,14 +9,29 @@ import itertools
 import json
 import logging
 import os
-import re
 import uuid
 from contextvars import ContextVar
 from typing import TYPE_CHECKING, Any
 
 from claude_agent_sdk import create_sdk_mcp_server, tool
 
+from backend.copilot.context import (
+    _current_project_dir,
+    _current_sandbox,
+    _current_sdk_cwd,
+    _current_session,
+    _current_user_id,
+    _encode_cwd_for_cli,
+    get_execution_context,
+    get_sdk_cwd,
+    is_allowed_local_path,
+)
 from backend.copilot.model import ChatSession
+from backend.copilot.sdk.file_ref import (
+    FileRefExpansionError,
+    expand_file_refs_in_args,
+    read_file_bytes,
+)
 from backend.copilot.tools import TOOL_REGISTRY
 from backend.copilot.tools.base import BaseTool
 from backend.util.truncate import truncate
@@ -28,84 +43,13 @@ if TYPE_CHECKING:
 
 logger = logging.getLogger(__name__)
 
-# Allowed base directory for the Read tool (SDK saves oversized tool results here).
-# Restricted to ~/.claude/projects/ and further validated to require "tool-results"
-# in the path — prevents reading settings, credentials, or other sensitive files.
-_SDK_PROJECTS_DIR = os.path.realpath(os.path.expanduser("~/.claude/projects"))
-
 # Max MCP response size in chars — keeps tool output under the SDK's 10 MB JSON buffer.
 _MCP_MAX_CHARS = 500_000
 
-# Context variable holding the encoded project directory name for the current
-# session (e.g. "-private-tmp-copilot-<uuid>").  Set by set_execution_context()
-# so that path validation can scope tool-results reads to the current session.
-_current_project_dir: ContextVar[str] = ContextVar("_current_project_dir", default="")
-
-
-def _encode_cwd_for_cli(cwd: str) -> str:
-    """Encode a working directory path the same way the Claude CLI does.
-
-    The CLI replaces all non-alphanumeric characters with ``-``.
-    """
-    return re.sub(r"[^a-zA-Z0-9]", "-", os.path.realpath(cwd))
-
-
-def is_allowed_local_path(path: str, sdk_cwd: str | None = None) -> bool:
-    """Check whether *path* is an allowed host-filesystem path.
-
-    Allowed:
-    - Files under *sdk_cwd* (``/tmp/copilot-<session>/``)
-    - Files under ``~/.claude/projects/<encoded-cwd>/`` — the SDK's
-      project directory for this session (tool-results, transcripts, etc.)
-
-    Both checks are scoped to the **current session** so sessions cannot
-    read each other's data.
-    """
-    if not path:
-        return False
-
-    if path.startswith("~"):
-        resolved = os.path.realpath(os.path.expanduser(path))
-    elif not os.path.isabs(path) and sdk_cwd:
-        resolved = os.path.realpath(os.path.join(sdk_cwd, path))
-    else:
-        resolved = os.path.realpath(path)
-
-    # Allow access within the SDK working directory
-    if sdk_cwd:
-        norm_cwd = os.path.realpath(sdk_cwd)
-        if resolved == norm_cwd or resolved.startswith(norm_cwd + os.sep):
-            return True
-
-    # Allow access within the current session's CLI project directory
-    # (~/.claude/projects/<encoded-cwd>/).
-    encoded = _current_project_dir.get("")
-    if encoded:
-        session_project = os.path.join(_SDK_PROJECTS_DIR, encoded)
-        if resolved == session_project or resolved.startswith(session_project + os.sep):
-            return True
-
-    return False
-
-
 # MCP server naming - the SDK prefixes tool names as "mcp__{server_name}__{tool}"
 MCP_SERVER_NAME = "copilot"
 MCP_TOOL_PREFIX = f"mcp__{MCP_SERVER_NAME}__"
 
-# Context variables to pass user/session info to tool execution
-_current_user_id: ContextVar[str | None] = ContextVar("current_user_id", default=None)
-_current_session: ContextVar[ChatSession | None] = ContextVar(
-    "current_session", default=None
-)
-# E2B cloud sandbox for the current turn (None when E2B is not configured).
-# Passed to bash_exec so commands run on E2B instead of the local bwrap sandbox.
-_current_sandbox: ContextVar["AsyncSandbox | None"] = ContextVar(
-    "_current_sandbox", default=None
-)
-# Raw SDK working directory path (e.g. /tmp/copilot-<session_id>).
-# Used by workspace tools to save binary files for the CLI's built-in Read.
-_current_sdk_cwd: ContextVar[str] = ContextVar("_current_sdk_cwd", default="")
-
 # Stash for MCP tool outputs before the SDK potentially truncates them.
 # Keyed by tool_name → full output string. Consumed (popped) by the
 # response adapter when it builds StreamToolOutputAvailable.
@@ -149,24 +93,6 @@ def set_execution_context(
     _stash_event.set(asyncio.Event())
 
 
-def get_current_sandbox() -> "AsyncSandbox | None":
-    """Return the E2B sandbox for the current turn, or None."""
-    return _current_sandbox.get()
-
-
-def get_sdk_cwd() -> str:
-    """Return the SDK ephemeral working directory for the current turn."""
-    return _current_sdk_cwd.get()
-
-
-def get_execution_context() -> tuple[str | None, ChatSession | None]:
-    """Get the current execution context."""
-    return (
-        _current_user_id.get(),
-        _current_session.get(),
-    )
-
-
 def pop_pending_tool_output(tool_name: str) -> str | None:
     """Pop and return the oldest stashed output for *tool_name*.
 
@@ -259,7 +185,11 @@ async def _execute_tool_sync(
     session: ChatSession,
     args: dict[str, Any],
 ) -> dict[str, Any]:
-    """Execute a tool synchronously and return MCP-formatted response."""
+    """Execute a tool synchronously and return MCP-formatted response.
+
+    Note: ``@@agptfile:`` expansion is handled upstream in the ``_truncating`` wrapper
+    so all registered handlers (BaseTool, E2B, Read) expand uniformly.
+    """
     effective_id = f"sdk-{uuid.uuid4().hex[:12]}"
     result = await base_tool.execute(
         user_id=user_id,
@@ -320,42 +250,50 @@ def _build_input_schema(base_tool: BaseTool) -> dict[str, Any]:
 
 
 async def _read_file_handler(args: dict[str, Any]) -> dict[str, Any]:
-    """Read a local file with optional offset/limit.
+    """Read a file with optional offset/limit.
 
-    Only allows paths that pass :func:`is_allowed_local_path` — the current
-    session's tool-results directory and ephemeral working directory.
+    Supports ``workspace://`` URIs (delegated to the workspace manager) and
+    local paths within the session's allowed directories (sdk_cwd + tool-results).
     """
     file_path = args.get("file_path", "")
-    offset = args.get("offset", 0)
-    limit = args.get("limit", 2000)
+    offset = max(0, int(args.get("offset", 0)))
+    limit = max(1, int(args.get("limit", 2000)))
 
-    if not is_allowed_local_path(file_path):
-        return {
-            "content": [{"type": "text", "text": f"Access denied: {file_path}"}],
-            "isError": True,
-        }
+    def _mcp_err(text: str) -> dict[str, Any]:
+        return {"content": [{"type": "text", "text": text}], "isError": True}
+
+    def _mcp_ok(text: str) -> dict[str, Any]:
+        return {"content": [{"type": "text", "text": text}], "isError": False}
+
+    if file_path.startswith("workspace://"):
+        user_id, session = get_execution_context()
+        if session is None:
+            return _mcp_err("workspace:// file references require an active session")
+        try:
+            raw = await read_file_bytes(file_path, user_id, session)
+        except ValueError as exc:
+            return _mcp_err(str(exc))
+        lines = raw.decode("utf-8", errors="replace").splitlines(keepends=True)
+        selected = list(itertools.islice(lines, offset, offset + limit))
+        numbered = "".join(
+            f"{i + offset + 1:>6}\t{line}" for i, line in enumerate(selected)
+        )
+        return _mcp_ok(numbered)
+
+    if not is_allowed_local_path(file_path, get_sdk_cwd()):
+        return _mcp_err(f"Path not allowed: {file_path}")
 
     resolved = os.path.realpath(os.path.expanduser(file_path))
     try:
         with open(resolved) as f:
             selected = list(itertools.islice(f, offset, offset + limit))
-        content = "".join(selected)
         # Cleanup happens in _cleanup_sdk_tool_results after session ends;
         # don't delete here — the SDK may read in multiple chunks.
-        return {
-            "content": [{"type": "text", "text": content}],
-            "isError": False,
-        }
+        return _mcp_ok("".join(selected))
     except FileNotFoundError:
-        return {
-            "content": [{"type": "text", "text": f"File not found: {file_path}"}],
-            "isError": True,
-        }
+        return _mcp_err(f"File not found: {file_path}")
     except Exception as e:
-        return {
-            "content": [{"type": "text", "text": f"Error reading file: {e}"}],
-            "isError": True,
-        }
+        return _mcp_err(f"Error reading file: {e}")
 
 
 _READ_TOOL_NAME = "Read"
@@ -414,9 +352,23 @@ def create_copilot_mcp_server(*, use_e2b: bool = False):
         SDK's 10 MB JSON buffer, and stash the (truncated) output for the
         response adapter before the SDK can apply its own head-truncation.
 
+        Also expands ``@@agptfile:`` references in args so every registered tool
+        (BaseTool, E2B file tools, Read) receives resolved content uniformly.
+
         Applied once to every registered tool."""
 
         async def wrapper(args: dict[str, Any]) -> dict[str, Any]:
+            user_id, session = get_execution_context()
+            if session is not None:
+                try:
+                    args = await expand_file_refs_in_args(args, user_id, session)
+                except FileRefExpansionError as exc:
+                    return _mcp_error(
+                        f"@@agptfile: reference could not be resolved: {exc}. "
+                        "Ensure the file exists before referencing it. "
+                        "For sandbox paths use bash_exec to verify the file exists first; "
+                        "for workspace files use a workspace:// URI."
+                    )
             result = await fn(args)
             truncated = truncate(result, _MCP_MAX_CHARS)
 

autogpt_platform/backend/backend/copilot/sdk/tool_adapter_test.py

@@ -2,12 +2,12 @@
 
 import pytest
 
+from backend.copilot.context import get_sdk_cwd
 from backend.util.truncate import truncate
 
 from .tool_adapter import (
     _MCP_MAX_CHARS,
     _text_from_mcp_result,
-    get_sdk_cwd,
     pop_pending_tool_output,
     set_execution_context,
     stash_pending_tool_output,

autogpt_platform/backend/backend/copilot/sdk/transcript_builder.py

@@ -44,6 +44,15 @@ class TranscriptBuilder:
         self._entries: list[TranscriptEntry] = []
         self._last_uuid: str | None = None
 
+    def _last_is_assistant(self) -> bool:
+        return bool(self._entries) and self._entries[-1].type == "assistant"
+
+    def _last_message_id(self) -> str:
+        """Return the message.id of the last entry, or '' if none."""
+        if self._entries:
+            return self._entries[-1].message.get("id", "")
+        return ""
+
     def load_previous(self, content: str, log_prefix: str = "[Transcript]") -> None:
         """Load complete previous transcript.
 
@@ -91,10 +100,8 @@ class TranscriptBuilder:
             self._last_uuid[:12] if self._last_uuid else None,
         )
 
-    def add_user_message(
-        self, content: str | list[dict], uuid: str | None = None
-    ) -> None:
-        """Add user message to the complete context."""
+    def append_user(self, content: str | list[dict], uuid: str | None = None) -> None:
+        """Append a user entry."""
         msg_uuid = uuid or str(uuid4())
 
         self._entries.append(
@@ -107,10 +114,34 @@ class TranscriptBuilder:
         )
         self._last_uuid = msg_uuid
 
-    def add_assistant_message(
-        self, content_blocks: list[dict], model: str = ""
+    def append_tool_result(self, tool_use_id: str, content: str) -> None:
+        """Append a tool result as a user entry (one per tool call)."""
+        self.append_user(
+            content=[
+                {"type": "tool_result", "tool_use_id": tool_use_id, "content": content}
+            ]
+        )
+
+    def append_assistant(
+        self,
+        content_blocks: list[dict],
+        model: str = "",
+        stop_reason: str | None = None,
     ) -> None:
-        """Add assistant message to the complete context."""
+        """Append an assistant entry.
+
+        Consecutive assistant entries automatically share the same message ID
+        so the CLI can merge them (thinking → text → tool_use) into a single
+        API message on ``--resume``.  A new ID is assigned whenever an
+        assistant entry follows a non-assistant entry (user message or tool
+        result), because that marks the start of a new API response.
+        """
+        message_id = (
+            self._last_message_id()
+            if self._last_is_assistant()
+            else f"msg_sdk_{uuid4().hex[:24]}"
+        )
+
         msg_uuid = str(uuid4())
 
         self._entries.append(
@@ -121,7 +152,11 @@ class TranscriptBuilder:
                 message={
                     "role": "assistant",
                     "model": model,
+                    "id": message_id,
+                    "type": "message",
                     "content": content_blocks,
+                    "stop_reason": stop_reason,
+                    "stop_sequence": None,
                 },
             )
         )
@@ -130,6 +165,9 @@ class TranscriptBuilder:
     def to_jsonl(self) -> str:
         """Export complete context as JSONL.
 
+        Consecutive assistant entries are kept separate to match the
+        native CLI format — the SDK merges them internally on resume.
+
         Returns the FULL conversation state (all entries), not incremental.
         This output REPLACES any previous transcript.
         """

autogpt_platform/backend/backend/copilot/service.py

@@ -18,7 +18,7 @@ from langfuse.openai import (
 
 from backend.data.db_accessors import understanding_db
 from backend.data.understanding import format_understanding_for_prompt
-from backend.util.exceptions import NotFoundError
+from backend.util.exceptions import NotAuthorizedError, NotFoundError
 from backend.util.settings import AppEnvironment, Settings
 
 from .config import ChatConfig
@@ -198,6 +198,12 @@ async def assign_user_to_session(
     session = await get_chat_session(session_id, None)
     if not session:
         raise NotFoundError(f"Session {session_id} not found")
+    if session.user_id is not None and session.user_id != user_id:
+        logger.warning(
+            f"[SECURITY] Attempt to claim session {session_id} by user {user_id}, "
+            f"but it already belongs to user {session.user_id}"
+        )
+        raise NotAuthorizedError(f"Not authorized to claim session {session_id}")
     session.user_id = user_id
     session = await upsert_chat_session(session)
     return session

autogpt_platform/backend/backend/copilot/tools/__init__.py

@@ -19,11 +19,23 @@ from .feature_requests import CreateFeatureRequestTool, SearchFeatureRequestsToo
 from .find_agent import FindAgentTool
 from .find_block import FindBlockTool
 from .find_library_agent import FindLibraryAgentTool
+from .fix_agent import FixAgentGraphTool
+from .get_agent_building_guide import GetAgentBuildingGuideTool
 from .get_doc_page import GetDocPageTool
+from .get_mcp_guide import GetMCPGuideTool
+from .manage_folders import (
+    CreateFolderTool,
+    DeleteFolderTool,
+    ListFoldersTool,
+    MoveAgentsToFolderTool,
+    MoveFolderTool,
+    UpdateFolderTool,
+)
 from .run_agent import RunAgentTool
 from .run_block import RunBlockTool
 from .run_mcp_tool import RunMCPToolTool
 from .search_docs import SearchDocsTool
+from .validate_agent import ValidateAgentGraphTool
 from .web_fetch import WebFetchTool
 from .workspace_files import (
     DeleteWorkspaceFileTool,
@@ -47,12 +59,21 @@ TOOL_REGISTRY: dict[str, BaseTool] = {
     "find_agent": FindAgentTool(),
     "find_block": FindBlockTool(),
     "find_library_agent": FindLibraryAgentTool(),
+    # Folder management tools
+    "create_folder": CreateFolderTool(),
+    "list_folders": ListFoldersTool(),
+    "update_folder": UpdateFolderTool(),
+    "move_folder": MoveFolderTool(),
+    "delete_folder": DeleteFolderTool(),
+    "move_agents_to_folder": MoveAgentsToFolderTool(),
     "run_agent": RunAgentTool(),
     "run_block": RunBlockTool(),
     "run_mcp_tool": RunMCPToolTool(),
+    "get_mcp_guide": GetMCPGuideTool(),
     "view_agent_output": AgentOutputTool(),
     "search_docs": SearchDocsTool(),
     "get_doc_page": GetDocPageTool(),
+    "get_agent_building_guide": GetAgentBuildingGuideTool(),
     # Web fetch for safe URL retrieval
     "web_fetch": WebFetchTool(),
     # Agent-browser multi-step automation (navigate, act, screenshot)
@@ -65,6 +86,9 @@ TOOL_REGISTRY: dict[str, BaseTool] = {
     # Feature request tools
     "search_feature_requests": SearchFeatureRequestsTool(),
     "create_feature_request": CreateFeatureRequestTool(),
+    # Agent generation tools (local validation/fixing)
+    "validate_agent_graph": ValidateAgentGraphTool(),
+    "fix_agent_graph": FixAgentGraphTool(),
     # Workspace tools for CoPilot file operations
     "list_workspace_files": ListWorkspaceFilesTool(),
     "read_workspace_file": ReadWorkspaceFileTool(),

autogpt_platform/backend/backend/copilot/tools/_test_data.py

@@ -151,8 +151,8 @@ async def setup_test_data(server):
     unique_slug = f"test-agent-{str(uuid.uuid4())[:8]}"
     store_submission = await store_db.create_store_submission(
         user_id=user.id,
-        agent_id=created_graph.id,
-        agent_version=created_graph.version,
+        graph_id=created_graph.id,
+        graph_version=created_graph.version,
         slug=unique_slug,
         name="Test Agent",
         description="A simple test agent",
@@ -161,10 +161,10 @@ async def setup_test_data(server):
         image_urls=["https://example.com/image.jpg"],
     )
 
-    assert store_submission.store_listing_version_id is not None
+    assert store_submission.listing_version_id is not None
     # 4. Approve the store listing version
     await store_db.review_store_submission(
-        store_listing_version_id=store_submission.store_listing_version_id,
+        store_listing_version_id=store_submission.listing_version_id,
         is_approved=True,
         external_comments="Approved for testing",
         internal_comments="Test approval",
@@ -321,8 +321,8 @@ async def setup_llm_test_data(server):
     unique_slug = f"llm-test-agent-{str(uuid.uuid4())[:8]}"
     store_submission = await store_db.create_store_submission(
         user_id=user.id,
-        agent_id=created_graph.id,
-        agent_version=created_graph.version,
+        graph_id=created_graph.id,
+        graph_version=created_graph.version,
         slug=unique_slug,
         name="LLM Test Agent",
         description="An agent with LLM capabilities",
@@ -330,9 +330,9 @@ async def setup_llm_test_data(server):
         categories=["testing", "ai"],
         image_urls=["https://example.com/image.jpg"],
     )
-    assert store_submission.store_listing_version_id is not None
+    assert store_submission.listing_version_id is not None
     await store_db.review_store_submission(
-        store_listing_version_id=store_submission.store_listing_version_id,
+        store_listing_version_id=store_submission.listing_version_id,
         is_approved=True,
         external_comments="Approved for testing",
         internal_comments="Test approval for LLM agent",
@@ -476,8 +476,8 @@ async def setup_firecrawl_test_data(server):
     unique_slug = f"firecrawl-test-agent-{str(uuid.uuid4())[:8]}"
     store_submission = await store_db.create_store_submission(
         user_id=user.id,
-        agent_id=created_graph.id,
-        agent_version=created_graph.version,
+        graph_id=created_graph.id,
+        graph_version=created_graph.version,
         slug=unique_slug,
         name="Firecrawl Test Agent",
         description="An agent with Firecrawl integration (no credentials)",
@@ -485,9 +485,9 @@ async def setup_firecrawl_test_data(server):
         categories=["testing", "scraping"],
         image_urls=["https://example.com/image.jpg"],
     )
-    assert store_submission.store_listing_version_id is not None
+    assert store_submission.listing_version_id is not None
     await store_db.review_store_submission(
-        store_listing_version_id=store_submission.store_listing_version_id,
+        store_listing_version_id=store_submission.listing_version_id,
         is_approved=True,
         external_comments="Approved for testing",
         internal_comments="Test approval for Firecrawl agent",

autogpt_platform/backend/backend/copilot/tools/agent_generator/__init__.py

@@ -1,20 +1,15 @@
 """Agent generator package - Creates agents from natural language."""
 
 from .core import (
-    AgentGeneratorNotConfiguredError,
     AgentJsonValidationError,
     AgentSummary,
     DecompositionResult,
     DecompositionStep,
     LibraryAgentSummary,
     MarketplaceAgentSummary,
-    customize_template,
-    decompose_goal,
     enrich_library_agents_from_steps,
     extract_search_terms_from_steps,
     extract_uuids_from_text,
-    generate_agent,
-    generate_agent_patch,
     get_agent_as_json,
     get_all_relevant_agents_for_generation,
     get_library_agent_by_graph_id,
@@ -27,25 +22,20 @@ from .core import (
     search_marketplace_agents_for_generation,
 )
 from .errors import get_user_message_for_error
-from .service import health_check as check_external_service_health
-from .service import is_external_service_configured
+from .validation import AgentFixer, AgentValidator
 
 __all__ = [
-    "AgentGeneratorNotConfiguredError",
+    "AgentFixer",
+    "AgentValidator",
     "AgentJsonValidationError",
     "AgentSummary",
     "DecompositionResult",
     "DecompositionStep",
     "LibraryAgentSummary",
     "MarketplaceAgentSummary",
-    "check_external_service_health",
-    "customize_template",
-    "decompose_goal",
     "enrich_library_agents_from_steps",
     "extract_search_terms_from_steps",
     "extract_uuids_from_text",
-    "generate_agent",
-    "generate_agent_patch",
     "get_agent_as_json",
     "get_all_relevant_agents_for_generation",
     "get_library_agent_by_graph_id",
@@ -54,7 +44,6 @@ __all__ = [
     "get_library_agents_for_generation",
     "get_user_message_for_error",
     "graph_to_json",
-    "is_external_service_configured",
     "json_to_graph",
     "save_agent_to_library",
     "search_marketplace_agents_for_generation",

autogpt_platform/backend/backend/copilot/tools/agent_generator/blocks.py

@@ -0,0 +1,66 @@
+"""Block management for agent generation.
+
+Provides cached access to block metadata for validation and fixing.
+"""
+
+import logging
+from typing import Any, Type
+
+from backend.blocks import get_blocks as get_block_classes
+from backend.blocks._base import Block
+
+logger = logging.getLogger(__name__)
+
+__all__ = ["get_blocks_as_dicts", "reset_block_caches"]
+
+# ---------------------------------------------------------------------------
+# Module-level caches
+# ---------------------------------------------------------------------------
+_blocks_cache: list[dict[str, Any]] | None = None
+
+
+def reset_block_caches() -> None:
+    """Reset all module-level caches (useful after updating block descriptions)."""
+    global _blocks_cache
+    _blocks_cache = None
+
+
+# ---------------------------------------------------------------------------
+# 1. get_blocks_as_dicts
+# ---------------------------------------------------------------------------
+
+
+def get_blocks_as_dicts() -> list[dict[str, Any]]:
+    """Get all available blocks as dicts (cached after first call).
+
+    Each dict contains the keys returned by ``Block.get_info().model_dump()``:
+    id, name, description, inputSchema, outputSchema, categories,
+    staticOutput, costs, contributors, uiType.
+
+    Returns:
+        List of block info dicts.
+    """
+    global _blocks_cache
+    if _blocks_cache is not None:
+        return _blocks_cache
+
+    block_classes: dict[str, Type[Block]] = get_block_classes()  # type: ignore[assignment]
+    blocks: list[dict[str, Any]] = []
+    for block_cls in block_classes.values():
+        try:
+            instance = block_cls()
+            info = instance.get_info().model_dump()
+            # Use optimized description if available (loaded at startup)
+            if instance.optimized_description:
+                info["description"] = instance.optimized_description
+            blocks.append(info)
+        except Exception:
+            logger.warning(
+                "Failed to load block info for %s, skipping",
+                getattr(block_cls, "__name__", "unknown"),
+                exc_info=True,
+            )
+
+    _blocks_cache = blocks
+    logger.info("Cached %d block dicts", len(blocks))
+    return _blocks_cache

autogpt_platform/backend/backend/copilot/tools/agent_generator/core.py

@@ -10,13 +10,7 @@ from backend.data.db_accessors import graph_db, library_db, store_db
 from backend.data.graph import Graph, Link, Node
 from backend.util.exceptions import DatabaseError, NotFoundError
 
-from .service import (
-    customize_template_external,
-    decompose_goal_external,
-    generate_agent_external,
-    generate_agent_patch_external,
-    is_external_service_configured,
-)
+from .helpers import UUID_RE_STR
 
 logger = logging.getLogger(__name__)
 
@@ -78,38 +72,7 @@ class DecompositionResult(TypedDict, total=False):
 AgentSummary = LibraryAgentSummary | MarketplaceAgentSummary | dict[str, Any]
 
 
-def _to_dict_list(
-    agents: Sequence[AgentSummary] | Sequence[dict[str, Any]] | None,
-) -> list[dict[str, Any]] | None:
-    """Convert typed agent summaries to plain dicts for external service calls."""
-    if agents is None:
-        return None
-    return [dict(a) for a in agents]
-
-
-class AgentGeneratorNotConfiguredError(Exception):
-    """Raised when the external Agent Generator service is not configured."""
-
-    pass
-
-
-def _check_service_configured() -> None:
-    """Check if the external Agent Generator service is configured.
-
-    Raises:
-        AgentGeneratorNotConfiguredError: If the service is not configured.
-    """
-    if not is_external_service_configured():
-        raise AgentGeneratorNotConfiguredError(
-            "Agent Generator service is not configured. "
-            "Set AGENTGENERATOR_HOST environment variable to enable agent generation."
-        )
-
-
-_UUID_PATTERN = re.compile(
-    r"[a-f0-9]{8}-[a-f0-9]{4}-4[a-f0-9]{3}-[89ab][a-f0-9]{3}-[a-f0-9]{12}",
-    re.IGNORECASE,
-)
+_UUID_PATTERN = re.compile(UUID_RE_STR, re.IGNORECASE)
 
 
 def extract_uuids_from_text(text: str) -> list[str]:
@@ -553,69 +516,6 @@ async def enrich_library_agents_from_steps(
     return all_agents
 
 
-async def decompose_goal(
-    description: str,
-    context: str = "",
-    library_agents: Sequence[AgentSummary] | None = None,
-) -> DecompositionResult | None:
-    """Break down a goal into steps or return clarifying questions.
-
-    Args:
-        description: Natural language goal description
-        context: Additional context (e.g., answers to previous questions)
-        library_agents: User's library agents available for sub-agent composition
-
-    Returns:
-        DecompositionResult with either:
-        - {"type": "clarifying_questions", "questions": [...]}
-        - {"type": "instructions", "steps": [...]}
-        Or None on error
-
-    Raises:
-        AgentGeneratorNotConfiguredError: If the external service is not configured.
-    """
-    _check_service_configured()
-    logger.info("Calling external Agent Generator service for decompose_goal")
-    result = await decompose_goal_external(
-        description, context, _to_dict_list(library_agents)
-    )
-    return result  # type: ignore[return-value]
-
-
-async def generate_agent(
-    instructions: DecompositionResult | dict[str, Any],
-    library_agents: Sequence[AgentSummary] | Sequence[dict[str, Any]] | None = None,
-) -> dict[str, Any] | None:
-    """Generate agent JSON from instructions.
-
-    Args:
-        instructions: Structured instructions from decompose_goal
-        library_agents: User's library agents available for sub-agent composition
-
-    Returns:
-        Agent JSON dict, error dict {"type": "error", ...}, or None on error
-
-    Raises:
-        AgentGeneratorNotConfiguredError: If the external service is not configured.
-    """
-    _check_service_configured()
-    logger.info("Calling external Agent Generator service for generate_agent")
-    result = await generate_agent_external(
-        dict(instructions), _to_dict_list(library_agents)
-    )
-
-    if result:
-        if isinstance(result, dict) and result.get("type") == "error":
-            return result
-        if "id" not in result:
-            result["id"] = str(uuid.uuid4())
-        if "version" not in result:
-            result["version"] = 1
-        if "is_active" not in result:
-            result["is_active"] = True
-    return result
-
-
 class AgentJsonValidationError(Exception):
     """Raised when agent JSON is invalid or missing required fields."""
 
@@ -695,7 +595,10 @@ def json_to_graph(agent_json: dict[str, Any]) -> Graph:
 
 
 async def save_agent_to_library(
-    agent_json: dict[str, Any], user_id: str, is_update: bool = False
+    agent_json: dict[str, Any],
+    user_id: str,
+    is_update: bool = False,
+    folder_id: str | None = None,
 ) -> tuple[Graph, Any]:
     """Save agent to database and user's library.
 
@@ -703,6 +606,7 @@ async def save_agent_to_library(
         agent_json: Agent JSON dict
         user_id: User ID
         is_update: Whether this is an update to an existing agent
+        folder_id: Optional folder ID to place the agent in
 
     Returns:
         Tuple of (created Graph, LibraryAgent)
@@ -711,7 +615,7 @@ async def save_agent_to_library(
     db = library_db()
     if is_update:
         return await db.update_graph_in_library(graph, user_id)
-    return await db.create_graph_in_library(graph, user_id)
+    return await db.create_graph_in_library(graph, user_id, folder_id=folder_id)
 
 
 def graph_to_json(graph: Graph) -> dict[str, Any]:
@@ -788,70 +692,3 @@ async def get_agent_as_json(
         return None
 
     return graph_to_json(graph)
-
-
-async def generate_agent_patch(
-    update_request: str,
-    current_agent: dict[str, Any],
-    library_agents: Sequence[AgentSummary] | None = None,
-) -> dict[str, Any] | None:
-    """Update an existing agent using natural language.
-
-    The external Agent Generator service handles:
-    - Generating the patch
-    - Applying the patch
-    - Fixing and validating the result
-
-    Args:
-        update_request: Natural language description of changes
-        current_agent: Current agent JSON
-        library_agents: User's library agents available for sub-agent composition
-
-    Returns:
-        Updated agent JSON, clarifying questions dict {"type": "clarifying_questions", ...},
-        error dict {"type": "error", ...}, or None on error
-
-    Raises:
-        AgentGeneratorNotConfiguredError: If the external service is not configured.
-    """
-    _check_service_configured()
-    logger.info("Calling external Agent Generator service for generate_agent_patch")
-    return await generate_agent_patch_external(
-        update_request,
-        current_agent,
-        _to_dict_list(library_agents),
-    )
-
-
-async def customize_template(
-    template_agent: dict[str, Any],
-    modification_request: str,
-    context: str = "",
-) -> dict[str, Any] | None:
-    """Customize a template/marketplace agent using natural language.
-
-    This is used when users want to modify a template or marketplace agent
-    to fit their specific needs before adding it to their library.
-
-    The external Agent Generator service handles:
-    - Understanding the modification request
-    - Applying changes to the template
-    - Fixing and validating the result
-
-    Args:
-        template_agent: The template agent JSON to customize
-        modification_request: Natural language description of customizations
-        context: Additional context (e.g., answers to previous questions)
-
-    Returns:
-        Customized agent JSON, clarifying questions dict {"type": "clarifying_questions", ...},
-        error dict {"type": "error", ...}, or None on unexpected error
-
-    Raises:
-        AgentGeneratorNotConfiguredError: If the external service is not configured.
-    """
-    _check_service_configured()
-    logger.info("Calling external Agent Generator service for customize_template")
-    return await customize_template_external(
-        template_agent, modification_request, context
-    )

autogpt_platform/backend/backend/copilot/tools/agent_generator/dummy.py

@@ -1,165 +0,0 @@
-"""Dummy Agent Generator for testing.
-
-Returns mock responses matching the format expected from the external service.
-Enable via AGENTGENERATOR_USE_DUMMY=true in settings.
-
-WARNING: This is for testing only. Do not use in production.
-"""
-
-import asyncio
-import logging
-import uuid
-from typing import Any
-
-logger = logging.getLogger(__name__)
-
-# Dummy decomposition result (instructions type)
-DUMMY_DECOMPOSITION_RESULT: dict[str, Any] = {
-    "type": "instructions",
-    "steps": [
-        {
-            "description": "Get input from user",
-            "action": "input",
-            "block_name": "AgentInputBlock",
-        },
-        {
-            "description": "Process the input",
-            "action": "process",
-            "block_name": "TextFormatterBlock",
-        },
-        {
-            "description": "Return output to user",
-            "action": "output",
-            "block_name": "AgentOutputBlock",
-        },
-    ],
-}
-
-# Block IDs from backend/blocks/io.py
-AGENT_INPUT_BLOCK_ID = "c0a8e994-ebf1-4a9c-a4d8-89d09c86741b"
-AGENT_OUTPUT_BLOCK_ID = "363ae599-353e-4804-937e-b2ee3cef3da4"
-
-
-def _generate_dummy_agent_json() -> dict[str, Any]:
-    """Generate a minimal valid agent JSON for testing."""
-    input_node_id = str(uuid.uuid4())
-    output_node_id = str(uuid.uuid4())
-
-    return {
-        "id": str(uuid.uuid4()),
-        "version": 1,
-        "is_active": True,
-        "name": "Dummy Test Agent",
-        "description": "A dummy agent generated for testing purposes",
-        "nodes": [
-            {
-                "id": input_node_id,
-                "block_id": AGENT_INPUT_BLOCK_ID,
-                "input_default": {
-                    "name": "input",
-                    "title": "Input",
-                    "description": "Enter your input",
-                    "placeholder_values": [],
-                },
-                "metadata": {"position": {"x": 0, "y": 0}},
-            },
-            {
-                "id": output_node_id,
-                "block_id": AGENT_OUTPUT_BLOCK_ID,
-                "input_default": {
-                    "name": "output",
-                    "title": "Output",
-                    "description": "Agent output",
-                    "format": "{output}",
-                },
-                "metadata": {"position": {"x": 400, "y": 0}},
-            },
-        ],
-        "links": [
-            {
-                "id": str(uuid.uuid4()),
-                "source_id": input_node_id,
-                "sink_id": output_node_id,
-                "source_name": "result",
-                "sink_name": "value",
-                "is_static": False,
-            },
-        ],
-    }
-
-
-async def decompose_goal_dummy(
-    description: str,
-    context: str = "",
-    library_agents: list[dict[str, Any]] | None = None,
-) -> dict[str, Any]:
-    """Return dummy decomposition result."""
-    logger.info("Using dummy agent generator for decompose_goal")
-    return DUMMY_DECOMPOSITION_RESULT.copy()
-
-
-async def generate_agent_dummy(
-    instructions: dict[str, Any],
-    library_agents: list[dict[str, Any]] | None = None,
-    operation_id: str | None = None,
-    session_id: str | None = None,
-) -> dict[str, Any]:
-    """Return dummy agent synchronously (blocks for 30s, returns agent JSON).
-
-    Note: operation_id and session_id parameters are ignored - we always use synchronous mode.
-    """
-    logger.info(
-        "Using dummy agent generator (sync mode): returning agent JSON after 30s"
-    )
-    await asyncio.sleep(30)
-    return _generate_dummy_agent_json()
-
-
-async def generate_agent_patch_dummy(
-    update_request: str,
-    current_agent: dict[str, Any],
-    library_agents: list[dict[str, Any]] | None = None,
-    operation_id: str | None = None,
-    session_id: str | None = None,
-) -> dict[str, Any]:
-    """Return dummy patched agent synchronously (blocks for 30s, returns patched agent JSON).
-
-    Note: operation_id and session_id parameters are ignored - we always use synchronous mode.
-    """
-    logger.info(
-        "Using dummy agent generator patch (sync mode): returning patched agent after 30s"
-    )
-    await asyncio.sleep(30)
-    patched = current_agent.copy()
-    patched["description"] = (
-        f"{current_agent.get('description', '')} (updated: {update_request})"
-    )
-    return patched
-
-
-async def customize_template_dummy(
-    template_agent: dict[str, Any],
-    modification_request: str,
-    context: str = "",
-) -> dict[str, Any]:
-    """Return dummy customized template (returns template with updated description)."""
-    logger.info("Using dummy agent generator for customize_template")
-    customized = template_agent.copy()
-    customized["description"] = (
-        f"{template_agent.get('description', '')} (customized: {modification_request})"
-    )
-    return customized
-
-
-async def get_blocks_dummy() -> list[dict[str, Any]]:
-    """Return dummy blocks list."""
-    logger.info("Using dummy agent generator for get_blocks")
-    return [
-        {"id": AGENT_INPUT_BLOCK_ID, "name": "AgentInputBlock"},
-        {"id": AGENT_OUTPUT_BLOCK_ID, "name": "AgentOutputBlock"},
-    ]
-
-
-async def health_check_dummy() -> bool:
-    """Always returns healthy for dummy service."""
-    return True

