fix(frontend): upgrade Docker Node.js from v21 (EOL) to v22 LTS (#12561)

## Summary
Upgrade the frontend **Docker image** from **Node.js v21** (EOL since
June 2024) to **Node.js v22 LTS** (supported through April 2027).

> **Scope:** This only affects the **Dockerfile** used for local
development (`docker compose`) and CI. It does **not** affect Vercel
(which manages its own Node.js runtime) or Kubernetes (the frontend Helm
chart was removed in Dec 2025 — the frontend is deployed exclusively via
Vercel).

## Why
- Node v21.7.3 has a **known TransformStream race condition bug**
causing `TypeError: controller[kState].transformAlgorithm is not a
function` — this is
[BUILDER-3KF](https://significant-gravitas.sentry.io/issues/BUILDER-3KF)
with **567,000+ Sentry events**
- The error is entirely in Node.js internals
(`node:internal/webstreams/transformstream`), zero first-party code
- Node 21 is **not an LTS release** and has been EOL since June 2024
- `package.json` already declares `"engines": { "node": "22.x" }` — the
Dockerfile was inconsistent
- Node 22.x LTS (v22.22.1) fixes the TransformStream bug
- Next.js 15.4.x requires Node 18.18+, so Node 22 is fully compatible

## Changes
- `autogpt_platform/frontend/Dockerfile`: `node:21-alpine` →
`node:22.22-alpine3.23` (both `base` and `prod` stages)

## Test plan
- [ ] Verify frontend Docker image builds successfully via `docker
compose`
- [ ] Verify frontend starts and serves pages correctly in local Docker
environment
- [ ] Monitor Sentry for BUILDER-3KF — should drop to zero for
Docker-based runs

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

@@ -1,106 +0,0 @@
----
-name: open-pr
-description: Open a pull request with proper PR template, test coverage, and review workflow. Guides agents through creating a PR that follows repo conventions, ensures existing behaviors aren't broken, covers new behaviors with tests, and handles review via bot when local testing isn't possible. TRIGGER when user asks to "open a PR", "create a PR", "make a PR", "submit a PR", "open pull request", "push and create PR", or any variation of opening/submitting a pull request.
-user-invocable: true
-args: "[base-branch] — optional target branch (defaults to dev)."
-metadata:
-  author: autogpt-team
-  version: "1.0.0"
----
-
-# Open a Pull Request
-
-## Step 1: Pre-flight checks
-
-Before opening the PR:
-
-1. Ensure all changes are committed
-2. Ensure the branch is pushed to the remote (`git push -u origin <branch>`)
-3. Run linters/formatters across the whole repo (not just changed files) and commit any fixes
-
-## Step 2: Test coverage
-
-**This is critical.** Before opening the PR, verify:
-
-### Existing behavior is not broken
-- Identify which modules/components your changes touch
-- Run the existing test suites for those areas
-- If tests fail, fix them before opening the PR — do not open a PR with known regressions
-
-### New behavior has test coverage
-- Every new feature, endpoint, or behavior change needs tests
-- If you added a new block, add tests for that block
-- If you changed API behavior, add or update API tests
-- If you changed frontend behavior, verify it doesn't break existing flows
-
-If you cannot run the full test suite locally, note which tests you ran and which you couldn't in the test plan.
-
-## Step 3: Create the PR using the repo template
-
-Read the canonical PR template at `.github/PULL_REQUEST_TEMPLATE.md` and use it **verbatim** as your PR body:
-
-1. Read the template: `cat .github/PULL_REQUEST_TEMPLATE.md`
-2. Preserve the exact section titles and formatting, including:
-   - `### Why / What / How`
-   - `### Changes 🏗️`
-   - `### Checklist 📋`
-3. Replace HTML comment prompts (`<!-- ... -->`) with actual content; do not leave them in
-4. **Do not pre-check boxes** — leave all checkboxes as `- [ ]` until each step is actually completed
-5. Do not alter the template structure, rename sections, or remove any checklist items
-
-**PR title must use conventional commit format** (e.g., `feat(backend): add new block`, `fix(frontend): resolve routing bug`, `dx(skills): update PR workflow`). See CLAUDE.md for the full list of scopes.
-
-Use `gh pr create` with the base branch (defaults to `dev` if no `[base-branch]` was provided). Use `--body-file` to avoid shell interpretation of backticks and special characters:
-
-```bash
-BASE_BRANCH="${BASE_BRANCH:-dev}"
-PR_BODY=$(mktemp)
-cat > "$PR_BODY" << 'PREOF'
-<filled-in template from .github/PULL_REQUEST_TEMPLATE.md>
-PREOF
-gh pr create --base "$BASE_BRANCH" --title "<type>(scope): short description" --body-file "$PR_BODY"
-rm "$PR_BODY"
-```
-
-## Step 4: Review workflow
-
-### If you have a workspace that allows testing (docker, running backend, etc.)
-- Run `/pr-test` to do E2E manual testing of the PR using docker compose, agent-browser, and API calls. This is the most thorough way to validate your changes before review.
-- After testing, run `/pr-review` to self-review the PR for correctness, security, code quality, and testing gaps before requesting human review.
-
-### If you do NOT have a workspace that allows testing
-This is common for agents running in worktrees without a full stack. In this case:
-
-1. Run `/pr-review` locally to catch obvious issues before pushing
-2. **Comment `/review` on the PR** after creating it to trigger the review bot
-3. **Poll for the review** rather than blindly waiting — check for new review comments every 30 seconds using `gh api repos/Significant-Gravitas/AutoGPT/pulls/{N}/reviews --paginate` and the GraphQL inline threads query. The bot typically responds within 30 minutes, but polling lets the agent react as soon as it arrives.
-4. Do NOT proceed or merge until the bot review comes back
-5. Address any issues the bot raises — use `/pr-address` which has a full polling loop with CI + comment tracking
-
-```bash
-# After creating the PR:
-PR_NUMBER=$(gh pr view --json number -q .number)
-gh pr comment "$PR_NUMBER" --body "/review"
-# Then use /pr-address to poll for and address the review when it arrives
-```
-
-## Step 5: Address review feedback
-
-Once the review bot or human reviewers leave comments:
-- Run `/pr-address` to address review comments. It will loop until CI is green and all comments are resolved.
-- Do not merge without human approval.
-
-## Related skills
-
-| Skill | When to use |
-|---|---|
-| `/pr-test` | E2E testing with docker compose, agent-browser, API calls — use when you have a running workspace |
-| `/pr-review` | Review for correctness, security, code quality — use before requesting human review |
-| `/pr-address` | Address reviewer comments and loop until CI green — use after reviews come in |
-
-## Step 6: Post-creation
-
-After the PR is created and review is triggered:
-- Share the PR URL with the user
-- If waiting on the review bot, let the user know the expected wait time (~30 min)
-- Do not merge without human approval

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

@@ -1,195 +0,0 @@
----
-name: setup-repo
-description: Initialize a worktree-based repo layout for parallel development. Creates a main worktree, a reviews worktree for PR reviews, and N numbered work branches. Handles .env creation, dependency installation, and branchlet config. TRIGGER when user asks to set up the repo from scratch, initialize worktrees, bootstrap their dev environment, "setup repo", "setup worktrees", "initialize dev environment", "set up branches", or when a freshly cloned repo has no sibling worktrees.
-user-invocable: true
-args: "No arguments — interactive setup via prompts."
-metadata:
-  author: autogpt-team
-  version: "1.0.0"
----
-
-# Repository Setup
-
-This skill sets up a worktree-based development layout from a freshly cloned repo. It creates:
-- A **main** worktree (the primary checkout)
-- A **reviews** worktree (for PR reviews)
-- **N work branches** (branch1..branchN) for parallel development
-
-## Step 1: Identify the repo
-
-Determine the repo root and parent directory:
-
-```bash
-ROOT=$(git rev-parse --show-toplevel)
-REPO_NAME=$(basename "$ROOT")
-PARENT=$(dirname "$ROOT")
-```
-
-Detect if the repo is already inside a worktree layout by counting sibling worktrees (not just checking the directory name, which could be anything):
-
-```bash
-# Count worktrees that are siblings (live under $PARENT but aren't $ROOT itself)
-SIBLING_COUNT=$(git worktree list --porcelain 2>/dev/null | grep "^worktree " | grep -c "$PARENT/" || true)
-if [ "$SIBLING_COUNT" -gt 1 ]; then
-  echo "INFO: Existing worktree layout detected at $PARENT ($SIBLING_COUNT worktrees)"
-  # Use $ROOT as-is; skip renaming/restructuring
-else
-  echo "INFO: Fresh clone detected, proceeding with setup"
-fi
-```
-
-## Step 2: Ask the user questions
-
-Use AskUserQuestion to gather setup preferences:
-
-1. **How many parallel work branches do you need?** (Options: 4, 8, 16, or custom)
-   - These become `branch1` through `branchN`
-2. **Which branch should be the base?** (Options: origin/master, origin/dev, or custom)
-   - All work branches and reviews will start from this
-
-## Step 3: Fetch and set up branches
-
-```bash
-cd "$ROOT"
-git fetch origin
-
-# Create the reviews branch from base (skip if already exists)
-if git show-ref --verify --quiet refs/heads/reviews; then
-  echo "INFO: Branch 'reviews' already exists, skipping"
-else
-  git branch reviews <base-branch>
-fi
-
-# Create numbered work branches from base (skip if already exists)
-for i in $(seq 1 "$COUNT"); do
-  if git show-ref --verify --quiet "refs/heads/branch$i"; then
-    echo "INFO: Branch 'branch$i' already exists, skipping"
-  else
-    git branch "branch$i" <base-branch>
-  fi
-done
-```
-
-## Step 4: Create worktrees
-
-Create worktrees as siblings to the main checkout:
-
-```bash
-if [ -d "$PARENT/reviews" ]; then
-  echo "INFO: Worktree '$PARENT/reviews' already exists, skipping"
-else
-  git worktree add "$PARENT/reviews" reviews
-fi
-
-for i in $(seq 1 "$COUNT"); do
-  if [ -d "$PARENT/branch$i" ]; then
-    echo "INFO: Worktree '$PARENT/branch$i' already exists, skipping"
-  else
-    git worktree add "$PARENT/branch$i" "branch$i"
-  fi
-done
-```
-
-## Step 5: Set up environment files
-
-**Do NOT assume .env files exist.** For each worktree (including main if needed):
-
-1. Check if `.env` exists in the source worktree for each path
-2. If `.env` exists, copy it
-3. If only `.env.default` or `.env.example` exists, copy that as `.env`
-4. If neither exists, warn the user and list which env files are missing
-
-Env file locations to check (same as the `/worktree` skill — keep these in sync):
-- `autogpt_platform/.env`
-- `autogpt_platform/backend/.env`
-- `autogpt_platform/frontend/.env`
-
-> **Note:** This env copying logic intentionally mirrors the `/worktree` skill's approach. If you update the path list or fallback logic here, update `/worktree` as well.
-
-```bash
-SOURCE="$ROOT"
-WORKTREES="reviews"
-for i in $(seq 1 "$COUNT"); do WORKTREES="$WORKTREES branch$i"; done
-
-FOUND_ANY_ENV=0
-for wt in $WORKTREES; do
-  TARGET="$PARENT/$wt"
-  for envpath in autogpt_platform autogpt_platform/backend autogpt_platform/frontend; do
-    if [ -f "$SOURCE/$envpath/.env" ]; then
-      FOUND_ANY_ENV=1
-      cp "$SOURCE/$envpath/.env" "$TARGET/$envpath/.env"
-    elif [ -f "$SOURCE/$envpath/.env.default" ]; then
-      FOUND_ANY_ENV=1
-      cp "$SOURCE/$envpath/.env.default" "$TARGET/$envpath/.env"
-      echo "NOTE: $wt/$envpath/.env was created from .env.default — you may need to edit it"
-    elif [ -f "$SOURCE/$envpath/.env.example" ]; then
-      FOUND_ANY_ENV=1
-      cp "$SOURCE/$envpath/.env.example" "$TARGET/$envpath/.env"
-      echo "NOTE: $wt/$envpath/.env was created from .env.example — you may need to edit it"
-    else
-      echo "WARNING: No .env, .env.default, or .env.example found at $SOURCE/$envpath/"
-    fi
-  done
-done
-
-if [ "$FOUND_ANY_ENV" -eq 0 ]; then
-  echo "WARNING: No environment files or templates were found in the source worktree."
-  # Use AskUserQuestion to confirm: "Continue setup without env files?"
-  # If the user declines, stop here and let them set up .env files first.
-fi
-```
-
-## Step 6: Copy branchlet config
-
-Copy `.branchlet.json` from main to each worktree so branchlet can manage sub-worktrees:
-
-```bash
-if [ -f "$ROOT/.branchlet.json" ]; then
-  for wt in $WORKTREES; do
-    cp "$ROOT/.branchlet.json" "$PARENT/$wt/.branchlet.json"
-  done
-fi
-```
-
-## Step 7: Install dependencies
-
-Install deps in all worktrees. Run these sequentially per worktree:
-
-```bash
-for wt in $WORKTREES; do
-  TARGET="$PARENT/$wt"
-  echo "=== Installing deps for $wt ==="
-  (cd "$TARGET/autogpt_platform/autogpt_libs" && poetry install) &&
-  (cd "$TARGET/autogpt_platform/backend" && poetry install && poetry run prisma generate) &&
-  (cd "$TARGET/autogpt_platform/frontend" && pnpm install) &&
-  echo "=== Done: $wt ===" ||
-  echo "=== FAILED: $wt ==="
-done
-```
-
-This is slow. Run in background if possible and notify when complete.
-
-## Step 8: Verify and report
-
-After setup, verify and report to the user:
-
-```bash
-git worktree list
-```
-
-Summarize:
-- Number of worktrees created
-- Which env files were copied vs created from defaults vs missing
-- Any warnings or errors encountered
-
-## Final directory layout
-
-```
-parent/
-  main/              # Primary checkout (already exists)
-  reviews/           # PR review worktree
-  branch1/           # Work branch 1
-  branch2/           # Work branch 2
-  ...
-  branchN/           # Work branch N
-```

README.md

@@ -83,13 +83,13 @@ The AutoGPT frontend is where users interact with our powerful AI automation pla
 
    **Agent Builder:** For those who want to customize, our intuitive, low-code interface allows you to design and configure your own AI agents. 
    
-   **Workflow Management:** Build, modify, and optimize your automation workflows with ease. You build your agent by connecting blocks, where each block performs a single action.
+   **Workflow Management:** Build, modify, and optimize your automation workflows with ease. You build your agent by connecting blocks, where each block     performs a single action.
    
    **Deployment Controls:** Manage the lifecycle of your agents, from testing to production.
    
    **Ready-to-Use Agents:** Don't want to build? Simply select from our library of pre-configured agents and put them to work immediately.
    
-   **Agent Interaction:** Whether you've built your own or are using pre-configured agents, easily run and interact with them through our user-friendly interface.
+   **Agent Interaction:** Whether you've built your own or are using pre-configured agents, easily run and interact with them through our user-friendly      interface.
 
    **Monitoring and Analytics:** Keep track of your agents' performance and gain insights to continually improve your automation processes.
 

autogpt_platform/backend/.env.default

@@ -178,7 +178,6 @@ SMTP_USERNAME=
 SMTP_PASSWORD=
 
 # Business & Marketing Tools
-AGENTMAIL_API_KEY=
 APOLLO_API_KEY=
 ENRICHLAYER_API_KEY=
 AYRSHARE_API_KEY=

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

@@ -31,10 +31,7 @@ from backend.data.model import (
     UserPasswordCredentials,
     is_sdk_default,
 )
-from backend.integrations.credentials_store import (
-    is_system_credential,
-    provider_matches,
-)
+from backend.integrations.credentials_store import provider_matches
 from backend.integrations.creds_manager import IntegrationCredentialsManager
 from backend.integrations.oauth import CREDENTIALS_BY_PROVIDER, HANDLERS_BY_NAME
 from backend.integrations.providers import ProviderName
@@ -621,11 +618,6 @@ async def delete_credential(
         raise HTTPException(
             status_code=status.HTTP_404_NOT_FOUND, detail="Credentials not found"
         )
-    if is_system_credential(cred_id):
-        raise HTTPException(
-            status_code=status.HTTP_403_FORBIDDEN,
-            detail="System-managed credentials cannot be deleted",
-        )
     creds = await creds_manager.store.get_creds_by_id(auth.user_id, cred_id)
     if not creds:
         raise HTTPException(

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

@@ -1,146 +0,0 @@
-"""Admin endpoints for checking and resetting user CoPilot rate limit usage."""
-
-import logging
-from typing import Optional
-
-from autogpt_libs.auth import get_user_id, requires_admin_user
-from fastapi import APIRouter, Body, HTTPException, Security
-from pydantic import BaseModel
-
-from backend.copilot.config import ChatConfig
-from backend.copilot.rate_limit import (
-    get_global_rate_limits,
-    get_usage_status,
-    reset_user_usage,
-)
-from backend.data.user import get_user_by_email, get_user_email_by_id
-
-logger = logging.getLogger(__name__)
-
-config = ChatConfig()
-
-router = APIRouter(
-    prefix="/admin",
-    tags=["copilot", "admin"],
-    dependencies=[Security(requires_admin_user)],
-)
-
-
-class UserRateLimitResponse(BaseModel):
-    user_id: str
-    user_email: Optional[str] = None
-    daily_token_limit: int
-    weekly_token_limit: int
-    daily_tokens_used: int
-    weekly_tokens_used: int
-
-
-async def _resolve_user_id(
-    user_id: Optional[str], email: Optional[str]
-) -> tuple[str, Optional[str]]:
-    """Resolve a user_id and email from the provided parameters.
-
-    Returns (user_id, email). Accepts either user_id or email; at least one
-    must be provided.  When both are provided, ``email`` takes precedence.
-    """
-    if email:
-        user = await get_user_by_email(email)
-        if not user:
-            raise HTTPException(
-                status_code=404, detail="No user found with the provided email."
-            )
-        return user.id, email
-
-    if not user_id:
-        raise HTTPException(
-            status_code=400,
-            detail="Either user_id or email query parameter is required.",
-        )
-
-    # We have a user_id; try to look up their email for display purposes.
-    # This is non-critical -- a failure should not block the response.
-    try:
-        resolved_email = await get_user_email_by_id(user_id)
-    except Exception:
-        logger.warning("Failed to resolve email for user %s", user_id, exc_info=True)
-        resolved_email = None
-    return user_id, resolved_email
-
-
-@router.get(
-    "/rate_limit",
-    response_model=UserRateLimitResponse,
-    summary="Get User Rate Limit",
-)
-async def get_user_rate_limit(
-    user_id: Optional[str] = None,
-    email: Optional[str] = None,
-    admin_user_id: str = Security(get_user_id),
-) -> UserRateLimitResponse:
-    """Get a user's current usage and effective rate limits. Admin-only.
-
-    Accepts either ``user_id`` or ``email`` as a query parameter.
-    When ``email`` is provided the user is looked up by email first.
-    """
-    resolved_id, resolved_email = await _resolve_user_id(user_id, email)
-
-    logger.info("Admin %s checking rate limit for user %s", admin_user_id, resolved_id)
-
-    daily_limit, weekly_limit = await get_global_rate_limits(
-        resolved_id, config.daily_token_limit, config.weekly_token_limit
-    )
-    usage = await get_usage_status(resolved_id, daily_limit, weekly_limit)
-
-    return UserRateLimitResponse(
-        user_id=resolved_id,
-        user_email=resolved_email,
-        daily_token_limit=daily_limit,
-        weekly_token_limit=weekly_limit,
-        daily_tokens_used=usage.daily.used,
-        weekly_tokens_used=usage.weekly.used,
-    )
-
-
-@router.post(
-    "/rate_limit/reset",
-    response_model=UserRateLimitResponse,
-    summary="Reset User Rate Limit Usage",
-)
-async def reset_user_rate_limit(
-    user_id: str = Body(embed=True),
-    reset_weekly: bool = Body(False, embed=True),
-    admin_user_id: str = Security(get_user_id),
-) -> UserRateLimitResponse:
-    """Reset a user's daily usage counter (and optionally weekly). Admin-only."""
-    logger.info(
-        "Admin %s resetting rate limit for user %s (reset_weekly=%s)",
-        admin_user_id,
-        user_id,
-        reset_weekly,
-    )
-
-    try:
-        await reset_user_usage(user_id, reset_weekly=reset_weekly)
-    except Exception as e:
-        logger.exception("Failed to reset user usage")
-        raise HTTPException(status_code=500, detail="Failed to reset usage") from e
-
-    daily_limit, weekly_limit = await get_global_rate_limits(
-        user_id, config.daily_token_limit, config.weekly_token_limit
-    )
-    usage = await get_usage_status(user_id, daily_limit, weekly_limit)
-
-    try:
-        resolved_email = await get_user_email_by_id(user_id)
-    except Exception:
-        logger.warning("Failed to resolve email for user %s", user_id, exc_info=True)
-        resolved_email = None
-
-    return UserRateLimitResponse(
-        user_id=user_id,
-        user_email=resolved_email,
-        daily_token_limit=daily_limit,
-        weekly_token_limit=weekly_limit,
-        daily_tokens_used=usage.daily.used,
-        weekly_tokens_used=usage.weekly.used,
-    )

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

@@ -1,263 +0,0 @@
-import json
-from types import SimpleNamespace
-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
-
-from backend.copilot.rate_limit import CoPilotUsageStatus, UsageWindow
-
-from .rate_limit_admin_routes import router as rate_limit_admin_router
-
-app = fastapi.FastAPI()
-app.include_router(rate_limit_admin_router)
-
-client = fastapi.testclient.TestClient(app)
-
-_MOCK_MODULE = "backend.api.features.admin.rate_limit_admin_routes"
-
-_TARGET_EMAIL = "target@example.com"
-
-
-@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 _mock_usage_status(
-    daily_used: int = 500_000, weekly_used: int = 3_000_000
-) -> CoPilotUsageStatus:
-    from datetime import UTC, datetime, timedelta
-
-    now = datetime.now(UTC)
-    return CoPilotUsageStatus(
-        daily=UsageWindow(
-            used=daily_used, limit=2_500_000, resets_at=now + timedelta(hours=6)
-        ),
-        weekly=UsageWindow(
-            used=weekly_used, limit=12_500_000, resets_at=now + timedelta(days=3)
-        ),
-    )
-
-
-def _patch_rate_limit_deps(
-    mocker: pytest_mock.MockerFixture,
-    target_user_id: str,
-    daily_used: int = 500_000,
-    weekly_used: int = 3_000_000,
-):
-    """Patch the common rate-limit + user-lookup dependencies."""
-    mocker.patch(
-        f"{_MOCK_MODULE}.get_global_rate_limits",
-        new_callable=AsyncMock,
-        return_value=(2_500_000, 12_500_000),
-    )
-    mocker.patch(
-        f"{_MOCK_MODULE}.get_usage_status",
-        new_callable=AsyncMock,
-        return_value=_mock_usage_status(daily_used=daily_used, weekly_used=weekly_used),
-    )
-    mocker.patch(
-        f"{_MOCK_MODULE}.get_user_email_by_id",
-        new_callable=AsyncMock,
-        return_value=_TARGET_EMAIL,
-    )
-
-
-def test_get_rate_limit(
-    mocker: pytest_mock.MockerFixture,
-    configured_snapshot: Snapshot,
-    target_user_id: str,
-) -> None:
-    """Test getting rate limit and usage for a user."""
-    _patch_rate_limit_deps(mocker, target_user_id)
-
-    response = client.get("/admin/rate_limit", params={"user_id": target_user_id})
-
-    assert response.status_code == 200
-    data = response.json()
-    assert data["user_id"] == target_user_id
-    assert data["user_email"] == _TARGET_EMAIL
-    assert data["daily_token_limit"] == 2_500_000
-    assert data["weekly_token_limit"] == 12_500_000
-    assert data["daily_tokens_used"] == 500_000
-    assert data["weekly_tokens_used"] == 3_000_000
-
-    configured_snapshot.assert_match(
-        json.dumps(data, indent=2, sort_keys=True) + "\n",
-        "get_rate_limit",
-    )
-
-
-def test_get_rate_limit_by_email(
-    mocker: pytest_mock.MockerFixture,
-    target_user_id: str,
-) -> None:
-    """Test looking up rate limits via email instead of user_id."""
-    _patch_rate_limit_deps(mocker, target_user_id)
-
-    mock_user = SimpleNamespace(id=target_user_id, email=_TARGET_EMAIL)
-    mocker.patch(
-        f"{_MOCK_MODULE}.get_user_by_email",
-        new_callable=AsyncMock,
-        return_value=mock_user,
-    )
-
-    response = client.get("/admin/rate_limit", params={"email": _TARGET_EMAIL})
-
-    assert response.status_code == 200
-    data = response.json()
-    assert data["user_id"] == target_user_id
-    assert data["user_email"] == _TARGET_EMAIL
-    assert data["daily_token_limit"] == 2_500_000
-
-
-def test_get_rate_limit_by_email_not_found(
-    mocker: pytest_mock.MockerFixture,
-) -> None:
-    """Test that looking up a non-existent email returns 404."""
-    mocker.patch(
-        f"{_MOCK_MODULE}.get_user_by_email",
-        new_callable=AsyncMock,
-        return_value=None,
-    )
-
-    response = client.get("/admin/rate_limit", params={"email": "nobody@example.com"})
-
-    assert response.status_code == 404
-
-
-def test_get_rate_limit_no_params() -> None:
-    """Test that omitting both user_id and email returns 400."""
-    response = client.get("/admin/rate_limit")
-    assert response.status_code == 400
-
-
-def test_reset_user_usage_daily_only(
-    mocker: pytest_mock.MockerFixture,
-    configured_snapshot: Snapshot,
-    target_user_id: str,
-) -> None:
-    """Test resetting only daily usage (default behaviour)."""
-    mock_reset = mocker.patch(
-        f"{_MOCK_MODULE}.reset_user_usage",
-        new_callable=AsyncMock,
-    )
-    _patch_rate_limit_deps(mocker, target_user_id, daily_used=0, weekly_used=3_000_000)
-
-    response = client.post(
-        "/admin/rate_limit/reset",
-        json={"user_id": target_user_id},
-    )
-
-    assert response.status_code == 200
-    data = response.json()
-    assert data["daily_tokens_used"] == 0
-    # Weekly is untouched
-    assert data["weekly_tokens_used"] == 3_000_000
-
-    mock_reset.assert_awaited_once_with(target_user_id, reset_weekly=False)
-
-    configured_snapshot.assert_match(
-        json.dumps(data, indent=2, sort_keys=True) + "\n",
-        "reset_user_usage_daily_only",
-    )
-
-
-def test_reset_user_usage_daily_and_weekly(
-    mocker: pytest_mock.MockerFixture,
-    configured_snapshot: Snapshot,
-    target_user_id: str,
-) -> None:
-    """Test resetting both daily and weekly usage."""
-    mock_reset = mocker.patch(
-        f"{_MOCK_MODULE}.reset_user_usage",
-        new_callable=AsyncMock,
-    )
-    _patch_rate_limit_deps(mocker, target_user_id, daily_used=0, weekly_used=0)
-
-    response = client.post(
-        "/admin/rate_limit/reset",
-        json={"user_id": target_user_id, "reset_weekly": True},
-    )
-
-    assert response.status_code == 200
-    data = response.json()
-    assert data["daily_tokens_used"] == 0
-    assert data["weekly_tokens_used"] == 0
-
-    mock_reset.assert_awaited_once_with(target_user_id, reset_weekly=True)
-
-    configured_snapshot.assert_match(
-        json.dumps(data, indent=2, sort_keys=True) + "\n",
-        "reset_user_usage_daily_and_weekly",
-    )
-
-
-def test_reset_user_usage_redis_failure(
-    mocker: pytest_mock.MockerFixture,
-    target_user_id: str,
-) -> None:
-    """Test that Redis failure on reset returns 500."""
-    mocker.patch(
-        f"{_MOCK_MODULE}.reset_user_usage",
-        new_callable=AsyncMock,
-        side_effect=Exception("Redis connection refused"),
-    )
-
-    response = client.post(
-        "/admin/rate_limit/reset",
-        json={"user_id": target_user_id},
-    )
-
-    assert response.status_code == 500
-
-
-def test_get_rate_limit_email_lookup_failure(
-    mocker: pytest_mock.MockerFixture,
-    target_user_id: str,
-) -> None:
-    """Test that failing to resolve a user email degrades gracefully."""
-    mocker.patch(
-        f"{_MOCK_MODULE}.get_global_rate_limits",
-        new_callable=AsyncMock,
-        return_value=(2_500_000, 12_500_000),
-    )
-    mocker.patch(
-        f"{_MOCK_MODULE}.get_usage_status",
-        new_callable=AsyncMock,
-        return_value=_mock_usage_status(),
-    )
-    mocker.patch(
-        f"{_MOCK_MODULE}.get_user_email_by_id",
-        new_callable=AsyncMock,
-        side_effect=Exception("DB connection lost"),
-    )
-
-    response = client.get("/admin/rate_limit", params={"user_id": target_user_id})
-
-    assert response.status_code == 200
-    data = response.json()
-    assert data["user_id"] == target_user_id
-    assert data["user_email"] is None
-
-
-def test_admin_endpoints_require_admin_role(mock_jwt_user) -> None:
-    """Test that rate limit admin endpoints require admin role."""
-    app.dependency_overrides[get_jwt_payload] = mock_jwt_user["get_jwt_payload"]
-
-    response = client.get("/admin/rate_limit", params={"user_id": "test"})
-    assert response.status_code == 403
-
-    response = client.post(
-        "/admin/rate_limit/reset",
-        json={"user_id": "test"},
-    )
-    assert response.status_code == 403

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

@@ -30,14 +30,8 @@ from backend.copilot.model import (
 from backend.copilot.rate_limit import (
     CoPilotUsageStatus,
     RateLimitExceeded,
-    acquire_reset_lock,
     check_rate_limit,
-    get_daily_reset_count,
-    get_global_rate_limits,
     get_usage_status,
-    increment_daily_reset_count,
-    release_reset_lock,
-    reset_daily_usage,
 )
 from backend.copilot.response_model import StreamError, StreamFinish, StreamHeartbeat
 from backend.copilot.tools.e2b_sandbox import kill_sandbox
@@ -65,16 +59,9 @@ from backend.copilot.tools.models import (
     UnderstandingUpdatedResponse,
 )
 from backend.copilot.tracking import track_user_message
-from backend.data.credit import UsageTransactionMetadata, get_user_credit_model
 from backend.data.redis_client import get_redis_async
-from backend.data.understanding import get_business_understanding
 from backend.data.workspace import get_or_create_workspace
-from backend.util.exceptions import InsufficientBalanceError, NotFoundError
-from backend.util.settings import Settings
-
-settings = Settings()
-
-logger = logging.getLogger(__name__)
+from backend.util.exceptions import NotFoundError
 
 config = ChatConfig()
 
@@ -82,6 +69,8 @@ _UUID_RE = re.compile(
     r"^[0-9a-f]{8}-[0-9a-f]{4}-[0-9a-f]{4}-[0-9a-f]{4}-[0-9a-f]{12}$", re.I
 )
 
+logger = logging.getLogger(__name__)
+
 
 async def _validate_and_get_session(
     session_id: str,
@@ -432,187 +421,11 @@ async def get_copilot_usage(
     """Get CoPilot usage status for the authenticated user.
 