autogpt_platform/backend/backend/copilot/tools/agent_generator/fixer_test.py

@@ -0,0 +1,913 @@
+"""Unit tests for AgentFixer."""
+
+from .fixer import (
+    _ADDTODICTIONARY_BLOCK_ID,
+    _ADDTOLIST_BLOCK_ID,
+    _CODE_EXECUTION_BLOCK_ID,
+    _DATA_SAMPLING_BLOCK_ID,
+    _GET_CURRENT_DATE_BLOCK_ID,
+    _STORE_VALUE_BLOCK_ID,
+    _TEXT_REPLACE_BLOCK_ID,
+    _UNIVERSAL_TYPE_CONVERTER_BLOCK_ID,
+    AGENT_EXECUTOR_BLOCK_ID,
+    MCP_TOOL_BLOCK_ID,
+    AgentFixer,
+)
+from .helpers import generate_uuid
+
+
+def _make_agent(
+    nodes: list | None = None,
+    links: list | None = None,
+    agent_id: str | None = None,
+) -> dict:
+    """Build a minimal agent dict for testing."""
+    return {
+        "id": agent_id or generate_uuid(),
+        "name": "Test Agent",
+        "nodes": nodes or [],
+        "links": links or [],
+    }
+
+
+def _make_node(
+    node_id: str | None = None,
+    block_id: str = "block-1",
+    input_default: dict | None = None,
+    position: tuple[int, int] = (0, 0),
+) -> dict:
+    """Build a minimal node dict for testing."""
+    return {
+        "id": node_id or generate_uuid(),
+        "block_id": block_id,
+        "input_default": input_default or {},
+        "metadata": {"position": {"x": position[0], "y": position[1]}},
+    }
+
+
+def _make_link(
+    link_id: str | None = None,
+    source_id: str = "",
+    source_name: str = "output",
+    sink_id: str = "",
+    sink_name: str = "input",
+    is_static: bool = False,
+) -> dict:
+    """Build a minimal link dict for testing."""
+    return {
+        "id": link_id or generate_uuid(),
+        "source_id": source_id,
+        "source_name": source_name,
+        "sink_id": sink_id,
+        "sink_name": sink_name,
+        "is_static": is_static,
+    }
+
+
+class TestFixAgentIds:
+    """Tests for fix_agent_ids."""
+
+    def test_valid_uuids_unchanged(self):
+        fixer = AgentFixer()
+        agent_id = generate_uuid()
+        link_id = generate_uuid()
+        agent = _make_agent(agent_id=agent_id, links=[{"id": link_id}])
+
+        result = fixer.fix_agent_ids(agent)
+
+        assert result["id"] == agent_id
+        assert result["links"][0]["id"] == link_id
+        assert fixer.fixes_applied == []
+
+    def test_invalid_agent_id_replaced(self):
+        fixer = AgentFixer()
+        agent = _make_agent(agent_id="bad-id")
+
+        result = fixer.fix_agent_ids(agent)
+
+        assert result["id"] != "bad-id"
+        assert len(fixer.fixes_applied) == 1
+        assert "agent ID" in fixer.fixes_applied[0]
+
+    def test_invalid_link_id_replaced(self):
+        fixer = AgentFixer()
+        agent = _make_agent(links=[{"id": "not-a-uuid"}])
+
+        result = fixer.fix_agent_ids(agent)
+
+        assert result["links"][0]["id"] != "not-a-uuid"
+        assert len(fixer.fixes_applied) == 1
+
+
+class TestFixDoubleCurlyBraces:
+    """Tests for fix_double_curly_braces."""
+
+    def test_single_braces_converted_to_double(self):
+        fixer = AgentFixer()
+        node = _make_node(input_default={"prompt": "Hello {name}!"})
+        agent = _make_agent(nodes=[node])
+
+        result = fixer.fix_double_curly_braces(agent)
+
+        assert result["nodes"][0]["input_default"]["prompt"] == "Hello {{name}}!"
+
+    def test_double_braces_unchanged(self):
+        fixer = AgentFixer()
+        node = _make_node(input_default={"prompt": "Hello {{name}}!"})
+        agent = _make_agent(nodes=[node])
+
+        result = fixer.fix_double_curly_braces(agent)
+
+        assert result["nodes"][0]["input_default"]["prompt"] == "Hello {{name}}!"
+        assert fixer.fixes_applied == []
+
+    def test_non_string_prompt_skipped(self):
+        fixer = AgentFixer()
+        node = _make_node(input_default={"prompt": 42})
+        agent = _make_agent(nodes=[node])
+
+        result = fixer.fix_double_curly_braces(agent)
+
+        assert result["nodes"][0]["input_default"]["prompt"] == 42
+
+    def test_non_string_prompt_with_prompt_values_skipped(self):
+        """Ensure non-string prompt fields don't crash re.search in the
+        prompt_values path."""
+        fixer = AgentFixer()
+        node_id = generate_uuid()
+        source_id = generate_uuid()
+        node = _make_node(
+            node_id=node_id, input_default={"prompt": None, "prompt_values": {}}
+        )
+        source_node = _make_node(node_id=source_id)
+        link = _make_link(
+            source_id=source_id,
+            source_name="output",
+            sink_id=node_id,
+            sink_name="prompt_values_$_name",
+        )
+        agent = _make_agent(nodes=[node, source_node], links=[link])
+
+        result = fixer.fix_double_curly_braces(agent)
+
+        # Should not crash and prompt stays None
+        assert result["nodes"][0]["input_default"]["prompt"] is None
+
+
+class TestFixCredentials:
+    """Tests for fix_credentials."""
+
+    def test_credentials_removed(self):
+        fixer = AgentFixer()
+        node = _make_node(
+            input_default={
+                "credentials": {"key": "secret"},
+                "url": "http://example.com",
+            }
+        )
+        agent = _make_agent(nodes=[node])
+
+        result = fixer.fix_credentials(agent)
+
+        assert "credentials" not in result["nodes"][0]["input_default"]
+        assert result["nodes"][0]["input_default"]["url"] == "http://example.com"
+        assert len(fixer.fixes_applied) == 1
+
+    def test_no_credentials_unchanged(self):
+        fixer = AgentFixer()
+        node = _make_node(input_default={"url": "http://example.com"})
+        agent = _make_agent(nodes=[node])
+
+        result = fixer.fix_credentials(agent)
+
+        assert result["nodes"][0]["input_default"]["url"] == "http://example.com"
+        assert fixer.fixes_applied == []
+
+
+class TestFixCodeExecutionOutput:
+    """Tests for fix_code_execution_output."""
+
+    def test_response_renamed_to_stdout_logs(self):
+        fixer = AgentFixer()
+        node = _make_node(node_id="n1", block_id=_CODE_EXECUTION_BLOCK_ID)
+        link = _make_link(source_id="n1", source_name="response", sink_id="n2")
+        agent = _make_agent(nodes=[node], links=[link])
+
+        result = fixer.fix_code_execution_output(agent)
+
+        assert result["links"][0]["source_name"] == "stdout_logs"
+        assert len(fixer.fixes_applied) == 1
+
+    def test_non_response_source_unchanged(self):
+        fixer = AgentFixer()
+        node = _make_node(node_id="n1", block_id=_CODE_EXECUTION_BLOCK_ID)
+        link = _make_link(source_id="n1", source_name="stdout_logs", sink_id="n2")
+        agent = _make_agent(nodes=[node], links=[link])
+
+        result = fixer.fix_code_execution_output(agent)
+
+        assert result["links"][0]["source_name"] == "stdout_logs"
+        assert fixer.fixes_applied == []
+
+
+class TestFixDataSamplingSampleSize:
+    """Tests for fix_data_sampling_sample_size."""
+
+    def test_sample_size_set_to_1(self):
+        fixer = AgentFixer()
+        node = _make_node(
+            node_id="n1",
+            block_id=_DATA_SAMPLING_BLOCK_ID,
+            input_default={"sample_size": 10},
+        )
+        agent = _make_agent(nodes=[node])
+
+        result = fixer.fix_data_sampling_sample_size(agent)
+
+        assert result["nodes"][0]["input_default"]["sample_size"] == 1
+
+    def test_removes_links_to_sample_size(self):
+        fixer = AgentFixer()
+        node = _make_node(node_id="n1", block_id=_DATA_SAMPLING_BLOCK_ID)
+        link = _make_link(sink_id="n1", sink_name="sample_size", source_id="n2")
+        agent = _make_agent(nodes=[node], links=[link])
+
+        result = fixer.fix_data_sampling_sample_size(agent)
+
+        assert len(result["links"]) == 0
+        assert result["nodes"][0]["input_default"]["sample_size"] == 1
+
+
+class TestFixTextReplaceNewParameter:
+    """Tests for fix_text_replace_new_parameter."""
+
+    def test_empty_new_changed_to_space(self):
+        fixer = AgentFixer()
+        node = _make_node(
+            block_id=_TEXT_REPLACE_BLOCK_ID,
+            input_default={"new": ""},
+        )
+        agent = _make_agent(nodes=[node])
+
+        result = fixer.fix_text_replace_new_parameter(agent)
+
+        assert result["nodes"][0]["input_default"]["new"] == " "
+
+    def test_nonempty_new_unchanged(self):
+        fixer = AgentFixer()
+        node = _make_node(
+            block_id=_TEXT_REPLACE_BLOCK_ID,
+            input_default={"new": "replacement"},
+        )
+        agent = _make_agent(nodes=[node])
+
+        result = fixer.fix_text_replace_new_parameter(agent)
+
+        assert result["nodes"][0]["input_default"]["new"] == "replacement"
+        assert fixer.fixes_applied == []
+
+
+class TestFixGetCurrentDateOffset:
+    """Tests for fix_getcurrentdate_offset."""
+
+    def test_negative_offset_made_positive(self):
+        fixer = AgentFixer()
+        node = _make_node(
+            block_id=_GET_CURRENT_DATE_BLOCK_ID,
+            input_default={"offset": -5},
+        )
+        agent = _make_agent(nodes=[node])
+
+        result = fixer.fix_getcurrentdate_offset(agent)
+
+        assert result["nodes"][0]["input_default"]["offset"] == 5
+
+    def test_positive_offset_unchanged(self):
+        fixer = AgentFixer()
+        node = _make_node(
+            block_id=_GET_CURRENT_DATE_BLOCK_ID,
+            input_default={"offset": 3},
+        )
+        agent = _make_agent(nodes=[node])
+
+        result = fixer.fix_getcurrentdate_offset(agent)
+
+        assert result["nodes"][0]["input_default"]["offset"] == 3
+        assert fixer.fixes_applied == []
+
+
+class TestFixNodeXCoordinates:
+    """Tests for fix_node_x_coordinates."""
+
+    def test_close_nodes_spread_apart(self):
+        fixer = AgentFixer()
+        src_node = _make_node(node_id="src", position=(0, 0))
+        sink_node = _make_node(node_id="sink", position=(100, 0))
+        link = _make_link(source_id="src", sink_id="sink")
+        agent = _make_agent(nodes=[src_node, sink_node], links=[link])
+
+        result = fixer.fix_node_x_coordinates(agent)
+
+        sink = next(n for n in result["nodes"] if n["id"] == "sink")
+        assert sink["metadata"]["position"]["x"] >= 800
+
+    def test_far_apart_nodes_unchanged(self):
+        fixer = AgentFixer()
+        src_node = _make_node(node_id="src", position=(0, 0))
+        sink_node = _make_node(node_id="sink", position=(1000, 0))
+        link = _make_link(source_id="src", sink_id="sink")
+        agent = _make_agent(nodes=[src_node, sink_node], links=[link])
+
+        result = fixer.fix_node_x_coordinates(agent)
+
+        sink = next(n for n in result["nodes"] if n["id"] == "sink")
+        assert sink["metadata"]["position"]["x"] == 1000
+        assert fixer.fixes_applied == []
+
+
+class TestFixAddToDictionaryBlocks:
+    """Tests for fix_addtodictionary_blocks."""
+
+    def test_removes_create_dictionary_nodes(self):
+        fixer = AgentFixer()
+        create_dict_id = "b924ddf4-de4f-4b56-9a85-358930dcbc91"
+        dict_node = _make_node(node_id="dict-1", block_id=create_dict_id)
+        add_to_dict_node = _make_node(
+            node_id="add-1", block_id=_ADDTODICTIONARY_BLOCK_ID
+        )
+        link = _make_link(source_id="dict-1", sink_id="add-1")
+        agent = _make_agent(nodes=[dict_node, add_to_dict_node], links=[link])
+
+        result = fixer.fix_addtodictionary_blocks(agent)
+
+        node_ids = [n["id"] for n in result["nodes"]]
+        assert "dict-1" not in node_ids
+        assert "add-1" in node_ids
+        assert len(result["links"]) == 0
+
+
+class TestFixStoreValueBeforeCondition:
+    """Tests for fix_storevalue_before_condition."""
+
+    def test_inserts_storevalue_block(self):
+        fixer = AgentFixer()
+        condition_block_id = "715696a0-e1da-45c8-b209-c2fa9c3b0be6"
+        src_node = _make_node(node_id="src")
+        cond_node = _make_node(node_id="cond", block_id=condition_block_id)
+        link = _make_link(
+            source_id="src", source_name="output", sink_id="cond", sink_name="value2"
+        )
+        agent = _make_agent(nodes=[src_node, cond_node], links=[link])
+
+        result = fixer.fix_storevalue_before_condition(agent)
+
+        # Should have 3 nodes now (original 2 + new StoreValueBlock)
+        assert len(result["nodes"]) == 3
+        store_nodes = [
+            n for n in result["nodes"] if n["block_id"] == _STORE_VALUE_BLOCK_ID
+        ]
+        assert len(store_nodes) == 1
+        assert store_nodes[0]["input_default"]["data"] is None
+
+
+class TestFixAddToListBlocks:
+    """Tests for fix_addtolist_blocks - self-reference links."""
+
+    def test_addtolist_gets_self_reference_link(self):
+        fixer = AgentFixer()
+        node = _make_node(node_id="atl-1", block_id=_ADDTOLIST_BLOCK_ID)
+        # Source link to AddToList (from some other node)
+        link = _make_link(
+            source_id="other",
+            source_name="output",
+            sink_id="atl-1",
+            sink_name="item",
+        )
+        other_node = _make_node(node_id="other")
+        agent = _make_agent(nodes=[other_node, node], links=[link])
+
+        result = fixer.fix_addtolist_blocks(agent)
+
+        # Should have a self-reference link: atl-1.updated_list -> atl-1.list
+        self_ref_links = [
+            lnk
+            for lnk in result["links"]
+            if lnk["source_id"] == "atl-1"
+            and lnk["sink_id"] == "atl-1"
+            and lnk["source_name"] == "updated_list"
+            and lnk["sink_name"] == "list"
+        ]
+        assert len(self_ref_links) == 1
+
+
+class TestFixLinkStaticProperties:
+    """Tests for fix_link_static_properties."""
+
+    def test_sets_is_static_from_block_schema(self):
+        fixer = AgentFixer()
+        block_id = generate_uuid()
+        node = _make_node(node_id="n1", block_id=block_id)
+        link = _make_link(source_id="n1", sink_id="n2", is_static=False)
+        agent = _make_agent(nodes=[node], links=[link])
+
+        blocks = [{"id": block_id, "staticOutput": True}]
+
+        result = fixer.fix_link_static_properties(agent, blocks)
+
+        assert result["links"][0]["is_static"] is True
+
+    def test_unknown_block_leaves_link_unchanged(self):
+        fixer = AgentFixer()
+        node = _make_node(node_id="n1", block_id="unknown-block")
+        link = _make_link(source_id="n1", sink_id="n2", is_static=True)
+        agent = _make_agent(nodes=[node], links=[link])
+
+        result = fixer.fix_link_static_properties(agent, blocks=[])
+
+        # Unknown block → skipped, link stays as-is
+        assert result["links"][0]["is_static"] is True
+
+
+class TestFixAiModelParameter:
+    """Tests for fix_ai_model_parameter."""
+
+    def test_missing_model_gets_default(self):
+        fixer = AgentFixer()
+        block_id = generate_uuid()
+        node = _make_node(node_id="n1", block_id=block_id, input_default={})
+        agent = _make_agent(nodes=[node])
+
+        blocks = [
+            {
+                "id": block_id,
+                "categories": [{"category": "AI"}],
+                "inputSchema": {
+                    "properties": {"model": {"type": "string"}},
+                },
+            }
+        ]
+
+        result = fixer.fix_ai_model_parameter(agent, blocks)
+
+        assert result["nodes"][0]["input_default"]["model"] == "gpt-4o"
+
+    def test_valid_model_unchanged(self):
+        fixer = AgentFixer()
+        block_id = generate_uuid()
+        node = _make_node(
+            node_id="n1",
+            block_id=block_id,
+            input_default={"model": "claude-opus-4-6"},
+        )
+        agent = _make_agent(nodes=[node])
+
+        blocks = [
+            {
+                "id": block_id,
+                "categories": [{"category": "AI"}],
+                "inputSchema": {
+                    "properties": {"model": {"type": "string"}},
+                },
+            }
+        ]
+
+        result = fixer.fix_ai_model_parameter(agent, blocks)
+
+        assert result["nodes"][0]["input_default"]["model"] == "claude-opus-4-6"
+
+
+class TestFixAgentExecutorBlocks:
+    """Tests for fix_agent_executor_blocks."""
+
+    def test_fills_schemas_from_library_agent(self):
+        fixer = AgentFixer()
+        lib_agent_id = generate_uuid()
+        node = _make_node(
+            node_id="n1",
+            block_id=AGENT_EXECUTOR_BLOCK_ID,
+            input_default={
+                "graph_id": lib_agent_id,
+                "graph_version": 1,
+                "user_id": "user-1",
+            },
+        )
+        agent = _make_agent(nodes=[node])
+
+        # Library agents use graph_id as the lookup key
+        library_agents = [
+            {
+                "graph_id": lib_agent_id,
+                "graph_version": 2,
+                "input_schema": {"field1": {"type": "string"}},
+                "output_schema": {"result": {"type": "string"}},
+            }
+        ]
+
+        result = fixer.fix_agent_executor_blocks(agent, library_agents)
+
+        node_result = result["nodes"][0]["input_default"]
+        assert node_result["graph_version"] == 2
+        assert node_result["input_schema"] == {"field1": {"type": "string"}}
+        assert node_result["output_schema"] == {"result": {"type": "string"}}
+
+
+class TestFixInvalidNestedSinkLinks:
+    """Tests for fix_invalid_nested_sink_links."""
+
+    def test_removes_numeric_index_links(self):
+        fixer = AgentFixer()
+        block_id = generate_uuid()
+        node = _make_node(node_id="n1", block_id=block_id)
+        link = _make_link(source_id="n2", sink_id="n1", sink_name="values_#_0")
+        agent = _make_agent(nodes=[node], links=[link])
+
+        blocks = [
+            {
+                "id": block_id,
+                "inputSchema": {"properties": {"values": {"type": "array"}}},
+            }
+        ]
+
+        result = fixer.fix_invalid_nested_sink_links(agent, blocks)
+
+        assert len(result["links"]) == 0
+
+    def test_valid_nested_links_kept(self):
+        fixer = AgentFixer()
+        block_id = generate_uuid()
+        node = _make_node(node_id="n1", block_id=block_id)
+        link = _make_link(source_id="n2", sink_id="n1", sink_name="values_#_name")
+        agent = _make_agent(nodes=[node], links=[link])
+
+        blocks = [
+            {
+                "id": block_id,
+                "inputSchema": {
+                    "properties": {"values": {"type": "object"}},
+                },
+            }
+        ]
+
+        result = fixer.fix_invalid_nested_sink_links(agent, blocks)
+
+        assert len(result["links"]) == 1
+
+
+class TestApplyAllFixes:
+    """Tests for apply_all_fixes orchestration."""
+
+    def test_is_sync(self):
+        """apply_all_fixes should be a sync function."""
+        import inspect
+
+        assert not inspect.iscoroutinefunction(AgentFixer.apply_all_fixes)
+
+    def test_applies_multiple_fixes(self):
+        fixer = AgentFixer()
+        agent = _make_agent(
+            agent_id="bad-id",
+            nodes=[
+                _make_node(
+                    block_id=_TEXT_REPLACE_BLOCK_ID,
+                    input_default={"new": "", "credentials": {"key": "secret"}},
+                )
+            ],
+        )
+
+        result = fixer.apply_all_fixes(agent)
+
+        # Agent ID should be fixed
+        assert result["id"] != "bad-id"
+        # Credentials should be removed
+        assert "credentials" not in result["nodes"][0]["input_default"]
+        # Text replace "new" should be space
+        assert result["nodes"][0]["input_default"]["new"] == " "
+        # Multiple fixes applied
+        assert len(fixer.fixes_applied) >= 3
+
+    def test_empty_agent_no_crash(self):
+        fixer = AgentFixer()
+        agent = _make_agent()
+
+        result = fixer.apply_all_fixes(agent)
+
+        assert "nodes" in result
+        assert "links" in result
+
+    def test_returns_deep_copy_behavior(self):
+        """Fixer mutates in place — verify the same dict is returned."""
+        fixer = AgentFixer()
+        agent = _make_agent()
+        result = fixer.apply_all_fixes(agent)
+        assert result is agent
+
+
+class TestFixMCPToolBlocks:
+    """Tests for fix_mcp_tool_blocks."""
+
+    def test_adds_missing_tool_arguments(self):
+        fixer = AgentFixer()
+        node = _make_node(
+            node_id="n1",
+            block_id=MCP_TOOL_BLOCK_ID,
+            input_default={
+                "server_url": "https://mcp.example.com/sse",
+                "selected_tool": "search",
+                "tool_input_schema": {},
+            },
+        )
+        agent = _make_agent(nodes=[node])
+
+        result = fixer.fix_mcp_tool_blocks(agent)
+
+        assert result["nodes"][0]["input_default"]["tool_arguments"] == {}
+        assert any("tool_arguments" in f for f in fixer.fixes_applied)
+
+    def test_adds_missing_tool_input_schema(self):
+        fixer = AgentFixer()
+        node = _make_node(
+            node_id="n1",
+            block_id=MCP_TOOL_BLOCK_ID,
+            input_default={
+                "server_url": "https://mcp.example.com/sse",
+                "selected_tool": "search",
+                "tool_arguments": {},
+            },
+        )
+        agent = _make_agent(nodes=[node])
+
+        result = fixer.fix_mcp_tool_blocks(agent)
+
+        assert result["nodes"][0]["input_default"]["tool_input_schema"] == {}
+        assert any("tool_input_schema" in f for f in fixer.fixes_applied)
+
+    def test_populates_tool_arguments_from_schema(self):
+        fixer = AgentFixer()
+        node = _make_node(
+            node_id="n1",
+            block_id=MCP_TOOL_BLOCK_ID,
+            input_default={
+                "server_url": "https://mcp.example.com/sse",
+                "selected_tool": "search",
+                "tool_input_schema": {
+                    "properties": {
+                        "query": {"type": "string", "default": "hello"},
+                        "limit": {"type": "integer"},
+                    }
+                },
+                "tool_arguments": {},
+            },
+        )
+        agent = _make_agent(nodes=[node])
+
+        result = fixer.fix_mcp_tool_blocks(agent)
+
+        tool_args = result["nodes"][0]["input_default"]["tool_arguments"]
+        assert tool_args["query"] == "hello"
+        assert tool_args["limit"] is None
+
+    def test_no_op_when_already_complete(self):
+        fixer = AgentFixer()
+        node = _make_node(
+            node_id="n1",
+            block_id=MCP_TOOL_BLOCK_ID,
+            input_default={
+                "server_url": "https://mcp.example.com/sse",
+                "selected_tool": "search",
+                "tool_input_schema": {},
+                "tool_arguments": {},
+            },
+        )
+        agent = _make_agent(nodes=[node])
+
+        fixer.fix_mcp_tool_blocks(agent)
+
+        assert len(fixer.fixes_applied) == 0
+
+
+class TestFixDynamicBlockSinkNames:
+    """Tests for fix_dynamic_block_sink_names."""
+
+    def test_mcp_tool_arguments_prefix_removed(self):
+        fixer = AgentFixer()
+        node = _make_node(node_id="n1", block_id=MCP_TOOL_BLOCK_ID)
+        link = _make_link(
+            source_id="src", sink_id="n1", sink_name="tool_arguments_#_query"
+        )
+        agent = _make_agent(nodes=[node], links=[link])
+
+        fixer.fix_dynamic_block_sink_names(agent)
+
+        assert agent["links"][0]["sink_name"] == "query"
+        assert len(fixer.fixes_applied) == 1
+
+    def test_agent_executor_inputs_prefix_removed(self):
+        fixer = AgentFixer()
+        node = _make_node(node_id="n1", block_id=AGENT_EXECUTOR_BLOCK_ID)
+        link = _make_link(source_id="src", sink_id="n1", sink_name="inputs_#_url")
+        agent = _make_agent(nodes=[node], links=[link])
+
+        fixer.fix_dynamic_block_sink_names(agent)
+
+        assert agent["links"][0]["sink_name"] == "url"
+        assert len(fixer.fixes_applied) == 1
+
+    def test_bare_sink_name_unchanged(self):
+        fixer = AgentFixer()
+        node = _make_node(node_id="n1", block_id=MCP_TOOL_BLOCK_ID)
+        link = _make_link(source_id="src", sink_id="n1", sink_name="query")
+        agent = _make_agent(nodes=[node], links=[link])
+
+        fixer.fix_dynamic_block_sink_names(agent)
+
+        assert agent["links"][0]["sink_name"] == "query"
+        assert len(fixer.fixes_applied) == 0
+
+    def test_non_dynamic_block_unchanged(self):
+        fixer = AgentFixer()
+        node = _make_node(node_id="n1", block_id="some-other-block-id")
+        link = _make_link(source_id="src", sink_id="n1", sink_name="values_#_key")
+        agent = _make_agent(nodes=[node], links=[link])
+
+        fixer.fix_dynamic_block_sink_names(agent)
+
+        assert agent["links"][0]["sink_name"] == "values_#_key"
+        assert len(fixer.fixes_applied) == 0
+
+
+class TestFixDataTypeMismatch:
+    """Tests for fix_data_type_mismatch."""
+
+    @staticmethod
+    def _make_block(
+        block_id: str,
+        name: str = "TestBlock",
+        input_schema: dict | None = None,
+        output_schema: dict | None = None,
+    ) -> dict:
+        return {
+            "id": block_id,
+            "name": name,
+            "inputSchema": input_schema or {"properties": {}},
+            "outputSchema": output_schema or {"properties": {}},
+        }
+
+    def test_inserts_converter_for_incompatible_types(self):
+        fixer = AgentFixer()
+        src_block_id = generate_uuid()
+        sink_block_id = generate_uuid()
+
+        src_node = _make_node(node_id="src", block_id=src_block_id)
+        sink_node = _make_node(node_id="sink", block_id=sink_block_id)
+        link = _make_link(
+            source_id="src",
+            source_name="result",
+            sink_id="sink",
+            sink_name="count",
+        )
+        agent = _make_agent(nodes=[src_node, sink_node], links=[link])
+
+        blocks = [
+            self._make_block(
+                src_block_id,
+                name="Source",
+                output_schema={"properties": {"result": {"type": "string"}}},
+            ),
+            self._make_block(
+                sink_block_id,
+                name="Sink",
+                input_schema={"properties": {"count": {"type": "integer"}}},
+            ),
+        ]
+
+        result = fixer.fix_data_type_mismatch(agent, blocks)
+
+        # A converter node should have been inserted
+        converter_nodes = [
+            n
+            for n in result["nodes"]
+            if n["block_id"] == _UNIVERSAL_TYPE_CONVERTER_BLOCK_ID
+        ]
+        assert len(converter_nodes) == 1
+        assert converter_nodes[0]["input_default"]["type"] == "number"
+
+        # Original link replaced by two new links through the converter
+        assert len(result["links"]) == 2
+        src_to_converter = result["links"][0]
+        converter_to_sink = result["links"][1]
+
+        assert src_to_converter["source_id"] == "src"
+        assert src_to_converter["sink_id"] == converter_nodes[0]["id"]
+        assert src_to_converter["sink_name"] == "value"
+
+        assert converter_to_sink["source_id"] == converter_nodes[0]["id"]
+        assert converter_to_sink["source_name"] == "value"
+        assert converter_to_sink["sink_id"] == "sink"
+        assert converter_to_sink["sink_name"] == "count"
+
+        assert len(fixer.fixes_applied) == 1
+
+    def test_compatible_types_unchanged(self):
+        fixer = AgentFixer()
+        block_id = generate_uuid()
+
+        src_node = _make_node(node_id="src", block_id=block_id)
+        sink_node = _make_node(node_id="sink", block_id=block_id)
+        link = _make_link(
+            source_id="src",
+            source_name="output",
+            sink_id="sink",
+            sink_name="input",
+        )
+        agent = _make_agent(nodes=[src_node, sink_node], links=[link])
+
+        blocks = [
+            self._make_block(
+                block_id,
+                input_schema={"properties": {"input": {"type": "string"}}},
+                output_schema={"properties": {"output": {"type": "string"}}},
+            ),
+        ]
+
+        result = fixer.fix_data_type_mismatch(agent, blocks)
+
+        # No converter inserted, original link kept
+        assert len(result["nodes"]) == 2
+        assert len(result["links"]) == 1
+        assert result["links"][0] is link
+        assert fixer.fixes_applied == []
+
+    def test_missing_block_keeps_link(self):
+        """Links referencing unknown blocks are kept unchanged."""
+        fixer = AgentFixer()
+        src_node = _make_node(node_id="src", block_id="unknown-block")
+        sink_node = _make_node(node_id="sink", block_id="unknown-block")
+        link = _make_link(source_id="src", sink_id="sink")
+        agent = _make_agent(nodes=[src_node, sink_node], links=[link])
+
+        result = fixer.fix_data_type_mismatch(agent, blocks=[])
+
+        assert len(result["links"]) == 1
+        assert result["links"][0] is link
+
+    def test_missing_type_info_keeps_link(self):
+        """Links where source/sink type is not defined are kept unchanged."""
+        fixer = AgentFixer()
+        block_id = generate_uuid()
+        src_node = _make_node(node_id="src", block_id=block_id)
+        sink_node = _make_node(node_id="sink", block_id=block_id)
+        link = _make_link(
+            source_id="src",
+            source_name="output",
+            sink_id="sink",
+            sink_name="input",
+        )
+        agent = _make_agent(nodes=[src_node, sink_node], links=[link])
+
+        # Block has no properties defined for the linked fields
+        blocks = [self._make_block(block_id)]
+
+        result = fixer.fix_data_type_mismatch(agent, blocks)
+
+        assert len(result["links"]) == 1
+        assert fixer.fixes_applied == []
+
+    def test_multiple_mismatches_insert_multiple_converters(self):
+        """Each incompatible link gets its own converter node."""
+        fixer = AgentFixer()
+        src_block_id = generate_uuid()
+        sink_block_id = generate_uuid()
+
+        src_node = _make_node(node_id="src", block_id=src_block_id)
+        sink1 = _make_node(node_id="sink1", block_id=sink_block_id)
+        sink2 = _make_node(node_id="sink2", block_id=sink_block_id)
+        link1 = _make_link(
+            source_id="src", source_name="out", sink_id="sink1", sink_name="count"
+        )
+        link2 = _make_link(
+            source_id="src", source_name="out", sink_id="sink2", sink_name="count"
+        )
+        agent = _make_agent(nodes=[src_node, sink1, sink2], links=[link1, link2])
+
+        blocks = [
+            self._make_block(
+                src_block_id,
+                output_schema={"properties": {"out": {"type": "string"}}},
+            ),
+            self._make_block(
+                sink_block_id,
+                input_schema={"properties": {"count": {"type": "integer"}}},
+            ),
+        ]
+
+        result = fixer.fix_data_type_mismatch(agent, blocks)
+
+        converter_nodes = [
+            n
+            for n in result["nodes"]
+            if n["block_id"] == _UNIVERSAL_TYPE_CONVERTER_BLOCK_ID
+        ]
+        assert len(converter_nodes) == 2
+        # Each original link becomes two links through its own converter
+        assert len(result["links"]) == 4
+        assert len(fixer.fixes_applied) == 2

autogpt_platform/backend/backend/copilot/tools/agent_generator/helpers.py

@@ -0,0 +1,67 @@
+"""Shared helpers for agent generation."""
+
+import re
+import uuid
+from typing import Any
+
+from .blocks import get_blocks_as_dicts
+
+__all__ = [
+    "AGENT_EXECUTOR_BLOCK_ID",
+    "AGENT_INPUT_BLOCK_ID",
+    "AGENT_OUTPUT_BLOCK_ID",
+    "AgentDict",
+    "MCP_TOOL_BLOCK_ID",
+    "UUID_REGEX",
+    "are_types_compatible",
+    "generate_uuid",
+    "get_blocks_as_dicts",
+    "get_defined_property_type",
+    "is_uuid",
+]
+
+
+# Type alias for the agent JSON structure passed through
+# the validation and fixing pipeline.
+AgentDict = dict[str, Any]
+
+# Shared base pattern (unanchored, lowercase hex); used for both full-string
+# validation (UUID_REGEX) and text extraction (core._UUID_PATTERN).
+UUID_RE_STR = r"[a-f0-9]{8}-[a-f0-9]{4}-4[a-f0-9]{3}-[a-f0-9]{4}-[a-f0-9]{12}"
+
+UUID_REGEX = re.compile(r"^" + UUID_RE_STR + r"$")
+
+AGENT_EXECUTOR_BLOCK_ID = "e189baac-8c20-45a1-94a7-55177ea42565"
+MCP_TOOL_BLOCK_ID = "a0a4b1c2-d3e4-4f56-a7b8-c9d0e1f2a3b4"
+AGENT_INPUT_BLOCK_ID = "c0a8e994-ebf1-4a9c-a4d8-89d09c86741b"
+AGENT_OUTPUT_BLOCK_ID = "363ae599-353e-4804-937e-b2ee3cef3da4"
+
+
+def is_uuid(value: str) -> bool:
+    """Check if a string is a valid UUID."""
+    return isinstance(value, str) and UUID_REGEX.match(value) is not None
+
+
+def generate_uuid() -> str:
+    """Generate a new UUID string."""
+    return str(uuid.uuid4())
+
+
+def get_defined_property_type(schema: dict[str, Any], name: str) -> str | None:
+    """Get property type from a schema, handling nested `_#_` notation."""
+    if "_#_" in name:
+        parent, child = name.split("_#_", 1)
+        parent_schema = schema.get(parent, {})
+        if "properties" in parent_schema and isinstance(
+            parent_schema["properties"], dict
+        ):
+            return parent_schema["properties"].get(child, {}).get("type")
+        return None
+    return schema.get(name, {}).get("type")
+
+
+def are_types_compatible(src: str, sink: str) -> bool:
+    """Check if two schema types are compatible."""
+    if {src, sink} <= {"integer", "number"}:
+        return True
+    return src == sink

autogpt_platform/backend/backend/copilot/tools/agent_generator/pipeline.py

@@ -0,0 +1,196 @@
+"""Shared fix → validate → preview/save pipeline for agent tools."""
+
+import json
+import logging
+from typing import Any, cast
+
+from backend.copilot.tools.models import (
+    AgentPreviewResponse,
+    AgentSavedResponse,
+    ErrorResponse,
+    ToolResponseBase,
+)
+
+from .blocks import get_blocks_as_dicts
+from .core import get_library_agents_by_ids, save_agent_to_library
+from .fixer import AgentFixer
+from .validator import AgentValidator
+
+logger = logging.getLogger(__name__)
+
+MAX_AGENT_JSON_SIZE = 1_000_000  # 1 MB
+
+
+async def fetch_library_agents(
+    user_id: str | None,
+    library_agent_ids: list[str],
+) -> list[dict[str, Any]] | None:
+    """Fetch library agents by IDs for AgentExecutorBlock validation.
+
+    Returns None if no IDs provided or user is not authenticated.
+    """
+    if not user_id or not library_agent_ids:
+        return None
+    try:
+        agents = await get_library_agents_by_ids(
+            user_id=user_id,
+            agent_ids=library_agent_ids,
+        )
+        return cast(list[dict[str, Any]], agents)
+    except Exception as e:
+        logger.warning(f"Failed to fetch library agents by IDs: {e}")
+        return None
+
+
+async def fix_validate_and_save(
+    agent_json: dict[str, Any],
+    *,
+    user_id: str | None,
+    session_id: str | None,
+    save: bool = True,
+    is_update: bool = False,
+    default_name: str = "Agent",
+    preview_message: str | None = None,
+    save_message: str | None = None,
+    library_agents: list[dict[str, Any]] | None = None,
+    folder_id: str | None = None,
+) -> ToolResponseBase:
+    """Shared pipeline: auto-fix → validate → preview or save.
+
+    Args:
+        agent_json: The agent JSON dict (must already have id/version/is_active set).
+        user_id: The authenticated user's ID.
+        session_id: The chat session ID.
+        save: Whether to save or just preview.
+        is_update: Whether this is an update to an existing agent.
+        default_name: Fallback name if agent_json has none.
+        preview_message: Custom preview message (optional).
+        save_message: Custom save success message (optional).
+        library_agents: Library agents for AgentExecutorBlock validation/fixing.
+
+    Returns:
+        An appropriate ToolResponseBase subclass.
+    """
+    # Size guard
+    json_size = len(json.dumps(agent_json))
+    if json_size > MAX_AGENT_JSON_SIZE:
+        return ErrorResponse(
+            message=(
+                f"Agent JSON is too large ({json_size:,} bytes, "
+                f"max {MAX_AGENT_JSON_SIZE:,}). Reduce the number of nodes."
+            ),
+            error="agent_json_too_large",
+            session_id=session_id,
+        )
+
+    blocks = get_blocks_as_dicts()
+
+    # Auto-fix
+    try:
+        fixer = AgentFixer()
+        agent_json = fixer.apply_all_fixes(agent_json, blocks, library_agents)
+        fixes = fixer.get_fixes_applied()
+        if fixes:
+            logger.info(f"Applied {len(fixes)} auto-fixes to agent JSON")
+    except Exception as e:
+        logger.warning(f"Auto-fix failed: {e}")
+
+    # Validate
+    try:
+        validator = AgentValidator()
+        is_valid, _ = validator.validate(agent_json, blocks, library_agents)
+        if not is_valid:
+            errors = validator.errors
+            return ErrorResponse(
+                message=(
+                    f"The agent has {len(errors)} validation error(s):\n"
+                    + "\n".join(f"- {e}" for e in errors[:5])
+                ),
+                error="validation_failed",
+                details={"errors": errors},
+                session_id=session_id,
+            )
+    except Exception as e:
+        logger.error(f"Validation failed with exception: {e}", exc_info=True)
+        return ErrorResponse(
+            message="Failed to validate the agent. Please try again.",
+            error="validation_exception",
+            details={"exception": str(e)},
+            session_id=session_id,
+        )
+
+    agent_name = agent_json.get("name", default_name)
+    agent_description = agent_json.get("description", "")
+    node_count = len(agent_json.get("nodes", []))
+    link_count = len(agent_json.get("links", []))
+
+    # Build a warning suffix when name/description is missing or generic
+    _GENERIC_NAMES = {
+        "agent",
+        "generated agent",
+        "customized agent",
+        "updated agent",
+        "new agent",
+        "my agent",
+    }
+    metadata_warnings: list[str] = []
+    if not agent_json.get("name") or agent_name.lower().strip() in _GENERIC_NAMES:
+        metadata_warnings.append("'name'")
+    if not agent_description:
+        metadata_warnings.append("'description'")
+    metadata_hint = ""
+    if metadata_warnings:
+        missing = " and ".join(metadata_warnings)
+        metadata_hint = (
+            f" Note: the agent is missing a meaningful {missing}. "
+            f"Please update the agent_json to include them."
+        )
+
+    if not save:
+        return AgentPreviewResponse(
+            message=(
+                (
+                    preview_message
+                    or f"Agent '{agent_name}' with {node_count} blocks is ready."
+                )
+                + metadata_hint
+            ),
+            agent_json=agent_json,
+            agent_name=agent_name,
+            description=agent_description,
+            node_count=node_count,
+            link_count=link_count,
+            session_id=session_id,
+        )
+
+    if not user_id:
+        return ErrorResponse(
+            message="You must be logged in to save agents.",
+            error="auth_required",
+            session_id=session_id,
+        )
+
+    try:
+        created_graph, library_agent = await save_agent_to_library(
+            agent_json, user_id, is_update=is_update, folder_id=folder_id
+        )
+        return AgentSavedResponse(
+            message=(
+                (save_message or f"Agent '{created_graph.name}' has been saved!")
+                + metadata_hint
+            ),
+            agent_id=created_graph.id,
+            agent_name=created_graph.name,
+            library_agent_id=library_agent.id,
+            library_agent_link=f"/library/agents/{library_agent.id}",
+            agent_page_link=f"/build?flowID={created_graph.id}",
+            session_id=session_id,
+        )
+    except Exception as e:
+        logger.error(f"Failed to save agent: {e}", exc_info=True)
+        return ErrorResponse(
+            message=f"Failed to save the agent: {str(e)}",
+            error="save_failed",
+            details={"exception": str(e)},
+            session_id=session_id,
+        )

autogpt_platform/backend/backend/copilot/tools/agent_generator/service.py

@@ -1,511 +0,0 @@
-"""External Agent Generator service client.
-
-This module provides a client for communicating with the external Agent Generator
-microservice. When AGENTGENERATOR_HOST is configured, the agent generation functions
-will delegate to the external service instead of using the built-in LLM-based implementation.
-"""
-
-import logging
-from typing import Any
-
-import httpx
-
-from backend.util.settings import Settings
-
-from .dummy import (
-    customize_template_dummy,
-    decompose_goal_dummy,
-    generate_agent_dummy,
-    generate_agent_patch_dummy,
-    get_blocks_dummy,
-    health_check_dummy,
-)
-
-logger = logging.getLogger(__name__)
-
-_dummy_mode_warned = False
-
-
-def _create_error_response(
-    error_message: str,
-    error_type: str = "unknown",
-    details: dict[str, Any] | None = None,
-) -> dict[str, Any]:
-    """Create a standardized error response dict.
-
-    Args:
-        error_message: Human-readable error message
-        error_type: Machine-readable error type
-        details: Optional additional error details
-
-    Returns:
-        Error dict with type="error" and error details
-    """
-    response: dict[str, Any] = {
-        "type": "error",
-        "error": error_message,
-        "error_type": error_type,
-    }
-    if details:
-        response["details"] = details
-    return response
-
-
-def _classify_http_error(e: httpx.HTTPStatusError) -> tuple[str, str]:
-    """Classify an HTTP error into error_type and message.
-
-    Args:
-        e: The HTTP status error
-
-    Returns:
-        Tuple of (error_type, error_message)
-    """
-    status = e.response.status_code
-    if status == 429:
-        return "rate_limit", f"Agent Generator rate limited: {e}"
-    elif status == 503:
-        return "service_unavailable", f"Agent Generator unavailable: {e}"
-    elif status == 504 or status == 408:
-        return "timeout", f"Agent Generator timed out: {e}"
-    else:
-        return "http_error", f"HTTP error calling Agent Generator: {e}"
-
-
-def _classify_request_error(e: httpx.RequestError) -> tuple[str, str]:
-    """Classify a request error into error_type and message.
-
-    Args:
-        e: The request error
-
-    Returns:
-        Tuple of (error_type, error_message)
-    """
-    error_str = str(e).lower()
-    if "timeout" in error_str or "timed out" in error_str:
-        return "timeout", f"Agent Generator request timed out: {e}"
-    elif "connect" in error_str:
-        return "connection_error", f"Could not connect to Agent Generator: {e}"
-    else:
-        return "request_error", f"Request error calling Agent Generator: {e}"
-
-
-_client: httpx.AsyncClient | None = None
-_settings: Settings | None = None
-
-
-def _get_settings() -> Settings:
-    """Get or create settings singleton."""
-    global _settings
-    if _settings is None:
-        _settings = Settings()
-    return _settings
-
-
-def _is_dummy_mode() -> bool:
-    """Check if dummy mode is enabled for testing."""
-    global _dummy_mode_warned
-    settings = _get_settings()
-    is_dummy = bool(settings.config.agentgenerator_use_dummy)
-    if is_dummy and not _dummy_mode_warned:
-        logger.warning(
-            "Agent Generator running in DUMMY MODE - returning mock responses. "
-            "Do not use in production!"
-        )
-        _dummy_mode_warned = True
-    return is_dummy
-
-
-def is_external_service_configured() -> bool:
-    """Check if external Agent Generator service is configured (or dummy mode)."""
-    settings = _get_settings()
-    return bool(settings.config.agentgenerator_host) or bool(
-        settings.config.agentgenerator_use_dummy
-    )
-
-
-def _get_base_url() -> str:
-    """Get the base URL for the external service."""
-    settings = _get_settings()
-    host = settings.config.agentgenerator_host
-    port = settings.config.agentgenerator_port
-    return f"http://{host}:{port}"
-
-
-def _get_client() -> httpx.AsyncClient:
-    """Get or create the HTTP client for the external service."""
-    global _client
-    if _client is None:
-        settings = _get_settings()
-        _client = httpx.AsyncClient(
-            base_url=_get_base_url(),
-            timeout=httpx.Timeout(settings.config.agentgenerator_timeout),
-        )
-    return _client
-
-
-async def decompose_goal_external(
-    description: str,
-    context: str = "",
-    library_agents: list[dict[str, Any]] | None = None,
-) -> dict[str, Any] | None:
-    """Call the external service to decompose a goal.
-
-    Args:
-        description: Natural language goal description
-        context: Additional context (e.g., answers to previous questions)
-        library_agents: User's library agents available for sub-agent composition
-
-    Returns:
-        Dict with either:
-        - {"type": "clarifying_questions", "questions": [...]}
-        - {"type": "instructions", "steps": [...]}
-        - {"type": "unachievable_goal", ...}
-        - {"type": "vague_goal", ...}
-        - {"type": "error", "error": "...", "error_type": "..."} on error
-        Or None on unexpected error
-    """
-    if _is_dummy_mode():
-        return await decompose_goal_dummy(description, context, library_agents)
-
-    client = _get_client()
-
-    if context:
-        description = f"{description}\n\nAdditional context from user:\n{context}"
-
-    payload: dict[str, Any] = {"description": description}
-    if library_agents:
-        payload["library_agents"] = library_agents
-
-    try:
-        response = await client.post("/api/decompose-description", json=payload)
-        response.raise_for_status()
-        data = response.json()
-
-        if not data.get("success"):
-            error_msg = data.get("error", "Unknown error from Agent Generator")
-            error_type = data.get("error_type", "unknown")
-            logger.error(
-                f"Agent Generator decomposition failed: {error_msg} "
-                f"(type: {error_type})"
-            )
-            return _create_error_response(error_msg, error_type)
-
-        # Map the response to the expected format
-        response_type = data.get("type")
-        if response_type == "instructions":
-            return {"type": "instructions", "steps": data.get("steps", [])}
-        elif response_type == "clarifying_questions":
-            return {
-                "type": "clarifying_questions",
-                "questions": data.get("questions", []),
-            }
-        elif response_type == "unachievable_goal":
-            return {
-                "type": "unachievable_goal",
-                "reason": data.get("reason"),
-                "suggested_goal": data.get("suggested_goal"),
-            }
-        elif response_type == "vague_goal":
-            return {
-                "type": "vague_goal",
-                "suggested_goal": data.get("suggested_goal"),
-            }
-        elif response_type == "error":
-            # Pass through error from the service
-            return _create_error_response(
-                data.get("error", "Unknown error"),
-                data.get("error_type", "unknown"),
-            )
-        else:
-            logger.error(
-                f"Unknown response type from external service: {response_type}"
-            )
-            return _create_error_response(
-                f"Unknown response type from Agent Generator: {response_type}",
-                "invalid_response",
-            )
-
-    except httpx.HTTPStatusError as e:
-        error_type, error_msg = _classify_http_error(e)
-        logger.error(error_msg)
-        return _create_error_response(error_msg, error_type)
-    except httpx.RequestError as e:
-        error_type, error_msg = _classify_request_error(e)
-        logger.error(error_msg)
-        return _create_error_response(error_msg, error_type)
-    except Exception as e:
-        error_msg = f"Unexpected error calling Agent Generator: {e}"
-        logger.error(error_msg)
-        return _create_error_response(error_msg, "unexpected_error")
-
-
-async def generate_agent_external(
-    instructions: dict[str, Any],
-    library_agents: list[dict[str, Any]] | None = None,
-) -> dict[str, Any] | None:
-    """Call the external service to generate an agent from instructions.
-
-    Args:
-        instructions: Structured instructions from decompose_goal
-        library_agents: User's library agents available for sub-agent composition
-
-    Returns:
-        Agent JSON dict or error dict {"type": "error", ...} on error
-    """
-    if _is_dummy_mode():
-        return await generate_agent_dummy(instructions, library_agents)
-
-    client = _get_client()
-
-    # Build request payload
-    payload: dict[str, Any] = {"instructions": instructions}
-    if library_agents:
-        payload["library_agents"] = library_agents
-
-    try:
-        response = await client.post("/api/generate-agent", json=payload)
-        response.raise_for_status()
-        data = response.json()
-
-        if not data.get("success"):
-            error_msg = data.get("error", "Unknown error from Agent Generator")
-            error_type = data.get("error_type", "unknown")
-            logger.error(
-                f"Agent Generator generation failed: {error_msg} (type: {error_type})"
-            )
-            return _create_error_response(error_msg, error_type)
-
-        return data.get("agent_json")
-
-    except httpx.HTTPStatusError as e:
-        error_type, error_msg = _classify_http_error(e)
-        logger.error(error_msg)
-        return _create_error_response(error_msg, error_type)
-    except httpx.RequestError as e:
-        error_type, error_msg = _classify_request_error(e)
-        logger.error(error_msg)
-        return _create_error_response(error_msg, error_type)
-    except Exception as e:
-        error_msg = f"Unexpected error calling Agent Generator: {e}"
-        logger.error(error_msg)
-        return _create_error_response(error_msg, "unexpected_error")
-
-
-async def generate_agent_patch_external(
-    update_request: str,
-    current_agent: dict[str, Any],
-    library_agents: list[dict[str, Any]] | None = None,
-) -> dict[str, Any] | None:
-    """Call the external service to generate a patch for an existing agent.
-
-    Args:
-        update_request: Natural language description of changes
-        current_agent: Current agent JSON
-        library_agents: User's library agents available for sub-agent composition
-        operation_id: Operation ID for async processing (enables Redis Streams callback)
-        session_id: Session ID for async processing (enables Redis Streams callback)
-
-    Returns:
-        Updated agent JSON, clarifying questions dict, {"status": "accepted"} for async, or error dict on error
-    """
-    if _is_dummy_mode():
-        return await generate_agent_patch_dummy(
-            update_request, current_agent, library_agents
-        )
-
-    client = _get_client()
-
-    # Build request payload
-    payload: dict[str, Any] = {
-        "update_request": update_request,
-        "current_agent_json": current_agent,
-    }
-    if library_agents:
-        payload["library_agents"] = library_agents
-
-    try:
-        response = await client.post("/api/update-agent", json=payload)
-        response.raise_for_status()
-        data = response.json()
-
-        if not data.get("success"):
-            error_msg = data.get("error", "Unknown error from Agent Generator")
-            error_type = data.get("error_type", "unknown")
-            logger.error(
-                f"Agent Generator patch generation failed: {error_msg} "
-                f"(type: {error_type})"
-            )
-            return _create_error_response(error_msg, error_type)
-
-        # Check if it's clarifying questions
-        if data.get("type") == "clarifying_questions":
-            return {
-                "type": "clarifying_questions",
-                "questions": data.get("questions", []),
-            }
-
-        # Check if it's an error passed through
-        if data.get("type") == "error":
-            return _create_error_response(
-                data.get("error", "Unknown error"),
-                data.get("error_type", "unknown"),
-            )
-
-        # Otherwise return the updated agent JSON
-        return data.get("agent_json")
-
-    except httpx.HTTPStatusError as e:
-        error_type, error_msg = _classify_http_error(e)
-        logger.error(error_msg)
-        return _create_error_response(error_msg, error_type)
-    except httpx.RequestError as e:
-        error_type, error_msg = _classify_request_error(e)
-        logger.error(error_msg)
-        return _create_error_response(error_msg, error_type)
-    except Exception as e:
-        error_msg = f"Unexpected error calling Agent Generator: {e}"
-        logger.error(error_msg)
-        return _create_error_response(error_msg, "unexpected_error")
-
-
-async def customize_template_external(
-    template_agent: dict[str, Any],
-    modification_request: str,
-    context: str = "",
-) -> dict[str, Any] | None:
-    """Call the external service to customize a template/marketplace agent.
-
-    Args:
-        template_agent: The template agent JSON to customize
-        modification_request: Natural language description of customizations
-        context: Additional context (e.g., answers to previous questions)
-        operation_id: Operation ID for async processing (enables Redis Streams callback)
-        session_id: Session ID for async processing (enables Redis Streams callback)
-
-    Returns:
-        Customized agent JSON, clarifying questions dict, or error dict on error
-    """
-    if _is_dummy_mode():
-        return await customize_template_dummy(
-            template_agent, modification_request, context
-        )
-
-    client = _get_client()
-
-    request = modification_request
-    if context:
-        request = f"{modification_request}\n\nAdditional context from user:\n{context}"
-
-    payload: dict[str, Any] = {
-        "template_agent_json": template_agent,
-        "modification_request": request,
-    }
-
-    try:
-        response = await client.post("/api/template-modification", json=payload)
-        response.raise_for_status()
-        data = response.json()
-
-        if not data.get("success"):
-            error_msg = data.get("error", "Unknown error from Agent Generator")
-            error_type = data.get("error_type", "unknown")
-            logger.error(
-                f"Agent Generator template customization failed: {error_msg} "
-                f"(type: {error_type})"
-            )
-            return _create_error_response(error_msg, error_type)
-
-        # Check if it's clarifying questions
-        if data.get("type") == "clarifying_questions":
-            return {
-                "type": "clarifying_questions",
-                "questions": data.get("questions", []),
-            }
-
-        # Check if it's an error passed through
-        if data.get("type") == "error":
-            return _create_error_response(
-                data.get("error", "Unknown error"),
-                data.get("error_type", "unknown"),
-            )
-
-        # Otherwise return the customized agent JSON
-        return data.get("agent_json")
-
-    except httpx.HTTPStatusError as e:
-        error_type, error_msg = _classify_http_error(e)
-        logger.error(error_msg)
-        return _create_error_response(error_msg, error_type)
-    except httpx.RequestError as e:
-        error_type, error_msg = _classify_request_error(e)
-        logger.error(error_msg)
-        return _create_error_response(error_msg, error_type)
-    except Exception as e:
-        error_msg = f"Unexpected error calling Agent Generator: {e}"
-        logger.error(error_msg)
-        return _create_error_response(error_msg, "unexpected_error")
-
-
-async def get_blocks_external() -> list[dict[str, Any]] | None:
-    """Get available blocks from the external service.
-
-    Returns:
-        List of block info dicts or None on error
-    """
-    if _is_dummy_mode():
-        return await get_blocks_dummy()
-
-    client = _get_client()
-
-    try:
-        response = await client.get("/api/blocks")
-        response.raise_for_status()
-        data = response.json()
-
-        if not data.get("success"):
-            logger.error("External service returned error getting blocks")
-            return None
-
-        return data.get("blocks", [])
-
-    except httpx.HTTPStatusError as e:
-        logger.error(f"HTTP error getting blocks from external service: {e}")
-        return None
-    except httpx.RequestError as e:
-        logger.error(f"Request error getting blocks from external service: {e}")
-        return None
-    except Exception as e:
-        logger.error(f"Unexpected error getting blocks from external service: {e}")
-        return None
-
-
-async def health_check() -> bool:
-    """Check if the external service is healthy.
-
-    Returns:
-        True if healthy, False otherwise
-    """
-    if not is_external_service_configured():
-        return False
-
-    if _is_dummy_mode():
-        return await health_check_dummy()
-
-    client = _get_client()
-
-    try:
-        response = await client.get("/health")
-        response.raise_for_status()
-        data = response.json()
-        return data.get("status") == "healthy" and data.get("blocks_loaded", False)
-    except Exception as e:
-        logger.warning(f"External agent generator health check failed: {e}")
-        return False
-
-
-async def close_client() -> None:
-    """Close the HTTP client."""
-    global _client
-    if _client is not None:
-        await _client.aclose()
-        _client = None

autogpt_platform/backend/backend/copilot/tools/agent_generator/validation.py

@@ -0,0 +1,17 @@
+"""Agent generation validation — re-exports from split modules.
+
+This module was split into:
+- helpers.py: get_blocks_as_dicts, block cache
+- fixer.py: AgentFixer class
+- validator.py: AgentValidator class
+"""
+
+from .fixer import AgentFixer
+from .helpers import get_blocks_as_dicts
+from .validator import AgentValidator
+
+__all__ = [
+    "AgentFixer",
+    "AgentValidator",
+    "get_blocks_as_dicts",
+]