     Returns current token usage vs limits for daily and weekly windows.
-    Global defaults sourced from LaunchDarkly (falling back to config).
     """
-    daily_limit, weekly_limit = await get_global_rate_limits(
-        user_id, config.daily_token_limit, config.weekly_token_limit
-    )
     return await get_usage_status(
         user_id=user_id,
-        daily_token_limit=daily_limit,
-        weekly_token_limit=weekly_limit,
-        rate_limit_reset_cost=config.rate_limit_reset_cost,
-    )
-
-
-class RateLimitResetResponse(BaseModel):
-    """Response from resetting the daily rate limit."""
-
-    success: bool
-    credits_charged: int = Field(description="Credits charged (in cents)")
-    remaining_balance: int = Field(description="Credit balance after charge (in cents)")
-    usage: CoPilotUsageStatus = Field(description="Updated usage status after reset")
-
-
-@router.post(
-    "/usage/reset",
-    status_code=200,
-    responses={
-        400: {
-            "description": "Bad Request (feature disabled or daily limit not reached)"
-        },
-        402: {"description": "Payment Required (insufficient credits)"},
-        429: {
-            "description": "Too Many Requests (max daily resets exceeded or reset in progress)"
-        },
-        503: {
-            "description": "Service Unavailable (Redis reset failed; credits refunded or support needed)"
-        },
-    },
-)
-async def reset_copilot_usage(
-    user_id: Annotated[str, Security(auth.get_user_id)],
-) -> RateLimitResetResponse:
-    """Reset the daily CoPilot rate limit by spending credits.
-
-    Allows users who have hit their daily token limit to spend credits
-    to reset their daily usage counter and continue working.
-    Returns 400 if the feature is disabled or the user is not over the limit.
-    Returns 402 if the user has insufficient credits.
-    """
-    cost = config.rate_limit_reset_cost
-    if cost <= 0:
-        raise HTTPException(
-            status_code=400,
-            detail="Rate limit reset is not available.",
-        )
-
-    if not settings.config.enable_credit:
-        raise HTTPException(
-            status_code=400,
-            detail="Rate limit reset is not available (credit system is disabled).",
-        )
-
-    daily_limit, weekly_limit = await get_global_rate_limits(
-        user_id, config.daily_token_limit, config.weekly_token_limit
-    )
-
-    if daily_limit <= 0:
-        raise HTTPException(
-            status_code=400,
-            detail="No daily limit is configured — nothing to reset.",
-        )
-
-    # Check max daily resets.  get_daily_reset_count returns None when Redis
-    # is unavailable; reject the reset in that case to prevent unlimited
-    # free resets when the counter store is down.
-    reset_count = await get_daily_reset_count(user_id)
-    if reset_count is None:
-        raise HTTPException(
-            status_code=503,
-            detail="Unable to verify reset eligibility — please try again later.",
-        )
-    if config.max_daily_resets > 0 and reset_count >= config.max_daily_resets:
-        raise HTTPException(
-            status_code=429,
-            detail=f"You've used all {config.max_daily_resets} resets for today.",
-        )
-
-    # Acquire a per-user lock to prevent TOCTOU races (concurrent resets).
-    if not await acquire_reset_lock(user_id):
-        raise HTTPException(
-            status_code=429,
-            detail="A reset is already in progress. Please try again.",
-        )
-
-    try:
-        # Verify the user is actually at or over their daily limit.
-        usage_status = await get_usage_status(
-            user_id=user_id,
-            daily_token_limit=daily_limit,
-            weekly_token_limit=weekly_limit,
-        )
-        if daily_limit > 0 and usage_status.daily.used < daily_limit:
-            raise HTTPException(
-                status_code=400,
-                detail="You have not reached your daily limit yet.",
-            )
-
-        # If the weekly limit is also exhausted, resetting the daily counter
-        # won't help — the user would still be blocked by the weekly limit.
-        if weekly_limit > 0 and usage_status.weekly.used >= weekly_limit:
-            raise HTTPException(
-                status_code=400,
-                detail="Your weekly limit is also reached. Resetting the daily limit won't help.",
-            )
-
-        # Charge credits.
-        credit_model = await get_user_credit_model(user_id)
-        try:
-            remaining = await credit_model.spend_credits(
-                user_id=user_id,
-                cost=cost,
-                metadata=UsageTransactionMetadata(
-                    reason="CoPilot daily rate limit reset",
-                ),
-            )
-        except InsufficientBalanceError as e:
-            raise HTTPException(
-                status_code=402,
-                detail="Insufficient credits to reset your rate limit.",
-            ) from e
-
-        # Reset daily usage in Redis.  If this fails, refund the credits
-        # so the user is not charged for a service they did not receive.
-        if not await reset_daily_usage(user_id, daily_token_limit=daily_limit):
-            # Compensate: refund the charged credits.
-            refunded = False
-            try:
-                await credit_model.top_up_credits(user_id, cost)
-                refunded = True
-                logger.warning(
-                    "Refunded %d credits to user %s after Redis reset failure",
-                    cost,
-                    user_id[:8],
-                )
-            except Exception:
-                logger.error(
-                    "CRITICAL: Failed to refund %d credits to user %s "
-                    "after Redis reset failure — manual intervention required",
-                    cost,
-                    user_id[:8],
-                    exc_info=True,
-                )
-            if refunded:
-                raise HTTPException(
-                    status_code=503,
-                    detail="Rate limit reset failed — please try again later. "
-                    "Your credits have not been charged.",
-                )
-            raise HTTPException(
-                status_code=503,
-                detail="Rate limit reset failed and the automatic refund "
-                "also failed. Please contact support for assistance.",
-            )
-
-        # Track the reset count for daily cap enforcement.
-        await increment_daily_reset_count(user_id)
-    finally:
-        await release_reset_lock(user_id)
-
-    # Return updated usage status.
-    updated_usage = await get_usage_status(
-        user_id=user_id,
-        daily_token_limit=daily_limit,
-        weekly_token_limit=weekly_limit,
-        rate_limit_reset_cost=config.rate_limit_reset_cost,
-    )
-
-    return RateLimitResetResponse(
-        success=True,
-        credits_charged=cost,
-        remaining_balance=remaining,
-        usage=updated_usage,
+        daily_token_limit=config.daily_token_limit,
+        weekly_token_limit=config.weekly_token_limit,
     )
 
 
@@ -713,16 +526,12 @@ async def stream_chat_post(
 
     # Pre-turn rate limit check (token-based).
     # check_rate_limit short-circuits internally when both limits are 0.
-    # Global defaults sourced from LaunchDarkly, falling back to config.
     if user_id:
         try:
-            daily_limit, weekly_limit = await get_global_rate_limits(
-                user_id, config.daily_token_limit, config.weekly_token_limit
-            )
             await check_rate_limit(
                 user_id=user_id,
-                daily_token_limit=daily_limit,
-                weekly_token_limit=weekly_limit,
+                daily_token_limit=config.daily_token_limit,
+                weekly_token_limit=config.weekly_token_limit,
             )
         except RateLimitExceeded as e:
             raise HTTPException(status_code=429, detail=str(e)) from e
@@ -1085,47 +894,6 @@ async def session_assign_user(
     return {"status": "ok"}
 
 
-# ========== Suggested Prompts ==========
-
-
-class SuggestedTheme(BaseModel):
-    """A themed group of suggested prompts."""
-
-    name: str
-    prompts: list[str]
-
-
-class SuggestedPromptsResponse(BaseModel):
-    """Response model for user-specific suggested prompts grouped by theme."""
-
-    themes: list[SuggestedTheme]
-
-
-@router.get(
-    "/suggested-prompts",
-    dependencies=[Security(auth.requires_user)],
-)
-async def get_suggested_prompts(
-    user_id: Annotated[str, Security(auth.get_user_id)],
-) -> SuggestedPromptsResponse:
-    """
-    Get LLM-generated suggested prompts grouped by theme.
-
-    Returns personalized quick-action prompts based on the user's
-    business understanding. Returns empty themes list if no custom
-    prompts are available.
-    """
-    understanding = await get_business_understanding(user_id)
-    if understanding is None or not understanding.suggested_prompts:
-        return SuggestedPromptsResponse(themes=[])
-
-    themes = [
-        SuggestedTheme(name=name, prompts=prompts)
-        for name, prompts in understanding.suggested_prompts.items()
-    ]
-    return SuggestedPromptsResponse(themes=themes)
-
-
 # ========== Configuration ==========
 
 

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

@@ -1,7 +1,7 @@
 """Tests for chat API routes: session title update, file attachment validation, usage, and rate limiting."""
 
 from datetime import UTC, datetime, timedelta
-from unittest.mock import AsyncMock, MagicMock
+from unittest.mock import AsyncMock
 
 import fastapi
 import fastapi.testclient
@@ -368,7 +368,6 @@ def test_usage_returns_daily_and_weekly(
         user_id=test_user_id,
         daily_token_limit=10000,
         weekly_token_limit=50000,
-        rate_limit_reset_cost=chat_routes.config.rate_limit_reset_cost,
     )
 
 
@@ -381,7 +380,6 @@ def test_usage_uses_config_limits(
 
     mocker.patch.object(chat_routes.config, "daily_token_limit", 99999)
     mocker.patch.object(chat_routes.config, "weekly_token_limit", 77777)
-    mocker.patch.object(chat_routes.config, "rate_limit_reset_cost", 500)
 
     response = client.get("/usage")
 
@@ -390,7 +388,6 @@ def test_usage_uses_config_limits(
         user_id=test_user_id,
         daily_token_limit=99999,
         weekly_token_limit=77777,
-        rate_limit_reset_cost=500,
     )
 
 
@@ -403,69 +400,3 @@ def test_usage_rejects_unauthenticated_request() -> None:
     response = unauthenticated_client.get("/usage")
 
     assert response.status_code == 401
-
-
-# ─── Suggested prompts endpoint ──────────────────────────────────────
-
-
-def _mock_get_business_understanding(
-    mocker: pytest_mock.MockerFixture,
-    *,
-    return_value=None,
-):
-    """Mock get_business_understanding."""
-    return mocker.patch(
-        "backend.api.features.chat.routes.get_business_understanding",
-        new_callable=AsyncMock,
-        return_value=return_value,
-    )
-
-
-def test_suggested_prompts_returns_themes(
-    mocker: pytest_mock.MockerFixture,
-    test_user_id: str,
-) -> None:
-    """User with themed prompts gets them back as themes list."""
-    mock_understanding = MagicMock()
-    mock_understanding.suggested_prompts = {
-        "Learn": ["L1", "L2"],
-        "Create": ["C1"],
-    }
-    _mock_get_business_understanding(mocker, return_value=mock_understanding)
-
-    response = client.get("/suggested-prompts")
-
-    assert response.status_code == 200
-    data = response.json()
-    assert "themes" in data
-    themes_by_name = {t["name"]: t["prompts"] for t in data["themes"]}
-    assert themes_by_name["Learn"] == ["L1", "L2"]
-    assert themes_by_name["Create"] == ["C1"]
-
-
-def test_suggested_prompts_no_understanding(
-    mocker: pytest_mock.MockerFixture,
-    test_user_id: str,
-) -> None:
-    """User with no understanding gets empty themes list."""
-    _mock_get_business_understanding(mocker, return_value=None)
-
-    response = client.get("/suggested-prompts")
-
-    assert response.status_code == 200
-    assert response.json() == {"themes": []}
-
-
-def test_suggested_prompts_empty_prompts(
-    mocker: pytest_mock.MockerFixture,
-    test_user_id: str,
-) -> None:
-    """User with understanding but empty prompts gets empty themes list."""
-    mock_understanding = MagicMock()
-    mock_understanding.suggested_prompts = {}
-    _mock_get_business_understanding(mocker, return_value=mock_understanding)
-
-    response = client.get("/suggested-prompts")
-
-    assert response.status_code == 200
-    assert response.json() == {"themes": []}

autogpt_platform/backend/backend/api/features/integrations/router.py

@@ -40,15 +40,11 @@ from backend.data.onboarding import OnboardingStep, complete_onboarding_step
 from backend.data.user import get_user_integrations
 from backend.executor.utils import add_graph_execution
 from backend.integrations.ayrshare import AyrshareClient, SocialPlatform
-from backend.integrations.credentials_store import (
-    is_system_credential,
-    provider_matches,
-)
+from backend.integrations.credentials_store import provider_matches
 from backend.integrations.creds_manager import (
     IntegrationCredentialsManager,
     create_mcp_oauth_handler,
 )
-from backend.integrations.managed_credentials import ensure_managed_credentials
 from backend.integrations.oauth import CREDENTIALS_BY_PROVIDER, HANDLERS_BY_NAME
 from backend.integrations.providers import ProviderName
 from backend.integrations.webhooks import get_webhook_manager
@@ -114,7 +110,6 @@ class CredentialsMetaResponse(BaseModel):
         default=None,
         description="Host pattern for host-scoped or MCP server URL for MCP credentials",
     )
-    is_managed: bool = False
 
     @model_validator(mode="before")
     @classmethod
@@ -153,7 +148,6 @@ def to_meta_response(cred: Credentials) -> CredentialsMetaResponse:
         scopes=cred.scopes if isinstance(cred, OAuth2Credentials) else None,
         username=cred.username if isinstance(cred, OAuth2Credentials) else None,
         host=CredentialsMetaResponse.get_host(cred),
-        is_managed=cred.is_managed,
     )
 
 
@@ -230,9 +224,6 @@ async def callback(
 async def list_credentials(
     user_id: Annotated[str, Security(get_user_id)],
 ) -> list[CredentialsMetaResponse]:
-    # Fire-and-forget: provision missing managed credentials in the background.
-    # The credential appears on the next page load; listing is never blocked.
-    asyncio.create_task(ensure_managed_credentials(user_id, creds_manager.store))
     credentials = await creds_manager.store.get_all_creds(user_id)
 
     return [
@@ -247,7 +238,6 @@ async def list_credentials_by_provider(
     ],
     user_id: Annotated[str, Security(get_user_id)],
 ) -> list[CredentialsMetaResponse]:
-    asyncio.create_task(ensure_managed_credentials(user_id, creds_manager.store))
     credentials = await creds_manager.store.get_creds_by_provider(user_id, provider)
 
     return [
@@ -342,11 +332,6 @@ async def delete_credentials(
         raise HTTPException(
             status_code=status.HTTP_404_NOT_FOUND, detail="Credentials not found"
         )
-    if is_system_credential(cred_id):
-        raise HTTPException(
-            status_code=status.HTTP_403_FORBIDDEN,
-            detail="System-managed credentials cannot be deleted",
-        )
     creds = await creds_manager.store.get_creds_by_id(user_id, cred_id)
     if not creds:
         raise HTTPException(
@@ -357,11 +342,6 @@ async def delete_credentials(
             status_code=status.HTTP_404_NOT_FOUND,
             detail="Credentials not found",
         )
-    if creds.is_managed:
-        raise HTTPException(
-            status_code=status.HTTP_403_FORBIDDEN,
-            detail="AutoGPT-managed credentials cannot be deleted",
-        )
 
     try:
         await remove_all_webhooks_for_credentials(user_id, creds, force)

autogpt_platform/backend/backend/api/features/integrations/router_test.py

@@ -1,7 +1,6 @@
 """Tests for credentials API security: no secret leakage, SDK defaults filtered."""
 