autogpt_platform/backend/backend/copilot/tools/agent_generator/validator.py

@@ -0,0 +1,939 @@
+"""AgentValidator — validates agent JSON graphs for correctness."""
+
+import json
+import logging
+import re
+from typing import Any
+
+from .helpers import (
+    AGENT_EXECUTOR_BLOCK_ID,
+    AGENT_INPUT_BLOCK_ID,
+    AGENT_OUTPUT_BLOCK_ID,
+    MCP_TOOL_BLOCK_ID,
+    AgentDict,
+    are_types_compatible,
+    get_defined_property_type,
+)
+
+logger = logging.getLogger(__name__)
+
+
+class AgentValidator:
+    """
+    A comprehensive validator for AutoGPT agents that provides detailed error
+    reporting for LLM-based fixes.
+    """
+
+    def __init__(self):
+        self.errors: list[str] = []
+
+    def add_error(self, error_message: str) -> None:
+        """Add an error message to the validation errors list."""
+        self.errors.append(error_message)
+
+    def _values_equal(self, val1: Any, val2: Any) -> bool:
+        """Compare two values, handling complex types like dicts and lists."""
+        if type(val1) is not type(val2):
+            return False
+        if isinstance(val1, dict):
+            return json.dumps(val1, sort_keys=True) == json.dumps(val2, sort_keys=True)
+        if isinstance(val1, list):
+            return json.dumps(val1, sort_keys=True) == json.dumps(val2, sort_keys=True)
+        return val1 == val2
+
+    def validate_block_existence(
+        self, agent: AgentDict, blocks: list[dict[str, Any]]
+    ) -> bool:
+        """
+        Validate that all block IDs used in the agent actually exist in the
+        blocks list. Returns True if all block IDs exist, False otherwise.
+        """
+        valid = True
+
+        # Create a set of all valid block IDs for fast lookup
+        valid_block_ids = {block.get("id") for block in blocks if block.get("id")}
+
+        # Check each node's block_id
+        for node in agent.get("nodes", []):
+            block_id = node.get("block_id")
+            node_id = node.get("id")
+
+            if not block_id:
+                self.add_error(
+                    f"Node '{node_id}' is missing a 'block_id' field. "
+                    f"Every node must reference a valid block."
+                )
+                valid = False
+                continue
+
+            if block_id not in valid_block_ids:
+                self.add_error(
+                    f"Node '{node_id}' references block_id '{block_id}' "
+                    f"which does not exist in the available blocks. "
+                    f"This block may have been deprecated, removed, or "
+                    f"the ID is incorrect. Please use a valid block from "
+                    f"the blocks library."
+                )
+                valid = False
+
+        return valid
+
+    def validate_link_node_references(self, agent: AgentDict) -> bool:
+        """
+        Validate that all node IDs referenced in links actually exist in the
+        agent's nodes. Returns True if all link references are valid, False
+        otherwise.
+        """
+        valid = True
+
+        # Create a set of all valid node IDs for fast lookup
+        valid_node_ids = {
+            node.get("id") for node in agent.get("nodes", []) if node.get("id")
+        }
+
+        # Check each link's source_id and sink_id
+        for link in agent.get("links", []):
+            link_id = link.get("id", "Unknown")
+            source_id = link.get("source_id")
+            sink_id = link.get("sink_id")
+            source_name = link.get("source_name", "")
+            sink_name = link.get("sink_name", "")
+
+            # Check source_id
+            if not source_id:
+                self.add_error(
+                    f"Link '{link_id}' is missing a 'source_id' field. "
+                    f"Every link must reference a valid source node."
+                )
+                valid = False
+            elif source_id not in valid_node_ids:
+                self.add_error(
+                    f"Link '{link_id}' references source_id '{source_id}' "
+                    f"which does not exist in the agent's nodes. The link "
+                    f"from '{source_name}' cannot be established because "
+                    f"the source node is missing."
+                )
+                valid = False
+
+            # Check sink_id
+            if not sink_id:
+                self.add_error(
+                    f"Link '{link_id}' is missing a 'sink_id' field. "
+                    f"Every link must reference a valid sink (destination) "
+                    f"node."
+                )
+                valid = False
+            elif sink_id not in valid_node_ids:
+                self.add_error(
+                    f"Link '{link_id}' references sink_id '{sink_id}' "
+                    f"which does not exist in the agent's nodes. The link "
+                    f"to '{sink_name}' cannot be established because the "
+                    f"destination node is missing."
+                )
+                valid = False
+
+        return valid
+
+    def validate_required_inputs(
+        self, agent: AgentDict, blocks: list[dict[str, Any]]
+    ) -> bool:
+        """
+        Validate that all required inputs are provided for each node.
+        Returns True if all required inputs are satisfied, False otherwise.
+        """
+        valid = True
+
+        block_lookup = {b.get("id", ""): b for b in blocks}
+
+        for node in agent.get("nodes", []):
+            block_id = node.get("block_id")
+            block = block_lookup.get(block_id)
+
+            if not block:
+                continue
+
+            required_inputs = block.get("inputSchema", {}).get("required", [])
+            input_defaults = node.get("input_default", {})
+            node_id = node.get("id")
+
+            linked_inputs = set(
+                link.get("sink_name")
+                for link in agent.get("links", [])
+                if link.get("sink_id") == node_id and link.get("sink_name")
+            )
+
+            for req_input in required_inputs:
+                if (
+                    req_input not in input_defaults
+                    and req_input not in linked_inputs
+                    and req_input != "credentials"
+                ):
+                    block_name = block.get("name", "Unknown Block")
+                    self.add_error(
+                        f"Node '{node_id}' (block '{block_name}' - "
+                        f"{block_id}) is missing required input "
+                        f"'{req_input}'. This input must be either "
+                        f"provided as a default value in the node's "
+                        f"'input_default' field or connected via a link "
+                        f"from another node's output."
+                    )
+                    valid = False
+
+        return valid
+
+    def validate_data_type_compatibility(
+        self, agent: AgentDict, blocks: list[dict[str, Any]]
+    ) -> bool:
+        """
+        Validate that linked data types are compatible between source and sink.
+        Returns True if all data types are compatible, False otherwise.
+        """
+        valid = True
+        node_lookup = {node.get("id", ""): node for node in agent.get("nodes", [])}
+        block_lookup = {block.get("id", ""): block for block in blocks}
+
+        for link in agent.get("links", []):
+            source_id = link.get("source_id")
+            sink_id = link.get("sink_id")
+            source_name = link.get("source_name")
+            sink_name = link.get("sink_name")
+
+            if not all(
+                isinstance(v, str) and v
+                for v in (source_id, sink_id, source_name, sink_name)
+            ):
+                self.add_error(
+                    f"Link '{link.get('id', 'Unknown')}' is missing required "
+                    f"fields (source_id/sink_id/source_name/sink_name)."
+                )
+                valid = False
+                continue
+
+            source_node = node_lookup.get(source_id, "")
+            sink_node = node_lookup.get(sink_id, "")
+
+            if not source_node or not sink_node:
+                continue
+
+            source_block = block_lookup.get(source_node.get("block_id", ""))
+            sink_block = block_lookup.get(sink_node.get("block_id", ""))
+
+            if not source_block or not sink_block:
+                continue
+
+            source_outputs = source_block.get("outputSchema", {}).get("properties", {})
+            sink_inputs = sink_block.get("inputSchema", {}).get("properties", {})
+
+            source_type = get_defined_property_type(source_outputs, source_name)
+            sink_type = get_defined_property_type(sink_inputs, sink_name)
+
+            if (
+                source_type
+                and sink_type
+                and not are_types_compatible(source_type, sink_type)
+            ):
+                source_block_name = source_block.get("name", "Unknown Block")
+                sink_block_name = sink_block.get("name", "Unknown Block")
+                self.add_error(
+                    f"Data type mismatch in link '{link.get('id')}': "
+                    f"Source '{source_block_name}' output "
+                    f"'{link.get('source_name', '')}' outputs '{source_type}' "
+                    f"type, but sink '{sink_block_name}' input "
+                    f"'{link.get('sink_name', '')}' expects '{sink_type}' type. "
+                    f"These types must match for the connection to work "
+                    f"properly."
+                )
+                valid = False
+
+        return valid
+
+    def validate_nested_sink_links(
+        self, agent: AgentDict, blocks: list[dict[str, Any]]
+    ) -> bool:
+        """
+        Validate nested sink links (links with _#_ notation).
+        Returns True if all nested links are valid, False otherwise.
+        """
+        valid = True
+        block_input_schemas = {
+            block.get("id", ""): block.get("inputSchema", {}).get("properties", {})
+            for block in blocks
+        }
+        block_names = {
+            block.get("id", ""): block.get("name", "Unknown Block") for block in blocks
+        }
+        node_lookup = {node.get("id", ""): node for node in agent.get("nodes", [])}
+
+        for link in agent.get("links", []):
+            sink_name = link.get("sink_name", "")
+            sink_id = link.get("sink_id")
+
+            if not sink_name or not sink_id:
+                continue
+
+            if "_#_" in sink_name:
+                parent, child = sink_name.split("_#_", 1)
+
+                sink_node = node_lookup.get(sink_id)
+                if not sink_node:
+                    continue
+
+                block_id = sink_node.get("block_id")
+                input_props = block_input_schemas.get(block_id, {})
+
+                parent_schema = input_props.get(parent)
+                if not parent_schema:
+                    block_name = block_names.get(block_id, "Unknown Block")
+                    self.add_error(
+                        f"Invalid nested sink link '{sink_name}' for "
+                        f"node '{sink_id}' (block "
+                        f"'{block_name}' - {block_id}): Parent property "
+                        f"'{parent}' does not exist in the block's "
+                        f"input schema."
+                    )
+                    valid = False
+                    continue
+
+                # Check if additionalProperties is allowed either directly
+                # or via anyOf
+                allows_additional_properties = parent_schema.get(
+                    "additionalProperties", False
+                )
+
+                # Check anyOf for additionalProperties
+                if not allows_additional_properties and "anyOf" in parent_schema:
+                    any_of_schemas = parent_schema.get("anyOf", [])
+                    if isinstance(any_of_schemas, list):
+                        for schema_option in any_of_schemas:
+                            if isinstance(schema_option, dict) and schema_option.get(
+                                "additionalProperties"
+                            ):
+                                allows_additional_properties = True
+                                break
+
+                if not allows_additional_properties:
+                    if not (
+                        isinstance(parent_schema, dict)
+                        and "properties" in parent_schema
+                        and isinstance(parent_schema["properties"], dict)
+                        and child in parent_schema["properties"]
+                    ):
+                        block_name = block_names.get(block_id, "Unknown Block")
+                        self.add_error(
+                            f"Invalid nested sink link '{sink_name}' "
+                            f"for node '{link.get('sink_id', '')}' (block "
+                            f"'{block_name}' - {block_id}): Child "
+                            f"property '{child}' does not exist in "
+                            f"parent '{parent}' schema. Available "
+                            f"properties: "
+                            f"{list(parent_schema.get('properties', {}).keys())}"
+                        )
+                        valid = False
+
+        return valid
+
+    def validate_prompt_double_curly_braces_spaces(self, agent: AgentDict) -> bool:
+        """
+        Validate that prompt parameters do not contain spaces in double curly
+        braces.
+
+        Checks the 'prompt' parameter in input_default of each node and reports
+        errors if values within double curly braces ({{...}}) contain spaces.
+        For example, {{user name}} should be {{user_name}}.
+
+        Args:
+            agent: The agent dictionary to validate
+
+        Returns:
+            True if all prompts are valid (no spaces in double curly braces),
+            False otherwise
+        """
+        valid = True
+        nodes = agent.get("nodes", [])
+
+        for node in nodes:
+            node_id = node.get("id")
+            input_default = node.get("input_default", {})
+
+            # Check if 'prompt' parameter exists
+            if "prompt" not in input_default:
+                continue
+
+            prompt_text = input_default["prompt"]
+
+            # Only process if it's a string
+            if not isinstance(prompt_text, str):
+                continue
+
+            # Find all double curly brace patterns with spaces
+            matches = re.finditer(r"\{\{([^}]+)\}\}", prompt_text)
+
+            for match in matches:
+                content = match.group(1)
+                if " " in content:
+                    start_pos = match.start()
+                    snippet_start = max(0, start_pos - 30)
+                    snippet_end = min(len(prompt_text), match.end() + 30)
+                    snippet = prompt_text[snippet_start:snippet_end]
+
+                    self.add_error(
+                        f"Node '{node_id}' has spaces in double curly "
+                        f"braces in prompt parameter: "
+                        f"'{{{{{content}}}}}' should be "
+                        f"'{{{{{content.replace(' ', '_')}}}}}'. "
+                        f"Context: ...{snippet}..."
+                    )
+                    valid = False
+
+        return valid
+
+    def validate_source_output_existence(
+        self, agent: AgentDict, blocks: list[dict[str, Any]]
+    ) -> bool:
+        """
+        Validate that all source_names in links exist in the corresponding
+        block's output schema.
+
+        Checks that for each link, the source_name field references a valid
+        output property in the source block's outputSchema. Also handles nested
+        outputs with _#_ notation.
+
+        Args:
+            agent: The agent dictionary to validate
+            blocks: List of available blocks with their schemas
+
+        Returns:
+            True if all source output fields exist, False otherwise
+        """
+        valid = True
+
+        # Create lookup dictionaries for efficiency
+        block_output_schemas = {
+            block.get("id", ""): block.get("outputSchema", {}).get("properties", {})
+            for block in blocks
+        }
+        block_names = {
+            block.get("id", ""): block.get("name", "Unknown Block") for block in blocks
+        }
+        node_lookup = {node.get("id", ""): node for node in agent.get("nodes", [])}
+
+        for link in agent.get("links", []):
+            source_id = link.get("source_id")
+            source_name = link.get("source_name", "")
+            link_id = link.get("id", "Unknown")
+
+            if not source_name:
+                self.add_error(
+                    f"Link '{link_id}' is missing 'source_name'. "
+                    f"Every link must specify which output field to read from."
+                )
+                valid = False
+                continue
+
+            source_node = node_lookup.get(source_id)
+            if not source_node:
+                # This error is already caught by
+                # validate_link_node_references
+                continue
+
+            block_id = source_node.get("block_id")
+            block_name = block_names.get(block_id, "Unknown Block")
+
+            # Special handling for AgentExecutorBlock - use dynamic
+            # output_schema from input_default
+            if block_id == AGENT_EXECUTOR_BLOCK_ID:
+                input_default = source_node.get("input_default", {})
+                dynamic_output_schema = input_default.get("output_schema", {})
+                if not isinstance(dynamic_output_schema, dict):
+                    dynamic_output_schema = {}
+                output_props = dynamic_output_schema.get("properties", {})
+                if not isinstance(output_props, dict):
+                    output_props = {}
+            else:
+                output_props = block_output_schemas.get(block_id, {})
+
+            # Handle nested source names (with _#_ notation)
+            if "_#_" in source_name:
+                parent, child = source_name.split("_#_", 1)
+
+                parent_schema = output_props.get(parent)
+                if not parent_schema:
+                    self.add_error(
+                        f"Invalid source output field '{source_name}' "
+                        f"in link '{link_id}' from node '{source_id}' "
+                        f"(block '{block_name}' - {block_id}): Parent "
+                        f"property '{parent}' does not exist in the "
+                        f"block's output schema."
+                    )
+                    valid = False
+                    continue
+
+                # Check if additionalProperties is allowed either directly
+                # or via anyOf
+                allows_additional_properties = parent_schema.get(
+                    "additionalProperties", False
+                )
+                if not allows_additional_properties and "anyOf" in parent_schema:
+                    any_of_schemas = parent_schema.get("anyOf", [])
+                    if isinstance(any_of_schemas, list):
+                        for schema_option in any_of_schemas:
+                            if isinstance(schema_option, dict) and schema_option.get(
+                                "additionalProperties"
+                            ):
+                                allows_additional_properties = True
+                                break
+                            # Also allow when items have
+                            # additionalProperties (array of objects)
+                            if (
+                                isinstance(schema_option, dict)
+                                and "items" in schema_option
+                            ):
+                                items_schema = schema_option.get("items")
+                                if isinstance(items_schema, dict) and items_schema.get(
+                                    "additionalProperties"
+                                ):
+                                    allows_additional_properties = True
+                                    break
+
+                # Only require child in properties when
+                # additionalProperties is not allowed
+                if not allows_additional_properties:
+                    if not (
+                        isinstance(parent_schema, dict)
+                        and "properties" in parent_schema
+                        and isinstance(parent_schema["properties"], dict)
+                        and child in parent_schema["properties"]
+                    ):
+                        available_props = (
+                            list(parent_schema.get("properties", {}).keys())
+                            if isinstance(parent_schema, dict)
+                            else []
+                        )
+                        self.add_error(
+                            f"Invalid nested source output field "
+                            f"'{source_name}' in link '{link_id}' from "
+                            f"node '{source_id}' (block "
+                            f"'{block_name}' - {block_id}): Child "
+                            f"property '{child}' does not exist in "
+                            f"parent '{parent}' output schema. "
+                            f"Available properties: {available_props}"
+                        )
+                        valid = False
+            else:
+                # Check simple (non-nested) source name
+                if source_name not in output_props:
+                    available_outputs = list(output_props.keys())
+                    self.add_error(
+                        f"Invalid source output field '{source_name}' "
+                        f"in link '{link_id}' from node '{source_id}' "
+                        f"(block '{block_name}' - {block_id}): Output "
+                        f"property '{source_name}' does not exist in "
+                        f"the block's output schema. Available outputs: "
+                        f"{available_outputs}"
+                    )
+                    valid = False
+
+        return valid
+
+    def validate_io_blocks(self, agent: AgentDict) -> bool:
+        """
+        Validate that the agent has at least one AgentInputBlock and one
+        AgentOutputBlock. These blocks define the agent's interface.
+
+        Returns True if both are present, False otherwise.
+        """
+        valid = True
+        block_ids = {node.get("block_id") for node in agent.get("nodes", [])}
+
+        if AGENT_INPUT_BLOCK_ID not in block_ids:
+            self.add_error(
+                f"Agent is missing an AgentInputBlock (block_id: "
+                f"'{AGENT_INPUT_BLOCK_ID}'). Every agent must have at "
+                f"least one AgentInputBlock to define user-facing inputs. "
+                f"Add a node with block_id '{AGENT_INPUT_BLOCK_ID}' and "
+                f"set input_default with 'name' and optionally 'title'."
+            )
+            valid = False
+
+        if AGENT_OUTPUT_BLOCK_ID not in block_ids:
+            self.add_error(
+                f"Agent is missing an AgentOutputBlock (block_id: "
+                f"'{AGENT_OUTPUT_BLOCK_ID}'). Every agent must have at "
+                f"least one AgentOutputBlock to define user-facing outputs. "
+                f"Add a node with block_id '{AGENT_OUTPUT_BLOCK_ID}' and "
+                f"set input_default with 'name', then link 'value' from "
+                f"another block's output."
+            )
+            valid = False
+
+        return valid
+
+    def validate_agent_executor_blocks(
+        self,
+        agent: AgentDict,
+        library_agents: list[dict[str, Any]] | None = None,
+    ) -> bool:
+        """
+        Validate AgentExecutorBlock nodes have required fields and valid
+        references.
+
+        Checks that AgentExecutorBlock nodes:
+        1. Have a valid graph_id in input_default (required)
+        2. If graph_id matches a known library agent, validates version
+           consistency
+        3. Sub-agent required inputs are connected via links (not hardcoded)
+
+        Note: Unknown graph_ids are not treated as errors - they could be valid
+        direct references to agents by their actual ID (not via library_agents).
+        This is consistent with fix_agent_executor_blocks() behavior.
+
+        Args:
+            agent: The agent dictionary to validate
+            library_agents: List of available library agents (for version
+                            validation)
+
+        Returns:
+            True if all AgentExecutorBlock nodes are valid, False otherwise
+        """
+        valid = True
+        nodes = agent.get("nodes", [])
+        links = agent.get("links", [])
+
+        # Create lookup for library agents
+        library_agent_lookup: dict[str, dict[str, Any]] = {}
+        if library_agents:
+            library_agent_lookup = {la.get("graph_id", ""): la for la in library_agents}
+
+        for node in nodes:
+            if node.get("block_id") != AGENT_EXECUTOR_BLOCK_ID:
+                continue
+
+            node_id = node.get("id")
+            input_default = node.get("input_default", {})
+
+            # Check for required graph_id
+            graph_id = input_default.get("graph_id")
+            if not graph_id:
+                self.add_error(
+                    f"AgentExecutorBlock node '{node_id}' is missing "
+                    f"required 'graph_id' in input_default. This field "
+                    f"must reference the ID of the sub-agent to execute."
+                )
+                valid = False
+                continue
+
+            # If graph_id is not in library_agent_lookup, skip validation
+            if graph_id not in library_agent_lookup:
+                continue
+
+            # Validate version consistency for known library agents
+            library_agent = library_agent_lookup[graph_id]
+            expected_version = library_agent.get("graph_version")
+            current_version = input_default.get("graph_version")
+            if (
+                current_version
+                and expected_version
+                and current_version != expected_version
+            ):
+                self.add_error(
+                    f"AgentExecutorBlock node '{node_id}' has mismatched "
+                    f"graph_version: got {current_version}, expected "
+                    f"{expected_version} for library agent "
+                    f"'{library_agent.get('name')}'"
+                )
+                valid = False
+
+            # Validate sub-agent inputs are properly linked (not hardcoded)
+            sub_agent_input_schema = library_agent.get("input_schema", {})
+            if not isinstance(sub_agent_input_schema, dict):
+                sub_agent_input_schema = {}
+            sub_agent_required_inputs = sub_agent_input_schema.get("required", [])
+            sub_agent_properties = sub_agent_input_schema.get("properties", {})
+
+            # Get all linked inputs to this node
+            linked_sub_agent_inputs: set[str] = set()
+            for link in links:
+                if link.get("sink_id") == node_id:
+                    sink_name = link.get("sink_name", "")
+                    if sink_name in sub_agent_properties:
+                        linked_sub_agent_inputs.add(sink_name)
+
+            # Check for hardcoded inputs that should be linked
+            hardcoded_inputs = input_default.get("inputs", {})
+            input_schema = input_default.get("input_schema", {})
+            schema_properties = (
+                input_schema.get("properties", {})
+                if isinstance(input_schema, dict)
+                else {}
+            )
+            if isinstance(hardcoded_inputs, dict) and hardcoded_inputs:
+                for input_name, value in hardcoded_inputs.items():
+                    if input_name not in sub_agent_properties:
+                        continue
+                    if value is None:
+                        continue
+                    # Skip if this input is already linked
+                    if input_name in linked_sub_agent_inputs:
+                        continue
+                    prop_schema = schema_properties.get(input_name, {})
+                    schema_default = (
+                        prop_schema.get("default")
+                        if isinstance(prop_schema, dict)
+                        else None
+                    )
+                    if schema_default is not None and self._values_equal(
+                        value, schema_default
+                    ):
+                        continue
+                    # This is a non-default hardcoded value without a link
+                    self.add_error(
+                        f"AgentExecutorBlock node '{node_id}' has "
+                        f"hardcoded input '{input_name}'. Sub-agent "
+                        f"inputs should be connected via links using "
+                        f"'{input_name}' as sink_name, not hardcoded "
+                        f"in input_default.inputs. Create a link from "
+                        f"the appropriate source node."
+                    )
+                    valid = False
+
+            # Check for missing required sub-agent inputs.
+            # An input is satisfied if it is linked OR has an allowed
+            # hardcoded value (i.e. equals the schema default — the
+            # previous check already flags non-default hardcoded values).
+            hardcoded_inputs_dict = (
+                hardcoded_inputs if isinstance(hardcoded_inputs, dict) else {}
+            )
+            for req_input in sub_agent_required_inputs:
+                if req_input in linked_sub_agent_inputs:
+                    continue
+                # Check if fixer populated it with a schema default value
+                if req_input in hardcoded_inputs_dict:
+                    prop_schema = schema_properties.get(req_input, {})
+                    schema_default = (
+                        prop_schema.get("default")
+                        if isinstance(prop_schema, dict)
+                        else None
+                    )
+                    if schema_default is not None and self._values_equal(
+                        hardcoded_inputs_dict[req_input], schema_default
+                    ):
+                        continue
+                self.add_error(
+                    f"AgentExecutorBlock node '{node_id}' is "
+                    f"missing required sub-agent input "
+                    f"'{req_input}'. Create a link to this node "
+                    f"using sink_name '{req_input}' to connect "
+                    f"the input."
+                )
+                valid = False
+
+        return valid
+
+    def validate_agent_executor_block_schemas(
+        self,
+        agent: AgentDict,
+    ) -> bool:
+        """
+        Validate that AgentExecutorBlock nodes have valid input_schema and
+        output_schema.
+
+        This validation runs regardless of library_agents availability and
+        ensures that the schemas are properly populated to prevent frontend
+        crashes.
+
+        Args:
+            agent: The agent dictionary to validate
+
+        Returns:
+            True if all AgentExecutorBlock nodes have valid schemas, False
+            otherwise
+        """
+        valid = True
+        nodes = agent.get("nodes", [])
+
+        for node in nodes:
+            if node.get("block_id") != AGENT_EXECUTOR_BLOCK_ID:
+                continue
+
+            node_id = node.get("id")
+            input_default = node.get("input_default", {})
+            customized_name = (node.get("metadata") or {}).get(
+                "customized_name", "Unknown"
+            )
+
+            # Check input_schema
+            input_schema = input_default.get("input_schema")
+            if input_schema is None or not isinstance(input_schema, dict):
+                self.add_error(
+                    f"AgentExecutorBlock node '{node_id}' "
+                    f"({customized_name}) has missing or invalid "
+                    f"input_schema. The input_schema must be a valid "
+                    f"JSON Schema object with 'properties' and "
+                    f"'required' fields."
+                )
+                valid = False
+            elif not input_schema.get("properties") and not input_schema.get("type"):
+                # Empty schema like {} is invalid
+                self.add_error(
+                    f"AgentExecutorBlock node '{node_id}' "
+                    f"({customized_name}) has empty input_schema. The "
+                    f"input_schema must define the sub-agent's expected "
+                    f"inputs. This usually indicates the sub-agent "
+                    f"reference is incomplete or the library agent was "
+                    f"not properly passed."
+                )
+                valid = False
+
+            # Check output_schema
+            output_schema = input_default.get("output_schema")
+            if output_schema is None or not isinstance(output_schema, dict):
+                self.add_error(
+                    f"AgentExecutorBlock node '{node_id}' "
+                    f"({customized_name}) has missing or invalid "
+                    f"output_schema. The output_schema must be a valid "
+                    f"JSON Schema object defining the sub-agent's "
+                    f"outputs."
+                )
+                valid = False
+            elif not output_schema.get("properties") and not output_schema.get("type"):
+                # Empty schema like {} is invalid
+                self.add_error(
+                    f"AgentExecutorBlock node '{node_id}' "
+                    f"({customized_name}) has empty output_schema. "
+                    f"The output_schema must define the sub-agent's "
+                    f"expected outputs. This usually indicates the "
+                    f"sub-agent reference is incomplete or the library "
+                    f"agent was not properly passed."
+                )
+                valid = False
+
+        return valid
+
+    def validate_mcp_tool_blocks(self, agent: AgentDict) -> bool:
+        """Validate that MCPToolBlock nodes have required fields.
+
+        Checks that each MCPToolBlock node has:
+        1. A non-empty `server_url` in input_default
+        2. A non-empty `selected_tool` in input_default
+
+        Returns True if all MCPToolBlock nodes are valid, False otherwise.
+        """
+        valid = True
+        nodes = agent.get("nodes", [])
+
+        for node in nodes:
+            if node.get("block_id") != MCP_TOOL_BLOCK_ID:
+                continue
+
+            node_id = node.get("id", "unknown")
+            input_default = node.get("input_default", {})
+            customized_name = (node.get("metadata") or {}).get(
+                "customized_name", node_id
+            )
+
+            server_url = input_default.get("server_url")
+            if not server_url:
+                self.add_error(
+                    f"MCPToolBlock node '{customized_name}' ({node_id}) is "
+                    f"missing required 'server_url' in input_default. "
+                    f"Set this to the MCP server URL "
+                    f"(e.g. 'https://mcp.example.com/sse')."
+                )
+                valid = False
+
+            selected_tool = input_default.get("selected_tool")
+            if not selected_tool:
+                self.add_error(
+                    f"MCPToolBlock node '{customized_name}' ({node_id}) is "
+                    f"missing required 'selected_tool' in input_default. "
+                    f"Set this to the name of the MCP tool to execute."
+                )
+                valid = False
+
+        return valid
+
+    def validate(
+        self,
+        agent: AgentDict,
+        blocks: list[dict[str, Any]],
+        library_agents: list[dict[str, Any]] | None = None,
+    ) -> tuple[bool, str | None]:
+        """
+        Comprehensive validation of an agent against available blocks.
+
+        Returns:
+            Tuple[bool, Optional[str]]: (is_valid, error_message)
+            - is_valid: True if agent passes all validations, False otherwise
+            - error_message: Detailed error message if validation fails, None
+              if successful
+        """
+        logger.info("Validating agent...")
+        self.errors = []
+
+        checks = [
+            (
+                "Block existence",
+                self.validate_block_existence(agent, blocks),
+            ),
+            (
+                "Link node references",
+                self.validate_link_node_references(agent),
+            ),
+            (
+                "Required inputs",
+                self.validate_required_inputs(agent, blocks),
+            ),
+            (
+                "Data type compatibility",
+                self.validate_data_type_compatibility(agent, blocks),
+            ),
+            (
+                "Nested sink links",
+                self.validate_nested_sink_links(agent, blocks),
+            ),
+            (
+                "Source output existence",
+                self.validate_source_output_existence(agent, blocks),
+            ),
+            (
+                "Prompt double curly braces spaces",
+                self.validate_prompt_double_curly_braces_spaces(agent),
+            ),
+            (
+                "IO blocks",
+                self.validate_io_blocks(agent),
+            ),
+            # Always validate AgentExecutorBlock schemas to prevent
+            # frontend crashes
+            (
+                "AgentExecutorBlock schemas",
+                self.validate_agent_executor_block_schemas(agent),
+            ),
+            (
+                "MCP tool blocks",
+                self.validate_mcp_tool_blocks(agent),
+            ),
+        ]
+
+        # Add AgentExecutorBlock detailed validation if library_agents
+        # provided
+        if library_agents:
+            checks.append(
+                (
+                    "AgentExecutorBlock references",
+                    self.validate_agent_executor_blocks(agent, library_agents),
+                )
+            )
+
+        all_passed = all(check[1] for check in checks)
+
+        if all_passed:
+            logger.info("Agent validation successful.")
+            return True, None
+        else:
+            error_message = "Agent validation failed with the following errors:\n\n"
+            for i, error in enumerate(self.errors, 1):
+                error_message += f"{i}. {error}\n"
+
+            logger.error(f"Agent validation failed: {error_message}")
+            return False, error_message

autogpt_platform/backend/backend/copilot/tools/agent_generator/validator_test.py

@@ -0,0 +1,710 @@
+"""Unit tests for AgentValidator."""
+
+from .helpers import (
+    AGENT_EXECUTOR_BLOCK_ID,
+    AGENT_INPUT_BLOCK_ID,
+    AGENT_OUTPUT_BLOCK_ID,
+    MCP_TOOL_BLOCK_ID,
+    generate_uuid,
+)
+from .validator import AgentValidator
+
+
+def _make_agent(
+    nodes: list | None = None,
+    links: list | None = None,
+    agent_id: str | None = None,
+) -> dict:
+    """Build a minimal agent dict for testing."""
+    return {
+        "id": agent_id or generate_uuid(),
+        "name": "Test Agent",
+        "nodes": nodes or [],
+        "links": links or [],
+    }
+
+
+def _make_node(
+    node_id: str | None = None,
+    block_id: str = "block-1",
+    input_default: dict | None = None,
+    position: tuple[int, int] = (0, 0),
+) -> dict:
+    return {
+        "id": node_id or generate_uuid(),
+        "block_id": block_id,
+        "input_default": input_default or {},
+        "metadata": {"position": {"x": position[0], "y": position[1]}},
+    }
+
+
+def _make_link(
+    link_id: str | None = None,
+    source_id: str = "",
+    source_name: str = "output",
+    sink_id: str = "",
+    sink_name: str = "input",
+) -> dict:
+    return {
+        "id": link_id or generate_uuid(),
+        "source_id": source_id,
+        "source_name": source_name,
+        "sink_id": sink_id,
+        "sink_name": sink_name,
+    }
+
+
+def _make_block(
+    block_id: str = "block-1",
+    name: str = "TestBlock",
+    input_schema: dict | None = None,
+    output_schema: dict | None = None,
+    categories: list | None = None,
+    static_output: bool = False,
+) -> dict:
+    return {
+        "id": block_id,
+        "name": name,
+        "inputSchema": input_schema or {"properties": {}, "required": []},
+        "outputSchema": output_schema or {"properties": {}},
+        "categories": categories or [],
+        "staticOutput": static_output,
+    }
+
+
+# ============================================================================
+# validate_block_existence
+# ============================================================================
+
+
+class TestValidateBlockExistence:
+    def test_valid_blocks_pass(self):
+        v = AgentValidator()
+        node = _make_node(block_id="b1")
+        block = _make_block(block_id="b1")
+        agent = _make_agent(nodes=[node])
+
+        assert v.validate_block_existence(agent, [block]) is True
+        assert v.errors == []
+
+    def test_missing_block_fails(self):
+        v = AgentValidator()
+        node = _make_node(block_id="nonexistent")
+        agent = _make_agent(nodes=[node])
+
+        assert v.validate_block_existence(agent, []) is False
+        assert len(v.errors) == 1
+        assert "does not exist" in v.errors[0]
+
+    def test_missing_block_id_field(self):
+        v = AgentValidator()
+        node = {"id": "n1", "input_default": {}, "metadata": {}}
+        agent = _make_agent(nodes=[node])
+
+        assert v.validate_block_existence(agent, []) is False
+        assert "missing a 'block_id'" in v.errors[0]
+
+
+# ============================================================================
+# validate_link_node_references
+# ============================================================================
+
+
+class TestValidateLinkNodeReferences:
+    def test_valid_references_pass(self):
+        v = AgentValidator()
+        n1 = _make_node(node_id="n1")
+        n2 = _make_node(node_id="n2")
+        link = _make_link(source_id="n1", sink_id="n2")
+        agent = _make_agent(nodes=[n1, n2], links=[link])
+
+        assert v.validate_link_node_references(agent) is True
+        assert v.errors == []
+
+    def test_invalid_source_fails(self):
+        v = AgentValidator()
+        n1 = _make_node(node_id="n1")
+        link = _make_link(source_id="missing", sink_id="n1")
+        agent = _make_agent(nodes=[n1], links=[link])
+
+        assert v.validate_link_node_references(agent) is False
+        assert any("source_id" in e for e in v.errors)
+
+    def test_invalid_sink_fails(self):
+        v = AgentValidator()
+        n1 = _make_node(node_id="n1")
+        link = _make_link(source_id="n1", sink_id="missing")
+        agent = _make_agent(nodes=[n1], links=[link])
+
+        assert v.validate_link_node_references(agent) is False
+        assert any("sink_id" in e for e in v.errors)
+
+
+# ============================================================================
+# validate_required_inputs
+# ============================================================================
+
+
+class TestValidateRequiredInputs:
+    def test_satisfied_by_default_passes(self):
+        v = AgentValidator()
+        block = _make_block(
+            block_id="b1",
+            input_schema={
+                "properties": {"url": {"type": "string"}},
+                "required": ["url"],
+            },
+        )
+        node = _make_node(block_id="b1", input_default={"url": "http://example.com"})
+        agent = _make_agent(nodes=[node])
+
+        assert v.validate_required_inputs(agent, [block]) is True
+        assert v.errors == []
+
+    def test_satisfied_by_link_passes(self):
+        v = AgentValidator()
+        block = _make_block(
+            block_id="b1",
+            input_schema={
+                "properties": {"url": {"type": "string"}},
+                "required": ["url"],
+            },
+        )
+        node = _make_node(node_id="n1", block_id="b1")
+        link = _make_link(source_id="n2", sink_id="n1", sink_name="url")
+        agent = _make_agent(nodes=[node], links=[link])
+
+        assert v.validate_required_inputs(agent, [block]) is True
+
+    def test_missing_required_input_fails(self):
+        v = AgentValidator()
+        block = _make_block(
+            block_id="b1",
+            input_schema={
+                "properties": {"url": {"type": "string"}},
+                "required": ["url"],
+            },
+        )
+        node = _make_node(block_id="b1", input_default={})
+        agent = _make_agent(nodes=[node])
+
+        assert v.validate_required_inputs(agent, [block]) is False
+        assert any("missing required input" in e for e in v.errors)
+
+    def test_credentials_always_allowed_missing(self):
+        v = AgentValidator()
+        block = _make_block(
+            block_id="b1",
+            input_schema={
+                "properties": {"credentials": {"type": "object"}},
+                "required": ["credentials"],
+            },
+        )
+        node = _make_node(block_id="b1", input_default={})
+        agent = _make_agent(nodes=[node])
+
+        assert v.validate_required_inputs(agent, [block]) is True
+
+
+# ============================================================================
+# validate_data_type_compatibility
+# ============================================================================
+
+
+class TestValidateDataTypeCompatibility:
+    def test_matching_types_pass(self):
+        v = AgentValidator()
+        src_block = _make_block(
+            block_id="src-b",
+            output_schema={"properties": {"out": {"type": "string"}}},
+        )
+        sink_block = _make_block(
+            block_id="sink-b",
+            input_schema={"properties": {"inp": {"type": "string"}}, "required": []},
+        )
+        src_node = _make_node(node_id="n1", block_id="src-b")
+        sink_node = _make_node(node_id="n2", block_id="sink-b")
+        link = _make_link(
+            source_id="n1", source_name="out", sink_id="n2", sink_name="inp"
+        )
+        agent = _make_agent(nodes=[src_node, sink_node], links=[link])
+
+        assert (
+            v.validate_data_type_compatibility(agent, [src_block, sink_block]) is True
+        )
+
+    def test_int_number_compatible(self):
+        v = AgentValidator()
+        src_block = _make_block(
+            block_id="src-b",
+            output_schema={"properties": {"out": {"type": "integer"}}},
+        )
+        sink_block = _make_block(
+            block_id="sink-b",
+            input_schema={"properties": {"inp": {"type": "number"}}, "required": []},
+        )
+        src_node = _make_node(node_id="n1", block_id="src-b")
+        sink_node = _make_node(node_id="n2", block_id="sink-b")
+        link = _make_link(
+            source_id="n1", source_name="out", sink_id="n2", sink_name="inp"
+        )
+        agent = _make_agent(nodes=[src_node, sink_node], links=[link])
+
+        assert (
+            v.validate_data_type_compatibility(agent, [src_block, sink_block]) is True
+        )
+
+    def test_mismatched_types_fail(self):
+        v = AgentValidator()
+        src_block = _make_block(
+            block_id="src-b",
+            output_schema={"properties": {"out": {"type": "string"}}},
+        )
+        sink_block = _make_block(
+            block_id="sink-b",
+            input_schema={"properties": {"inp": {"type": "integer"}}, "required": []},
+        )
+        src_node = _make_node(node_id="n1", block_id="src-b")
+        sink_node = _make_node(node_id="n2", block_id="sink-b")
+        link = _make_link(
+            source_id="n1", source_name="out", sink_id="n2", sink_name="inp"
+        )
+        agent = _make_agent(nodes=[src_node, sink_node], links=[link])
+
+        assert (
+            v.validate_data_type_compatibility(agent, [src_block, sink_block]) is False
+        )
+        assert any("mismatch" in e.lower() for e in v.errors)
+
+
+# ============================================================================
+# validate_source_output_existence
+# ============================================================================
+
+
+class TestValidateSourceOutputExistence:
+    def test_valid_source_output_passes(self):
+        v = AgentValidator()
+        block = _make_block(
+            block_id="b1",
+            output_schema={"properties": {"result": {"type": "string"}}},
+        )
+        node = _make_node(node_id="n1", block_id="b1")
+        link = _make_link(source_id="n1", source_name="result", sink_id="n2")
+        agent = _make_agent(nodes=[node], links=[link])
+
+        assert v.validate_source_output_existence(agent, [block]) is True
+
+    def test_invalid_source_output_fails(self):
+        v = AgentValidator()
+        block = _make_block(
+            block_id="b1",
+            output_schema={"properties": {"result": {"type": "string"}}},
+        )
+        node = _make_node(node_id="n1", block_id="b1")
+        link = _make_link(source_id="n1", source_name="nonexistent", sink_id="n2")
+        agent = _make_agent(nodes=[node], links=[link])
+
+        assert v.validate_source_output_existence(agent, [block]) is False
+        assert any("does not exist" in e for e in v.errors)
+
+
+# ============================================================================
+# validate_prompt_double_curly_braces_spaces
+# ============================================================================
+
+
+class TestValidatePromptDoubleCurlyBracesSpaces:
+    def test_no_spaces_passes(self):
+        v = AgentValidator()
+        node = _make_node(input_default={"prompt": "Hello {{name}}!"})
+        agent = _make_agent(nodes=[node])
+
+        assert v.validate_prompt_double_curly_braces_spaces(agent) is True
+
+    def test_spaces_in_braces_fails(self):
+        v = AgentValidator()
+        node = _make_node(input_default={"prompt": "Hello {{user name}}!"})
+        agent = _make_agent(nodes=[node])
+
+        assert v.validate_prompt_double_curly_braces_spaces(agent) is False
+        assert any("spaces" in e for e in v.errors)
+
+
+# ============================================================================
+# validate_nested_sink_links
+# ============================================================================
+
+
+class TestValidateNestedSinkLinks:
+    def test_valid_nested_link_passes(self):
+        v = AgentValidator()
+        block = _make_block(
+            block_id="b1",
+            input_schema={
+                "properties": {
+                    "config": {
+                        "type": "object",
+                        "properties": {"key": {"type": "string"}},
+                    }
+                },
+                "required": [],
+            },
+        )
+        node = _make_node(node_id="n1", block_id="b1")
+        link = _make_link(sink_id="n1", sink_name="config_#_key", source_id="n2")
+        agent = _make_agent(nodes=[node], links=[link])
+
+        assert v.validate_nested_sink_links(agent, [block]) is True
+
+    def test_invalid_parent_fails(self):
+        v = AgentValidator()
+        block = _make_block(block_id="b1")
+        node = _make_node(node_id="n1", block_id="b1")
+        link = _make_link(sink_id="n1", sink_name="nonexistent_#_key", source_id="n2")
+        agent = _make_agent(nodes=[node], links=[link])
+
+        assert v.validate_nested_sink_links(agent, [block]) is False
+        assert any("does not exist" in e for e in v.errors)
+
+
+# ============================================================================
+# validate_agent_executor_block_schemas
+# ============================================================================
+
+
+class TestValidateAgentExecutorBlockSchemas:
+    def test_valid_schemas_pass(self):
+        v = AgentValidator()
+        node = _make_node(
+            block_id=AGENT_EXECUTOR_BLOCK_ID,
+            input_default={
+                "graph_id": generate_uuid(),
+                "input_schema": {"properties": {"q": {"type": "string"}}},
+                "output_schema": {"properties": {"result": {"type": "string"}}},
+            },
+        )
+        agent = _make_agent(nodes=[node])
+
+        assert v.validate_agent_executor_block_schemas(agent) is True
+        assert v.errors == []
+
+    def test_empty_input_schema_fails(self):
+        v = AgentValidator()
+        node = _make_node(
+            block_id=AGENT_EXECUTOR_BLOCK_ID,
+            input_default={
+                "graph_id": generate_uuid(),
+                "input_schema": {},
+                "output_schema": {"properties": {"result": {"type": "string"}}},
+            },
+        )
+        agent = _make_agent(nodes=[node])
+
+        assert v.validate_agent_executor_block_schemas(agent) is False
+        assert any("empty input_schema" in e for e in v.errors)
+
+    def test_missing_output_schema_fails(self):
+        v = AgentValidator()
+        node = _make_node(
+            block_id=AGENT_EXECUTOR_BLOCK_ID,
+            input_default={
+                "graph_id": generate_uuid(),
+                "input_schema": {"properties": {"q": {"type": "string"}}},
+            },
+        )
+        agent = _make_agent(nodes=[node])
+
+        assert v.validate_agent_executor_block_schemas(agent) is False
+        assert any("output_schema" in e for e in v.errors)
+
+
+# ============================================================================
+# validate_agent_executor_blocks
+# ============================================================================
+
+
+class TestValidateAgentExecutorBlocks:
+    def test_missing_graph_id_fails(self):
+        v = AgentValidator()
+        node = _make_node(
+            block_id=AGENT_EXECUTOR_BLOCK_ID,
+            input_default={},
+        )
+        agent = _make_agent(nodes=[node])
+
+        assert v.validate_agent_executor_blocks(agent) is False
+        assert any("graph_id" in e for e in v.errors)
+
+    def test_valid_graph_id_passes(self):
+        v = AgentValidator()
+        node = _make_node(
+            block_id=AGENT_EXECUTOR_BLOCK_ID,
+            input_default={"graph_id": generate_uuid()},
+        )
+        agent = _make_agent(nodes=[node])
+
+        assert v.validate_agent_executor_blocks(agent) is True
+
+    def test_version_mismatch_with_library_agent(self):
+        v = AgentValidator()
+        lib_id = generate_uuid()
+        node = _make_node(
+            node_id="n1",
+            block_id=AGENT_EXECUTOR_BLOCK_ID,
+            input_default={"graph_id": lib_id, "graph_version": 1},
+        )
+        agent = _make_agent(nodes=[node])
+
+        library_agents = [{"graph_id": lib_id, "graph_version": 3, "name": "Sub Agent"}]
+
+        assert v.validate_agent_executor_blocks(agent, library_agents) is False
+        assert any("mismatched graph_version" in e for e in v.errors)
+
+    def test_required_input_satisfied_by_schema_default_passes(self):
+        """Required sub-agent inputs filled with their schema default by the fixer
+        should NOT be flagged as missing."""
+        v = AgentValidator()
+        lib_id = generate_uuid()
+        node = _make_node(
+            node_id="n1",
+            block_id=AGENT_EXECUTOR_BLOCK_ID,
+            input_default={
+                "graph_id": lib_id,
+                "input_schema": {
+                    "properties": {"mode": {"type": "string", "default": "fast"}}
+                },
+                "inputs": {"mode": "fast"},  # fixer populated with schema default
+            },
+        )
+        agent = _make_agent(nodes=[node])
+        library_agents = [
+            {
+                "graph_id": lib_id,
+                "graph_version": 1,
+                "name": "Sub",
+                "input_schema": {
+                    "required": ["mode"],
+                    "properties": {"mode": {"type": "string", "default": "fast"}},
+                },
+                "output_schema": {},
+            }
+        ]
+
+        assert v.validate_agent_executor_blocks(agent, library_agents) is True
+        assert v.errors == []
+
+    def test_required_input_not_linked_and_no_default_fails(self):
+        """Required sub-agent inputs without a link or schema default must fail."""
+        v = AgentValidator()
+        lib_id = generate_uuid()
+        node = _make_node(
+            node_id="n1",
+            block_id=AGENT_EXECUTOR_BLOCK_ID,
+            input_default={
+                "graph_id": lib_id,
+                "input_schema": {"properties": {"query": {"type": "string"}}},
+                "inputs": {},
+            },
+        )
+        agent = _make_agent(nodes=[node])
+        library_agents = [
+            {
+                "graph_id": lib_id,
+                "graph_version": 1,
+                "name": "Sub",
+                "input_schema": {
+                    "required": ["query"],
+                    "properties": {"query": {"type": "string"}},
+                },
+                "output_schema": {},
+            }
+        ]
+
+        assert v.validate_agent_executor_blocks(agent, library_agents) is False
+        assert any("missing required sub-agent input" in e for e in v.errors)
+
+
+# ============================================================================
+# validate_io_blocks
+# ============================================================================
+
+
+class TestValidateIoBlocks:
+    def test_missing_input_block_reports_error(self):
+        v = AgentValidator()
+        # Agent has output block but no input block
+        node = _make_node(block_id=AGENT_OUTPUT_BLOCK_ID)
+        agent = _make_agent(nodes=[node])
+
+        assert v.validate_io_blocks(agent) is False
+        assert len(v.errors) == 1
+        assert "AgentInputBlock" in v.errors[0]
+
+    def test_missing_output_block_reports_error(self):
+        v = AgentValidator()
+        # Agent has input block but no output block
+        node = _make_node(block_id=AGENT_INPUT_BLOCK_ID)
+        agent = _make_agent(nodes=[node])
+
+        assert v.validate_io_blocks(agent) is False
+        assert len(v.errors) == 1
+        assert "AgentOutputBlock" in v.errors[0]
+
+    def test_missing_both_io_blocks_reports_two_errors(self):
+        v = AgentValidator()
+        node = _make_node(block_id="some-other-block")
+        agent = _make_agent(nodes=[node])
+
+        assert v.validate_io_blocks(agent) is False
+        assert len(v.errors) == 2
+
+    def test_both_io_blocks_present_no_error(self):
+        v = AgentValidator()
+        input_node = _make_node(block_id=AGENT_INPUT_BLOCK_ID)
+        output_node = _make_node(block_id=AGENT_OUTPUT_BLOCK_ID)
+        agent = _make_agent(nodes=[input_node, output_node])
+
+        assert v.validate_io_blocks(agent) is True
+        assert v.errors == []
+
+    def test_empty_agent_reports_both_missing(self):
+        v = AgentValidator()
+        agent = _make_agent(nodes=[])
+
+        assert v.validate_io_blocks(agent) is False
+        assert len(v.errors) == 2
+
+
+# ============================================================================
+# validate (integration)
+# ============================================================================
+
+
+class TestValidate:
+    def test_valid_agent_passes(self):
+        v = AgentValidator()
+        block = _make_block(
+            block_id="b1",
+            input_schema={
+                "properties": {"url": {"type": "string"}},
+                "required": ["url"],
+            },
+            output_schema={"properties": {"result": {"type": "string"}}},
+        )
+        input_block = _make_block(
+            block_id=AGENT_INPUT_BLOCK_ID,
+            name="AgentInputBlock",
+            output_schema={"properties": {"result": {}}},
+        )
+        output_block = _make_block(
+            block_id=AGENT_OUTPUT_BLOCK_ID,
+            name="AgentOutputBlock",
+        )
+        input_node = _make_node(
+            node_id="n-in",
+            block_id=AGENT_INPUT_BLOCK_ID,
+            input_default={"name": "url"},
+        )
+        n1 = _make_node(
+            node_id="n1", block_id="b1", input_default={"url": "http://example.com"}
+        )
+        n2 = _make_node(
+            node_id="n2", block_id="b1", input_default={"url": "http://example2.com"}
+        )
+        output_node = _make_node(
+            node_id="n-out",
+            block_id=AGENT_OUTPUT_BLOCK_ID,
+            input_default={"name": "result"},
+        )
+        link = _make_link(
+            source_id="n1", source_name="result", sink_id="n2", sink_name="url"
+        )
+        agent = _make_agent(nodes=[input_node, n1, n2, output_node], links=[link])
+
+        is_valid, error_message = v.validate(agent, [block, input_block, output_block])
+
+        assert is_valid is True
+        assert error_message is None
+
+    def test_invalid_agent_returns_errors(self):
+        v = AgentValidator()
+        node = _make_node(block_id="nonexistent")
+        agent = _make_agent(nodes=[node])
+
+        is_valid, error_message = v.validate(agent, [])
+
+        assert is_valid is False
+        assert error_message is not None
+        assert "does not exist" in error_message
+
+    def test_empty_agent_fails_io_validation(self):
+        v = AgentValidator()
+        agent = _make_agent()
+
+        is_valid, error_message = v.validate(agent, [])
+
+        assert is_valid is False
+        assert error_message is not None
+        assert "AgentInputBlock" in error_message
+        assert "AgentOutputBlock" in error_message
+
+
+class TestValidateMCPToolBlocks:
+    """Tests for validate_mcp_tool_blocks."""
+
+    def test_missing_server_url_reports_error(self):
+        v = AgentValidator()
+        node = _make_node(
+            block_id=MCP_TOOL_BLOCK_ID,
+            input_default={"selected_tool": "my_tool"},
+        )
+        agent = _make_agent(nodes=[node])
+
+        result = v.validate_mcp_tool_blocks(agent)
+
+        assert result is False
+        assert any("server_url" in e for e in v.errors)
+
+    def test_missing_selected_tool_reports_error(self):
+        v = AgentValidator()
+        node = _make_node(
+            block_id=MCP_TOOL_BLOCK_ID,
+            input_default={"server_url": "https://mcp.example.com/sse"},
+        )
+        agent = _make_agent(nodes=[node])
+
+        result = v.validate_mcp_tool_blocks(agent)
+
+        assert result is False
+        assert any("selected_tool" in e for e in v.errors)
+
+    def test_valid_mcp_block_passes(self):
+        v = AgentValidator()
+        node = _make_node(
+            block_id=MCP_TOOL_BLOCK_ID,
+            input_default={
+                "server_url": "https://mcp.example.com/sse",
+                "selected_tool": "search",
+                "tool_input_schema": {"properties": {"query": {"type": "string"}}},
+                "tool_arguments": {},
+            },
+        )
+        agent = _make_agent(nodes=[node])
+
+        result = v.validate_mcp_tool_blocks(agent)
+
+        assert result is True
+        assert len(v.errors) == 0
+
+    def test_both_missing_reports_two_errors(self):
+        v = AgentValidator()
+        node = _make_node(
+            block_id=MCP_TOOL_BLOCK_ID,
+            input_default={},
+        )
+        agent = _make_agent(nodes=[node])
+
+        v.validate_mcp_tool_blocks(agent)
+
+        assert len(v.errors) == 2

autogpt_platform/backend/backend/copilot/tools/agent_search.py

@@ -208,6 +208,9 @@ def _library_agent_to_info(agent: LibraryAgent) -> AgentInfo:
         has_external_trigger=agent.has_external_trigger,
         new_output=agent.new_output,
         graph_id=agent.graph_id,
+        graph_version=agent.graph_version,
+        input_schema=agent.input_schema,
+        output_schema=agent.output_schema,
     )
 
 

autogpt_platform/backend/backend/copilot/tools/bash_exec.py

@@ -21,10 +21,10 @@ from typing import Any
 from e2b import AsyncSandbox
 from e2b.exceptions import TimeoutException
 
+from backend.copilot.context import E2B_WORKDIR, get_current_sandbox
 from backend.copilot.model import ChatSession
 
 from .base import BaseTool
-from .e2b_sandbox import E2B_WORKDIR
 from .models import BashExecResponse, ErrorResponse, ToolResponseBase
 from .sandbox import get_workspace_dir, has_full_sandbox, run_sandboxed
 
@@ -94,9 +94,6 @@ class BashExecTool(BaseTool):
                 session_id=session_id,
             )
 
-        # E2B path: run on remote cloud sandbox when available.
-        from backend.copilot.sdk.tool_adapter import get_current_sandbox
-
         sandbox = get_current_sandbox()
         if sandbox is not None:
             return await self._execute_on_e2b(sandbox, command, timeout, session_id)

autogpt_platform/backend/backend/copilot/tools/create_agent.py

@@ -1,34 +1,20 @@
-"""CreateAgentTool - Creates agents from natural language descriptions."""
+"""CreateAgentTool - Creates agents from pre-built JSON."""
 
 import logging
+import uuid
 from typing import Any
 
 from backend.copilot.model import ChatSession
 
-from .agent_generator import (
-    AgentGeneratorNotConfiguredError,
-    decompose_goal,
-    enrich_library_agents_from_steps,
-    generate_agent,
-    get_user_message_for_error,
-    save_agent_to_library,
-)
+from .agent_generator.pipeline import fetch_library_agents, fix_validate_and_save
 from .base import BaseTool
-from .models import (
-    AgentPreviewResponse,
-    AgentSavedResponse,
-    ClarificationNeededResponse,
-    ClarifyingQuestion,
-    ErrorResponse,
-    SuggestedGoalResponse,
-    ToolResponseBase,
-)
+from .models import ErrorResponse, ToolResponseBase
 
 logger = logging.getLogger(__name__)
 
 
 class CreateAgentTool(BaseTool):
-    """Tool for creating agents from natural language descriptions."""
+    """Tool for creating agents from pre-built JSON."""
 
     @property
     def name(self) -> str:
@@ -37,11 +23,12 @@ class CreateAgentTool(BaseTool):
     @property
     def description(self) -> str:
         return (
-            "Create a new agent workflow from a natural language description. "
-            "First generates a preview, then saves to library if save=true. "
-            "\n\nIMPORTANT: Before calling this tool, search for relevant existing agents "
+            "Create a new agent workflow. Pass `agent_json` with the complete "
+            "agent graph JSON you generated using block schemas from find_block. "
+            "The tool validates, auto-fixes, and saves.\n\n"
+            "IMPORTANT: Before calling this tool, search for relevant existing agents "
             "using find_library_agent that could be used as building blocks. "
-            "Pass their IDs in the library_agent_ids parameter so the generator can compose them."
+            "Pass their IDs in the library_agent_ids parameter."
         )
 
     @property
@@ -53,39 +40,39 @@ class CreateAgentTool(BaseTool):
         return {
             "type": "object",
             "properties": {
-                "description": {
-                    "type": "string",
+                "agent_json": {
+                    "type": "object",
                     "description": (
-                        "Natural language description of what the agent should do. "
-                        "Be specific about inputs, outputs, and the workflow steps."
-                    ),
-                },
-                "context": {
-                    "type": "string",
-                    "description": (
-                        "Additional context or answers to previous clarifying questions. "
-                        "Include any preferences or constraints mentioned by the user."
+                        "The agent JSON to validate and save. "
+                        "Must contain 'nodes' and 'links' arrays, and optionally "
+                        "'name' and 'description'."
                     ),
                 },
                 "library_agent_ids": {
                     "type": "array",
                     "items": {"type": "string"},
                     "description": (
-                        "List of library agent IDs to use as building blocks. "
-                        "Search for relevant agents using find_library_agent first, "
-                        "then pass their IDs here so they can be composed into the new agent."
+                        "List of library agent IDs to use as building blocks."
                     ),
                 },
                 "save": {
                     "type": "boolean",
                     "description": (
-                        "Whether to save the agent to the user's library. "
-                        "Default is true. Set to false for preview only."
+                        "Whether to save the agent. Default is true. "
+                        "Set to false for preview only."
                     ),
                     "default": True,
                 },
+                "folder_id": {
+                    "type": "string",
+                    "description": (
+                        "Optional folder ID to save the agent into. "
+                        "If not provided, the agent is saved at root level. "
+                        "Use list_folders to find available folders."
+                    ),
+                },
             },
-            "required": ["description"],
+            "required": ["agent_json"],
         }
 
     async def _execute(
@@ -94,277 +81,49 @@ class CreateAgentTool(BaseTool):
         session: ChatSession,
         **kwargs,
     ) -> ToolResponseBase:
-        """Execute the create_agent tool.
-
-        Flow:
-        1. Decompose the description into steps (may return clarifying questions)
-        2. Generate agent JSON (external service handles fixing and validation)
-        3. Preview or save based on the save parameter
-        """
-        description = kwargs.get("description", "").strip()
-        context = kwargs.get("context", "")
-        library_agent_ids = kwargs.get("library_agent_ids", [])
-        save = kwargs.get("save", True)
+        agent_json: dict[str, Any] | None = kwargs.get("agent_json")
         session_id = session.session_id if session else None
 
-        logger.info(
-            f"[AGENT_CREATE_DEBUG] START - description_len={len(description)}, "
-            f"library_agent_ids={library_agent_ids}, save={save}, user_id={user_id}, session_id={session_id}"
+        if not agent_json:
+            return ErrorResponse(
+                message=(
+                    "Please provide agent_json with the complete agent graph. "
+                    "Use find_block to discover blocks, then generate the JSON."
+                ),
+                error="missing_agent_json",
+                session_id=session_id,
+            )
+
+        save = kwargs.get("save", True)
+        library_agent_ids = kwargs.get("library_agent_ids", [])
+        folder_id: str | None = kwargs.get("folder_id")
+
+        nodes = agent_json.get("nodes", [])
+        if not nodes:
+            return ErrorResponse(
+                message="The agent JSON has no nodes. An agent needs at least one block.",
+                error="empty_agent",
+                session_id=session_id,
+            )
+
+        # Ensure top-level fields
+        if "id" not in agent_json:
+            agent_json["id"] = str(uuid.uuid4())
+        if "version" not in agent_json:
+            agent_json["version"] = 1
+        if "is_active" not in agent_json:
+            agent_json["is_active"] = True
+
+        # Fetch library agents for AgentExecutorBlock validation
+        library_agents = await fetch_library_agents(user_id, library_agent_ids)
+
+        return await fix_validate_and_save(
+            agent_json,
+            user_id=user_id,
+            session_id=session_id,
+            save=save,
+            is_update=False,
+            default_name="Generated Agent",
+            library_agents=library_agents,
+            folder_id=folder_id,
         )
-
-        if not description:
-            return ErrorResponse(
-                message="Please provide a description of what the agent should do.",
-                error="Missing description parameter",
-                session_id=session_id,
-            )
-
-        # Fetch library agents by IDs if provided
-        library_agents = None
-        if user_id and library_agent_ids:
-            try:
-                from .agent_generator import get_library_agents_by_ids
-
-                library_agents = await get_library_agents_by_ids(
-                    user_id=user_id,
-                    agent_ids=library_agent_ids,
-                )
-                logger.debug(
-                    f"Fetched {len(library_agents)} library agents by ID for sub-agent composition"
-                )
-            except Exception as e:
-                logger.warning(f"Failed to fetch library agents by IDs: {e}")
-
-        try:
-            decomposition_result = await decompose_goal(
-                description, context, library_agents
-            )
-            logger.info(
-                f"[AGENT_CREATE_DEBUG] DECOMPOSE - type={decomposition_result.get('type') if decomposition_result else None}, "
-                f"session_id={session_id}"
-            )
-        except AgentGeneratorNotConfiguredError:
-            logger.error(
-                f"[AGENT_CREATE_DEBUG] ERROR - AgentGeneratorNotConfigured, session_id={session_id}"
-            )
-            return ErrorResponse(
-                message=(
-                    "Agent generation is not available. "
-                    "The Agent Generator service is not configured."
-                ),
-                error="service_not_configured",
-                session_id=session_id,
-            )
-
-        if decomposition_result is None:
-            return ErrorResponse(
-                message="Failed to analyze the goal. The agent generation service may be unavailable. Please try again.",
-                error="decomposition_failed",
-                details={"description": description[:100]},
-                session_id=session_id,
-            )
-
-        if decomposition_result.get("type") == "error":
-            error_msg = decomposition_result.get("error", "Unknown error")
-            error_type = decomposition_result.get("error_type", "unknown")
-            user_message = get_user_message_for_error(
-                error_type,
-                operation="analyze the goal",
-                llm_parse_message="The AI had trouble understanding this request. Please try rephrasing your goal.",
-            )
-            return ErrorResponse(
-                message=user_message,
-                error=f"decomposition_failed:{error_type}",
-                details={
-                    "description": description[:100],
-                    "service_error": error_msg,
-                    "error_type": error_type,
-                },
-                session_id=session_id,
-            )
-
-        if decomposition_result.get("type") == "clarifying_questions":
-            questions = decomposition_result.get("questions", [])
-            return ClarificationNeededResponse(
-                message=(
-                    "I need some more information to create this agent. "
-                    "Please answer the following questions:"
-                ),
-                questions=[
-                    ClarifyingQuestion(
-                        question=q.get("question", ""),
-                        keyword=q.get("keyword", ""),
-                        example=q.get("example"),
-                    )
-                    for q in questions
-                ],
-                session_id=session_id,
-            )
-
-        if decomposition_result.get("type") == "unachievable_goal":
-            suggested = decomposition_result.get("suggested_goal", "")
-            reason = decomposition_result.get("reason", "")
-            return SuggestedGoalResponse(
-                message=(
-                    f"This goal cannot be accomplished with the available blocks. {reason}"
-                ),
-                suggested_goal=suggested,
-                reason=reason,
-                original_goal=description,
-                goal_type="unachievable",
-                session_id=session_id,
-            )
-
-        if decomposition_result.get("type") == "vague_goal":
-            suggested = decomposition_result.get("suggested_goal", "")
-            reason = decomposition_result.get(
-                "reason", "The goal needs more specific details"
-            )
-            return SuggestedGoalResponse(
-                message="The goal is too vague to create a specific workflow.",
-                suggested_goal=suggested,
-                reason=reason,
-                original_goal=description,
-                goal_type="vague",
-                session_id=session_id,
-            )
-
-        if user_id and library_agents is not None:
-            try:
-                library_agents = await enrich_library_agents_from_steps(
-                    user_id=user_id,
-                    decomposition_result=decomposition_result,
-                    existing_agents=library_agents,
-                    include_marketplace=True,
-                )
-                logger.debug(
-                    f"After enrichment: {len(library_agents)} total agents for sub-agent composition"
-                )
-            except Exception as e:
-                logger.warning(f"Failed to enrich library agents from steps: {e}")
-
-        try:
-            agent_json = await generate_agent(
-                decomposition_result,
-                library_agents,
-            )
-            logger.info(
-                f"[AGENT_CREATE_DEBUG] GENERATE - "
-                f"success={agent_json is not None}, "
-                f"is_error={isinstance(agent_json, dict) and agent_json.get('type') == 'error'}, "
-                f"session_id={session_id}"
-            )
-        except AgentGeneratorNotConfiguredError:
-            logger.error(
-                f"[AGENT_CREATE_DEBUG] ERROR - AgentGeneratorNotConfigured during generation, session_id={session_id}"
-            )
-            return ErrorResponse(
-                message=(
-                    "Agent generation is not available. "
-                    "The Agent Generator service is not configured."
-                ),
-                error="service_not_configured",
-                session_id=session_id,
-            )
-
-        if agent_json is None:
-            return ErrorResponse(
-                message="Failed to generate the agent. The agent generation service may be unavailable. Please try again.",
-                error="generation_failed",
-                details={"description": description[:100]},
-                session_id=session_id,
-            )
-
-        if isinstance(agent_json, dict) and agent_json.get("type") == "error":
-            error_msg = agent_json.get("error", "Unknown error")
-            error_type = agent_json.get("error_type", "unknown")
-            user_message = get_user_message_for_error(
-                error_type,
-                operation="generate the agent",
-                llm_parse_message="The AI had trouble generating the agent. Please try again or simplify your goal.",
-                validation_message=(
-                    "I wasn't able to create a valid agent for this request. "
-                    "The generated workflow had some structural issues. "
-                    "Please try simplifying your goal or breaking it into smaller steps."
-                ),
-                error_details=error_msg,
-            )
-            return ErrorResponse(
-                message=user_message,
-                error=f"generation_failed:{error_type}",
-                details={
-                    "description": description[:100],
-                    "service_error": error_msg,
-                    "error_type": error_type,
-                },
-                session_id=session_id,
-            )
-
-        agent_name = agent_json.get("name", "Generated Agent")
-        agent_description = agent_json.get("description", "")
-        node_count = len(agent_json.get("nodes", []))
-        link_count = len(agent_json.get("links", []))
-
-        logger.info(
-            f"[AGENT_CREATE_DEBUG] AGENT_JSON - name={agent_name}, "
-            f"nodes={node_count}, links={link_count}, save={save}, session_id={session_id}"
-        )
-
-        if not save:
-            logger.info(
-                f"[AGENT_CREATE_DEBUG] RETURN - AgentPreviewResponse, session_id={session_id}"
-            )
-            return AgentPreviewResponse(
-                message=(
-                    f"I've generated an agent called '{agent_name}' with {node_count} blocks. "
-                    f"Review it and call create_agent with save=true to save it to your library."
-                ),
-                agent_json=agent_json,
-                agent_name=agent_name,
-                description=agent_description,
-                node_count=node_count,
-                link_count=link_count,
-                session_id=session_id,
-            )
-
-        if not user_id:
-            return ErrorResponse(
-                message="You must be logged in to save agents.",
-                error="auth_required",
-                session_id=session_id,
-            )
-
-        try:
-            created_graph, library_agent = await save_agent_to_library(
-                agent_json, user_id
-            )
-
-            logger.info(
-                f"[AGENT_CREATE_DEBUG] SAVED - graph_id={created_graph.id}, "
-                f"library_agent_id={library_agent.id}, session_id={session_id}"
-            )
-            logger.info(
-                f"[AGENT_CREATE_DEBUG] RETURN - AgentSavedResponse, session_id={session_id}"
-            )
-            return AgentSavedResponse(
-                message=f"Agent '{created_graph.name}' has been saved to your library!",
-                agent_id=created_graph.id,
-                agent_name=created_graph.name,
-                library_agent_id=library_agent.id,
-                library_agent_link=f"/library/agents/{library_agent.id}",
-                agent_page_link=f"/build?flowID={created_graph.id}",
-                session_id=session_id,
-            )
-        except Exception as e:
-            logger.error(
-                f"[AGENT_CREATE_DEBUG] ERROR - save_failed: {str(e)}, session_id={session_id}"
-            )
-            logger.info(
-                f"[AGENT_CREATE_DEBUG] RETURN - ErrorResponse (save_failed), session_id={session_id}"
-            )
-            return ErrorResponse(
-                message=f"Failed to save the agent: {str(e)}",
-                error="save_failed",
-                details={"exception": str(e)},
-                session_id=session_id,
-            )

autogpt_platform/backend/backend/copilot/tools/create_agent_test.py

@@ -1,19 +1,16 @@
-"""Tests for CreateAgentTool response types."""
+"""Tests for CreateAgentTool."""
 
-from unittest.mock import AsyncMock, patch
+from unittest.mock import MagicMock, patch
 
 import pytest
 
 from backend.copilot.tools.create_agent import CreateAgentTool
-from backend.copilot.tools.models import (
-    ClarificationNeededResponse,
-    ErrorResponse,
-    SuggestedGoalResponse,
-)
+from backend.copilot.tools.models import AgentPreviewResponse, ErrorResponse
 
 from ._test_data import make_session
 
 _TEST_USER_ID = "test-user-create-agent"
+_PIPELINE = "backend.copilot.tools.agent_generator.pipeline"
 
 
 @pytest.fixture
@@ -26,102 +23,147 @@ def session():
     return make_session(_TEST_USER_ID)
 
 
+# ── Input validation tests ──────────────────────────────────────────────
+
+
 @pytest.mark.asyncio
-async def test_missing_description_returns_error(tool, session):
-    """Missing description returns ErrorResponse."""
-    result = await tool._execute(user_id=_TEST_USER_ID, session=session, description="")
+async def test_missing_agent_json_returns_error(tool, session):
+    """Missing agent_json returns ErrorResponse."""
+    result = await tool._execute(user_id=_TEST_USER_ID, session=session)
     assert isinstance(result, ErrorResponse)
-    assert result.error == "Missing description parameter"
+    assert result.error == "missing_agent_json"
+
+
+# ── Local mode tests ────────────────────────────────────────────────────
 
 
 @pytest.mark.asyncio
-async def test_vague_goal_returns_suggested_goal_response(tool, session):
-    """vague_goal decomposition result returns SuggestedGoalResponse, not ErrorResponse."""
-    vague_result = {
-        "type": "vague_goal",
-        "suggested_goal": "Monitor Twitter mentions for a specific keyword and send a daily digest email",
-    }
-
-    with (
-        patch(
-            "backend.copilot.tools.create_agent.decompose_goal",
-            new_callable=AsyncMock,
-            return_value=vague_result,
-        ),
-    ):
-        result = await tool._execute(
-            user_id=_TEST_USER_ID,
-            session=session,
-            description="monitor social media",
-        )
-
-    assert isinstance(result, SuggestedGoalResponse)
-    assert result.goal_type == "vague"
-    assert result.suggested_goal == vague_result["suggested_goal"]
-    assert result.original_goal == "monitor social media"
-    assert result.reason == "The goal needs more specific details"
-    assert not isinstance(result, ErrorResponse)
+async def test_local_mode_empty_nodes_returns_error(tool, session):
+    """Local mode with no nodes returns ErrorResponse."""
+    result = await tool._execute(
+        user_id=_TEST_USER_ID,
+        session=session,
+        agent_json={"nodes": [], "links": []},
+    )
+    assert isinstance(result, ErrorResponse)
+    assert "no nodes" in result.message.lower()
 
 
 @pytest.mark.asyncio
-async def test_unachievable_goal_returns_suggested_goal_response(tool, session):
-    """unachievable_goal decomposition result returns SuggestedGoalResponse, not ErrorResponse."""
-    unachievable_result = {
-        "type": "unachievable_goal",
-        "suggested_goal": "Summarize the latest news articles on a topic and send them by email",
-        "reason": "There are no blocks for mind-reading.",
-    }
-
-    with (
-        patch(
-            "backend.copilot.tools.create_agent.decompose_goal",
-            new_callable=AsyncMock,
-            return_value=unachievable_result,
-        ),
-    ):
-        result = await tool._execute(
-            user_id=_TEST_USER_ID,
-            session=session,
-            description="read my mind",
-        )
-
-    assert isinstance(result, SuggestedGoalResponse)
-    assert result.goal_type == "unachievable"
-    assert result.suggested_goal == unachievable_result["suggested_goal"]
-    assert result.original_goal == "read my mind"
-    assert result.reason == unachievable_result["reason"]
-    assert not isinstance(result, ErrorResponse)
-
-
-@pytest.mark.asyncio
-async def test_clarifying_questions_returns_clarification_needed_response(
-    tool, session
-):
-    """clarifying_questions decomposition result returns ClarificationNeededResponse."""
-    clarifying_result = {
-        "type": "clarifying_questions",
-        "questions": [
+async def test_local_mode_preview(tool, session):
+    """Local mode with save=false returns AgentPreviewResponse."""
+    agent_json = {
+        "name": "Test Agent",
+        "description": "A test agent",
+        "nodes": [
             {
-                "question": "What platform should be monitored?",
-                "keyword": "platform",
-                "example": "Twitter, Reddit",
+                "id": "node-1",
+                "block_id": "block-1",
+                "input_default": {},
+                "metadata": {"position": {"x": 0, "y": 0}},
             }
         ],
+        "links": [],
     }
 
+    mock_fixer = MagicMock()
+    mock_fixer.apply_all_fixes = MagicMock(return_value=agent_json)
+    mock_fixer.get_fixes_applied.return_value = []
+
+    mock_validator = MagicMock()
+    mock_validator.validate.return_value = (True, None)
+    mock_validator.errors = []
+
     with (
-        patch(
-            "backend.copilot.tools.create_agent.decompose_goal",
-            new_callable=AsyncMock,
-            return_value=clarifying_result,
-        ),
+        patch(f"{_PIPELINE}.get_blocks_as_dicts", return_value=[]),
+        patch(f"{_PIPELINE}.AgentFixer", return_value=mock_fixer),
+        patch(f"{_PIPELINE}.AgentValidator", return_value=mock_validator),
     ):
         result = await tool._execute(
             user_id=_TEST_USER_ID,
             session=session,
-            description="monitor social media and alert me",
+            agent_json=agent_json,
+            save=False,
         )
 
-    assert isinstance(result, ClarificationNeededResponse)
-    assert len(result.questions) == 1
-    assert result.questions[0].keyword == "platform"
+    assert isinstance(result, AgentPreviewResponse)
+    assert result.agent_name == "Test Agent"
+    assert result.node_count == 1
+
+
+@pytest.mark.asyncio
+async def test_local_mode_validation_failure(tool, session):
+    """Local mode returns ErrorResponse when validation fails after fixing."""
+    agent_json = {
+        "nodes": [
+            {
+                "id": "node-1",
+                "block_id": "bad-block",
+                "input_default": {},
+                "metadata": {},
+            }
+        ],
+        "links": [],
+    }
+
+    mock_fixer = MagicMock()
+    mock_fixer.apply_all_fixes = MagicMock(return_value=agent_json)
+    mock_fixer.get_fixes_applied.return_value = []
+
+    mock_validator = MagicMock()
+    mock_validator.validate.return_value = (False, "Block 'bad-block' not found")
+    mock_validator.errors = ["Block 'bad-block' not found"]
+
+    with (
+        patch(f"{_PIPELINE}.get_blocks_as_dicts", return_value=[]),
+        patch(f"{_PIPELINE}.AgentFixer", return_value=mock_fixer),
+        patch(f"{_PIPELINE}.AgentValidator", return_value=mock_validator),
+    ):
+        result = await tool._execute(
+            user_id=_TEST_USER_ID,
+            session=session,
+            agent_json=agent_json,
+        )
+
+    assert isinstance(result, ErrorResponse)
+    assert result.error == "validation_failed"
+    assert "Block 'bad-block' not found" in result.message
+
+
+@pytest.mark.asyncio
+async def test_local_mode_no_auth_returns_error(tool, session):
+    """Local mode with save=true and no user returns ErrorResponse."""
+    agent_json = {
+        "nodes": [
+            {
+                "id": "node-1",
+                "block_id": "block-1",
+                "input_default": {},
+                "metadata": {},
+            }
+        ],
+        "links": [],
+    }
+
+    mock_fixer = MagicMock()
+    mock_fixer.apply_all_fixes = MagicMock(return_value=agent_json)
+    mock_fixer.get_fixes_applied.return_value = []
+
+    mock_validator = MagicMock()
+    mock_validator.validate.return_value = (True, None)
+    mock_validator.errors = []
+
+    with (
+        patch(f"{_PIPELINE}.get_blocks_as_dicts", return_value=[]),
+        patch(f"{_PIPELINE}.AgentFixer", return_value=mock_fixer),
+        patch(f"{_PIPELINE}.AgentValidator", return_value=mock_validator),
+    ):
+        result = await tool._execute(
+            user_id=None,
+            session=session,
+            agent_json=agent_json,
+            save=True,
+        )
+
+    assert isinstance(result, ErrorResponse)
+    assert "logged in" in result.message.lower()

autogpt_platform/backend/backend/copilot/tools/customize_agent.py

@@ -1,34 +1,20 @@
-"""CustomizeAgentTool - Customizes marketplace/template agents using natural language."""
+"""CustomizeAgentTool - Customizes marketplace/template agents."""
 
 import logging
+import uuid
 from typing import Any
 
-from backend.api.features.store.exceptions import AgentNotFoundError
 from backend.copilot.model import ChatSession
-from backend.data.db_accessors import store_db as get_store_db
 
-from .agent_generator import (
-    AgentGeneratorNotConfiguredError,
-    customize_template,
-    get_user_message_for_error,
-    graph_to_json,
-    save_agent_to_library,
-)
+from .agent_generator.pipeline import fetch_library_agents, fix_validate_and_save
 from .base import BaseTool
-from .models import (
-    AgentPreviewResponse,
-    AgentSavedResponse,
-    ClarificationNeededResponse,
-    ClarifyingQuestion,
-    ErrorResponse,
-    ToolResponseBase,
-)
+from .models import ErrorResponse, ToolResponseBase
 
 logger = logging.getLogger(__name__)
 
 
 class CustomizeAgentTool(BaseTool):
-    """Tool for customizing marketplace/template agents using natural language."""
+    """Tool for customizing marketplace/template agents."""
 