-from contextlib import asynccontextmanager
-from unittest.mock import AsyncMock, MagicMock, patch
+from unittest.mock import AsyncMock, patch
 
 import fastapi
 import fastapi.testclient
@@ -277,294 +276,3 @@ class TestCreateCredentialNoSecretInResponse:
 
         assert resp.status_code == 403
         mock_mgr.create.assert_not_called()
-
-
-class TestManagedCredentials:
-    """AutoGPT-managed credentials cannot be deleted by users."""
-
-    def test_delete_is_managed_returns_403(self):
-        cred = APIKeyCredentials(
-            id="managed-cred-1",
-            provider="agent_mail",
-            title="AgentMail (managed by AutoGPT)",
-            api_key=SecretStr("sk-managed-key"),
-            is_managed=True,
-        )
-        with patch(
-            "backend.api.features.integrations.router.creds_manager"
-        ) as mock_mgr:
-            mock_mgr.store.get_creds_by_id = AsyncMock(return_value=cred)
-            resp = client.request("DELETE", "/agent_mail/credentials/managed-cred-1")
-
-        assert resp.status_code == 403
-        assert "AutoGPT-managed" in resp.json()["detail"]
-
-    def test_list_credentials_includes_is_managed_field(self):
-        managed = APIKeyCredentials(
-            id="managed-1",
-            provider="agent_mail",
-            title="AgentMail (managed)",
-            api_key=SecretStr("sk-key"),
-            is_managed=True,
-        )
-        regular = APIKeyCredentials(
-            id="regular-1",
-            provider="openai",
-            title="My Key",
-            api_key=SecretStr("sk-key"),
-        )
-        with patch(
-            "backend.api.features.integrations.router.creds_manager"
-        ) as mock_mgr:
-            mock_mgr.store.get_all_creds = AsyncMock(return_value=[managed, regular])
-            resp = client.get("/credentials")
-
-        assert resp.status_code == 200
-        data = resp.json()
-        managed_cred = next(c for c in data if c["id"] == "managed-1")
-        regular_cred = next(c for c in data if c["id"] == "regular-1")
-        assert managed_cred["is_managed"] is True
-        assert regular_cred["is_managed"] is False
-
-
-# ---------------------------------------------------------------------------
-# Managed credential provisioning infrastructure
-# ---------------------------------------------------------------------------
-
-
-def _make_managed_cred(
-    provider: str = "agent_mail", pod_id: str = "pod-abc"
-) -> APIKeyCredentials:
-    return APIKeyCredentials(
-        id="managed-auto",
-        provider=provider,
-        title="AgentMail (managed by AutoGPT)",
-        api_key=SecretStr("sk-pod-key"),
-        is_managed=True,
-        metadata={"pod_id": pod_id},
-    )
-
-
-def _make_store_mock(**kwargs) -> MagicMock:
-    """Create a store mock with a working async ``locks()`` context manager."""
-
-    @asynccontextmanager
-    async def _noop_locked(key):
-        yield
-
-    locks_obj = MagicMock()
-    locks_obj.locked = _noop_locked
-
-    store = MagicMock(**kwargs)
-    store.locks = AsyncMock(return_value=locks_obj)
-    return store
-
-
-class TestEnsureManagedCredentials:
-    """Unit tests for the ensure/cleanup helpers in managed_credentials.py."""
-
-    @pytest.mark.asyncio
-    async def test_provisions_when_missing(self):
-        """Provider.provision() is called when no managed credential exists."""
-        from backend.integrations.managed_credentials import (
-            _PROVIDERS,
-            _provisioned_users,
-            ensure_managed_credentials,
-        )
-
-        cred = _make_managed_cred()
-        provider = MagicMock()
-        provider.provider_name = "test_provider"
-        provider.is_available = AsyncMock(return_value=True)
-        provider.provision = AsyncMock(return_value=cred)
-
-        store = _make_store_mock()
-        store.has_managed_credential = AsyncMock(return_value=False)
-        store.add_managed_credential = AsyncMock()
-
-        saved = dict(_PROVIDERS)
-        _PROVIDERS.clear()
-        _PROVIDERS["test_provider"] = provider
-        _provisioned_users.pop("user-1", None)
-        try:
-            await ensure_managed_credentials("user-1", store)
-        finally:
-            _PROVIDERS.clear()
-            _PROVIDERS.update(saved)
-            _provisioned_users.pop("user-1", None)
-
-        provider.provision.assert_awaited_once_with("user-1")
-        store.add_managed_credential.assert_awaited_once_with("user-1", cred)
-
-    @pytest.mark.asyncio
-    async def test_skips_when_already_exists(self):
-        """Provider.provision() is NOT called when managed credential exists."""
-        from backend.integrations.managed_credentials import (
-            _PROVIDERS,
-            _provisioned_users,
-            ensure_managed_credentials,
-        )
-
-        provider = MagicMock()
-        provider.provider_name = "test_provider"
-        provider.is_available = AsyncMock(return_value=True)
-        provider.provision = AsyncMock()
-
-        store = _make_store_mock()
-        store.has_managed_credential = AsyncMock(return_value=True)
-
-        saved = dict(_PROVIDERS)
-        _PROVIDERS.clear()
-        _PROVIDERS["test_provider"] = provider
-        _provisioned_users.pop("user-1", None)
-        try:
-            await ensure_managed_credentials("user-1", store)
-        finally:
-            _PROVIDERS.clear()
-            _PROVIDERS.update(saved)
-            _provisioned_users.pop("user-1", None)
-
-        provider.provision.assert_not_awaited()
-
-    @pytest.mark.asyncio
-    async def test_skips_when_unavailable(self):
-        """Provider.provision() is NOT called when provider is not available."""
-        from backend.integrations.managed_credentials import (
-            _PROVIDERS,
-            _provisioned_users,
-            ensure_managed_credentials,
-        )
-
-        provider = MagicMock()
-        provider.provider_name = "test_provider"
-        provider.is_available = AsyncMock(return_value=False)
-        provider.provision = AsyncMock()
-
-        store = _make_store_mock()
-        store.has_managed_credential = AsyncMock()
-
-        saved = dict(_PROVIDERS)
-        _PROVIDERS.clear()
-        _PROVIDERS["test_provider"] = provider
-        _provisioned_users.pop("user-1", None)
-        try:
-            await ensure_managed_credentials("user-1", store)
-        finally:
-            _PROVIDERS.clear()
-            _PROVIDERS.update(saved)
-            _provisioned_users.pop("user-1", None)
-
-        provider.provision.assert_not_awaited()
-        store.has_managed_credential.assert_not_awaited()
-
-    @pytest.mark.asyncio
-    async def test_provision_failure_does_not_propagate(self):
-        """A failed provision is logged but does not raise."""
-        from backend.integrations.managed_credentials import (
-            _PROVIDERS,
-            _provisioned_users,
-            ensure_managed_credentials,
-        )
-
-        provider = MagicMock()
-        provider.provider_name = "test_provider"
-        provider.is_available = AsyncMock(return_value=True)
-        provider.provision = AsyncMock(side_effect=RuntimeError("boom"))
-
-        store = _make_store_mock()
-        store.has_managed_credential = AsyncMock(return_value=False)
-
-        saved = dict(_PROVIDERS)
-        _PROVIDERS.clear()
-        _PROVIDERS["test_provider"] = provider
-        _provisioned_users.pop("user-1", None)
-        try:
-            await ensure_managed_credentials("user-1", store)
-        finally:
-            _PROVIDERS.clear()
-            _PROVIDERS.update(saved)
-            _provisioned_users.pop("user-1", None)
-
-        # No exception raised — provisioning failure is swallowed.
-
-
-class TestCleanupManagedCredentials:
-    """Unit tests for cleanup_managed_credentials."""
-
-    @pytest.mark.asyncio
-    async def test_calls_deprovision_for_managed_creds(self):
-        from backend.integrations.managed_credentials import (
-            _PROVIDERS,
-            cleanup_managed_credentials,
-        )
-
-        cred = _make_managed_cred()
-        provider = MagicMock()
-        provider.provider_name = "agent_mail"
-        provider.deprovision = AsyncMock()
-
-        store = MagicMock()
-        store.get_all_creds = AsyncMock(return_value=[cred])
-
-        saved = dict(_PROVIDERS)
-        _PROVIDERS.clear()
-        _PROVIDERS["agent_mail"] = provider
-        try:
-            await cleanup_managed_credentials("user-1", store)
-        finally:
-            _PROVIDERS.clear()
-            _PROVIDERS.update(saved)
-
-        provider.deprovision.assert_awaited_once_with("user-1", cred)
-
-    @pytest.mark.asyncio
-    async def test_skips_non_managed_creds(self):
-        from backend.integrations.managed_credentials import (
-            _PROVIDERS,
-            cleanup_managed_credentials,
-        )
-
-        regular = _make_api_key_cred()
-        provider = MagicMock()
-        provider.provider_name = "openai"
-        provider.deprovision = AsyncMock()
-
-        store = MagicMock()
-        store.get_all_creds = AsyncMock(return_value=[regular])
-
-        saved = dict(_PROVIDERS)
-        _PROVIDERS.clear()
-        _PROVIDERS["openai"] = provider
-        try:
-            await cleanup_managed_credentials("user-1", store)
-        finally:
-            _PROVIDERS.clear()
-            _PROVIDERS.update(saved)
-
-        provider.deprovision.assert_not_awaited()
-
-    @pytest.mark.asyncio
-    async def test_deprovision_failure_does_not_propagate(self):
-        from backend.integrations.managed_credentials import (
-            _PROVIDERS,
-            cleanup_managed_credentials,
-        )
-
-        cred = _make_managed_cred()
-        provider = MagicMock()
-        provider.provider_name = "agent_mail"
-        provider.deprovision = AsyncMock(side_effect=RuntimeError("boom"))
-
-        store = MagicMock()
-        store.get_all_creds = AsyncMock(return_value=[cred])
-
-        saved = dict(_PROVIDERS)
-        _PROVIDERS.clear()
-        _PROVIDERS["agent_mail"] = provider
-        try:
-            await cleanup_managed_credentials("user-1", store)
-        finally:
-            _PROVIDERS.clear()
-            _PROVIDERS.update(saved)
-
-        # No exception raised — cleanup failure is swallowed.

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

@@ -17,6 +17,8 @@ from backend.data.includes import library_agent_include
 from backend.util.exceptions import NotFoundError
 from backend.util.json import SafeJson
 
+from .db import get_library_agent_by_graph_id, update_library_agent
+
 logger = logging.getLogger(__name__)
 
 
@@ -59,17 +61,28 @@ async def add_graph_to_library(
     graph_model: GraphModel,
     user_id: str,
 ) -> library_model.LibraryAgent:
-    """Check existing / restore soft-deleted / create new LibraryAgent.
+    """Check existing / restore soft-deleted / create new LibraryAgent."""
+    if existing := await get_library_agent_by_graph_id(
+        user_id, graph_model.id, graph_model.version
+    ):
+        return existing
 
-    Uses a create-then-catch-UniqueViolationError-then-update pattern on
-    the (userId, agentGraphId, agentGraphVersion) composite unique constraint.
-    This is more robust than ``upsert`` because Prisma's upsert atomicity
-    guarantees are not well-documented for all versions.
-    """
-    settings_json = SafeJson(GraphSettings.from_graph(graph_model).model_dump())
-    _include = library_agent_include(
-        user_id, include_nodes=False, include_executions=False
+    deleted_agent = await prisma.models.LibraryAgent.prisma().find_unique(
+        where={
+            "userId_agentGraphId_agentGraphVersion": {
+                "userId": user_id,
+                "agentGraphId": graph_model.id,
+                "agentGraphVersion": graph_model.version,
+            }
+        },
     )
+    if deleted_agent and (deleted_agent.isDeleted or deleted_agent.isArchived):
+        return await update_library_agent(
+            deleted_agent.id,
+            user_id,
+            is_deleted=False,
+            is_archived=False,
+        )
 
     try:
         added_agent = await prisma.models.LibraryAgent.prisma().create(
@@ -85,32 +98,23 @@ async def add_graph_to_library(
                 },
                 "isCreatedByUser": False,
                 "useGraphIsActiveVersion": False,
-                "settings": settings_json,
+                "settings": SafeJson(
+                    GraphSettings.from_graph(graph_model).model_dump()
+                ),
             },
-            include=_include,
+            include=library_agent_include(
+                user_id, include_nodes=False, include_executions=False
+            ),
         )
     except prisma.errors.UniqueViolationError:
-        # Already exists — update to restore if previously soft-deleted/archived
-        added_agent = await prisma.models.LibraryAgent.prisma().update(
-            where={
-                "userId_agentGraphId_agentGraphVersion": {
-                    "userId": user_id,
-                    "agentGraphId": graph_model.id,
-                    "agentGraphVersion": graph_model.version,
-                }
-            },
-            data={
-                "isDeleted": False,
-                "isArchived": False,
-                "settings": settings_json,
-            },
-            include=_include,
+        # Race condition: concurrent request created the row between our
+        # check and create.  Re-read instead of crashing.
+        existing = await get_library_agent_by_graph_id(
+            user_id, graph_model.id, graph_model.version
         )
-        if added_agent is None:
-            raise NotFoundError(
-                f"LibraryAgent for graph #{graph_model.id} "
-                f"v{graph_model.version} not found after UniqueViolationError"
-            )
+        if existing:
+            return existing
+        raise  # Shouldn't happen, but don't swallow unexpected errors
 
     logger.debug(
         f"Added graph #{graph_model.id} v{graph_model.version} "

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

@@ -1,80 +1,71 @@
 from unittest.mock import AsyncMock, MagicMock, patch
 
-import prisma.errors
 import pytest
 
 from ._add_to_library import add_graph_to_library
 
 
 @pytest.mark.asyncio
-async def test_add_graph_to_library_create_new_agent() -> None:
-    """When no matching LibraryAgent exists, create inserts a new one."""
-    graph_model = MagicMock(id="graph-id", version=2, nodes=[])
-    created_agent = MagicMock(name="CreatedLibraryAgent")
-    converted_agent = MagicMock(name="ConvertedLibraryAgent")
+async def test_add_graph_to_library_restores_archived_agent() -> None:
+    graph_model = MagicMock(id="graph-id", version=2)
+    archived_agent = MagicMock(id="library-agent-id", isDeleted=False, isArchived=True)
+    restored_agent = MagicMock(name="LibraryAgentModel")
 
     with (
+        patch(
+            "backend.api.features.library._add_to_library.get_library_agent_by_graph_id",
+            new=AsyncMock(return_value=None),
+        ),
         patch(
             "backend.api.features.library._add_to_library.prisma.models.LibraryAgent.prisma"
         ) as mock_prisma,
         patch(
-            "backend.api.features.library._add_to_library.library_model.LibraryAgent.from_db",
-            return_value=converted_agent,
-        ) as mock_from_db,
+            "backend.api.features.library._add_to_library.update_library_agent",
+            new=AsyncMock(return_value=restored_agent),
+        ) as mock_update,
     ):
-        mock_prisma.return_value.create = AsyncMock(return_value=created_agent)
+        mock_prisma.return_value.find_unique = AsyncMock(return_value=archived_agent)
 
         result = await add_graph_to_library("slv-id", graph_model, "user-id")
 
-    assert result is converted_agent
-    mock_from_db.assert_called_once_with(created_agent)
-    # Verify create was called with correct data
-    create_call = mock_prisma.return_value.create.call_args
-    create_data = create_call.kwargs["data"]
-    assert create_data["User"] == {"connect": {"id": "user-id"}}
-    assert create_data["AgentGraph"] == {
-        "connect": {"graphVersionId": {"id": "graph-id", "version": 2}}
-    }
-    assert create_data["isCreatedByUser"] is False
-    assert create_data["useGraphIsActiveVersion"] is False
+    assert result is restored_agent
+    mock_update.assert_awaited_once_with(
+        "library-agent-id",
+        "user-id",
+        is_deleted=False,
+        is_archived=False,
+    )
+    mock_prisma.return_value.create.assert_not_called()
 
 
 @pytest.mark.asyncio
-async def test_add_graph_to_library_unique_violation_updates_existing() -> None:
-    """UniqueViolationError on create falls back to update."""
-    graph_model = MagicMock(id="graph-id", version=2, nodes=[])
-    updated_agent = MagicMock(name="UpdatedLibraryAgent")
-    converted_agent = MagicMock(name="ConvertedLibraryAgent")
+async def test_add_graph_to_library_restores_deleted_agent() -> None:
+    graph_model = MagicMock(id="graph-id", version=2)
+    deleted_agent = MagicMock(id="library-agent-id", isDeleted=True, isArchived=False)
+    restored_agent = MagicMock(name="LibraryAgentModel")
 
     with (
+        patch(
+            "backend.api.features.library._add_to_library.get_library_agent_by_graph_id",
+            new=AsyncMock(return_value=None),
+        ),
         patch(
             "backend.api.features.library._add_to_library.prisma.models.LibraryAgent.prisma"
         ) as mock_prisma,
         patch(
-            "backend.api.features.library._add_to_library.library_model.LibraryAgent.from_db",
-            return_value=converted_agent,
-        ) as mock_from_db,
+            "backend.api.features.library._add_to_library.update_library_agent",
+            new=AsyncMock(return_value=restored_agent),
+        ) as mock_update,
     ):
-        mock_prisma.return_value.create = AsyncMock(
-            side_effect=prisma.errors.UniqueViolationError(
-                MagicMock(), message="unique constraint"
-            )
-        )
-        mock_prisma.return_value.update = AsyncMock(return_value=updated_agent)
+        mock_prisma.return_value.find_unique = AsyncMock(return_value=deleted_agent)
 
         result = await add_graph_to_library("slv-id", graph_model, "user-id")
 
-    assert result is converted_agent
-    mock_from_db.assert_called_once_with(updated_agent)
-    # Verify update was called with correct where and data
-    update_call = mock_prisma.return_value.update.call_args
-    assert update_call.kwargs["where"] == {
-        "userId_agentGraphId_agentGraphVersion": {
-            "userId": "user-id",
-            "agentGraphId": "graph-id",
-            "agentGraphVersion": 2,
-        }
-    }
-    update_data = update_call.kwargs["data"]
-    assert update_data["isDeleted"] is False
-    assert update_data["isArchived"] is False
+    assert result is restored_agent
+    mock_update.assert_awaited_once_with(
+        "library-agent-id",
+        "user-id",
+        is_deleted=False,
+        is_archived=False,
+    )
+    mock_prisma.return_value.create.assert_not_called()

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

@@ -436,53 +436,32 @@ async def create_library_agent(
     async with transaction() as tx:
         library_agents = await asyncio.gather(
             *(
-                prisma.models.LibraryAgent.prisma(tx).upsert(
-                    where={
-                        "userId_agentGraphId_agentGraphVersion": {
-                            "userId": user_id,
-                            "agentGraphId": graph_entry.id,
-                            "agentGraphVersion": graph_entry.version,
-                        }
-                    },
-                    data={
-                        "create": prisma.types.LibraryAgentCreateInput(
-                            isCreatedByUser=(user_id == graph.user_id),
-                            useGraphIsActiveVersion=True,
-                            User={"connect": {"id": user_id}},
-                            AgentGraph={
-                                "connect": {
-                                    "graphVersionId": {
-                                        "id": graph_entry.id,
-                                        "version": graph_entry.version,
-                                    }
+                prisma.models.LibraryAgent.prisma(tx).create(
+                    data=prisma.types.LibraryAgentCreateInput(
+                        isCreatedByUser=(user_id == user_id),
+                        useGraphIsActiveVersion=True,
+                        User={"connect": {"id": user_id}},
+                        AgentGraph={
+                            "connect": {
+                                "graphVersionId": {
+                                    "id": graph_entry.id,
+                                    "version": graph_entry.version,
                                 }
-                            },
-                            settings=SafeJson(
-                                GraphSettings.from_graph(
-                                    graph_entry,
-                                    hitl_safe_mode=hitl_safe_mode,
-                                    sensitive_action_safe_mode=sensitive_action_safe_mode,
-                                ).model_dump()
-                            ),
-                            **(
-                                {"Folder": {"connect": {"id": folder_id}}}
-                                if folder_id and graph_entry is graph
-                                else {}
-                            ),
-                        ),
-                        "update": {
-                            "isDeleted": False,
-                            "isArchived": False,
-                            "useGraphIsActiveVersion": True,
-                            "settings": SafeJson(
-                                GraphSettings.from_graph(
-                                    graph_entry,
-                                    hitl_safe_mode=hitl_safe_mode,
-                                    sensitive_action_safe_mode=sensitive_action_safe_mode,
-                                ).model_dump()
-                            ),
+                            }
                         },
-                    },
+                        settings=SafeJson(
+                            GraphSettings.from_graph(
+                                graph_entry,
+                                hitl_safe_mode=hitl_safe_mode,
+                                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
                     ),

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

@@ -1,6 +1,4 @@
-from contextlib import asynccontextmanager
 from datetime import datetime
-from unittest.mock import AsyncMock, MagicMock, patch
 
 import prisma.enums
 import prisma.models
@@ -87,6 +85,10 @@ async def test_get_library_agents(mocker):
 async def test_add_agent_to_library(mocker):
     await connect()
 
+    # Mock the transaction context
+    mock_transaction = mocker.patch("backend.api.features.library.db.transaction")
+    mock_transaction.return_value.__aenter__ = mocker.AsyncMock(return_value=None)
+    mock_transaction.return_value.__aexit__ = mocker.AsyncMock(return_value=None)
     # Mock data
     mock_store_listing_data = prisma.models.StoreListingVersion(
         id="version123",
@@ -141,11 +143,13 @@ async def test_add_agent_to_library(mocker):
     )
 
     mock_library_agent = mocker.patch("prisma.models.LibraryAgent.prisma")
+    mock_library_agent.return_value.find_first = mocker.AsyncMock(return_value=None)
+    mock_library_agent.return_value.find_unique = mocker.AsyncMock(return_value=None)
     mock_library_agent.return_value.create = mocker.AsyncMock(
         return_value=mock_library_agent_data
     )
 
-    # Mock graph_db.get_graph function that's called in resolve_graph_for_library
+    # Mock graph_db.get_graph function that's called to check for HITL blocks
     # (lives in _add_to_library.py after refactor, not db.py)
     mock_graph_db = mocker.patch(
         "backend.api.features.library._add_to_library.graph_db"
@@ -171,27 +175,37 @@ async def test_add_agent_to_library(mocker):
     mock_store_listing_version.return_value.find_unique.assert_called_once_with(
         where={"id": "version123"}, include={"AgentGraph": True}
     )
+    mock_library_agent.return_value.find_unique.assert_called_once_with(
+        where={
+            "userId_agentGraphId_agentGraphVersion": {
+                "userId": "test-user",
+                "agentGraphId": "agent1",
+                "agentGraphVersion": 1,
+            }
+        },
+    )
     # Check that create was called with the expected data including settings
     create_call_args = mock_library_agent.return_value.create.call_args
     assert create_call_args is not None
 
-    # Verify the create data structure
-    create_data = create_call_args.kwargs["data"]
-    expected_create = {
+    # Verify the main structure
+    expected_data = {
         "User": {"connect": {"id": "test-user"}},
         "AgentGraph": {"connect": {"graphVersionId": {"id": "agent1", "version": 1}}},
         "isCreatedByUser": False,
-        "useGraphIsActiveVersion": False,
     }
-    for key, value in expected_create.items():
-        assert create_data[key] == value
+
+    actual_data = create_call_args[1]["data"]
+    # Check that all expected fields are present
+    for key, value in expected_data.items():
+        assert actual_data[key] == value
 
     # Check that settings field is present and is a SafeJson object
-    assert "settings" in create_data
-    assert hasattr(create_data["settings"], "__class__")  # Should be a SafeJson object
+    assert "settings" in actual_data
+    assert hasattr(actual_data["settings"], "__class__")  # Should be a SafeJson object
 
     # Check include parameter
-    assert create_call_args.kwargs["include"] == library_agent_include(
+    assert create_call_args[1]["include"] == library_agent_include(
         "test-user", include_nodes=False, include_executions=False
     )
 
@@ -306,50 +320,3 @@ async def test_update_graph_in_library_allows_archived_library_agent(mocker):
         include_archived=True,
     )
     mock_update_library_agent.assert_awaited_once_with("test-user", created_graph)
-
-
-@pytest.mark.asyncio
-async def test_create_library_agent_uses_upsert():
-    """create_library_agent should use upsert (not create) to handle duplicates."""
-    mock_graph = MagicMock()
-    mock_graph.id = "graph-1"
-    mock_graph.version = 1
-    mock_graph.user_id = "user-1"
-    mock_graph.nodes = []
-    mock_graph.sub_graphs = []
-
-    mock_upserted = MagicMock(name="UpsertedLibraryAgent")
-
-    @asynccontextmanager
-    async def fake_tx():
-        yield None
-
-    with (
-        patch("backend.api.features.library.db.transaction", fake_tx),
-        patch("prisma.models.LibraryAgent.prisma") as mock_prisma,
-        patch(
-            "backend.api.features.library.db.add_generated_agent_image",
-            new=AsyncMock(),
-        ),
-        patch(
-            "backend.api.features.library.model.LibraryAgent.from_db",
-            return_value=MagicMock(),
-        ),
-    ):
-        mock_prisma.return_value.upsert = AsyncMock(return_value=mock_upserted)
-
-        result = await db.create_library_agent(mock_graph, "user-1")
-
-    assert len(result) == 1
-    upsert_call = mock_prisma.return_value.upsert.call_args
-    assert upsert_call is not None
-    # Verify the upsert where clause uses the composite unique key
-    where = upsert_call.kwargs["where"]
-    assert "userId_agentGraphId_agentGraphVersion" in where
-    # Verify the upsert data has both create and update branches
-    data = upsert_call.kwargs["data"]
-    assert "create" in data
-    assert "update" in data
-    # Verify update branch restores soft-deleted/archived agents
-    assert data["update"]["isDeleted"] is False
-    assert data["update"]["isArchived"] is False

autogpt_platform/backend/backend/api/features/oauth_test.py

@@ -12,7 +12,6 @@ Tests cover:
 5. Complete OAuth flow end-to-end
 """
 
-import asyncio
 import base64
 import hashlib
 import secrets
@@ -59,27 +58,14 @@ async def test_user(server, test_user_id: str):
 
     yield test_user_id
 
-    # Cleanup - delete in correct order due to foreign key constraints.
-    # Wrap in try/except because the event loop or Prisma engine may already
-    # be closed during session teardown on Python 3.12+.
-    try:
-        await asyncio.gather(
-            PrismaOAuthAccessToken.prisma().delete_many(where={"userId": test_user_id}),
-            PrismaOAuthRefreshToken.prisma().delete_many(
-                where={"userId": test_user_id}
-            ),
-            PrismaOAuthAuthorizationCode.prisma().delete_many(
-                where={"userId": test_user_id}
-            ),
-        )
-        await asyncio.gather(
-            PrismaOAuthApplication.prisma().delete_many(
-                where={"ownerId": test_user_id}
-            ),
-            PrismaUser.prisma().delete(where={"id": test_user_id}),
-        )
-    except RuntimeError:
-        pass
+    # Cleanup - delete in correct order due to foreign key constraints
+    await PrismaOAuthAccessToken.prisma().delete_many(where={"userId": test_user_id})
+    await PrismaOAuthRefreshToken.prisma().delete_many(where={"userId": test_user_id})
+    await PrismaOAuthAuthorizationCode.prisma().delete_many(
+        where={"userId": test_user_id}
+    )
+    await PrismaOAuthApplication.prisma().delete_many(where={"ownerId": test_user_id})
+    await PrismaUser.prisma().delete(where={"id": test_user_id})
 
 
 @pytest_asyncio.fixture

autogpt_platform/backend/backend/api/rest_api.py

@@ -18,7 +18,6 @@ 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.rate_limit_admin_routes
 import backend.api.features.admin.store_admin_routes
 import backend.api.features.builder
 import backend.api.features.builder.routes
@@ -118,11 +117,6 @@ async def lifespan_context(app: fastapi.FastAPI):
 
     AutoRegistry.patch_integrations()
 
-    # Register managed credential providers (e.g. AgentMail)
-    from backend.integrations.managed_providers import register_all
-
-    register_all()
-
     await backend.data.block.initialize_blocks()
 
     await backend.data.user.migrate_and_encrypt_user_integrations()
@@ -324,11 +318,6 @@ app.include_router(
     tags=["v2", "admin"],
     prefix="/api/executions",
 )
-app.include_router(
-    backend.api.features.admin.rate_limit_admin_routes.router,
-    tags=["v2", "admin"],
-    prefix="/api/copilot",
-)
 app.include_router(
     backend.api.features.executions.review.routes.router,
     tags=["v2", "executions", "review"],

autogpt_platform/backend/backend/blocks/ai_condition.py

@@ -1,4 +1,3 @@
-import re
 from typing import Any
 
 from backend.blocks._base import (
@@ -20,33 +19,6 @@ from backend.blocks.llm import (
 )
 from backend.data.model import APIKeyCredentials, NodeExecutionStats, SchemaField
 
-# Minimum max_output_tokens accepted by OpenAI-compatible APIs.
-# A true/false answer fits comfortably within this budget.
-MIN_LLM_OUTPUT_TOKENS = 16
-
-
-def _parse_boolean_response(response_text: str) -> tuple[bool, str | None]:
-    """Parse an LLM response into a boolean result.
-
-    Returns a ``(result, error)`` tuple.  *error* is ``None`` when the
-    response is unambiguous; otherwise it contains a diagnostic message
-    and *result* defaults to ``False``.
-    """
-    text = response_text.strip().lower()
-    if text == "true":
-        return True, None
-    if text == "false":
-        return False, None
-
-    # Fuzzy match – use word boundaries to avoid false positives like "untrue".
-    tokens = set(re.findall(r"\b(true|false|yes|no|1|0)\b", text))
-    if tokens == {"true"} or tokens == {"yes"} or tokens == {"1"}:
-        return True, None
-    if tokens == {"false"} or tokens == {"no"} or tokens == {"0"}:
-        return False, None
-
-    return False, f"Unclear AI response: '{response_text}'"
-
 
 class AIConditionBlock(AIBlockBase):
     """
@@ -190,26 +162,54 @@ class AIConditionBlock(AIBlockBase):
         ]
 
         # Call the LLM
-        response = await self.llm_call(
-            credentials=credentials,
-            llm_model=input_data.model,
-            prompt=prompt,
-            max_tokens=MIN_LLM_OUTPUT_TOKENS,
-        )
-
-        # Extract the boolean result from the response
-        result, error = _parse_boolean_response(response.response)
-        if error:
-            yield "error", error
-
-        # Update internal stats
-        self.merge_stats(
-            NodeExecutionStats(
-                input_token_count=response.prompt_tokens,
-                output_token_count=response.completion_tokens,
+        try:
+            response = await self.llm_call(
+                credentials=credentials,
+                llm_model=input_data.model,
+                prompt=prompt,
+                max_tokens=10,  # We only expect a true/false response
             )
-        )
-        self.prompt = response.prompt
+
+            # Extract the boolean result from the response
+            response_text = response.response.strip().lower()
+            if response_text == "true":
+                result = True
+            elif response_text == "false":
+                result = False
+            else:
+                # If the response is not clear, try to interpret it using word boundaries
+                import re
+
+                # Use word boundaries to avoid false positives like 'untrue' or '10'
+                tokens = set(re.findall(r"\b(true|false|yes|no|1|0)\b", response_text))
+
+                if tokens == {"true"} or tokens == {"yes"} or tokens == {"1"}:
+                    result = True
+                elif tokens == {"false"} or tokens == {"no"} or tokens == {"0"}:
+                    result = False
+                else:
+                    # Unclear or conflicting response - default to False and yield error
+                    result = False
+                    yield "error", f"Unclear AI response: '{response.response}'"
+
+            # Update internal stats
+            self.merge_stats(
+                NodeExecutionStats(
+                    input_token_count=response.prompt_tokens,
+                    output_token_count=response.completion_tokens,
+                )
+            )
+            self.prompt = response.prompt
+
+        except Exception as e:
+            # In case of any error, default to False to be safe
+            result = False
+            # Log the error but don't fail the block execution
+            import logging
+
+            logger = logging.getLogger(__name__)
+            logger.error(f"AI condition evaluation failed: {str(e)}")
+            yield "error", f"AI evaluation failed: {str(e)}"
 
         # Yield results
         yield "result", result

autogpt_platform/backend/backend/blocks/ai_condition_test.py

@@ -1,147 +0,0 @@
-"""Tests for AIConditionBlock – regression coverage for max_tokens and error propagation."""
-
-from __future__ import annotations
-
-from typing import cast
-
-import pytest
-
-from backend.blocks.ai_condition import (
-    MIN_LLM_OUTPUT_TOKENS,
-    AIConditionBlock,
-    _parse_boolean_response,
-)
-from backend.blocks.llm import (
-    DEFAULT_LLM_MODEL,
-    TEST_CREDENTIALS,
-    TEST_CREDENTIALS_INPUT,
-    AICredentials,
-    LLMResponse,
-)
-
-_TEST_AI_CREDENTIALS = cast(AICredentials, TEST_CREDENTIALS_INPUT)
-
-
-# ---------------------------------------------------------------------------
-# Helper to collect all yields from the async generator
-# ---------------------------------------------------------------------------
-
-
-async def _collect_outputs(block: AIConditionBlock, input_data, credentials):
-    outputs: dict[str, object] = {}
-    async for name, value in block.run(input_data, credentials=credentials):
-        outputs[name] = value
-    return outputs
-
-
-def _make_input(**overrides) -> AIConditionBlock.Input:
-    defaults: dict = {
-        "input_value": "hello@example.com",
-        "condition": "the input is an email address",
-        "yes_value": "yes!",
-        "no_value": "no!",
-        "model": DEFAULT_LLM_MODEL,
-        "credentials": TEST_CREDENTIALS_INPUT,
-    }
-    defaults.update(overrides)
-    return AIConditionBlock.Input(**defaults)
-
-
-def _mock_llm_response(response_text: str) -> LLMResponse:
-    return LLMResponse(
-        raw_response="",
-        prompt=[],
-        response=response_text,
-        tool_calls=None,
-        prompt_tokens=10,
-        completion_tokens=5,
-        reasoning=None,
-    )
-
-
-# ---------------------------------------------------------------------------
-# _parse_boolean_response unit tests
-# ---------------------------------------------------------------------------
-
-
-class TestParseBooleanResponse:
-    def test_true_exact(self):
-        assert _parse_boolean_response("true") == (True, None)
-
-    def test_false_exact(self):
-        assert _parse_boolean_response("false") == (False, None)
-
-    def test_true_with_whitespace(self):
-        assert _parse_boolean_response("  True  ") == (True, None)
-
-    def test_yes_fuzzy(self):
-        assert _parse_boolean_response("Yes") == (True, None)
-
-    def test_no_fuzzy(self):
-        assert _parse_boolean_response("no") == (False, None)
-
-    def test_one_fuzzy(self):
-        assert _parse_boolean_response("1") == (True, None)
-
-    def test_zero_fuzzy(self):
-        assert _parse_boolean_response("0") == (False, None)
-
-    def test_unclear_response(self):
-        result, error = _parse_boolean_response("I'm not sure")
-        assert result is False
-        assert error is not None
-        assert "Unclear" in error
-
-    def test_conflicting_tokens(self):
-        result, error = _parse_boolean_response("true and false")
-        assert result is False
-        assert error is not None
-
-
-# ---------------------------------------------------------------------------
-# Regression: max_tokens is set to MIN_LLM_OUTPUT_TOKENS
-# ---------------------------------------------------------------------------
-
-
-class TestMaxTokensRegression:
-    @pytest.mark.asyncio
-    async def test_llm_call_receives_min_output_tokens(self):
-        """max_tokens must be MIN_LLM_OUTPUT_TOKENS (16) – the previous value
-        of 1 was too low and caused OpenAI to reject the request."""
-        block = AIConditionBlock()
-        captured_kwargs: dict = {}
-
-        async def spy_llm_call(**kwargs):
-            captured_kwargs.update(kwargs)
-            return _mock_llm_response("true")
-
-        block.llm_call = spy_llm_call  # type: ignore[assignment]
-
-        input_data = _make_input()
-        await _collect_outputs(block, input_data, credentials=TEST_CREDENTIALS)
-
-        assert captured_kwargs["max_tokens"] == MIN_LLM_OUTPUT_TOKENS
-        assert captured_kwargs["max_tokens"] == 16
-
-
-# ---------------------------------------------------------------------------
-# Regression: exceptions from llm_call must propagate
-# ---------------------------------------------------------------------------
-
-
-class TestExceptionPropagation:
-    @pytest.mark.asyncio
-    async def test_llm_call_exception_propagates(self):
-        """If llm_call raises, the exception must NOT be swallowed.
-        Previously the block caught all exceptions and silently returned
-        result=False."""
-        block = AIConditionBlock()
-
-        async def boom(**kwargs):
-            raise RuntimeError("LLM provider error")
-
-        block.llm_call = boom  # type: ignore[assignment]
-
-        input_data = _make_input()
-        with pytest.raises(RuntimeError, match="LLM provider error"):
-            await _collect_outputs(block, input_data, credentials=TEST_CREDENTIALS)