     @property
     def name(self) -> str:
@@ -37,9 +23,9 @@ class CustomizeAgentTool(BaseTool):
     @property
     def description(self) -> str:
         return (
-            "Customize a marketplace or template agent using natural language. "
-            "Takes an existing agent from the marketplace and modifies it based on "
-            "the user's requirements before adding to their library."
+            "Customize a marketplace or template agent. Pass `agent_json` "
+            "with the complete customized agent JSON. The tool validates, "
+            "auto-fixes, and saves."
         )
 
     @property
@@ -51,37 +37,37 @@ class CustomizeAgentTool(BaseTool):
         return {
             "type": "object",
             "properties": {
-                "agent_id": {
-                    "type": "string",
+                "agent_json": {
+                    "type": "object",
                     "description": (
-                        "The marketplace agent ID in format 'creator/slug' "
-                        "(e.g., 'autogpt/newsletter-writer'). "
-                        "Get this from find_agent results."
+                        "Complete customized agent JSON to validate and save. "
+                        "Optionally include 'name' and 'description'."
                     ),
                 },
-                "modifications": {
-                    "type": "string",
+                "library_agent_ids": {
+                    "type": "array",
+                    "items": {"type": "string"},
                     "description": (
-                        "Natural language description of how to customize the agent. "
-                        "Be specific about what changes you want to make."
-                    ),
-                },
-                "context": {
-                    "type": "string",
-                    "description": (
-                        "Additional context or answers to previous clarifying questions."
+                        "List of library agent IDs to use as building blocks."
                     ),
                 },
                 "save": {
                     "type": "boolean",
                     "description": (
-                        "Whether to save the customized agent to the user's library. "
-                        "Default is true. Set to false for preview only."
+                        "Whether to save the customized agent. Default is true."
                     ),
                     "default": True,
                 },
+                "folder_id": {
+                    "type": "string",
+                    "description": (
+                        "Optional folder ID to save the agent into. "
+                        "If not provided, the agent is saved at root level. "
+                        "Use list_folders to find available folders."
+                    ),
+                },
             },
-            "required": ["agent_id", "modifications"],
+            "required": ["agent_json"],
         }
 
     async def _execute(
@@ -90,246 +76,46 @@ class CustomizeAgentTool(BaseTool):
         session: ChatSession,
         **kwargs,
     ) -> ToolResponseBase:
-        """Execute the customize_agent tool.
-
-        Flow:
-        1. Parse the agent ID to get creator/slug
-        2. Fetch the template agent from the marketplace
-        3. Call customize_template with the modification request
-        4. Preview or save based on the save parameter
-        """
-        agent_id = kwargs.get("agent_id", "").strip()
-        modifications = kwargs.get("modifications", "").strip()
-        context = kwargs.get("context", "")
-        save = kwargs.get("save", True)
+        agent_json: dict[str, Any] | None = kwargs.get("agent_json")
         session_id = session.session_id if session else None
 
-        if not agent_id:
-            return ErrorResponse(
-                message="Please provide the marketplace agent ID (e.g., 'creator/agent-name').",
-                error="missing_agent_id",
-                session_id=session_id,
-            )
-
-        if not modifications:
-            return ErrorResponse(
-                message="Please describe how you want to customize this agent.",
-                error="missing_modifications",
-                session_id=session_id,
-            )
-
-        # Parse agent_id in format "creator/slug"
-        parts = [p.strip() for p in agent_id.split("/")]
-        if len(parts) != 2 or not parts[0] or not parts[1]:
+        if not agent_json:
             return ErrorResponse(
                 message=(
-                    f"Invalid agent ID format: '{agent_id}'. "
-                    "Expected format is 'creator/agent-name' "
-                    "(e.g., 'autogpt/newsletter-writer')."
+                    "Please provide agent_json with the complete customized agent graph."
                 ),
-                error="invalid_agent_id_format",
+                error="missing_agent_json",
                 session_id=session_id,
             )
 
-        creator_username, agent_slug = parts
+        save = kwargs.get("save", True)
+        library_agent_ids = kwargs.get("library_agent_ids", [])
+        folder_id: str | None = kwargs.get("folder_id")
 
-        store_db = get_store_db()
-
-        # Fetch the marketplace agent details
-        try:
-            agent_details = await store_db.get_store_agent_details(
-                username=creator_username, agent_name=agent_slug
-            )
-        except AgentNotFoundError:
+        nodes = agent_json.get("nodes", [])
+        if not nodes:
             return ErrorResponse(
-                message=(
-                    f"Could not find marketplace agent '{agent_id}'. "
-                    "Please check the agent ID and try again."
-                ),
-                error="agent_not_found",
-                session_id=session_id,
-            )
-        except Exception as e:
-            logger.error(f"Error fetching marketplace agent {agent_id}: {e}")
-            return ErrorResponse(
-                message="Failed to fetch the marketplace agent. Please try again.",
-                error="fetch_error",
+                message="The agent JSON has no nodes.",
+                error="empty_agent",
                 session_id=session_id,
             )
 
-        if not agent_details.store_listing_version_id:
-            return ErrorResponse(
-                message=(
-                    f"The agent '{agent_id}' does not have an available version. "
-                    "Please try a different agent."
-                ),
-                error="no_version_available",
-                session_id=session_id,
-            )
+        # Ensure top-level fields before the fixer pipeline
+        if "id" not in agent_json:
+            agent_json["id"] = str(uuid.uuid4())
+        agent_json.setdefault("version", 1)
+        agent_json.setdefault("is_active", True)
 
-        # Get the full agent graph
-        try:
-            graph = await store_db.get_agent(agent_details.store_listing_version_id)
-            template_agent = graph_to_json(graph)
-        except Exception as e:
-            logger.error(f"Error fetching agent graph for {agent_id}: {e}")
-            return ErrorResponse(
-                message="Failed to fetch the agent configuration. Please try again.",
-                error="graph_fetch_error",
-                session_id=session_id,
-            )
+        # Fetch library agents for AgentExecutorBlock validation
+        library_agents = await fetch_library_agents(user_id, library_agent_ids)
 
-        # Call customize_template
-        try:
-            result = await customize_template(
-                template_agent=template_agent,
-                modification_request=modifications,
-                context=context,
-            )
-        except AgentGeneratorNotConfiguredError:
-            return ErrorResponse(
-                message=(
-                    "Agent customization is not available. "
-                    "The Agent Generator service is not configured."
-                ),
-                error="service_not_configured",
-                session_id=session_id,
-            )
-        except Exception as e:
-            logger.error(f"Error calling customize_template for {agent_id}: {e}")
-            return ErrorResponse(
-                message=(
-                    "Failed to customize the agent due to a service error. "
-                    "Please try again."
-                ),
-                error="customization_service_error",
-                session_id=session_id,
-            )
-
-        if result is None:
-            return ErrorResponse(
-                message=(
-                    "Failed to customize the agent. "
-                    "The agent generation service may be unavailable or timed out. "
-                    "Please try again."
-                ),
-                error="customization_failed",
-                session_id=session_id,
-            )
-
-        # Handle error response
-        if isinstance(result, dict) and result.get("type") == "error":
-            error_msg = result.get("error", "Unknown error")
-            error_type = result.get("error_type", "unknown")
-            user_message = get_user_message_for_error(
-                error_type,
-                operation="customize the agent",
-                llm_parse_message=(
-                    "The AI had trouble customizing the agent. "
-                    "Please try again or simplify your request."
-                ),
-                validation_message=(
-                    "The customized agent failed validation. "
-                    "Please try rephrasing your request."
-                ),
-                error_details=error_msg,
-            )
-            return ErrorResponse(
-                message=user_message,
-                error=f"customization_failed:{error_type}",
-                session_id=session_id,
-            )
-
-        # Handle clarifying questions
-        if isinstance(result, dict) and result.get("type") == "clarifying_questions":
-            questions = result.get("questions") or []
-            if not isinstance(questions, list):
-                logger.error(
-                    f"Unexpected clarifying questions format: {type(questions)}"
-                )
-                questions = []
-            return ClarificationNeededResponse(
-                message=(
-                    "I need some more information to customize this agent. "
-                    "Please answer the following questions:"
-                ),
-                questions=[
-                    ClarifyingQuestion(
-                        question=q.get("question", ""),
-                        keyword=q.get("keyword", ""),
-                        example=q.get("example"),
-                    )
-                    for q in questions
-                    if isinstance(q, dict)
-                ],
-                session_id=session_id,
-            )
-
-        # Result should be the customized agent JSON
-        if not isinstance(result, dict):
-            logger.error(f"Unexpected customize_template response type: {type(result)}")
-            return ErrorResponse(
-                message="Failed to customize the agent due to an unexpected response.",
-                error="unexpected_response_type",
-                session_id=session_id,
-            )
-
-        customized_agent = result
-
-        agent_name = customized_agent.get(
-            "name", f"Customized {agent_details.agent_name}"
+        return await fix_validate_and_save(
+            agent_json,
+            user_id=user_id,
+            session_id=session_id,
+            save=save,
+            is_update=False,
+            default_name="Customized Agent",
+            library_agents=library_agents,
+            folder_id=folder_id,
         )
-        agent_description = customized_agent.get("description", "")
-        nodes = customized_agent.get("nodes")
-        links = customized_agent.get("links")
-        node_count = len(nodes) if isinstance(nodes, list) else 0
-        link_count = len(links) if isinstance(links, list) else 0
-
-        if not save:
-            return AgentPreviewResponse(
-                message=(
-                    f"I've customized the agent '{agent_details.agent_name}'. "
-                    f"The customized agent has {node_count} blocks. "
-                    f"Review it and call customize_agent with save=true to save it."
-                ),
-                agent_json=customized_agent,
-                agent_name=agent_name,
-                description=agent_description,
-                node_count=node_count,
-                link_count=link_count,
-                session_id=session_id,
-            )
-
-        if not user_id:
-            return ErrorResponse(
-                message="You must be logged in to save agents.",
-                error="auth_required",
-                session_id=session_id,
-            )
-
-        # Save to user's library
-        try:
-            created_graph, library_agent = await save_agent_to_library(
-                customized_agent, user_id, is_update=False
-            )
-
-            return AgentSavedResponse(
-                message=(
-                    f"Customized agent '{created_graph.name}' "
-                    f"(based on '{agent_details.agent_name}') "
-                    f"has been saved to your library!"
-                ),
-                agent_id=created_graph.id,
-                agent_name=created_graph.name,
-                library_agent_id=library_agent.id,
-                library_agent_link=f"/library/agents/{library_agent.id}",
-                agent_page_link=f"/build?flowID={created_graph.id}",
-                session_id=session_id,
-            )
-        except Exception as e:
-            logger.error(f"Error saving customized agent: {e}")
-            return ErrorResponse(
-                message="Failed to save the customized agent. Please try again.",
-                error="save_failed",
-                session_id=session_id,
-            )

autogpt_platform/backend/backend/copilot/tools/customize_agent_test.py

@@ -0,0 +1,172 @@
+"""Tests for CustomizeAgentTool local mode."""
+
+from unittest.mock import MagicMock, patch
+
+import pytest
+
+from backend.copilot.tools.customize_agent import CustomizeAgentTool
+from backend.copilot.tools.models import AgentPreviewResponse, ErrorResponse
+
+from ._test_data import make_session
+
+_TEST_USER_ID = "test-user-customize-agent"
+_PIPELINE = "backend.copilot.tools.agent_generator.pipeline"
+
+
+@pytest.fixture
+def tool():
+    return CustomizeAgentTool()
+
+
+@pytest.fixture
+def session():
+    return make_session(_TEST_USER_ID)
+
+
+# ── Input validation tests ───────────────────────────────────────────────
+
+
+@pytest.mark.asyncio
+async def test_missing_agent_json_returns_error(tool, session):
+    """Missing agent_json returns ErrorResponse."""
+    result = await tool._execute(
+        user_id=_TEST_USER_ID,
+        session=session,
+    )
+    assert isinstance(result, ErrorResponse)
+    assert result.error == "missing_agent_json"
+
+
+# ── Local mode tests (agent_json provided) ───────────────────────────────
+
+
+@pytest.mark.asyncio
+async def test_local_mode_empty_nodes_returns_error(tool, session):
+    """Local mode with no nodes returns ErrorResponse."""
+    result = await tool._execute(
+        user_id=_TEST_USER_ID,
+        session=session,
+        agent_json={"nodes": [], "links": []},
+    )
+    assert isinstance(result, ErrorResponse)
+    assert "no nodes" in result.message.lower()
+
+
+@pytest.mark.asyncio
+async def test_local_mode_preview(tool, session):
+    """Local mode with save=false returns AgentPreviewResponse."""
+    agent_json = {
+        "name": "Customized Agent",
+        "description": "A customized agent",
+        "nodes": [
+            {
+                "id": "node-1",
+                "block_id": "block-1",
+                "input_default": {},
+                "metadata": {"position": {"x": 0, "y": 0}},
+            }
+        ],
+        "links": [],
+    }
+
+    mock_fixer = MagicMock()
+    mock_fixer.apply_all_fixes = MagicMock(return_value=agent_json)
+    mock_fixer.get_fixes_applied.return_value = []
+
+    mock_validator = MagicMock()
+    mock_validator.validate.return_value = (True, None)
+    mock_validator.errors = []
+
+    with (
+        patch(f"{_PIPELINE}.get_blocks_as_dicts", return_value=[]),
+        patch(f"{_PIPELINE}.AgentFixer", return_value=mock_fixer),
+        patch(f"{_PIPELINE}.AgentValidator", return_value=mock_validator),
+    ):
+        result = await tool._execute(
+            user_id=_TEST_USER_ID,
+            session=session,
+            agent_json=agent_json,
+            save=False,
+        )
+
+    assert isinstance(result, AgentPreviewResponse)
+    assert result.agent_name == "Customized Agent"
+    assert result.node_count == 1
+
+
+@pytest.mark.asyncio
+async def test_local_mode_validation_failure(tool, session):
+    """Local mode returns ErrorResponse when validation fails."""
+    agent_json = {
+        "nodes": [
+            {
+                "id": "node-1",
+                "block_id": "bad-block",
+                "input_default": {},
+                "metadata": {},
+            }
+        ],
+        "links": [],
+    }
+
+    mock_fixer = MagicMock()
+    mock_fixer.apply_all_fixes = MagicMock(return_value=agent_json)
+    mock_fixer.get_fixes_applied.return_value = []
+
+    mock_validator = MagicMock()
+    mock_validator.validate.return_value = (False, "Block 'bad-block' not found")
+    mock_validator.errors = ["Block 'bad-block' not found"]
+
+    with (
+        patch(f"{_PIPELINE}.get_blocks_as_dicts", return_value=[]),
+        patch(f"{_PIPELINE}.AgentFixer", return_value=mock_fixer),
+        patch(f"{_PIPELINE}.AgentValidator", return_value=mock_validator),
+    ):
+        result = await tool._execute(
+            user_id=_TEST_USER_ID,
+            session=session,
+            agent_json=agent_json,
+        )
+
+    assert isinstance(result, ErrorResponse)
+    assert result.error == "validation_failed"
+    assert "Block 'bad-block' not found" in result.message
+
+
+@pytest.mark.asyncio
+async def test_local_mode_no_auth_returns_error(tool, session):
+    """Local mode with save=true and no user returns ErrorResponse."""
+    agent_json = {
+        "nodes": [
+            {
+                "id": "node-1",
+                "block_id": "block-1",
+                "input_default": {},
+                "metadata": {},
+            }
+        ],
+        "links": [],
+    }
+
+    mock_fixer = MagicMock()
+    mock_fixer.apply_all_fixes = MagicMock(return_value=agent_json)
+    mock_fixer.get_fixes_applied.return_value = []
+
+    mock_validator = MagicMock()
+    mock_validator.validate.return_value = (True, None)
+    mock_validator.errors = []
+
+    with (
+        patch(f"{_PIPELINE}.get_blocks_as_dicts", return_value=[]),
+        patch(f"{_PIPELINE}.AgentFixer", return_value=mock_fixer),
+        patch(f"{_PIPELINE}.AgentValidator", return_value=mock_validator),
+    ):
+        result = await tool._execute(
+            user_id=None,
+            session=session,
+            agent_json=agent_json,
+            save=True,
+        )
+
+    assert isinstance(result, ErrorResponse)
+    assert "logged in" in result.message.lower()

autogpt_platform/backend/backend/copilot/tools/e2b_sandbox.py

@@ -10,13 +10,34 @@ Lifecycle
 ---------
 1. **Turn start** – connect to the existing sandbox (sandbox_id in Redis) or
    create a new one via ``get_or_create_sandbox()``.
+   ``connect()`` in e2b v2 auto-resumes paused sandboxes.
 2. **Execution** – ``bash_exec`` and MCP file tools operate directly on the
    sandbox's ``/home/user`` filesystem.
-3. **Session expiry** – E2B sandbox is killed by its own timeout (session_ttl).
+3. **Turn end** – the sandbox is paused via ``pause_sandbox()`` (fire-and-forget)
+   so idle time between turns costs nothing.  Paused sandboxes have no compute
+   cost.
+4. **Session delete** – ``kill_sandbox()`` fully terminates the sandbox.
+
+Cost control
+------------
+Sandboxes are created with a configurable ``on_timeout`` lifecycle action
+(default: ``"pause"``).  The explicit per-turn ``pause_sandbox()`` call is the
+primary mechanism; the lifecycle setting is a safety net.  Paused sandboxes are
+free.
+
+The sandbox_id is stored in Redis.  The same key doubles as a creation lock:
+a ``"creating"`` sentinel value is written with a short TTL while a new sandbox
+is being provisioned, preventing duplicate creation under concurrent requests.
+
+E2B project-level "paused sandbox lifetime" should be set to match
+``_SANDBOX_ID_TTL`` (48 h) so orphaned paused sandboxes are auto-killed before
+the Redis key expires.
 """
 
 import asyncio
+import contextlib
 import logging
+from typing import Any, Awaitable, Callable, Literal
 
 from e2b import AsyncSandbox
 
@@ -24,147 +45,245 @@ from backend.data.redis_client import get_redis_async
 
 logger = logging.getLogger(__name__)
 
-_SANDBOX_REDIS_PREFIX = "copilot:e2b:sandbox:"
-E2B_WORKDIR = "/home/user"
-_CREATING = "__creating__"
-_CREATION_LOCK_TTL = 60
-_MAX_WAIT_ATTEMPTS = 20  # 20 * 0.5s = 10s max wait
+_SANDBOX_KEY_PREFIX = "copilot:e2b:sandbox:"
+_CREATING_SENTINEL = "creating"
+
+# Short TTL for the "creating" sentinel — if the process dies mid-creation the
+# lock auto-expires so other callers are not blocked forever.
+_CREATION_LOCK_TTL = 60  # seconds
+
+_MAX_WAIT_ATTEMPTS = 20  # 20 × 0.5 s = 10 s max wait
+
+# Timeout for E2B API calls (pause/kill) — short because these are control-plane
+# operations; if the sandbox is unreachable, fail fast and retry on the next turn.
+_E2B_API_TIMEOUT_SECONDS = 10
+
+# Redis TTL for the sandbox key.  Must be ≥ the E2B project "paused sandbox
+# lifetime" setting (recommended: set both to 48 h).
+_SANDBOX_ID_TTL = 48 * 3600  # 48 hours
+
+
+def _sandbox_key(session_id: str) -> str:
+    return f"{_SANDBOX_KEY_PREFIX}{session_id}"
+
+
+async def _get_stored_sandbox_id(session_id: str) -> str | None:
+    redis = await get_redis_async()
+    raw = await redis.get(_sandbox_key(session_id))
+    value = raw.decode() if isinstance(raw, bytes) else raw
+    return None if value == _CREATING_SENTINEL else value
+
+
+async def _set_stored_sandbox_id(session_id: str, sandbox_id: str) -> None:
+    redis = await get_redis_async()
+    await redis.set(_sandbox_key(session_id), sandbox_id, ex=_SANDBOX_ID_TTL)
+
+
+async def _clear_stored_sandbox_id(session_id: str) -> None:
+    redis = await get_redis_async()
+    await redis.delete(_sandbox_key(session_id))
 
 
 async def _try_reconnect(
-    sandbox_id: str, api_key: str, redis_key: str, timeout: int
+    sandbox_id: str, session_id: str, api_key: str
 ) -> "AsyncSandbox | None":
     """Try to reconnect to an existing sandbox. Returns None on failure."""
     try:
         sandbox = await AsyncSandbox.connect(sandbox_id, api_key=api_key)
         if await sandbox.is_running():
-            redis = await get_redis_async()
-            await redis.expire(redis_key, timeout)
+            # Refresh TTL so an active session cannot lose its sandbox_id at expiry.
+            await _set_stored_sandbox_id(session_id, sandbox_id)
             return sandbox
     except Exception as exc:
         logger.warning("[E2B] Reconnect to %.12s failed: %s", sandbox_id, exc)
 
-    # Stale — clear Redis so a new sandbox can be created.
-    redis = await get_redis_async()
-    await redis.delete(redis_key)
+    # Stale — clear the sandbox_id from Redis so a new one can be created.
+    await _clear_stored_sandbox_id(session_id)
     return None
 
 
 async def get_or_create_sandbox(
     session_id: str,
     api_key: str,
+    timeout: int,
     template: str = "base",
-    timeout: int = 43200,
+    on_timeout: Literal["kill", "pause"] = "pause",
 ) -> AsyncSandbox:
     """Return the existing E2B sandbox for *session_id* or create a new one.
 
-    The sandbox_id is persisted in Redis so the same sandbox is reused
-    across turns. Concurrent calls for the same session are serialised
-    via a Redis ``SET NX`` creation lock.
+    The sandbox key in Redis serves a dual purpose: it stores the sandbox_id
+    and acts as a creation lock via a ``"creating"`` sentinel value.  This
+    removes the need for a separate lock key.
+
+    *timeout* controls how long the e2b sandbox may run continuously before
+    the ``on_timeout`` lifecycle rule fires (default: 3 h).
+    *on_timeout* controls what happens on timeout: ``"pause"`` (default, free)
+    or ``"kill"``.
     """
     redis = await get_redis_async()
-    redis_key = f"{_SANDBOX_REDIS_PREFIX}{session_id}"
+    key = _sandbox_key(session_id)
 
-    # 1. Try reconnecting to an existing sandbox.
-    raw = await redis.get(redis_key)
-    if raw:
-        sandbox_id = raw if isinstance(raw, str) else raw.decode()
-        if sandbox_id != _CREATING:
-            sandbox = await _try_reconnect(sandbox_id, api_key, redis_key, timeout)
+    for _ in range(_MAX_WAIT_ATTEMPTS):
+        raw = await redis.get(key)
+        value = raw.decode() if isinstance(raw, bytes) else raw
+
+        if value and value != _CREATING_SENTINEL:
+            # Existing sandbox ID — try to reconnect (auto-resumes if paused).
+            sandbox = await _try_reconnect(value, session_id, api_key)
             if sandbox:
                 logger.info(
                     "[E2B] Reconnected to %.12s for session %.12s",
-                    sandbox_id,
+                    value,
                     session_id,
                 )
                 return sandbox
+            # _try_reconnect cleared the key — loop to create a new sandbox.
+            continue
 
-    # 2. Claim creation lock. If another request holds it, wait for the result.
-    claimed = await redis.set(redis_key, _CREATING, nx=True, ex=_CREATION_LOCK_TTL)
-    if not claimed:
-        for _ in range(_MAX_WAIT_ATTEMPTS):
+        if value == _CREATING_SENTINEL:
+            # Another coroutine is creating — wait for it to finish.
             await asyncio.sleep(0.5)
-            raw = await redis.get(redis_key)
-            if not raw:
-                break  # Lock expired — fall through to retry creation
-            sandbox_id = raw if isinstance(raw, str) else raw.decode()
-            if sandbox_id != _CREATING:
-                sandbox = await _try_reconnect(sandbox_id, api_key, redis_key, timeout)
-                if sandbox:
-                    return sandbox
-                break  # Stale sandbox cleared — fall through to create
+            continue
 
-        # Try to claim creation lock again after waiting.
-        claimed = await redis.set(redis_key, _CREATING, nx=True, ex=_CREATION_LOCK_TTL)
-        if not claimed:
-            # Another process may have created a sandbox — try to use it.
-            raw = await redis.get(redis_key)
-            if raw:
-                sandbox_id = raw if isinstance(raw, str) else raw.decode()
-                if sandbox_id != _CREATING:
-                    sandbox = await _try_reconnect(
-                        sandbox_id, api_key, redis_key, timeout
-                    )
-                    if sandbox:
-                        return sandbox
-            raise RuntimeError(
-                f"Could not acquire E2B creation lock for session {session_id[:12]}"
-            )
-
-    # 3. Create a new sandbox.
-    try:
-        sandbox = await AsyncSandbox.create(
-            template=template, api_key=api_key, timeout=timeout
+        # No sandbox and no active creation — atomically claim the creation slot.
+        claimed = await redis.set(
+            key, _CREATING_SENTINEL, nx=True, ex=_CREATION_LOCK_TTL
         )
-    except Exception:
-        await redis.delete(redis_key)
-        raise
+        if not claimed:
+            # Race lost — another coroutine just claimed it.
+            await asyncio.sleep(0.1)
+            continue
 
-    await redis.setex(redis_key, timeout, sandbox.sandbox_id)
-    logger.info(
-        "[E2B] Created sandbox %.12s for session %.12s",
-        sandbox.sandbox_id,
-        session_id,
-    )
-    return sandbox
+        # We hold the slot — create the sandbox.
+        try:
+            sandbox = await AsyncSandbox.create(
+                template=template,
+                api_key=api_key,
+                timeout=timeout,
+                lifecycle={"on_timeout": on_timeout},
+            )
+            try:
+                await _set_stored_sandbox_id(session_id, sandbox.sandbox_id)
+            except Exception:
+                # Redis save failed — kill the sandbox to avoid leaking it.
+                with contextlib.suppress(Exception):
+                    await sandbox.kill()
+                raise
+        except Exception:
+            # Release the creation slot so other callers can proceed.
+            await redis.delete(key)
+            raise
+
+        logger.info(
+            "[E2B] Created sandbox %.12s for session %.12s",
+            sandbox.sandbox_id,
+            session_id,
+        )
+        return sandbox
+
+    raise RuntimeError(f"Could not acquire E2B sandbox for session {session_id[:12]}")
 
 
-async def kill_sandbox(session_id: str, api_key: str) -> bool:
-    """Kill the E2B sandbox for *session_id* and clean up its Redis entry.
+async def _act_on_sandbox(
+    session_id: str,
+    api_key: str,
+    action: str,
+    fn: Callable[[AsyncSandbox], Awaitable[Any]],
+    *,
+    clear_stored_id: bool = False,
+) -> bool:
+    """Connect to the sandbox for *session_id* and run *fn* on it.
 
-    Returns ``True`` if a sandbox was found and killed, ``False`` otherwise.
-    Safe to call even when no sandbox exists for the session.
+    Shared by ``pause_sandbox`` and ``kill_sandbox``.  Returns ``True`` on
+    success, ``False`` when no sandbox is found or the action fails.
+    If *clear_stored_id* is ``True``, the sandbox_id is removed from Redis
+    only after the action succeeds so a failed kill can be retried.
     """
-    redis = await get_redis_async()
-    redis_key = f"{_SANDBOX_REDIS_PREFIX}{session_id}"
-    raw = await redis.get(redis_key)
-    if not raw:
+    sandbox_id = await _get_stored_sandbox_id(session_id)
+    if not sandbox_id:
         return False
 
-    sandbox_id = raw if isinstance(raw, str) else raw.decode()
-    await redis.delete(redis_key)
-
-    if sandbox_id == _CREATING:
-        return False
+    async def _run() -> None:
+        await fn(await AsyncSandbox.connect(sandbox_id, api_key=api_key))
 
     try:
-
-        async def _connect_and_kill():
-            sandbox = await AsyncSandbox.connect(sandbox_id, api_key=api_key)
-            await sandbox.kill()
-
-        await asyncio.wait_for(_connect_and_kill(), timeout=10)
+        await asyncio.wait_for(_run(), timeout=_E2B_API_TIMEOUT_SECONDS)
+        if clear_stored_id:
+            await _clear_stored_sandbox_id(session_id)
         logger.info(
-            "[E2B] Killed sandbox %.12s for session %.12s",
+            "[E2B] %s sandbox %.12s for session %.12s",
+            action.capitalize(),
             sandbox_id,
             session_id,
         )
         return True
     except Exception as exc:
         logger.warning(
-            "[E2B] Failed to kill sandbox %.12s for session %.12s: %s",
+            "[E2B] Failed to %s sandbox %.12s for session %.12s: %s",
+            action,
             sandbox_id,
             session_id,
             exc,
         )
         return False
+
+
+async def pause_sandbox(session_id: str, api_key: str) -> bool:
+    """Pause the E2B sandbox for *session_id* to stop billing between turns.
+
+    Paused sandboxes cost nothing and are resumed automatically by
+    ``get_or_create_sandbox()`` on the next turn (via ``AsyncSandbox.connect()``).
+    The sandbox_id is kept in Redis so reconnection works seamlessly.
+
+    Prefer ``pause_sandbox_direct()`` when the sandbox object is already in
+    scope — it skips the Redis lookup and reconnect round-trip.
+
+    Returns ``True`` if the sandbox was found and paused, ``False`` otherwise.
+    Safe to call even when no sandbox exists for the session.
+    """
+    return await _act_on_sandbox(session_id, api_key, "pause", lambda sb: sb.pause())
+
+
+async def pause_sandbox_direct(sandbox: "AsyncSandbox", session_id: str) -> bool:
+    """Pause an already-connected sandbox without a reconnect round-trip.
+
+    Use this in callers that already hold the live sandbox object (e.g. turn
+    teardown in ``service.py``).  Saves the Redis lookup and
+    ``AsyncSandbox.connect()`` call that ``pause_sandbox()`` would make.
+
+    Returns ``True`` on success, ``False`` on failure or timeout.
+    """
+    try:
+        await asyncio.wait_for(sandbox.pause(), timeout=_E2B_API_TIMEOUT_SECONDS)
+        logger.info(
+            "[E2B] Paused sandbox %.12s for session %.12s",
+            sandbox.sandbox_id,
+            session_id,
+        )
+        return True
+    except Exception as exc:
+        logger.warning(
+            "[E2B] Failed to pause sandbox %.12s for session %.12s: %s",
+            sandbox.sandbox_id,
+            session_id,
+            exc,
+        )
+        return False
+
+
+async def kill_sandbox(
+    session_id: str,
+    api_key: str,
+) -> bool:
+    """Kill the E2B sandbox for *session_id* and clear its Redis entry.
+
+    Returns ``True`` if a sandbox was found and killed, ``False`` otherwise.
+    Safe to call even when no sandbox exists for the session.
+    """
+    return await _act_on_sandbox(
+        session_id,
+        api_key,
+        "kill",
+        lambda sb: sb.kill(),
+        clear_stored_id=True,
+    )

autogpt_platform/backend/backend/copilot/tools/e2b_sandbox_test.py

@@ -1,6 +1,12 @@
 """Tests for e2b_sandbox: get_or_create_sandbox, _try_reconnect, kill_sandbox.
 