autogpt_platform/backend/backend/blocks/discord/bot_blocks.py

@@ -73,7 +73,7 @@ class ReadDiscordMessagesBlock(Block):
             id="df06086a-d5ac-4abb-9996-2ad0acb2eff7",
             input_schema=ReadDiscordMessagesBlock.Input,  # Assign input schema
             output_schema=ReadDiscordMessagesBlock.Output,  # Assign output schema
-            description="Reads new messages from a Discord channel using a bot token and triggers when a new message is posted",
+            description="Reads messages from a Discord channel using a bot token.",
             categories={BlockCategory.SOCIAL},
             test_input={
                 "continuous_read": False,

autogpt_platform/backend/backend/blocks/google/gmail.py

@@ -1,6 +1,5 @@
 import asyncio
 import base64
-import re
 from abc import ABC
 from email import encoders
 from email.mime.base import MIMEBase
@@ -9,7 +8,7 @@ from email.mime.text import MIMEText
 from email.policy import SMTP
 from email.utils import getaddresses, parseaddr
 from pathlib import Path
-from typing import List, Literal, Optional, Protocol, runtime_checkable
+from typing import List, Literal, Optional
 
 from google.oauth2.credentials import Credentials
 from googleapiclient.discovery import build
@@ -43,52 +42,8 @@ NO_WRAP_POLICY = SMTP.clone(max_line_length=0)
 
 
 def serialize_email_recipients(recipients: list[str]) -> str:
-    """Serialize recipients list to comma-separated string.
-
-    Strips leading/trailing whitespace from each address to keep MIME
-    headers clean (mirrors the strip done in ``validate_email_recipients``).
-    """
-    return ", ".join(addr.strip() for addr in recipients)
-
-
-# RFC 5322 simplified pattern: local@domain where domain has at least one dot
-_EMAIL_RE = re.compile(r"^[^@\s]+@[^@\s]+\.[^@\s]+$")
-
-
-def validate_email_recipients(recipients: list[str], field_name: str = "to") -> None:
-    """Validate that all recipients are plausible email addresses.
-
-    Raises ``ValueError`` with a user-friendly message listing every
-    invalid entry so the caller (or LLM) can correct them in one pass.
-    """
-    invalid = [addr for addr in recipients if not _EMAIL_RE.match(addr.strip())]
-    if invalid:
-        formatted = ", ".join(f"'{a}'" for a in invalid)
-        raise ValueError(
-            f"Invalid email address(es) in '{field_name}': {formatted}. "
-            f"Each entry must be a valid email address (e.g. user@example.com)."
-        )
-
-
-@runtime_checkable
-class HasRecipients(Protocol):
-    to: list[str]
-    cc: list[str]
-    bcc: list[str]
-
-
-def validate_all_recipients(input_data: HasRecipients) -> None:
-    """Validate to/cc/bcc recipient fields on an input namespace.
-
-    Calls ``validate_email_recipients`` for ``to`` (required) and
-    ``cc``/``bcc`` (when non-empty), raising ``ValueError`` on the
-    first field that contains an invalid address.
-    """
-    validate_email_recipients(input_data.to, "to")
-    if input_data.cc:
-        validate_email_recipients(input_data.cc, "cc")
-    if input_data.bcc:
-        validate_email_recipients(input_data.bcc, "bcc")
+    """Serialize recipients list to comma-separated string."""
+    return ", ".join(recipients)
 
 
 def _make_mime_text(
@@ -145,16 +100,14 @@ async def create_mime_message(
 ) -> str:
     """Create a MIME message with attachments and return base64-encoded raw message."""
 
-    validate_all_recipients(input_data)
-
     message = MIMEMultipart()
     message["to"] = serialize_email_recipients(input_data.to)
     message["subject"] = input_data.subject
 
     if input_data.cc:
-        message["cc"] = serialize_email_recipients(input_data.cc)
+        message["cc"] = ", ".join(input_data.cc)
     if input_data.bcc:
-        message["bcc"] = serialize_email_recipients(input_data.bcc)
+        message["bcc"] = ", ".join(input_data.bcc)
 
     # Use the new helper function with content_type if available
     content_type = getattr(input_data, "content_type", None)
@@ -1214,15 +1167,13 @@ async def _build_reply_message(
         references.append(headers["message-id"])
 
     # Create MIME message
-    validate_all_recipients(input_data)
-
     msg = MIMEMultipart()
     if input_data.to:
-        msg["To"] = serialize_email_recipients(input_data.to)
+        msg["To"] = ", ".join(input_data.to)
     if input_data.cc:
-        msg["Cc"] = serialize_email_recipients(input_data.cc)
+        msg["Cc"] = ", ".join(input_data.cc)
     if input_data.bcc:
-        msg["Bcc"] = serialize_email_recipients(input_data.bcc)
+        msg["Bcc"] = ", ".join(input_data.bcc)
     msg["Subject"] = subject
     if headers.get("message-id"):
         msg["In-Reply-To"] = headers["message-id"]
@@ -1734,16 +1685,13 @@ To: {original_to}
         else:
             body = f"{forward_header}\n\n{original_body}"
 
-        # Validate all recipient lists before building the MIME message
-        validate_all_recipients(input_data)
-
         # Create MIME message
         msg = MIMEMultipart()
-        msg["To"] = serialize_email_recipients(input_data.to)
+        msg["To"] = ", ".join(input_data.to)
         if input_data.cc:
-            msg["Cc"] = serialize_email_recipients(input_data.cc)
+            msg["Cc"] = ", ".join(input_data.cc)
         if input_data.bcc:
-            msg["Bcc"] = serialize_email_recipients(input_data.bcc)
+            msg["Bcc"] = ", ".join(input_data.bcc)
         msg["Subject"] = subject
 
         # Add body with proper content type

autogpt_platform/backend/backend/blocks/io.py

@@ -28,9 +28,9 @@ class AgentInputBlock(Block):
     """
     This block is used to provide input to the graph.
 
-    It takes in a value, name, and description.
+    It takes in a value, name, description, default values list and bool to limit selection to default values.
 
-    It outputs the value passed as input.
+    It Outputs the value passed as input.
     """
 
     class Input(BlockSchemaInput):
@@ -47,6 +47,12 @@ class AgentInputBlock(Block):
             default=None,
             advanced=True,
         )
+        placeholder_values: list = SchemaField(
+            description="The placeholder values to be passed as input.",
+            default_factory=list,
+            advanced=True,
+            hidden=True,
+        )
         advanced: bool = SchemaField(
             description="Whether to show the input in the advanced section, if the field is not required.",
             default=False,
@@ -59,7 +65,10 @@ class AgentInputBlock(Block):
         )
 
         def generate_schema(self):
-            return copy.deepcopy(self.get_field_schema("value"))
+            schema = copy.deepcopy(self.get_field_schema("value"))
+            if possible_values := self.placeholder_values:
+                schema["enum"] = possible_values
+            return schema
 
     class Output(BlockSchema):
         # Use BlockSchema to avoid automatic error field for interface definition
@@ -77,16 +86,18 @@ class AgentInputBlock(Block):
                         "value": "Hello, World!",
                         "name": "input_1",
                         "description": "Example test input.",
+                        "placeholder_values": [],
                     },
                     {
-                        "value": 42,
+                        "value": "Hello, World!",
                         "name": "input_2",
-                        "description": "Example numeric input.",
+                        "description": "Example test input with placeholders.",
+                        "placeholder_values": ["Hello, World!"],
                     },
                 ],
                 "test_output": [
                     ("result", "Hello, World!"),
-                    ("result", 42),
+                    ("result", "Hello, World!"),
                 ],
                 "categories": {BlockCategory.INPUT, BlockCategory.BASIC},
                 "block_type": BlockType.INPUT,
@@ -234,11 +245,13 @@ class AgentShortTextInputBlock(AgentInputBlock):
                     "value": "Hello",
                     "name": "short_text_1",
                     "description": "Short text example 1",
+                    "placeholder_values": [],
                 },
                 {
                     "value": "Quick test",
                     "name": "short_text_2",
                     "description": "Short text example 2",
+                    "placeholder_values": ["Quick test", "Another option"],
                 },
             ],
             test_output=[
@@ -272,11 +285,13 @@ class AgentLongTextInputBlock(AgentInputBlock):
                     "value": "Lorem ipsum dolor sit amet...",
                     "name": "long_text_1",
                     "description": "Long text example 1",
+                    "placeholder_values": [],
                 },
                 {
                     "value": "Another multiline text input.",
                     "name": "long_text_2",
                     "description": "Long text example 2",
+                    "placeholder_values": ["Another multiline text input."],
                 },
             ],
             test_output=[
@@ -310,11 +325,13 @@ class AgentNumberInputBlock(AgentInputBlock):
                     "value": 42,
                     "name": "number_input_1",
                     "description": "Number example 1",
+                    "placeholder_values": [],
                 },
                 {
                     "value": 314,
                     "name": "number_input_2",
                     "description": "Number example 2",
+                    "placeholder_values": [314, 2718],
                 },
             ],
             test_output=[
@@ -484,12 +501,6 @@ class AgentDropdownInputBlock(AgentInputBlock):
             title="Dropdown Options",
         )
 
-        def generate_schema(self):
-            schema = super().generate_schema()
-            if possible_values := self.placeholder_values:
-                schema["enum"] = possible_values
-            return schema
-
     class Output(AgentInputBlock.Output):
         result: str = SchemaField(description="Selected dropdown value.")
 

autogpt_platform/backend/backend/blocks/llm.py

@@ -104,18 +104,6 @@ class LlmModelMeta(EnumMeta):
 
 
 class LlmModel(str, Enum, metaclass=LlmModelMeta):
-
-    @classmethod
-    def _missing_(cls, value: object) -> "LlmModel | None":
-        """Handle provider-prefixed model names like 'anthropic/claude-sonnet-4-6'."""
-        if isinstance(value, str) and "/" in value:
-            stripped = value.split("/", 1)[1]
-            try:
-                return cls(stripped)
-            except ValueError:
-                return None
-        return None
-
     # OpenAI models
     O3_MINI = "o3-mini"
     O3 = "o3-2025-04-16"
@@ -724,9 +712,6 @@ def convert_openai_tool_fmt_to_anthropic(
 def extract_openai_reasoning(response) -> str | None:
     """Extract reasoning from OpenAI-compatible response if available."""
     """Note: This will likely not working since the reasoning is not present in another Response API"""
-    if not response.choices:
-        logger.warning("LLM response has empty choices in extract_openai_reasoning")
-        return None
     reasoning = None
     choice = response.choices[0]
     if hasattr(choice, "reasoning") and getattr(choice, "reasoning", None):
@@ -742,9 +727,6 @@ def extract_openai_reasoning(response) -> str | None:
 
 def extract_openai_tool_calls(response) -> list[ToolContentBlock] | None:
     """Extract tool calls from OpenAI-compatible response."""
-    if not response.choices:
-        logger.warning("LLM response has empty choices in extract_openai_tool_calls")
-        return None
     if response.choices[0].message.tool_calls:
         return [
             ToolContentBlock(
@@ -978,8 +960,6 @@ async def llm_call(
             response_format=response_format,  # type: ignore
             max_tokens=max_tokens,
         )
-        if not response.choices:
-            raise ValueError("Groq returned empty choices in response")
         return LLMResponse(
             raw_response=response.choices[0].message,
             prompt=prompt,
@@ -1039,8 +1019,12 @@ async def llm_call(
             parallel_tool_calls=parallel_tool_calls_param,
         )
 
+        # If there's no response, raise an error
         if not response.choices:
-            raise ValueError(f"OpenRouter returned empty choices: {response}")
+            if response:
+                raise ValueError(f"OpenRouter error: {response}")
+            else:
+                raise ValueError("No response from OpenRouter.")
 
         tool_calls = extract_openai_tool_calls(response)
         reasoning = extract_openai_reasoning(response)
@@ -1077,8 +1061,12 @@ async def llm_call(
             parallel_tool_calls=parallel_tool_calls_param,
         )
 
+        # If there's no response, raise an error
         if not response.choices:
-            raise ValueError(f"Llama API returned empty choices: {response}")
+            if response:
+                raise ValueError(f"Llama API error: {response}")
+            else:
+                raise ValueError("No response from Llama API.")
 
         tool_calls = extract_openai_tool_calls(response)
         reasoning = extract_openai_reasoning(response)
@@ -1108,8 +1096,6 @@ async def llm_call(
             messages=prompt,  # type: ignore
             max_tokens=max_tokens,
         )
-        if not completion.choices:
-            raise ValueError("AI/ML API returned empty choices in response")
 
         return LLMResponse(
             raw_response=completion.choices[0].message,
@@ -1146,9 +1132,6 @@ async def llm_call(
             parallel_tool_calls=parallel_tool_calls_param,
         )
 
-        if not response.choices:
-            raise ValueError(f"v0 API returned empty choices: {response}")
-
         tool_calls = extract_openai_tool_calls(response)
         reasoning = extract_openai_reasoning(response)
 
@@ -2016,19 +1999,6 @@ class AIConversationBlock(AIBlockBase):
     async def run(
         self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
     ) -> BlockOutput:
-        has_messages = any(
-            isinstance(m, dict)
-            and isinstance(m.get("content"), str)
-            and bool(m["content"].strip())
-            for m in (input_data.messages or [])
-        )
-        has_prompt = bool(input_data.prompt and input_data.prompt.strip())
-        if not has_messages and not has_prompt:
-            raise ValueError(
-                "Cannot call LLM with no messages and no prompt. "
-                "Provide at least one message or a non-empty prompt."
-            )
-
         response = await self.llm_call(
             AIStructuredResponseGeneratorBlock.Input(
                 prompt=input_data.prompt,

autogpt_platform/backend/backend/blocks/test/test_block.py

@@ -4,8 +4,6 @@ import pytest
 
 from backend.blocks import get_blocks
 from backend.blocks._base import Block, BlockSchemaInput
-from backend.blocks.io import AgentDropdownInputBlock, AgentInputBlock
-from backend.data.graph import BaseGraph
 from backend.data.model import SchemaField
 from backend.util.test import execute_block_test
 