-Uses mock Redis and mock AsyncSandbox — no external dependencies.
+sandbox_id is stored in Redis under _SANDBOX_KEY_PREFIX + session_id.
+The same key doubles as a creation lock via a "creating" sentinel value.
+
+Tests mock:
+- ``get_redis_async`` (sandbox key storage + creation lock sentinel)
+- ``AsyncSandbox`` (E2B SDK)
+
 Tests are synchronous (using asyncio.run) to avoid conflicts with the
 session-scoped event loop in conftest.py.
 """
@@ -11,36 +17,50 @@ from unittest.mock import AsyncMock, MagicMock, patch
 import pytest
 
 from .e2b_sandbox import (
-    _CREATING,
-    _SANDBOX_REDIS_PREFIX,
+    _CREATING_SENTINEL,
     _try_reconnect,
     get_or_create_sandbox,
     kill_sandbox,
+    pause_sandbox,
+    pause_sandbox_direct,
 )
 
-_KEY = f"{_SANDBOX_REDIS_PREFIX}sess-123"
+_SESSION_ID = "sess-123"
 _API_KEY = "test-api-key"
+_SANDBOX_ID = "sb-abc"
 _TIMEOUT = 300
 
 
-def _mock_sandbox(sandbox_id: str = "sb-abc", running: bool = True) -> MagicMock:
+def _mock_sandbox(sandbox_id: str = _SANDBOX_ID, running: bool = True) -> MagicMock:
     sb = MagicMock()
     sb.sandbox_id = sandbox_id
     sb.is_running = AsyncMock(return_value=running)
+    sb.pause = AsyncMock()
+    sb.kill = AsyncMock()
     return sb
 
 
-def _mock_redis(get_val: str | bytes | None = None, set_nx_result: bool = True):
+def _mock_redis(
+    set_nx_result: bool = True,
+    stored_sandbox_id: str | None = None,
+) -> AsyncMock:
+    """Create a mock redis client.
+
+    *stored_sandbox_id* is returned by ``get()`` calls (simulates the sandbox_id
+    stored under the ``_SANDBOX_KEY_PREFIX`` key).  ``set_nx_result`` controls
+    whether the creation-slot ``SET NX`` succeeds.
+
+    If *stored_sandbox_id* is None the key is absent (no sandbox, no lock).
+    """
     r = AsyncMock()
-    r.get = AsyncMock(return_value=get_val)
+    raw = stored_sandbox_id.encode() if stored_sandbox_id else None
+    r.get = AsyncMock(return_value=raw)
     r.set = AsyncMock(return_value=set_nx_result)
-    r.setex = AsyncMock()
     r.delete = AsyncMock()
-    r.expire = AsyncMock()
     return r
 
 
-def _patch_redis(redis):
+def _patch_redis(redis: AsyncMock):
     return patch(
         "backend.copilot.tools.e2b_sandbox.get_redis_async",
         new_callable=AsyncMock,
@@ -55,6 +75,7 @@ def _patch_redis(redis):
 
 class TestTryReconnect:
     def test_reconnect_success(self):
+        """Returns the sandbox when it connects and is running; refreshes Redis TTL."""
         sb = _mock_sandbox()
         redis = _mock_redis()
         with (
@@ -62,36 +83,39 @@ class TestTryReconnect:
             _patch_redis(redis),
         ):
             mock_cls.connect = AsyncMock(return_value=sb)
-            result = asyncio.run(_try_reconnect("sb-abc", _API_KEY, _KEY, _TIMEOUT))
+            result = asyncio.run(_try_reconnect(_SANDBOX_ID, _SESSION_ID, _API_KEY))
 
         assert result is sb
-        redis.expire.assert_awaited_once_with(_KEY, _TIMEOUT)
         redis.delete.assert_not_awaited()
+        # TTL must be refreshed so an active session cannot lose its key at expiry.
+        redis.set.assert_awaited_once()
 
-    def test_reconnect_not_running_clears_key(self):
+    def test_reconnect_not_running_clears_redis(self):
+        """Clears sandbox_id in Redis when the sandbox is no longer running."""
         sb = _mock_sandbox(running=False)
-        redis = _mock_redis()
+        redis = _mock_redis(stored_sandbox_id=_SANDBOX_ID)
         with (
             patch("backend.copilot.tools.e2b_sandbox.AsyncSandbox") as mock_cls,
             _patch_redis(redis),
         ):
             mock_cls.connect = AsyncMock(return_value=sb)
-            result = asyncio.run(_try_reconnect("sb-abc", _API_KEY, _KEY, _TIMEOUT))
+            result = asyncio.run(_try_reconnect(_SANDBOX_ID, _SESSION_ID, _API_KEY))
 
         assert result is None
-        redis.delete.assert_awaited_once_with(_KEY)
+        redis.delete.assert_awaited_once()
 
-    def test_reconnect_exception_clears_key(self):
-        redis = _mock_redis()
+    def test_reconnect_exception_clears_redis(self):
+        """Clears sandbox_id in Redis when connect raises an exception."""
+        redis = _mock_redis(stored_sandbox_id=_SANDBOX_ID)
         with (
             patch("backend.copilot.tools.e2b_sandbox.AsyncSandbox") as mock_cls,
             _patch_redis(redis),
         ):
             mock_cls.connect = AsyncMock(side_effect=ConnectionError("gone"))
-            result = asyncio.run(_try_reconnect("sb-abc", _API_KEY, _KEY, _TIMEOUT))
+            result = asyncio.run(_try_reconnect(_SANDBOX_ID, _SESSION_ID, _API_KEY))
 
         assert result is None
-        redis.delete.assert_awaited_once_with(_KEY)
+        redis.delete.assert_awaited_once()
 
 
 # ---------------------------------------------------------------------------
@@ -103,38 +127,63 @@ class TestGetOrCreateSandbox:
     def test_reconnect_existing(self):
         """When Redis has a valid sandbox_id, reconnect to it."""
         sb = _mock_sandbox()
-        redis = _mock_redis(get_val="sb-abc")
+        redis = _mock_redis(stored_sandbox_id=_SANDBOX_ID)
         with (
             patch("backend.copilot.tools.e2b_sandbox.AsyncSandbox") as mock_cls,
             _patch_redis(redis),
         ):
             mock_cls.connect = AsyncMock(return_value=sb)
             result = asyncio.run(
-                get_or_create_sandbox("sess-123", _API_KEY, timeout=_TIMEOUT)
+                get_or_create_sandbox(_SESSION_ID, _API_KEY, timeout=_TIMEOUT)
             )
 
         assert result is sb
         mock_cls.create.assert_not_called()
+        # redis.set called once to refresh TTL, not to claim a creation slot
+        redis.set.assert_awaited_once()
 
-    def test_create_new_when_no_key(self):
-        """When Redis is empty, claim lock and create a new sandbox."""
-        sb = _mock_sandbox("sb-new")
-        redis = _mock_redis(get_val=None, set_nx_result=True)
+    def test_create_new_when_no_stored_id(self):
+        """When Redis has no sandbox_id, claim slot and create a new sandbox."""
+        new_sb = _mock_sandbox("sb-new")
+        redis = _mock_redis(set_nx_result=True, stored_sandbox_id=None)
         with (
             patch("backend.copilot.tools.e2b_sandbox.AsyncSandbox") as mock_cls,
             _patch_redis(redis),
         ):
-            mock_cls.create = AsyncMock(return_value=sb)
+            mock_cls.create = AsyncMock(return_value=new_sb)
             result = asyncio.run(
-                get_or_create_sandbox("sess-123", _API_KEY, timeout=_TIMEOUT)
+                get_or_create_sandbox(_SESSION_ID, _API_KEY, timeout=_TIMEOUT)
             )
 
-        assert result is sb
-        redis.setex.assert_awaited_once_with(_KEY, _TIMEOUT, "sb-new")
+        assert result is new_sb
+        mock_cls.create.assert_awaited_once()
+        # Verify lifecycle param is set
+        _, kwargs = mock_cls.create.call_args
+        assert kwargs.get("lifecycle") == {"on_timeout": "pause"}
+        # sandbox_id should be saved to Redis
+        redis.set.assert_awaited()
 
-    def test_create_failure_clears_lock(self):
-        """If sandbox creation fails, the Redis lock is deleted."""
-        redis = _mock_redis(get_val=None, set_nx_result=True)
+    def test_create_with_on_timeout_kill(self):
+        """on_timeout='kill' is passed through to AsyncSandbox.create."""
+        new_sb = _mock_sandbox("sb-new")
+        redis = _mock_redis(set_nx_result=True, stored_sandbox_id=None)
+        with (
+            patch("backend.copilot.tools.e2b_sandbox.AsyncSandbox") as mock_cls,
+            _patch_redis(redis),
+        ):
+            mock_cls.create = AsyncMock(return_value=new_sb)
+            asyncio.run(
+                get_or_create_sandbox(
+                    _SESSION_ID, _API_KEY, timeout=_TIMEOUT, on_timeout="kill"
+                )
+            )
+
+        _, kwargs = mock_cls.create.call_args
+        assert kwargs.get("lifecycle") == {"on_timeout": "kill"}
+
+    def test_create_failure_releases_slot(self):
+        """If sandbox creation fails, the Redis creation slot is deleted."""
+        redis = _mock_redis(set_nx_result=True, stored_sandbox_id=None)
         with (
             patch("backend.copilot.tools.e2b_sandbox.AsyncSandbox") as mock_cls,
             _patch_redis(redis),
@@ -142,17 +191,53 @@ class TestGetOrCreateSandbox:
             mock_cls.create = AsyncMock(side_effect=RuntimeError("quota"))
             with pytest.raises(RuntimeError, match="quota"):
                 asyncio.run(
-                    get_or_create_sandbox("sess-123", _API_KEY, timeout=_TIMEOUT)
+                    get_or_create_sandbox(_SESSION_ID, _API_KEY, timeout=_TIMEOUT)
                 )
 
-        redis.delete.assert_awaited_once_with(_KEY)
+        redis.delete.assert_awaited_once()
 
-    def test_wait_for_lock_then_reconnect(self):
-        """When another process holds the lock, wait and reconnect."""
+    def test_redis_save_failure_kills_sandbox_and_releases_slot(self):
+        """If Redis save fails after creation, sandbox is killed and slot released."""
+        new_sb = _mock_sandbox("sb-new")
+        redis = _mock_redis(set_nx_result=True, stored_sandbox_id=None)
+        # First set() call = creation slot SET NX (returns True).
+        # Second set() call = sandbox_id save (raises).
+        call_count = 0
+
+        async def _set_side_effect(*args, **kwargs):
+            nonlocal call_count
+            call_count += 1
+            if call_count == 1:
+                return True  # creation slot claimed
+            raise RuntimeError("redis error")
+
+        redis.set = AsyncMock(side_effect=_set_side_effect)
+
+        with (
+            patch("backend.copilot.tools.e2b_sandbox.AsyncSandbox") as mock_cls,
+            _patch_redis(redis),
+        ):
+            mock_cls.create = AsyncMock(return_value=new_sb)
+            with pytest.raises(RuntimeError, match="redis error"):
+                asyncio.run(
+                    get_or_create_sandbox(_SESSION_ID, _API_KEY, timeout=_TIMEOUT)
+                )
+
+        # Sandbox must be killed to avoid leaking it
+        new_sb.kill.assert_awaited_once()
+        # Creation slot must always be released
+        redis.delete.assert_awaited_once()
+
+    def test_wait_for_creating_sentinel_then_reconnect(self):
+        """When the key holds the 'creating' sentinel, wait then reconnect."""
         sb = _mock_sandbox("sb-other")
-        redis = _mock_redis()
-        redis.get = AsyncMock(side_effect=[_CREATING, "sb-other"])
+        # First get() returns the sentinel; second returns the real ID.
+        redis = AsyncMock()
+        creating_raw = _CREATING_SENTINEL.encode()
+        redis.get = AsyncMock(side_effect=[creating_raw, b"sb-other"])
         redis.set = AsyncMock(return_value=False)
+        redis.delete = AsyncMock()
+
         with (
             patch("backend.copilot.tools.e2b_sandbox.AsyncSandbox") as mock_cls,
             _patch_redis(redis),
@@ -163,16 +248,21 @@ class TestGetOrCreateSandbox:
         ):
             mock_cls.connect = AsyncMock(return_value=sb)
             result = asyncio.run(
-                get_or_create_sandbox("sess-123", _API_KEY, timeout=_TIMEOUT)
+                get_or_create_sandbox(_SESSION_ID, _API_KEY, timeout=_TIMEOUT)
             )
 
         assert result is sb
 
     def test_stale_reconnect_clears_and_creates(self):
-        """When stored sandbox is stale, clear key and create a new one."""
+        """When stored sandbox is stale (not running), clear it and create a new one."""
         stale_sb = _mock_sandbox("sb-stale", running=False)
         new_sb = _mock_sandbox("sb-fresh")
-        redis = _mock_redis(get_val="sb-stale", set_nx_result=True)
+        # First get() returns stale id (for reconnect check), then None (after clear).
+        redis = AsyncMock()
+        redis.get = AsyncMock(side_effect=[b"sb-stale", None])
+        redis.set = AsyncMock(return_value=True)
+        redis.delete = AsyncMock()
+
         with (
             patch("backend.copilot.tools.e2b_sandbox.AsyncSandbox") as mock_cls,
             _patch_redis(redis),
@@ -180,10 +270,11 @@ class TestGetOrCreateSandbox:
             mock_cls.connect = AsyncMock(return_value=stale_sb)
             mock_cls.create = AsyncMock(return_value=new_sb)
             result = asyncio.run(
-                get_or_create_sandbox("sess-123", _API_KEY, timeout=_TIMEOUT)
+                get_or_create_sandbox(_SESSION_ID, _API_KEY, timeout=_TIMEOUT)
             )
 
         assert result is new_sb
+        # Redis delete called at least once to clear stale id
         redis.delete.assert_awaited()
 
 
@@ -194,70 +285,48 @@ class TestGetOrCreateSandbox:
 
 class TestKillSandbox:
     def test_kill_existing_sandbox(self):
-        """Kill a running sandbox and clean up Redis."""
+        """Kill a running sandbox and clear its Redis entry."""
         sb = _mock_sandbox()
-        sb.kill = AsyncMock()
-        redis = _mock_redis(get_val="sb-abc")
+        redis = _mock_redis(stored_sandbox_id=_SANDBOX_ID)
         with (
             patch("backend.copilot.tools.e2b_sandbox.AsyncSandbox") as mock_cls,
             _patch_redis(redis),
         ):
             mock_cls.connect = AsyncMock(return_value=sb)
-            result = asyncio.run(kill_sandbox("sess-123", _API_KEY))
+            result = asyncio.run(kill_sandbox(_SESSION_ID, _API_KEY))
 
         assert result is True
-        redis.delete.assert_awaited_once_with(_KEY)
         sb.kill.assert_awaited_once()
+        # Redis key cleared after successful kill
+        redis.delete.assert_awaited_once()
 
     def test_kill_no_sandbox(self):
-        """No-op when no sandbox exists in Redis."""
-        redis = _mock_redis(get_val=None)
+        """No-op when Redis has no sandbox_id."""
+        redis = _mock_redis(stored_sandbox_id=None)
         with _patch_redis(redis):
-            result = asyncio.run(kill_sandbox("sess-123", _API_KEY))
+            result = asyncio.run(kill_sandbox(_SESSION_ID, _API_KEY))
 
         assert result is False
-        redis.delete.assert_not_awaited()
 
-    def test_kill_creating_state(self):
-        """Clears Redis key but returns False when sandbox is still being created."""
-        redis = _mock_redis(get_val=_CREATING)
-        with _patch_redis(redis):
-            result = asyncio.run(kill_sandbox("sess-123", _API_KEY))
+    def test_kill_connect_failure_keeps_redis(self):
+        """Returns False and leaves Redis entry intact when connect/kill fails.
 
-        assert result is False
-        redis.delete.assert_awaited_once_with(_KEY)
-
-    def test_kill_connect_failure(self):
-        """Returns False and cleans Redis if connect/kill fails."""
-        redis = _mock_redis(get_val="sb-abc")
+        Keeping the sandbox_id in Redis allows the kill to be retried.
+        """
+        redis = _mock_redis(stored_sandbox_id=_SANDBOX_ID)
         with (
             patch("backend.copilot.tools.e2b_sandbox.AsyncSandbox") as mock_cls,
             _patch_redis(redis),
         ):
             mock_cls.connect = AsyncMock(side_effect=ConnectionError("gone"))
-            result = asyncio.run(kill_sandbox("sess-123", _API_KEY))
+            result = asyncio.run(kill_sandbox(_SESSION_ID, _API_KEY))
 
         assert result is False
-        redis.delete.assert_awaited_once_with(_KEY)
+        redis.delete.assert_not_awaited()
 
-    def test_kill_with_bytes_redis_value(self):
-        """Redis may return bytes — kill_sandbox should decode correctly."""
-        sb = _mock_sandbox()
-        sb.kill = AsyncMock()
-        redis = _mock_redis(get_val=b"sb-abc")
-        with (
-            patch("backend.copilot.tools.e2b_sandbox.AsyncSandbox") as mock_cls,
-            _patch_redis(redis),
-        ):
-            mock_cls.connect = AsyncMock(return_value=sb)
-            result = asyncio.run(kill_sandbox("sess-123", _API_KEY))
-
-        assert result is True
-        sb.kill.assert_awaited_once()
-
-    def test_kill_timeout_returns_false(self):
-        """Returns False when E2B API calls exceed the 10s timeout."""
-        redis = _mock_redis(get_val="sb-abc")
+    def test_kill_timeout_keeps_redis(self):
+        """Returns False and leaves Redis entry intact when the E2B call times out."""
+        redis = _mock_redis(stored_sandbox_id=_SANDBOX_ID)
         with (
             _patch_redis(redis),
             patch(
@@ -266,7 +335,146 @@ class TestKillSandbox:
                 side_effect=asyncio.TimeoutError,
             ),
         ):
-            result = asyncio.run(kill_sandbox("sess-123", _API_KEY))
+            result = asyncio.run(kill_sandbox(_SESSION_ID, _API_KEY))
+
+        assert result is False
+        redis.delete.assert_not_awaited()
+
+    def test_kill_creating_sentinel_returns_false(self):
+        """No-op when the key holds the 'creating' sentinel (no real sandbox yet)."""
+        redis = _mock_redis(stored_sandbox_id=_CREATING_SENTINEL)
+        with _patch_redis(redis):
+            result = asyncio.run(kill_sandbox(_SESSION_ID, _API_KEY))
+
+        assert result is False
+
+
+# ---------------------------------------------------------------------------
+# pause_sandbox
+# ---------------------------------------------------------------------------
+
+
+class TestPauseSandbox:
+    def test_pause_existing_sandbox(self):
+        """Pause a running sandbox; Redis sandbox_id is preserved."""
+        sb = _mock_sandbox()
+        redis = _mock_redis(stored_sandbox_id=_SANDBOX_ID)
+        with (
+            patch("backend.copilot.tools.e2b_sandbox.AsyncSandbox") as mock_cls,
+            _patch_redis(redis),
+        ):
+            mock_cls.connect = AsyncMock(return_value=sb)
+            result = asyncio.run(pause_sandbox(_SESSION_ID, _API_KEY))
+
+        assert result is True
+        sb.pause.assert_awaited_once()
+        # sandbox_id should remain in Redis (not cleared on pause)
+        redis.delete.assert_not_awaited()
+
+    def test_pause_no_sandbox(self):
+        """No-op when Redis has no sandbox_id."""
+        redis = _mock_redis(stored_sandbox_id=None)
+        with _patch_redis(redis):
+            result = asyncio.run(pause_sandbox(_SESSION_ID, _API_KEY))
+
+        assert result is False
+
+    def test_pause_connect_failure(self):
+        """Returns False if connect fails."""
+        redis = _mock_redis(stored_sandbox_id=_SANDBOX_ID)
+        with (
+            patch("backend.copilot.tools.e2b_sandbox.AsyncSandbox") as mock_cls,
+            _patch_redis(redis),
+        ):
+            mock_cls.connect = AsyncMock(side_effect=ConnectionError("gone"))
+            result = asyncio.run(pause_sandbox(_SESSION_ID, _API_KEY))
+
+        assert result is False
+
+    def test_pause_creating_sentinel_returns_false(self):
+        """No-op when the key holds the 'creating' sentinel (no real sandbox yet)."""
+        redis = _mock_redis(stored_sandbox_id=_CREATING_SENTINEL)
+        with _patch_redis(redis):
+            result = asyncio.run(pause_sandbox(_SESSION_ID, _API_KEY))
+
+        assert result is False
+
+    def test_pause_timeout_returns_false(self):
+        """Returns False and preserves Redis entry when the E2B API call times out."""
+        redis = _mock_redis(stored_sandbox_id=_SANDBOX_ID)
+        with (
+            _patch_redis(redis),
+            patch(
+                "backend.copilot.tools.e2b_sandbox.asyncio.wait_for",
+                new_callable=AsyncMock,
+                side_effect=asyncio.TimeoutError,
+            ),
+        ):
+            result = asyncio.run(pause_sandbox(_SESSION_ID, _API_KEY))
+
+        assert result is False
+        # sandbox_id must remain in Redis so the next turn can reconnect
+        redis.delete.assert_not_awaited()
+
+    def test_pause_then_reconnect_reuses_sandbox(self):
+        """After pause, get_or_create_sandbox reconnects the same sandbox.
+
+        Covers the pause->reconnect cycle: connect() auto-resumes a paused
+        sandbox, and is_running() returns True once resume completes, so the
+        same sandbox_id is reused rather than a new one being created.
+        """
+        sb = _mock_sandbox(_SANDBOX_ID)
+        redis = _mock_redis(stored_sandbox_id=_SANDBOX_ID)
+        with (
+            patch("backend.copilot.tools.e2b_sandbox.AsyncSandbox") as mock_cls,
+            _patch_redis(redis),
+        ):
+            mock_cls.connect = AsyncMock(return_value=sb)
+
+            # Step 1: pause the sandbox
+            paused = asyncio.run(pause_sandbox(_SESSION_ID, _API_KEY))
+            assert paused is True
+            sb.pause.assert_awaited_once()
+
+            # Step 2: reconnect on next turn -- same sandbox should be returned
+            result = asyncio.run(
+                get_or_create_sandbox(_SESSION_ID, _API_KEY, timeout=_TIMEOUT)
+            )
+
+        assert result is sb
+        mock_cls.create.assert_not_called()
+
+
+# ---------------------------------------------------------------------------
+# pause_sandbox_direct
+# ---------------------------------------------------------------------------
+
+
+class TestPauseSandboxDirect:
+    def test_pause_direct_success(self):
+        """Pauses the sandbox directly without a Redis lookup or reconnect."""
+        sb = _mock_sandbox()
+        result = asyncio.run(pause_sandbox_direct(sb, _SESSION_ID))
+
+        assert result is True
+        sb.pause.assert_awaited_once()
+
+    def test_pause_direct_failure_returns_false(self):
+        """Returns False when sandbox.pause() raises."""
+        sb = _mock_sandbox()
+        sb.pause = AsyncMock(side_effect=RuntimeError("e2b error"))
+        result = asyncio.run(pause_sandbox_direct(sb, _SESSION_ID))
+
+        assert result is False
+
+    def test_pause_direct_timeout_returns_false(self):
+        """Returns False when sandbox.pause() exceeds the 10s timeout."""
+        sb = _mock_sandbox()
+        with patch(
+            "backend.copilot.tools.e2b_sandbox.asyncio.wait_for",
+            new_callable=AsyncMock,
+            side_effect=asyncio.TimeoutError,
+        ):
+            result = asyncio.run(pause_sandbox_direct(sb, _SESSION_ID))
 
         assert result is False
-        redis.delete.assert_awaited_once_with(_KEY)

autogpt_platform/backend/backend/copilot/tools/edit_agent.py

@@ -1,32 +1,20 @@
-"""EditAgentTool - Edits existing agents using natural language."""
+"""EditAgentTool - Edits existing agents using pre-built JSON."""
 
 import logging
 from typing import Any
 
 from backend.copilot.model import ChatSession
 
-from .agent_generator import (
-    AgentGeneratorNotConfiguredError,
-    generate_agent_patch,
-    get_agent_as_json,
-    get_user_message_for_error,
-    save_agent_to_library,
-)
+from .agent_generator import get_agent_as_json
+from .agent_generator.pipeline import fetch_library_agents, fix_validate_and_save
 from .base import BaseTool
-from .models import (
-    AgentPreviewResponse,
-    AgentSavedResponse,
-    ClarificationNeededResponse,
-    ClarifyingQuestion,
-    ErrorResponse,
-    ToolResponseBase,
-)
+from .models import ErrorResponse, ToolResponseBase
 
 logger = logging.getLogger(__name__)
 
 
 class EditAgentTool(BaseTool):
-    """Tool for editing existing agents using natural language."""
+    """Tool for editing existing agents using pre-built JSON."""
 
     @property
     def name(self) -> str:
@@ -35,11 +23,12 @@ class EditAgentTool(BaseTool):
     @property
     def description(self) -> str:
         return (
-            "Edit an existing agent from the user's library using natural language. "
-            "Generates updates to the agent while preserving unchanged parts. "
-            "\n\nIMPORTANT: Before calling this tool, if the changes involve adding new "
+            "Edit an existing agent. Pass `agent_json` with the complete "
+            "updated agent JSON you generated. The tool validates, auto-fixes, "
+            "and saves.\n\n"
+            "IMPORTANT: Before calling this tool, if the changes involve adding new "
             "functionality, search for relevant existing agents using find_library_agent "
-            "that could be used as building blocks. Pass their IDs in library_agent_ids."
+            "that could be used as building blocks."
         )
 
     @property
@@ -58,26 +47,20 @@ class EditAgentTool(BaseTool):
                         "Can be a graph ID or library agent ID."
                     ),
                 },
-                "changes": {
-                    "type": "string",
+                "agent_json": {
+                    "type": "object",
                     "description": (
-                        "Natural language description of what changes to make. "
-                        "Be specific about what to add, remove, or modify."
-                    ),
-                },
-                "context": {
-                    "type": "string",
-                    "description": (
-                        "Additional context or answers to previous clarifying questions."
+                        "Complete updated agent JSON to validate and save. "
+                        "Must contain 'nodes' and 'links'. "
+                        "Include 'name' and/or 'description' if they need "
+                        "to be updated."
                     ),
                 },
                 "library_agent_ids": {
                     "type": "array",
                     "items": {"type": "string"},
                     "description": (
-                        "List of library agent IDs to use as building blocks for the changes. "
-                        "If adding new functionality, search for relevant agents using "
-                        "find_library_agent first, then pass their IDs here."
+                        "List of library agent IDs to use as building blocks for the changes."
                     ),
                 },
                 "save": {
@@ -89,7 +72,7 @@ class EditAgentTool(BaseTool):
                     "default": True,
                 },
             },
-            "required": ["agent_id", "changes"],
+            "required": ["agent_id", "agent_json"],
         }
 
     async def _execute(
@@ -98,36 +81,39 @@ class EditAgentTool(BaseTool):
         session: ChatSession,
         **kwargs,
     ) -> ToolResponseBase:
-        """Execute the edit_agent tool.
-
-        Flow:
-        1. Fetch the current agent
-        2. Generate updated agent (external service handles fixing and validation)
-        3. Preview or save based on the save parameter
-        """
         agent_id = kwargs.get("agent_id", "").strip()
-        changes = kwargs.get("changes", "").strip()
-        context = kwargs.get("context", "")
-        library_agent_ids = kwargs.get("library_agent_ids", [])
-        save = kwargs.get("save", True)
+        agent_json: dict[str, Any] | None = kwargs.get("agent_json")
         session_id = session.session_id if session else None
 
         if not agent_id:
             return ErrorResponse(
                 message="Please provide the agent ID to edit.",
-                error="Missing agent_id parameter",
+                error="missing_agent_id",
                 session_id=session_id,
             )
 
-        if not changes:
+        if not agent_json:
             return ErrorResponse(
-                message="Please describe what changes you want to make.",
-                error="Missing changes parameter",
+                message=(
+                    "Please provide agent_json with the complete updated agent graph."
+                ),
+                error="missing_agent_json",
                 session_id=session_id,
             )
 
-        current_agent = await get_agent_as_json(agent_id, user_id)
+        save = kwargs.get("save", True)
+        library_agent_ids = kwargs.get("library_agent_ids", [])
 
+        nodes = agent_json.get("nodes", [])
+        if not nodes:
+            return ErrorResponse(
+                message="The agent JSON has no nodes.",
+                error="empty_agent",
+                session_id=session_id,
+            )
+
+        # Preserve original agent's ID
+        current_agent = await get_agent_as_json(agent_id, user_id)
         if current_agent is None:
             return ErrorResponse(
                 message=f"Could not find agent with ID '{agent_id}' in your library.",
@@ -135,142 +121,19 @@ class EditAgentTool(BaseTool):
                 session_id=session_id,
             )
 
-        # Fetch library agents by IDs if provided
-        library_agents = None
-        if user_id and library_agent_ids:
-            try:
-                from .agent_generator import get_library_agents_by_ids
+        agent_json["id"] = current_agent.get("id", agent_id)
+        agent_json["version"] = current_agent.get("version", 1)
+        agent_json.setdefault("is_active", True)
 
-                graph_id = current_agent.get("id")
-                # Filter out the current agent being edited
-                filtered_ids = [id for id in library_agent_ids if id != graph_id]
+        # Fetch library agents for AgentExecutorBlock validation
+        library_agents = await fetch_library_agents(user_id, library_agent_ids)
 
-                library_agents = await get_library_agents_by_ids(
-                    user_id=user_id,
-                    agent_ids=filtered_ids,
-                )
-                logger.debug(
-                    f"Fetched {len(library_agents)} library agents by ID for sub-agent composition"
-                )
-            except Exception as e:
-                logger.warning(f"Failed to fetch library agents by IDs: {e}")
-
-        update_request = changes
-        if context:
-            update_request = f"{changes}\n\nAdditional context:\n{context}"
-
-        try:
-            result = await generate_agent_patch(
-                update_request,
-                current_agent,
-                library_agents,
-            )
-        except AgentGeneratorNotConfiguredError:
-            return ErrorResponse(
-                message=(
-                    "Agent editing is not available. "
-                    "The Agent Generator service is not configured."
-                ),
-                error="service_not_configured",
-                session_id=session_id,
-            )
-
-        if result is None:
-            return ErrorResponse(
-                message="Failed to generate changes. The agent generation service may be unavailable or timed out. Please try again.",
-                error="update_generation_failed",
-                details={"agent_id": agent_id, "changes": changes[:100]},
-                session_id=session_id,
-            )
-
-        # Check if the result is an error from the external service
-        if isinstance(result, dict) and result.get("type") == "error":
-            error_msg = result.get("error", "Unknown error")
-            error_type = result.get("error_type", "unknown")
-            user_message = get_user_message_for_error(
-                error_type,
-                operation="generate the changes",
-                llm_parse_message="The AI had trouble generating the changes. Please try again or simplify your request.",
-                validation_message="The generated changes failed validation. Please try rephrasing your request.",
-                error_details=error_msg,
-            )
-            return ErrorResponse(
-                message=user_message,
-                error=f"update_generation_failed:{error_type}",
-                details={
-                    "agent_id": agent_id,
-                    "changes": changes[:100],
-                    "service_error": error_msg,
-                    "error_type": error_type,
-                },
-                session_id=session_id,
-            )
-
-        if result.get("type") == "clarifying_questions":
-            questions = result.get("questions", [])
-            return ClarificationNeededResponse(
-                message=(
-                    "I need some more information about the changes. "
-                    "Please answer the following questions:"
-                ),
-                questions=[
-                    ClarifyingQuestion(
-                        question=q.get("question", ""),
-                        keyword=q.get("keyword", ""),
-                        example=q.get("example"),
-                    )
-                    for q in questions
-                ],
-                session_id=session_id,
-            )
-
-        updated_agent = result
-
-        agent_name = updated_agent.get("name", "Updated Agent")
-        agent_description = updated_agent.get("description", "")
-        node_count = len(updated_agent.get("nodes", []))
-        link_count = len(updated_agent.get("links", []))
-
-        if not save:
-            return AgentPreviewResponse(
-                message=(
-                    f"I've updated the agent. "
-                    f"The agent now has {node_count} blocks. "
-                    f"Review it and call edit_agent with save=true to save the changes."
-                ),
-                agent_json=updated_agent,
-                agent_name=agent_name,
-                description=agent_description,
-                node_count=node_count,
-                link_count=link_count,
-                session_id=session_id,
-            )
-
-        if not user_id:
-            return ErrorResponse(
-                message="You must be logged in to save agents.",
-                error="auth_required",
-                session_id=session_id,
-            )
-
-        try:
-            created_graph, library_agent = await save_agent_to_library(
-                updated_agent, user_id, is_update=True
-            )
-
-            return AgentSavedResponse(
-                message=f"Updated agent '{created_graph.name}' has been saved to your library!",
-                agent_id=created_graph.id,
-                agent_name=created_graph.name,
-                library_agent_id=library_agent.id,
-                library_agent_link=f"/library/agents/{library_agent.id}",
-                agent_page_link=f"/build?flowID={created_graph.id}",
-                session_id=session_id,
-            )
-        except Exception as e:
-            return ErrorResponse(
-                message=f"Failed to save the updated agent: {str(e)}",
-                error="save_failed",
-                details={"exception": str(e)},
-                session_id=session_id,
-            )
+        return await fix_validate_and_save(
+            agent_json,
+            user_id=user_id,
+            session_id=session_id,
+            save=save,
+            is_update=True,
+            default_name="Updated Agent",
+            library_agents=library_agents,
+        )

autogpt_platform/backend/backend/copilot/tools/find_block.py

@@ -32,7 +32,7 @@ COPILOT_EXCLUDED_BLOCK_TYPES = {
     BlockType.NOTE,  # Visual annotation only - no runtime behavior
     BlockType.HUMAN_IN_THE_LOOP,  # Pauses for human approval - CoPilot IS human-in-the-loop
     BlockType.AGENT,  # AgentExecutorBlock requires execution_context - use run_agent tool
-    BlockType.MCP_TOOL,  # Has dedicated run_mcp_tool tool with proper discovery + auth flow
+    BlockType.MCP_TOOL,  # Has dedicated run_mcp_tool tool with discovery + auth flow
 }
 
 # Specific block IDs excluded from CoPilot (STANDARD type but still require graph context)
@@ -72,6 +72,15 @@ class FindBlockTool(BaseTool):
                         "Use keywords like 'email', 'http', 'text', 'ai', etc."
                     ),
                 },
+                "include_schemas": {
+                    "type": "boolean",
+                    "description": (
+                        "If true, include full input_schema and output_schema "
+                        "for each block. Use when generating agent JSON that "
+                        "needs block schemas. Default is false."
+                    ),
+                    "default": False,
+                },
             },
             "required": ["query"],
         }
@@ -99,6 +108,7 @@ class FindBlockTool(BaseTool):
             ErrorResponse: Error message
         """
         query = kwargs.get("query", "").strip()
+        include_schemas = kwargs.get("include_schemas", False)
         session_id = session.session_id
 
         if not query:
@@ -143,15 +153,21 @@ class FindBlockTool(BaseTool):
                 ):
                     continue
 
-                blocks.append(
-                    BlockInfoSummary(
-                        id=block_id,
-                        name=block.name,
-                        description=block.description or "",
-                        categories=[c.value for c in block.categories],
-                    )
+                summary = BlockInfoSummary(
+                    id=block_id,
+                    name=block.name,
+                    description=block.optimized_description or block.description or "",
+                    categories=[c.value for c in block.categories],
                 )
 
+                if include_schemas:
+                    info = block.get_info()
+                    summary.input_schema = info.inputSchema
+                    summary.output_schema = info.outputSchema
+                    summary.static_output = info.staticOutput
+
+                blocks.append(summary)
+
                 if len(blocks) >= _TARGET_RESULTS:
                     break
 

autogpt_platform/backend/backend/copilot/tools/find_block_test.py

@@ -25,6 +25,7 @@ def make_mock_block(
     input_schema: dict | None = None,
     output_schema: dict | None = None,
     credentials_fields: dict | None = None,
+    static_output: bool = False,
 ):
     """Create a mock block for testing."""
     mock = MagicMock()
@@ -33,6 +34,7 @@ def make_mock_block(
     mock.description = f"{name} description"
     mock.block_type = block_type
     mock.disabled = disabled
+    mock.static_output = static_output
     mock.input_schema = MagicMock()
     mock.input_schema.jsonschema.return_value = input_schema or {
         "properties": {},
@@ -42,6 +44,15 @@ def make_mock_block(
     mock.output_schema = MagicMock()
     mock.output_schema.jsonschema.return_value = output_schema or {}
     mock.categories = []
+    mock.optimized_description = None
+
+    # Mock get_info() for include_schemas support
+    mock_info = MagicMock()
+    mock_info.inputSchema = input_schema or {"properties": {}, "required": []}
+    mock_info.outputSchema = output_schema or {}
+    mock_info.staticOutput = static_output
+    mock.get_info.return_value = mock_info
+
     return mock
 