@@ -281,66 +279,3 @@ class TestAutoCredentialsFieldsValidation:
         assert "Duplicate auto_credentials kwarg_name 'credentials'" in str(
             exc_info.value
         )
-
-
-def test_agent_input_block_ignores_legacy_placeholder_values():
-    """Verify AgentInputBlock.Input.model_construct tolerates extra placeholder_values
-    for backward compatibility with existing agent JSON."""
-    legacy_data = {
-        "name": "url",
-        "value": "",
-        "description": "Enter a URL",
-        "placeholder_values": ["https://example.com"],
-    }
-    instance = AgentInputBlock.Input.model_construct(**legacy_data)
-    schema = instance.generate_schema()
-    assert (
-        "enum" not in schema
-    ), "AgentInputBlock should not produce enum from legacy placeholder_values"
-
-
-def test_dropdown_input_block_produces_enum():
-    """Verify AgentDropdownInputBlock.Input.generate_schema() produces enum."""
-    options = ["Option A", "Option B"]
-    instance = AgentDropdownInputBlock.Input.model_construct(
-        name="choice", value=None, placeholder_values=options
-    )
-    schema = instance.generate_schema()
-    assert schema.get("enum") == options
-
-
-def test_generate_schema_integration_legacy_placeholder_values():
-    """Test the full Graph._generate_schema path with legacy placeholder_values
-    on AgentInputBlock — verifies no enum leaks through the graph loading path."""
-    legacy_input_default = {
-        "name": "url",
-        "value": "",
-        "description": "Enter a URL",
-        "placeholder_values": ["https://example.com"],
-    }
-    result = BaseGraph._generate_schema(
-        (AgentInputBlock.Input, legacy_input_default),
-    )
-    url_props = result["properties"]["url"]
-    assert (
-        "enum" not in url_props
-    ), "Graph schema should not contain enum from AgentInputBlock placeholder_values"
-
-
-def test_generate_schema_integration_dropdown_produces_enum():
-    """Test the full Graph._generate_schema path with AgentDropdownInputBlock
-    — verifies enum IS produced for dropdown blocks."""
-    dropdown_input_default = {
-        "name": "color",
-        "value": None,
-        "placeholder_values": ["Red", "Green", "Blue"],
-    }
-    result = BaseGraph._generate_schema(
-        (AgentDropdownInputBlock.Input, dropdown_input_default),
-    )
-    color_props = result["properties"]["color"]
-    assert color_props.get("enum") == [
-        "Red",
-        "Green",
-        "Blue",
-    ], "Graph schema should contain enum from AgentDropdownInputBlock"

autogpt_platform/backend/backend/blocks/test/test_blocks_dos_vulnerability.py

@@ -207,51 +207,6 @@ class TestXMLParserBlockSecurity:
                 pass
 
 
-class TestXMLParserBlockSyntaxErrors:
-    """XML syntax errors should raise ValueError (not SyntaxError).
-
-    This ensures the base Block.execute() wraps them as BlockExecutionError
-    (expected / user-caused) instead of BlockUnknownError (unexpected / alerts
-    Sentry).
-    """
-
-    async def test_unclosed_tag_raises_value_error(self):
-        """Unclosed tags should raise ValueError, not SyntaxError."""
-        block = XMLParserBlock()
-        bad_xml = "<root><unclosed>"
-
-        with pytest.raises(ValueError, match="Unclosed tag"):
-            async for _ in block.run(XMLParserBlock.Input(input_xml=bad_xml)):
-                pass
-
-    async def test_unexpected_closing_tag_raises_value_error(self):
-        """Extra closing tags should raise ValueError, not SyntaxError."""
-        block = XMLParserBlock()
-        bad_xml = "</unexpected>"
-
-        with pytest.raises(ValueError):
-            async for _ in block.run(XMLParserBlock.Input(input_xml=bad_xml)):
-                pass
-
-    async def test_empty_xml_raises_value_error(self):
-        """Empty XML input should raise ValueError."""
-        block = XMLParserBlock()
-
-        with pytest.raises(ValueError, match="XML input is empty"):
-            async for _ in block.run(XMLParserBlock.Input(input_xml="")):
-                pass
-
-    async def test_syntax_error_from_parser_becomes_value_error(self):
-        """SyntaxErrors from gravitasml library become ValueError (BlockExecutionError)."""
-        block = XMLParserBlock()
-        # Malformed XML that might trigger a SyntaxError from the parser
-        bad_xml = "<root><child>no closing"
-
-        with pytest.raises(ValueError):
-            async for _ in block.run(XMLParserBlock.Input(input_xml=bad_xml)):
-                pass
-
-
 class TestStoreMediaFileSecurity:
     """Test file storage security limits."""
 

autogpt_platform/backend/backend/blocks/test/test_llm.py

@@ -488,154 +488,6 @@ class TestLLMStatsTracking:
         assert outputs["response"] == {"result": "test"}
 
 
-class TestAIConversationBlockValidation:
-    """Test that AIConversationBlock validates inputs before calling the LLM."""
-
-    @pytest.mark.asyncio
-    async def test_empty_messages_and_empty_prompt_raises_error(self):
-        """Empty messages with no prompt should raise ValueError, not a cryptic API error."""
-        block = llm.AIConversationBlock()
-
-        input_data = llm.AIConversationBlock.Input(
-            messages=[],
-            prompt="",
-            model=llm.DEFAULT_LLM_MODEL,
-            credentials=_TEST_AI_CREDENTIALS,
-        )
-
-        with pytest.raises(ValueError, match="no messages and no prompt"):
-            async for _ in block.run(input_data, credentials=llm.TEST_CREDENTIALS):
-                pass
-
-    @pytest.mark.asyncio
-    async def test_empty_messages_with_prompt_succeeds(self):
-        """Empty messages but a non-empty prompt should proceed without error."""
-        block = llm.AIConversationBlock()
-
-        async def mock_llm_call(input_data, credentials):
-            return {"response": "OK"}
-
-        with patch.object(block, "llm_call", new=AsyncMock(side_effect=mock_llm_call)):
-            input_data = llm.AIConversationBlock.Input(
-                messages=[],
-                prompt="Hello, how are you?",
-                model=llm.DEFAULT_LLM_MODEL,
-                credentials=_TEST_AI_CREDENTIALS,
-            )
-
-            outputs = {}
-            async for name, data in block.run(
-                input_data, credentials=llm.TEST_CREDENTIALS
-            ):
-                outputs[name] = data
-
-        assert outputs["response"] == "OK"
-
-    @pytest.mark.asyncio
-    async def test_nonempty_messages_with_empty_prompt_succeeds(self):
-        """Non-empty messages with no prompt should proceed without error."""
-        block = llm.AIConversationBlock()
-
-        async def mock_llm_call(input_data, credentials):
-            return {"response": "response from conversation"}
-
-        with patch.object(block, "llm_call", new=AsyncMock(side_effect=mock_llm_call)):
-            input_data = llm.AIConversationBlock.Input(
-                messages=[{"role": "user", "content": "Hello"}],
-                prompt="",
-                model=llm.DEFAULT_LLM_MODEL,
-                credentials=_TEST_AI_CREDENTIALS,
-            )
-
-            outputs = {}
-            async for name, data in block.run(
-                input_data, credentials=llm.TEST_CREDENTIALS
-            ):
-                outputs[name] = data
-
-        assert outputs["response"] == "response from conversation"
-
-    @pytest.mark.asyncio
-    async def test_messages_with_empty_content_raises_error(self):
-        """Messages with empty content strings should be treated as no messages."""
-        block = llm.AIConversationBlock()
-
-        input_data = llm.AIConversationBlock.Input(
-            messages=[{"role": "user", "content": ""}],
-            prompt="",
-            model=llm.DEFAULT_LLM_MODEL,
-            credentials=_TEST_AI_CREDENTIALS,
-        )
-
-        with pytest.raises(ValueError, match="no messages and no prompt"):
-            async for _ in block.run(input_data, credentials=llm.TEST_CREDENTIALS):
-                pass
-
-    @pytest.mark.asyncio
-    async def test_messages_with_whitespace_content_raises_error(self):
-        """Messages with whitespace-only content should be treated as no messages."""
-        block = llm.AIConversationBlock()
-
-        input_data = llm.AIConversationBlock.Input(
-            messages=[{"role": "user", "content": "   "}],
-            prompt="",
-            model=llm.DEFAULT_LLM_MODEL,
-            credentials=_TEST_AI_CREDENTIALS,
-        )
-
-        with pytest.raises(ValueError, match="no messages and no prompt"):
-            async for _ in block.run(input_data, credentials=llm.TEST_CREDENTIALS):
-                pass
-
-    @pytest.mark.asyncio
-    async def test_messages_with_none_entry_raises_error(self):
-        """Messages list containing None should be treated as no messages."""
-        block = llm.AIConversationBlock()
-
-        input_data = llm.AIConversationBlock.Input(
-            messages=[None],
-            prompt="",
-            model=llm.DEFAULT_LLM_MODEL,
-            credentials=_TEST_AI_CREDENTIALS,
-        )
-
-        with pytest.raises(ValueError, match="no messages and no prompt"):
-            async for _ in block.run(input_data, credentials=llm.TEST_CREDENTIALS):
-                pass
-
-    @pytest.mark.asyncio
-    async def test_messages_with_empty_dict_raises_error(self):
-        """Messages list containing empty dict should be treated as no messages."""
-        block = llm.AIConversationBlock()
-
-        input_data = llm.AIConversationBlock.Input(
-            messages=[{}],
-            prompt="",
-            model=llm.DEFAULT_LLM_MODEL,
-            credentials=_TEST_AI_CREDENTIALS,
-        )
-
-        with pytest.raises(ValueError, match="no messages and no prompt"):
-            async for _ in block.run(input_data, credentials=llm.TEST_CREDENTIALS):
-                pass
-
-    @pytest.mark.asyncio
-    async def test_messages_with_none_content_raises_error(self):
-        """Messages with content=None should not crash with AttributeError."""
-        block = llm.AIConversationBlock()
-
-        input_data = llm.AIConversationBlock.Input(
-            messages=[{"role": "user", "content": None}],
-            prompt="",
-            model=llm.DEFAULT_LLM_MODEL,
-            credentials=_TEST_AI_CREDENTIALS,
-        )
-
-        with pytest.raises(ValueError, match="no messages and no prompt"):
-            async for _ in block.run(input_data, credentials=llm.TEST_CREDENTIALS):
-                pass
-
-
 class TestAITextSummarizerValidation:
     """Test that AITextSummarizerBlock validates LLM responses are strings."""
 
@@ -957,33 +809,3 @@ class TestUserErrorStatusCodeHandling:
 
         mock_warning.assert_called_once()
         mock_exception.assert_not_called()
-
-
-class TestLlmModelMissing:
-    """Test that LlmModel handles provider-prefixed model names."""
-
-    def test_provider_prefixed_model_resolves(self):
-        """Provider-prefixed model string should resolve to the correct enum member."""
-        assert (
-            llm.LlmModel("anthropic/claude-sonnet-4-6")
-            == llm.LlmModel.CLAUDE_4_6_SONNET
-        )
-
-    def test_bare_model_still_works(self):
-        """Bare (non-prefixed) model string should still resolve correctly."""
-        assert llm.LlmModel("claude-sonnet-4-6") == llm.LlmModel.CLAUDE_4_6_SONNET
-
-    def test_invalid_prefixed_model_raises(self):
-        """Unknown provider-prefixed model string should raise ValueError."""
-        with pytest.raises(ValueError):
-            llm.LlmModel("invalid/nonexistent-model")
-
-    def test_slash_containing_value_direct_lookup(self):
-        """Enum values with '/' (e.g., OpenRouter models) should resolve via direct lookup, not _missing_."""
-        assert llm.LlmModel("google/gemini-2.5-pro") == llm.LlmModel.GEMINI_2_5_PRO
-
-    def test_double_prefixed_slash_model(self):
-        """Double-prefixed value should still resolve by stripping first prefix."""
-        assert (
-            llm.LlmModel("extra/google/gemini-2.5-pro") == llm.LlmModel.GEMINI_2_5_PRO
-        )

autogpt_platform/backend/backend/blocks/test/test_llm_empty_choices.py

@@ -1,87 +0,0 @@
-"""Tests for empty-choices guard in extract_openai_tool_calls() and extract_openai_reasoning()."""
-
-from unittest.mock import MagicMock
-
-from backend.blocks.llm import extract_openai_reasoning, extract_openai_tool_calls
-
-
-class TestExtractOpenaiToolCallsEmptyChoices:
-    """extract_openai_tool_calls() must return None when choices is empty."""
-
-    def test_returns_none_for_empty_choices(self):
-        response = MagicMock()
-        response.choices = []
-        assert extract_openai_tool_calls(response) is None
-
-    def test_returns_none_for_none_choices(self):
-        response = MagicMock()
-        response.choices = None
-        assert extract_openai_tool_calls(response) is None
-
-    def test_returns_tool_calls_when_choices_present(self):
-        tool = MagicMock()
-        tool.id = "call_1"
-        tool.type = "function"
-        tool.function.name = "my_func"
-        tool.function.arguments = '{"a": 1}'
-
-        message = MagicMock()
-        message.tool_calls = [tool]
-
-        choice = MagicMock()
-        choice.message = message
-
-        response = MagicMock()
-        response.choices = [choice]
-
-        result = extract_openai_tool_calls(response)
-        assert result is not None
-        assert len(result) == 1
-        assert result[0].function.name == "my_func"
-
-    def test_returns_none_when_no_tool_calls(self):
-        message = MagicMock()
-        message.tool_calls = None
-
-        choice = MagicMock()
-        choice.message = message
-
-        response = MagicMock()
-        response.choices = [choice]
-
-        assert extract_openai_tool_calls(response) is None
-
-
-class TestExtractOpenaiReasoningEmptyChoices:
-    """extract_openai_reasoning() must return None when choices is empty."""
-
-    def test_returns_none_for_empty_choices(self):
-        response = MagicMock()
-        response.choices = []
-        assert extract_openai_reasoning(response) is None
-
-    def test_returns_none_for_none_choices(self):
-        response = MagicMock()
-        response.choices = None
-        assert extract_openai_reasoning(response) is None
-
-    def test_returns_reasoning_from_choice(self):
-        choice = MagicMock()
-        choice.reasoning = "Step-by-step reasoning"
-        choice.message = MagicMock(spec=[])  # no 'reasoning' attr on message
-
-        response = MagicMock(spec=[])  # no 'reasoning' attr on response
-        response.choices = [choice]
-
-        result = extract_openai_reasoning(response)
-        assert result == "Step-by-step reasoning"
-
-    def test_returns_none_when_no_reasoning(self):
-        choice = MagicMock(spec=[])  # no 'reasoning' attr
-        choice.message = MagicMock(spec=[])  # no 'reasoning' attr
-
-        response = MagicMock(spec=[])  # no 'reasoning' attr
-        response.choices = [choice]
-
-        result = extract_openai_reasoning(response)
-        assert result is None

autogpt_platform/backend/backend/blocks/test/test_orchestrator.py

@@ -1074,7 +1074,6 @@ async def test_orchestrator_uses_customized_name_for_blocks():
     mock_node.block_id = StoreValueBlock().id
     mock_node.metadata = {"customized_name": "My Custom Tool Name"}
     mock_node.block = StoreValueBlock()
-    mock_node.input_default = {}
 
     # Create a mock link
     mock_link = MagicMock(spec=Link)
@@ -1106,7 +1105,6 @@ async def test_orchestrator_falls_back_to_block_name():
     mock_node.block_id = StoreValueBlock().id
     mock_node.metadata = {}  # No customized_name
     mock_node.block = StoreValueBlock()
-    mock_node.input_default = {}
 