 
@@ -399,3 +410,92 @@ class TestFindBlockFiltering:
             f"Average chars per block ({avg_chars}) exceeds 500. "
             f"Total response: {total_chars} chars for {response.count} blocks."
         )
+
+    @pytest.mark.asyncio(loop_scope="session")
+    async def test_include_schemas_false_omits_schemas(self):
+        """Without include_schemas, schemas should be empty dicts."""
+        session = make_session(user_id=_TEST_USER_ID)
+        input_schema = {"properties": {"url": {"type": "string"}}, "required": ["url"]}
+        output_schema = {"properties": {"result": {"type": "string"}}}
+
+        search_results = [{"content_id": "block-1", "score": 0.9}]
+        block = make_mock_block(
+            "block-1",
+            "Test Block",
+            BlockType.STANDARD,
+            input_schema=input_schema,
+            output_schema=output_schema,
+        )
+
+        mock_search_db = MagicMock()
+        mock_search_db.unified_hybrid_search = AsyncMock(
+            return_value=(search_results, 1)
+        )
+
+        with (
+            patch(
+                "backend.copilot.tools.find_block.search",
+                return_value=mock_search_db,
+            ),
+            patch(
+                "backend.copilot.tools.find_block.get_block",
+                return_value=block,
+            ),
+        ):
+            tool = FindBlockTool()
+            response = await tool._execute(
+                user_id=_TEST_USER_ID,
+                session=session,
+                query="test",
+                include_schemas=False,
+            )
+
+        assert isinstance(response, BlockListResponse)
+        assert response.blocks[0].input_schema == {}
+        assert response.blocks[0].output_schema == {}
+        assert response.blocks[0].static_output is False
+
+    @pytest.mark.asyncio(loop_scope="session")
+    async def test_include_schemas_true_populates_schemas(self):
+        """With include_schemas=true, schemas should be populated from block info."""
+        session = make_session(user_id=_TEST_USER_ID)
+        input_schema = {"properties": {"url": {"type": "string"}}, "required": ["url"]}
+        output_schema = {"properties": {"result": {"type": "string"}}}
+
+        search_results = [{"content_id": "block-1", "score": 0.9}]
+        block = make_mock_block(
+            "block-1",
+            "Test Block",
+            BlockType.STANDARD,
+            input_schema=input_schema,
+            output_schema=output_schema,
+            static_output=True,
+        )
+
+        mock_search_db = MagicMock()
+        mock_search_db.unified_hybrid_search = AsyncMock(
+            return_value=(search_results, 1)
+        )
+
+        with (
+            patch(
+                "backend.copilot.tools.find_block.search",
+                return_value=mock_search_db,
+            ),
+            patch(
+                "backend.copilot.tools.find_block.get_block",
+                return_value=block,
+            ),
+        ):
+            tool = FindBlockTool()
+            response = await tool._execute(
+                user_id=_TEST_USER_ID,
+                session=session,
+                query="test",
+                include_schemas=True,
+            )
+
+        assert isinstance(response, BlockListResponse)
+        assert response.blocks[0].input_schema == input_schema
+        assert response.blocks[0].output_schema == output_schema
+        assert response.blocks[0].static_output is True

autogpt_platform/backend/backend/copilot/tools/find_library_agent.py

@@ -22,6 +22,9 @@ class FindLibraryAgentTool(BaseTool):
             "Search for or list agents in the user's library. Use this to find "
             "agents the user has already added to their library, including agents "
             "they created or added from the marketplace. "
+            "When creating agents with sub-agent composition, use this to get "
+            "the agent's graph_id, graph_version, input_schema, and output_schema "
+            "needed for AgentExecutorBlock nodes. "
             "Omit the query to list all agents."
         )
 

autogpt_platform/backend/backend/copilot/tools/fix_agent.py

@@ -0,0 +1,134 @@
+"""FixAgentGraphTool - Auto-fixes common agent JSON issues."""
+
+import logging
+from typing import Any
+
+from backend.copilot.model import ChatSession
+
+from .agent_generator.validation import AgentFixer, AgentValidator, get_blocks_as_dicts
+from .base import BaseTool
+from .models import ErrorResponse, FixResultResponse, ToolResponseBase
+
+logger = logging.getLogger(__name__)
+
+
+class FixAgentGraphTool(BaseTool):
+    """Tool for auto-fixing common issues in agent JSON graphs."""
+
+    @property
+    def name(self) -> str:
+        return "fix_agent_graph"
+
+    @property
+    def description(self) -> str:
+        return (
+            "Auto-fix common issues in an agent JSON graph. Applies fixes for:\n"
+            "- Missing or invalid UUIDs on nodes and links\n"
+            "- StoreValueBlock prerequisites for ConditionBlock\n"
+            "- Double curly brace escaping in prompt templates\n"
+            "- AddToList/AddToDictionary prerequisite blocks\n"
+            "- CodeExecutionBlock output field naming\n"
+            "- Missing credentials configuration\n"
+            "- Node X coordinate spacing (800+ units apart)\n"
+            "- AI model default parameters\n"
+            "- Link static properties based on input schema\n"
+            "- Type mismatches (inserts conversion blocks)\n\n"
+            "Returns the fixed agent JSON plus a list of fixes applied. "
+            "After fixing, the agent is re-validated. If still invalid, "
+            "the remaining errors are included in the response."
+        )
+
+    @property
+    def requires_auth(self) -> bool:
+        return False
+
+    @property
+    def parameters(self) -> dict[str, Any]:
+        return {
+            "type": "object",
+            "properties": {
+                "agent_json": {
+                    "type": "object",
+                    "description": (
+                        "The agent JSON to fix. Must contain 'nodes' and 'links' arrays."
+                    ),
+                },
+            },
+            "required": ["agent_json"],
+        }
+
+    async def _execute(
+        self,
+        user_id: str | None,
+        session: ChatSession,
+        **kwargs,
+    ) -> ToolResponseBase:
+        agent_json = kwargs.get("agent_json")
+        session_id = session.session_id if session else None
+
+        if not agent_json or not isinstance(agent_json, dict):
+            return ErrorResponse(
+                message="Please provide a valid agent JSON object.",
+                error="Missing or invalid agent_json parameter",
+                session_id=session_id,
+            )
+
+        nodes = agent_json.get("nodes", [])
+
+        if not nodes:
+            return ErrorResponse(
+                message="The agent JSON has no nodes. An agent needs at least one block.",
+                error="empty_agent",
+                session_id=session_id,
+            )
+
+        try:
+            blocks = get_blocks_as_dicts()
+            fixer = AgentFixer()
+            fixed_agent = fixer.apply_all_fixes(agent_json, blocks)
+            fixes_applied = fixer.get_fixes_applied()
+        except Exception as e:
+            logger.error(f"Fixer error: {e}", exc_info=True)
+            return ErrorResponse(
+                message=f"Auto-fix encountered an error: {str(e)}",
+                error="fix_exception",
+                session_id=session_id,
+            )
+
+        # Re-validate after fixing
+        try:
+            validator = AgentValidator()
+            is_valid, _ = validator.validate(fixed_agent, blocks)
+            remaining_errors = validator.errors if not is_valid else []
+        except Exception as e:
+            logger.warning(f"Post-fix validation error: {e}", exc_info=True)
+            remaining_errors = [f"Post-fix validation failed: {str(e)}"]
+            is_valid = False
+
+        if is_valid:
+            return FixResultResponse(
+                message=(
+                    f"Applied {len(fixes_applied)} fix(es). "
+                    "Agent graph is now valid!"
+                ),
+                fixed_agent_json=fixed_agent,
+                fixes_applied=fixes_applied,
+                fix_count=len(fixes_applied),
+                valid_after_fix=True,
+                remaining_errors=[],
+                session_id=session_id,
+            )
+
+        return FixResultResponse(
+            message=(
+                f"Applied {len(fixes_applied)} fix(es), but "
+                f"{len(remaining_errors)} issue(s) remain. "
+                "Review the remaining errors and fix manually."
+            ),
+            fixed_agent_json=fixed_agent,
+            fixes_applied=fixes_applied,
+            fix_count=len(fixes_applied),
+            valid_after_fix=False,
+            remaining_errors=remaining_errors,
+            session_id=session_id,
+        )

autogpt_platform/backend/backend/copilot/tools/fix_agent_test.py

@@ -0,0 +1,189 @@
+"""Tests for FixAgentGraphTool."""
+
+from unittest.mock import MagicMock, patch
+
+import pytest
+
+from backend.copilot.tools.fix_agent import FixAgentGraphTool
+from backend.copilot.tools.models import ErrorResponse, FixResultResponse
+
+from ._test_data import make_session
+
+_TEST_USER_ID = "test-user-fix-agent"
+
+
+@pytest.fixture
+def tool():
+    return FixAgentGraphTool()
+
+
+@pytest.fixture
+def session():
+    return make_session(_TEST_USER_ID)
+
+
+@pytest.mark.asyncio
+async def test_missing_agent_json_returns_error(tool, session):
+    """Missing agent_json returns ErrorResponse."""
+    result = await tool._execute(user_id=_TEST_USER_ID, session=session)
+    assert isinstance(result, ErrorResponse)
+    assert result.error is not None
+    assert "agent_json" in result.error.lower()
+
+
+@pytest.mark.asyncio
+async def test_empty_nodes_returns_error(tool, session):
+    """Agent JSON with no nodes returns ErrorResponse."""
+    result = await tool._execute(
+        user_id=_TEST_USER_ID,
+        session=session,
+        agent_json={"nodes": [], "links": []},
+    )
+    assert isinstance(result, ErrorResponse)
+    assert "no nodes" in result.message.lower()
+
+
+@pytest.mark.asyncio
+async def test_fix_and_validate_success(tool, session):
+    """Fixer applies fixes and validator passes -> valid_after_fix=True."""
+    agent_json = {
+        "nodes": [
+            {
+                "id": "node-1",
+                "block_id": "block-1",
+                "input_default": {},
+                "metadata": {"position": {"x": 0, "y": 0}},
+            }
+        ],
+        "links": [],
+    }
+
+    fixed_agent = dict(agent_json)  # Fixer returns the full agent dict
+
+    mock_fixer = MagicMock()
+    mock_fixer.apply_all_fixes = MagicMock(return_value=fixed_agent)
+    mock_fixer.get_fixes_applied.return_value = ["Fixed node UUID format"]
+
+    mock_validator = MagicMock()
+    mock_validator.validate.return_value = (True, None)
+    mock_validator.errors = []
+
+    with (
+        patch(
+            "backend.copilot.tools.fix_agent.get_blocks_as_dicts",
+            return_value=[],
+        ),
+        patch(
+            "backend.copilot.tools.fix_agent.AgentFixer",
+            return_value=mock_fixer,
+        ),
+        patch(
+            "backend.copilot.tools.fix_agent.AgentValidator",
+            return_value=mock_validator,
+        ),
+    ):
+        result = await tool._execute(
+            user_id=_TEST_USER_ID,
+            session=session,
+            agent_json=agent_json,
+        )
+
+    assert isinstance(result, FixResultResponse)
+    assert result.valid_after_fix is True
+    assert result.fix_count == 1
+    assert result.fixes_applied == ["Fixed node UUID format"]
+    assert result.remaining_errors == []
+
+
+@pytest.mark.asyncio
+async def test_fix_with_remaining_errors(tool, session):
+    """Fixer applies some fixes but validation still fails."""
+    agent_json = {
+        "nodes": [
+            {
+                "id": "node-1",
+                "block_id": "block-1",
+                "input_default": {},
+                "metadata": {},
+            }
+        ],
+        "links": [
+            {
+                "id": "link-1",
+                "source_id": "node-1",
+                "source_name": "output",
+                "sink_id": "node-2",
+                "sink_name": "input",
+            }
+        ],
+    }
+
+    fixed_agent = dict(agent_json)
+
+    mock_fixer = MagicMock()
+    mock_fixer.apply_all_fixes = MagicMock(return_value=fixed_agent)
+    mock_fixer.get_fixes_applied.return_value = ["Fixed UUID"]
+
+    mock_validator = MagicMock()
+    mock_validator.validate.return_value = (
+        False,
+        "Link references non-existent node 'node-2'",
+    )
+    mock_validator.errors = ["Link references non-existent node 'node-2'"]
+
+    with (
+        patch(
+            "backend.copilot.tools.fix_agent.get_blocks_as_dicts",
+            return_value=[],
+        ),
+        patch(
+            "backend.copilot.tools.fix_agent.AgentFixer",
+            return_value=mock_fixer,
+        ),
+        patch(
+            "backend.copilot.tools.fix_agent.AgentValidator",
+            return_value=mock_validator,
+        ),
+    ):
+        result = await tool._execute(
+            user_id=_TEST_USER_ID,
+            session=session,
+            agent_json=agent_json,
+        )
+
+    assert isinstance(result, FixResultResponse)
+    assert result.valid_after_fix is False
+    assert result.fix_count == 1
+    assert len(result.remaining_errors) == 1
+
+
+@pytest.mark.asyncio
+async def test_fixer_exception_returns_error(tool, session):
+    """Fixer exception returns ErrorResponse."""
+    agent_json = {
+        "nodes": [{"id": "n1", "block_id": "b1", "input_default": {}, "metadata": {}}],
+        "links": [],
+    }
+
+    mock_fixer = MagicMock()
+    mock_fixer.apply_all_fixes = MagicMock(side_effect=RuntimeError("fixer crashed"))
+
+    with (
+        patch(
+            "backend.copilot.tools.fix_agent.get_blocks_as_dicts",
+            return_value=[],
+        ),
+        patch(
+            "backend.copilot.tools.fix_agent.AgentFixer",
+            return_value=mock_fixer,
+        ),
+    ):
+        result = await tool._execute(
+            user_id=_TEST_USER_ID,
+            session=session,
+            agent_json=agent_json,
+        )
+
+    assert isinstance(result, ErrorResponse)
+    assert result.error is not None
+    assert "fix_exception" in result.error

autogpt_platform/backend/backend/copilot/tools/get_agent_building_guide.py

@@ -0,0 +1,84 @@
+"""GetAgentBuildingGuideTool - Returns the complete agent building guide."""
+
+import logging
+from pathlib import Path
+from typing import Any
+
+from backend.copilot.model import ChatSession
+
+from .base import BaseTool
+from .models import ErrorResponse, ResponseType, ToolResponseBase
+
+logger = logging.getLogger(__name__)
+
+_GUIDE_CACHE: str | None = None
+
+
+def _load_guide() -> str:
+    global _GUIDE_CACHE
+    if _GUIDE_CACHE is None:
+        guide_path = Path(__file__).parent.parent / "sdk" / "agent_generation_guide.md"
+        _GUIDE_CACHE = guide_path.read_text(encoding="utf-8")
+    return _GUIDE_CACHE
+
+
+class AgentBuildingGuideResponse(ToolResponseBase):
+    """Response containing the agent building guide."""
+
+    type: ResponseType = ResponseType.AGENT_BUILDER_GUIDE
+    content: str
+
+
+class GetAgentBuildingGuideTool(BaseTool):
+    """Returns the complete guide for building agent JSON graphs.
+
+    Covers block IDs, link structure, AgentInputBlock, AgentOutputBlock,
+    AgentExecutorBlock (sub-agent composition), and MCPToolBlock usage.
+    """
+
+    @property
+    def name(self) -> str:
+        return "get_agent_building_guide"
+
+    @property
+    def description(self) -> str:
+        return (
+            "Returns the complete guide for building agent JSON graphs, including "
+            "block IDs, link structure, AgentInputBlock, AgentOutputBlock, "
+            "AgentExecutorBlock (for sub-agent composition), and MCPToolBlock usage. "
+            "Call this before generating agent JSON to ensure correct structure."
+        )
+
+    @property
+    def parameters(self) -> dict[str, Any]:
+        return {
+            "type": "object",
+            "properties": {},
+            "required": [],
+        }
+
+    @property
+    def requires_auth(self) -> bool:
+        return False
+
+    async def _execute(
+        self,
+        user_id: str | None,
+        session: ChatSession,
+        **kwargs,
+    ) -> ToolResponseBase:
+        session_id = session.session_id if session else None
+        try:
+            content = _load_guide()
+            return AgentBuildingGuideResponse(
+                message="Agent building guide loaded.",
+                content=content,
+                session_id=session_id,
+            )
+        except Exception as e:
+            logger.error("Failed to load agent building guide: %s", e)
+            return ErrorResponse(
+                message="Failed to load agent building guide.",
+                error=str(e),
+                session_id=session_id,
+            )

autogpt_platform/backend/backend/copilot/tools/get_mcp_guide.py

@@ -0,0 +1,79 @@
+"""GetMCPGuideTool - Returns the MCP tool usage guide."""
+
+import logging
+from pathlib import Path
+from typing import Any
+
+from backend.copilot.model import ChatSession
+
+from .base import BaseTool
+from .models import ErrorResponse, ResponseType, ToolResponseBase
+
+logger = logging.getLogger(__name__)
+
+_GUIDE_CACHE: str | None = None
+
+
+def _load_guide() -> str:
+    global _GUIDE_CACHE
+    if _GUIDE_CACHE is None:
+        guide_path = Path(__file__).parent.parent / "sdk" / "mcp_tool_guide.md"
+        _GUIDE_CACHE = guide_path.read_text(encoding="utf-8")
+    return _GUIDE_CACHE
+
+
+class MCPGuideResponse(ToolResponseBase):
+    """Response containing the MCP tool guide."""
+
+    type: ResponseType = ResponseType.MCP_GUIDE
+    content: str
+
+
+class GetMCPGuideTool(BaseTool):
+    """Returns the MCP tool usage guide with known server URLs and auth details."""
+
+    @property
+    def name(self) -> str:
+        return "get_mcp_guide"
+
+    @property
+    def description(self) -> str:
+        return (
+            "Returns the MCP tool guide: known hosted server URLs (Notion, Linear, "
+            "Stripe, Intercom, Cloudflare, Atlassian) and authentication workflow. "
+            "Call before using run_mcp_tool if you need a server URL or auth info."
+        )
+
+    @property
+    def parameters(self) -> dict[str, Any]:
+        return {
+            "type": "object",
+            "properties": {},
+            "required": [],
+        }
+
+    @property
+    def requires_auth(self) -> bool:
+        return False
+
+    async def _execute(
+        self,
+        user_id: str | None,
+        session: ChatSession,
+        **kwargs,
+    ) -> ToolResponseBase:
+        session_id = session.session_id if session else None
+        try:
+            content = _load_guide()
+            return MCPGuideResponse(
+                message="MCP guide loaded.",
+                content=content,
+                session_id=session_id,
+            )
+        except Exception as e:
+            logger.error("Failed to load MCP guide: %s", e)
+            return ErrorResponse(
+                message="Failed to load MCP guide.",
+                error=str(e),
+                session_id=session_id,
+            )

autogpt_platform/backend/backend/copilot/tools/manage_folders.py

@@ -0,0 +1,573 @@
+"""Folder management tools for the copilot."""
+
+from typing import Any
+
+from backend.api.features.library import model as library_model
+from backend.api.features.library.db import collect_tree_ids
+from backend.copilot.model import ChatSession
+from backend.data.db_accessors import library_db
+
+from .base import BaseTool
+from .models import (
+    AgentsMovedToFolderResponse,
+    ErrorResponse,
+    FolderAgentSummary,
+    FolderCreatedResponse,
+    FolderDeletedResponse,
+    FolderInfo,
+    FolderListResponse,
+    FolderMovedResponse,
+    FolderTreeInfo,
+    FolderUpdatedResponse,
+    ToolResponseBase,
+)
+
+
+def _folder_to_info(
+    folder: library_model.LibraryFolder,
+    agents: list[FolderAgentSummary] | None = None,
+) -> FolderInfo:
+    """Convert a LibraryFolder DB model to a FolderInfo response model."""
+    return FolderInfo(
+        id=folder.id,
+        name=folder.name,
+        parent_id=folder.parent_id,
+        icon=folder.icon,
+        color=folder.color,
+        agent_count=folder.agent_count,
+        subfolder_count=folder.subfolder_count,
+        agents=agents,
+    )
+
+
+def _tree_to_info(
+    tree: library_model.LibraryFolderTree,
+    agents_map: dict[str, list[FolderAgentSummary]] | None = None,
+) -> FolderTreeInfo:
+    """Recursively convert a LibraryFolderTree to a FolderTreeInfo response."""
+    return FolderTreeInfo(
+        id=tree.id,
+        name=tree.name,
+        parent_id=tree.parent_id,
+        icon=tree.icon,
+        color=tree.color,
+        agent_count=tree.agent_count,
+        subfolder_count=tree.subfolder_count,
+        children=[_tree_to_info(child, agents_map) for child in tree.children],
+        agents=agents_map.get(tree.id) if agents_map else None,
+    )
+
+
+def _to_agent_summaries(
+    raw: list[dict[str, str | None]],
+) -> list[FolderAgentSummary]:
+    """Convert raw agent dicts to typed FolderAgentSummary models."""
+    return [
+        FolderAgentSummary(
+            id=a["id"] or "",
+            name=a["name"] or "",
+            description=a["description"] or "",
+        )
+        for a in raw
+    ]
+
+
+def _to_agent_summaries_map(
+    raw: dict[str, list[dict[str, str | None]]],
+) -> dict[str, list[FolderAgentSummary]]:
+    """Convert a folder-id-keyed dict of raw agents to typed summaries."""
+    return {fid: _to_agent_summaries(agents) for fid, agents in raw.items()}
+
+
+class CreateFolderTool(BaseTool):
+    """Tool for creating a library folder."""
+
+    @property
+    def name(self) -> str:
+        return "create_folder"
+
+    @property
+    def description(self) -> str:
+        return (
+            "Create a new folder in the user's library to organize agents. "
+            "Optionally nest it inside an existing folder using parent_id."
+        )
+
+    @property
+    def requires_auth(self) -> bool:
+        return True
+
+    @property
+    def parameters(self) -> dict[str, Any]:
+        return {
+            "type": "object",
+            "properties": {
+                "name": {
+                    "type": "string",
+                    "description": "Name for the new folder (max 100 chars).",
+                },
+                "parent_id": {
+                    "type": "string",
+                    "description": (
+                        "ID of the parent folder to nest inside. "
+                        "Omit to create at root level."
+                    ),
+                },
+                "icon": {
+                    "type": "string",
+                    "description": "Optional icon identifier for the folder.",
+                },
+                "color": {
+                    "type": "string",
+                    "description": "Optional hex color code (#RRGGBB).",
+                },
+            },
+            "required": ["name"],
+        }
+
+    async def _execute(
+        self, user_id: str | None, session: ChatSession, **kwargs
+    ) -> ToolResponseBase:
+        """Create a folder with the given name and optional parent/icon/color."""
+        assert user_id is not None  # guaranteed by requires_auth
+        name = (kwargs.get("name") or "").strip()
+        parent_id = kwargs.get("parent_id")
+        icon = kwargs.get("icon")
+        color = kwargs.get("color")
+        session_id = session.session_id if session else None
+
+        if not name:
+            return ErrorResponse(
+                message="Please provide a folder name.",
+                error="missing_name",
+                session_id=session_id,
+            )
+
+        try:
+            folder = await library_db().create_folder(
+                user_id=user_id,
+                name=name,
+                parent_id=parent_id,
+                icon=icon,
+                color=color,
+            )
+        except Exception as e:
+            return ErrorResponse(
+                message=f"Failed to create folder: {e}",
+                error="create_folder_failed",
+                session_id=session_id,
+            )
+
+        return FolderCreatedResponse(
+            message=f"Folder '{folder.name}' created successfully!",
+            folder=_folder_to_info(folder),
+            session_id=session_id,
+        )
+
+
+class ListFoldersTool(BaseTool):
+    """Tool for listing library folders."""
+
+    @property
+    def name(self) -> str:
+        return "list_folders"
+
+    @property
+    def description(self) -> str:
+        return (
+            "List the user's library folders. "
+            "Omit parent_id to get the full folder tree. "
+            "Provide parent_id to list only direct children of that folder. "
+            "Set include_agents=true to also return the agents inside each folder "
+            "and root-level agents not in any folder. Always set include_agents=true "
+            "when the user asks about agents, wants to see what's in their folders, "
+            "or mentions agents alongside folders."
+        )
+
+    @property
+    def requires_auth(self) -> bool:
+        return True
+
+    @property
+    def parameters(self) -> dict[str, Any]:
+        return {
+            "type": "object",
+            "properties": {
+                "parent_id": {
+                    "type": "string",
+                    "description": (
+                        "List children of this folder. "
+                        "Omit to get the full folder tree."
+                    ),
+                },
+                "include_agents": {
+                    "type": "boolean",
+                    "description": (
+                        "Whether to include the list of agents inside each folder. "
+                        "Defaults to false."
+                    ),
+                },
+            },
+            "required": [],
+        }
+
+    async def _execute(
+        self, user_id: str | None, session: ChatSession, **kwargs
+    ) -> ToolResponseBase:
+        """List folders as a flat list (by parent) or full tree."""
+        assert user_id is not None  # guaranteed by requires_auth
+        parent_id = kwargs.get("parent_id")
+        include_agents = kwargs.get("include_agents", False)
+        session_id = session.session_id if session else None
+
+        try:
+            if parent_id:
+                folders = await library_db().list_folders(
+                    user_id=user_id, parent_id=parent_id
+                )
+                raw_map = (
+                    await library_db().get_folder_agents_map(
+                        user_id, [f.id for f in folders]
+                    )
+                    if include_agents
+                    else None
+                )
+                agents_map = _to_agent_summaries_map(raw_map) if raw_map else None
+                return FolderListResponse(
+                    message=f"Found {len(folders)} folder(s).",
+                    folders=[
+                        _folder_to_info(f, agents_map.get(f.id) if agents_map else None)
+                        for f in folders
+                    ],
+                    count=len(folders),
+                    session_id=session_id,
+                )
+            else:
+                tree = await library_db().get_folder_tree(user_id=user_id)
+                all_ids = collect_tree_ids(tree)
+                agents_map = None
+                root_agents = None
+                if include_agents:
+                    raw_map = await library_db().get_folder_agents_map(user_id, all_ids)
+                    agents_map = _to_agent_summaries_map(raw_map)
+                    root_agents = _to_agent_summaries(
+                        await library_db().get_root_agent_summaries(user_id)
+                    )
+                return FolderListResponse(
+                    message=f"Found {len(all_ids)} folder(s) in your library.",
+                    tree=[_tree_to_info(t, agents_map) for t in tree],
+                    root_agents=root_agents,
+                    count=len(all_ids),
+                    session_id=session_id,
+                )
+        except Exception as e:
+            return ErrorResponse(
+                message=f"Failed to list folders: {e}",
+                error="list_folders_failed",
+                session_id=session_id,
+            )
+
+
+class UpdateFolderTool(BaseTool):
+    """Tool for updating a folder's properties."""
+
+    @property
+    def name(self) -> str:
+        return "update_folder"
+
+    @property
+    def description(self) -> str:
+        return "Update a folder's name, icon, or color."
+
+    @property
+    def requires_auth(self) -> bool:
+        return True
+
+    @property
+    def parameters(self) -> dict[str, Any]:
+        return {
+            "type": "object",
+            "properties": {
+                "folder_id": {
+                    "type": "string",
+                    "description": "ID of the folder to update.",
+                },
+                "name": {
+                    "type": "string",
+                    "description": "New name for the folder.",
+                },
+                "icon": {
+                    "type": "string",
+                    "description": "New icon identifier.",
+                },
+                "color": {
+                    "type": "string",
+                    "description": "New hex color code (#RRGGBB).",
+                },
+            },
+            "required": ["folder_id"],
+        }
+
+    async def _execute(
+        self, user_id: str | None, session: ChatSession, **kwargs
+    ) -> ToolResponseBase:
+        """Update a folder's name, icon, or color."""
+        assert user_id is not None  # guaranteed by requires_auth
+        folder_id = (kwargs.get("folder_id") or "").strip()
+        name = kwargs.get("name")
+        icon = kwargs.get("icon")
+        color = kwargs.get("color")
+        session_id = session.session_id if session else None
+
+        if not folder_id:
+            return ErrorResponse(
+                message="Please provide a folder_id.",
+                error="missing_folder_id",
+                session_id=session_id,
+            )
+
+        try:
+            folder = await library_db().update_folder(
+                folder_id=folder_id,
+                user_id=user_id,
+                name=name,
+                icon=icon,
+                color=color,
+            )
+        except Exception as e:
+            return ErrorResponse(
+                message=f"Failed to update folder: {e}",
+                error="update_folder_failed",
+                session_id=session_id,
+            )
+
+        return FolderUpdatedResponse(
+            message=f"Folder updated to '{folder.name}'.",
+            folder=_folder_to_info(folder),
+            session_id=session_id,
+        )
+
+
+class MoveFolderTool(BaseTool):
+    """Tool for moving a folder to a new parent."""
+
+    @property
+    def name(self) -> str:
+        return "move_folder"
+
+    @property
+    def description(self) -> str:
+        return (
+            "Move a folder to a different parent folder. "
+            "Set target_parent_id to null to move to root level."
+        )
+
+    @property
+    def requires_auth(self) -> bool:
+        return True
+
+    @property
+    def parameters(self) -> dict[str, Any]:
+        return {
+            "type": "object",
+            "properties": {
+                "folder_id": {
+                    "type": "string",
+                    "description": "ID of the folder to move.",
+                },
+                "target_parent_id": {
+                    "type": ["string", "null"],
+                    "description": (
+                        "ID of the new parent folder. "
+                        "Use null to move to root level."
+                    ),
+                },
+            },
+            "required": ["folder_id"],
+        }
+
+    async def _execute(
+        self, user_id: str | None, session: ChatSession, **kwargs
+    ) -> ToolResponseBase:
+        """Move a folder to a new parent or to root level."""
+        assert user_id is not None  # guaranteed by requires_auth
+        folder_id = (kwargs.get("folder_id") or "").strip()
+        target_parent_id = kwargs.get("target_parent_id")
+        session_id = session.session_id if session else None
+
+        if not folder_id:
+            return ErrorResponse(
+                message="Please provide a folder_id.",
+                error="missing_folder_id",
+                session_id=session_id,
+            )
+
+        try:
+            folder = await library_db().move_folder(
+                folder_id=folder_id,
+                user_id=user_id,
+                target_parent_id=target_parent_id,
+            )
+        except Exception as e:
+            return ErrorResponse(
+                message=f"Failed to move folder: {e}",
+                error="move_folder_failed",
+                session_id=session_id,
+            )
+
+        dest = "a subfolder" if target_parent_id else "root level"
+        return FolderMovedResponse(
+            message=f"Folder '{folder.name}' moved to {dest}.",
+            folder=_folder_to_info(folder),
+            target_parent_id=target_parent_id,
+            session_id=session_id,
+        )
+
+
+class DeleteFolderTool(BaseTool):
+    """Tool for deleting a folder."""
+
+    @property
+    def name(self) -> str:
+        return "delete_folder"
+
+    @property
+    def description(self) -> str:
+        return (
+            "Delete a folder from the user's library. "
+            "Agents inside the folder are moved to root level (not deleted)."
+        )
+
+    @property
+    def requires_auth(self) -> bool:
+        return True
+
+    @property
+    def parameters(self) -> dict[str, Any]:
+        return {
+            "type": "object",
+            "properties": {
+                "folder_id": {
+                    "type": "string",
+                    "description": "ID of the folder to delete.",
+                },
+            },
+            "required": ["folder_id"],
+        }
+
+    async def _execute(
+        self, user_id: str | None, session: ChatSession, **kwargs
+    ) -> ToolResponseBase:
+        """Soft-delete a folder; agents inside are moved to root level."""
+        assert user_id is not None  # guaranteed by requires_auth
+        folder_id = (kwargs.get("folder_id") or "").strip()
+        session_id = session.session_id if session else None
+
+        if not folder_id:
+            return ErrorResponse(
+                message="Please provide a folder_id.",
+                error="missing_folder_id",
+                session_id=session_id,
+            )
+
+        try:
+            await library_db().delete_folder(
+                folder_id=folder_id,
+                user_id=user_id,
+                soft_delete=True,
+            )
+        except Exception as e:
+            return ErrorResponse(
+                message=f"Failed to delete folder: {e}",
+                error="delete_folder_failed",
+                session_id=session_id,
+            )
+
+        return FolderDeletedResponse(
+            message="Folder deleted. Any agents inside were moved to root level.",
+            folder_id=folder_id,
+            session_id=session_id,
+        )
+
+
+class MoveAgentsToFolderTool(BaseTool):
+    """Tool for moving agents into a folder."""
+
+    @property
+    def name(self) -> str:
+        return "move_agents_to_folder"
+
+    @property
+    def description(self) -> str:
+        return (
+            "Move one or more agents to a folder. "
+            "Set folder_id to null to move agents to root level."
+        )
+
+    @property
+    def requires_auth(self) -> bool:
+        return True
+
+    @property
+    def parameters(self) -> dict[str, Any]:
+        return {
+            "type": "object",
+            "properties": {
+                "agent_ids": {
+                    "type": "array",
+                    "items": {"type": "string"},
+                    "description": "List of library agent IDs to move.",
+                },
+                "folder_id": {
+                    "type": ["string", "null"],
+                    "description": (
+                        "Target folder ID. Use null to move to root level."
+                    ),
+                },
+            },
+            "required": ["agent_ids"],
+        }
+
+    async def _execute(
+        self, user_id: str | None, session: ChatSession, **kwargs
+    ) -> ToolResponseBase:
+        """Move one or more agents to a folder or to root level."""
+        assert user_id is not None  # guaranteed by requires_auth
+        agent_ids = kwargs.get("agent_ids", [])
+        folder_id = kwargs.get("folder_id")
+        session_id = session.session_id if session else None
+
+        if not agent_ids:
+            return ErrorResponse(
+                message="Please provide at least one agent ID.",
+                error="missing_agent_ids",
+                session_id=session_id,
+            )
+
+        try:
+            moved = await library_db().bulk_move_agents_to_folder(
+                agent_ids=agent_ids,
+                folder_id=folder_id,
+                user_id=user_id,
+            )
+        except Exception as e:
+            return ErrorResponse(
+                message=f"Failed to move agents: {e}",
+                error="move_agents_failed",
+                session_id=session_id,
+            )
+
+        moved_ids = [a.id for a in moved]
+        agent_names = [a.name for a in moved]
+        dest = "the folder" if folder_id else "root level"
+        names_str = (
+            ", ".join(agent_names) if agent_names else f"{len(agent_ids)} agent(s)"
+        )
+        return AgentsMovedToFolderResponse(
+            message=f"Moved {names_str} to {dest}.",
+            agent_ids=moved_ids,
+            agent_names=agent_names,
+            folder_id=folder_id,
+            count=len(moved),
+            session_id=session_id,
+        )