     # Create a mock link
     mock_link = MagicMock(spec=Link)

autogpt_platform/backend/backend/blocks/test/test_orchestrator_execution_mode.py

@@ -1,202 +0,0 @@
-"""Tests for ExecutionMode enum and provider validation in the orchestrator.
-
-Covers:
-- ExecutionMode enum members exist and have stable values
-- EXTENDED_THINKING provider validation (anthropic/open_router allowed, others rejected)
-- EXTENDED_THINKING model-name validation (must start with "claude")
-"""
-
-from unittest.mock import AsyncMock, MagicMock, patch
-
-import pytest
-
-from backend.blocks.llm import LlmModel
-from backend.blocks.orchestrator import ExecutionMode, OrchestratorBlock
-
-# ---------------------------------------------------------------------------
-# ExecutionMode enum integrity
-# ---------------------------------------------------------------------------
-
-
-class TestExecutionModeEnum:
-    """Guard against accidental renames or removals of enum members."""
-
-    def test_built_in_exists(self):
-        assert hasattr(ExecutionMode, "BUILT_IN")
-        assert ExecutionMode.BUILT_IN.value == "built_in"
-
-    def test_extended_thinking_exists(self):
-        assert hasattr(ExecutionMode, "EXTENDED_THINKING")
-        assert ExecutionMode.EXTENDED_THINKING.value == "extended_thinking"
-
-    def test_exactly_two_members(self):
-        """If a new mode is added, this test should be updated intentionally."""
-        assert set(ExecutionMode.__members__.keys()) == {
-            "BUILT_IN",
-            "EXTENDED_THINKING",
-        }
-
-    def test_string_enum(self):
-        """ExecutionMode is a str enum so it serialises cleanly to JSON."""
-        assert isinstance(ExecutionMode.BUILT_IN, str)
-        assert isinstance(ExecutionMode.EXTENDED_THINKING, str)
-
-    def test_round_trip_from_value(self):
-        """Constructing from the string value should return the same member."""
-        assert ExecutionMode("built_in") is ExecutionMode.BUILT_IN
-        assert ExecutionMode("extended_thinking") is ExecutionMode.EXTENDED_THINKING
-
-
-# ---------------------------------------------------------------------------
-# Provider validation (inline in OrchestratorBlock.run)
-# ---------------------------------------------------------------------------
-
-
-def _make_model_stub(provider: str, value: str):
-    """Create a lightweight stub that behaves like LlmModel for validation."""
-    metadata = MagicMock()
-    metadata.provider = provider
-    stub = MagicMock()
-    stub.metadata = metadata
-    stub.value = value
-    return stub
-
-
-class TestExtendedThinkingProviderValidation:
-    """The orchestrator rejects EXTENDED_THINKING for non-Anthropic providers."""
-
-    def test_anthropic_provider_accepted(self):
-        """provider='anthropic' + claude model should not raise."""
-        model = _make_model_stub("anthropic", "claude-opus-4-6")
-        provider = model.metadata.provider
-        model_name = model.value
-        assert provider in ("anthropic", "open_router")
-        assert model_name.startswith("claude")
-
-    def test_open_router_provider_accepted(self):
-        """provider='open_router' + claude model should not raise."""
-        model = _make_model_stub("open_router", "claude-sonnet-4-6")
-        provider = model.metadata.provider
-        model_name = model.value
-        assert provider in ("anthropic", "open_router")
-        assert model_name.startswith("claude")
-
-    def test_openai_provider_rejected(self):
-        """provider='openai' should be rejected for EXTENDED_THINKING."""
-        model = _make_model_stub("openai", "gpt-4o")
-        provider = model.metadata.provider
-        assert provider not in ("anthropic", "open_router")
-
-    def test_groq_provider_rejected(self):
-        model = _make_model_stub("groq", "llama-3.3-70b-versatile")
-        provider = model.metadata.provider
-        assert provider not in ("anthropic", "open_router")
-
-    def test_non_claude_model_rejected_even_if_anthropic_provider(self):
-        """A hypothetical non-Claude model with provider='anthropic' is rejected."""
-        model = _make_model_stub("anthropic", "not-a-claude-model")
-        model_name = model.value
-        assert not model_name.startswith("claude")
-
-    def test_real_gpt4o_model_rejected(self):
-        """Verify a real LlmModel enum member (GPT4O) fails the provider check."""
-        model = LlmModel.GPT4O
-        provider = model.metadata.provider
-        assert provider not in ("anthropic", "open_router")
-
-    def test_real_claude_model_passes(self):
-        """Verify a real LlmModel enum member (CLAUDE_4_6_SONNET) passes."""
-        model = LlmModel.CLAUDE_4_6_SONNET
-        provider = model.metadata.provider
-        model_name = model.value
-        assert provider in ("anthropic", "open_router")
-        assert model_name.startswith("claude")
-
-
-# ---------------------------------------------------------------------------
-# Integration-style: exercise the validation branch via OrchestratorBlock.run
-# ---------------------------------------------------------------------------
-
-
-def _make_input_data(model, execution_mode=ExecutionMode.EXTENDED_THINKING):
-    """Build a minimal MagicMock that satisfies OrchestratorBlock.run's early path."""
-    inp = MagicMock()
-    inp.execution_mode = execution_mode
-    inp.model = model
-    inp.prompt = "test"
-    inp.sys_prompt = ""
-    inp.conversation_history = []
-    inp.last_tool_output = None
-    inp.prompt_values = {}
-    return inp
-
-
-async def _collect_run_outputs(block, input_data, **kwargs):
-    """Exhaust the OrchestratorBlock.run async generator, collecting outputs."""
-    outputs = []
-    async for item in block.run(input_data, **kwargs):
-        outputs.append(item)
-    return outputs
-
-
-class TestExtendedThinkingValidationRaisesInBlock:
-    """Call OrchestratorBlock.run far enough to trigger the ValueError."""
-
-    @pytest.mark.asyncio
-    async def test_non_anthropic_provider_raises_valueerror(self):
-        """EXTENDED_THINKING + openai provider raises ValueError."""
-        block = OrchestratorBlock()
-        input_data = _make_input_data(model=LlmModel.GPT4O)
-
-        with (
-            patch.object(
-                block,
-                "_create_tool_node_signatures",
-                new_callable=AsyncMock,
-                return_value=[],
-            ),
-            pytest.raises(ValueError, match="Anthropic-compatible"),
-        ):
-            await _collect_run_outputs(
-                block,
-                input_data,
-                credentials=MagicMock(),
-                graph_id="g",
-                node_id="n",
-                graph_exec_id="ge",
-                node_exec_id="ne",
-                user_id="u",
-                graph_version=1,
-                execution_context=MagicMock(),
-                execution_processor=MagicMock(),
-            )
-
-    @pytest.mark.asyncio
-    async def test_non_claude_model_with_anthropic_provider_raises(self):
-        """A model with anthropic provider but non-claude name raises ValueError."""
-        block = OrchestratorBlock()
-        fake_model = _make_model_stub("anthropic", "not-a-claude-model")
-        input_data = _make_input_data(model=fake_model)
-
-        with (
-            patch.object(
-                block,
-                "_create_tool_node_signatures",
-                new_callable=AsyncMock,
-                return_value=[],
-            ),
-            pytest.raises(ValueError, match="only supports Claude models"),
-        ):
-            await _collect_run_outputs(
-                block,
-                input_data,
-                credentials=MagicMock(),
-                graph_id="g",
-                node_id="n",
-                graph_exec_id="ge",
-                node_exec_id="ne",
-                user_id="u",
-                graph_version=1,
-                execution_context=MagicMock(),
-                execution_processor=MagicMock(),
-            )

autogpt_platform/backend/backend/blocks/xml_parser.py

@@ -44,7 +44,7 @@ class XMLParserBlock(Block):
             elif token.type == "TAG_CLOSE":
                 depth -= 1
                 if depth < 0:
-                    raise ValueError("Unexpected closing tag in XML input.")
+                    raise SyntaxError("Unexpected closing tag in XML input.")
             elif token.type in {"TEXT", "ESCAPE"}:
                 if depth == 0 and token.value:
                     raise ValueError(
@@ -53,7 +53,7 @@ class XMLParserBlock(Block):
                     )
 
         if depth != 0:
-            raise ValueError("Unclosed tag detected in XML input.")
+            raise SyntaxError("Unclosed tag detected in XML input.")
         if not root_seen:
             raise ValueError("XML must include a root element.")
 
@@ -76,7 +76,4 @@ class XMLParserBlock(Block):
         except ValueError as val_e:
             raise ValueError(f"Validation error for dict:{val_e}") from val_e
         except SyntaxError as syn_e:
-            # Raise as ValueError so the base Block.execute() wraps it as
-            # BlockExecutionError (expected user-caused failure) instead of
-            # BlockUnknownError (unexpected platform error that alerts Sentry).
-            raise ValueError(f"Error in input xml syntax: {syn_e}") from syn_e
+            raise SyntaxError(f"Error in input xml syntax: {syn_e}") from syn_e

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

@@ -9,14 +9,11 @@ shared tool registry as the SDK path.
 import asyncio
 import logging
 import uuid
-from collections.abc import AsyncGenerator, Sequence
-from dataclasses import dataclass, field
-from functools import partial
-from typing import Any, cast
+from collections.abc import AsyncGenerator
+from typing import Any
 
 import orjson
 from langfuse import propagate_attributes
-from openai.types.chat import ChatCompletionMessageParam, ChatCompletionToolParam
 
 from backend.copilot.model import (
     ChatMessage,
@@ -51,17 +48,7 @@ from backend.copilot.token_tracking import persist_and_record_usage
 from backend.copilot.tools import execute_tool, get_available_tools
 from backend.copilot.tracking import track_user_message
 from backend.util.exceptions import NotFoundError
-from backend.util.prompt import (
-    compress_context,
-    estimate_token_count,
-    estimate_token_count_str,
-)
-from backend.util.tool_call_loop import (
-    LLMLoopResponse,
-    LLMToolCall,
-    ToolCallResult,
-    tool_call_loop,
-)
+from backend.util.prompt import compress_context
 
 logger = logging.getLogger(__name__)
 
@@ -72,247 +59,6 @@ _background_tasks: set[asyncio.Task[Any]] = set()
 _MAX_TOOL_ROUNDS = 30
 
 
-@dataclass
-class _BaselineStreamState:
-    """Mutable state shared between the tool-call loop callbacks.
-
-    Extracted from ``stream_chat_completion_baseline`` so that the callbacks
-    can be module-level functions instead of deeply nested closures.
-    """
-
-    pending_events: list[StreamBaseResponse] = field(default_factory=list)
-    assistant_text: str = ""
-    text_block_id: str = field(default_factory=lambda: str(uuid.uuid4()))
-    text_started: bool = False
-    turn_prompt_tokens: int = 0
-    turn_completion_tokens: int = 0
-
-
-async def _baseline_llm_caller(
-    messages: list[dict[str, Any]],
-    tools: Sequence[Any],
-    *,
-    state: _BaselineStreamState,
-) -> LLMLoopResponse:
-    """Stream an OpenAI-compatible response and collect results.
-
-    Extracted from ``stream_chat_completion_baseline`` for readability.
-    """
-    state.pending_events.append(StreamStartStep())
-
-    round_text = ""
-    try:
-        client = _get_openai_client()
-        typed_messages = cast(list[ChatCompletionMessageParam], messages)
-        if tools:
-            typed_tools = cast(list[ChatCompletionToolParam], tools)
-            response = await client.chat.completions.create(
-                model=config.model,
-                messages=typed_messages,
-                tools=typed_tools,
-                stream=True,
-                stream_options={"include_usage": True},
-            )
-        else:
-            response = await client.chat.completions.create(
-                model=config.model,
-                messages=typed_messages,
-                stream=True,
-                stream_options={"include_usage": True},
-            )
-        tool_calls_by_index: dict[int, dict[str, str]] = {}
-
-        async for chunk in response:
-            if chunk.usage:
-                state.turn_prompt_tokens += chunk.usage.prompt_tokens or 0
-                state.turn_completion_tokens += chunk.usage.completion_tokens or 0
-
-            delta = chunk.choices[0].delta if chunk.choices else None
-            if not delta:
-                continue
-
-            if delta.content:
-                if not state.text_started:
-                    state.pending_events.append(StreamTextStart(id=state.text_block_id))
-                    state.text_started = True
-                round_text += delta.content
-                state.pending_events.append(
-                    StreamTextDelta(id=state.text_block_id, delta=delta.content)
-                )
-
-            if delta.tool_calls:
-                for tc in delta.tool_calls:
-                    idx = tc.index
-                    if idx not in tool_calls_by_index:
-                        tool_calls_by_index[idx] = {
-                            "id": "",
-                            "name": "",
-                            "arguments": "",
-                        }
-                    entry = tool_calls_by_index[idx]
-                    if tc.id:
-                        entry["id"] = tc.id
-                    if tc.function and tc.function.name:
-                        entry["name"] = tc.function.name
-                    if tc.function and tc.function.arguments:
-                        entry["arguments"] += tc.function.arguments
-
-        # Close text block
-        if state.text_started:
-            state.pending_events.append(StreamTextEnd(id=state.text_block_id))
-            state.text_started = False
-            state.text_block_id = str(uuid.uuid4())
-    finally:
-        # Always persist partial text so the session history stays consistent,
-        # even when the stream is interrupted by an exception.
-        state.assistant_text += round_text
-        # Always emit StreamFinishStep to match the StreamStartStep,
-        # even if an exception occurred during streaming.
-        state.pending_events.append(StreamFinishStep())
-
-    # Convert to shared format
-    llm_tool_calls = [
-        LLMToolCall(
-            id=tc["id"],
-            name=tc["name"],
-            arguments=tc["arguments"] or "{}",
-        )
-        for tc in tool_calls_by_index.values()
-    ]
-
-    return LLMLoopResponse(
-        response_text=round_text or None,
-        tool_calls=llm_tool_calls,
-        raw_response=None,  # Not needed for baseline conversation updater
-        prompt_tokens=0,  # Tracked via state accumulators
-        completion_tokens=0,
-    )
-
-
-async def _baseline_tool_executor(
-    tool_call: LLMToolCall,
-    tools: Sequence[Any],
-    *,
-    state: _BaselineStreamState,
-    user_id: str | None,
-    session: ChatSession,
-) -> ToolCallResult:
-    """Execute a tool via the copilot tool registry.
-
-    Extracted from ``stream_chat_completion_baseline`` for readability.
-    """
-    tool_call_id = tool_call.id
-    tool_name = tool_call.name
-    raw_args = tool_call.arguments or "{}"
-
-    try:
-        tool_args = orjson.loads(raw_args)
-    except orjson.JSONDecodeError as parse_err:
-        parse_error = f"Invalid JSON arguments for tool '{tool_name}': {parse_err}"
-        logger.warning("[Baseline] %s", parse_error)
-        state.pending_events.append(
-            StreamToolOutputAvailable(
-                toolCallId=tool_call_id,
-                toolName=tool_name,
-                output=parse_error,
-                success=False,
-            )
-        )
-        return ToolCallResult(
-            tool_call_id=tool_call_id,
-            tool_name=tool_name,
-            content=parse_error,
-            is_error=True,
-        )
-
-    state.pending_events.append(
-        StreamToolInputStart(toolCallId=tool_call_id, toolName=tool_name)
-    )
-    state.pending_events.append(
-        StreamToolInputAvailable(
-            toolCallId=tool_call_id,
-            toolName=tool_name,
-            input=tool_args,
-        )
-    )
-
-    try:
-        result: StreamToolOutputAvailable = await execute_tool(
-            tool_name=tool_name,
-            parameters=tool_args,
-            user_id=user_id,
-            session=session,
-            tool_call_id=tool_call_id,
-        )
-        state.pending_events.append(result)
-        tool_output = (
-            result.output if isinstance(result.output, str) else str(result.output)
-        )
-        return ToolCallResult(
-            tool_call_id=tool_call_id,
-            tool_name=tool_name,
-            content=tool_output,
-        )
-    except Exception as e:
-        error_output = f"Tool execution error: {e}"
-        logger.error(
-            "[Baseline] Tool %s failed: %s",
-            tool_name,
-            error_output,
-            exc_info=True,
-        )
-        state.pending_events.append(
-            StreamToolOutputAvailable(
-                toolCallId=tool_call_id,
-                toolName=tool_name,
-                output=error_output,
-                success=False,
-            )
-        )
-        return ToolCallResult(
-            tool_call_id=tool_call_id,
-            tool_name=tool_name,
-            content=error_output,
-            is_error=True,
-        )
-
-
-def _baseline_conversation_updater(
-    messages: list[dict[str, Any]],
-    response: LLMLoopResponse,
-    tool_results: list[ToolCallResult] | None = None,
-) -> None:
-    """Update OpenAI message list with assistant response + tool results.
-
-    Extracted from ``stream_chat_completion_baseline`` for readability.
-    """
-    if tool_results:
-        # Build assistant message with tool_calls
-        assistant_msg: dict[str, Any] = {"role": "assistant"}
-        if response.response_text:
-            assistant_msg["content"] = response.response_text
-        assistant_msg["tool_calls"] = [
-            {
-                "id": tc.id,
-                "type": "function",
-                "function": {"name": tc.name, "arguments": tc.arguments},
-            }
-            for tc in response.tool_calls
-        ]
-        messages.append(assistant_msg)
-        for tr in tool_results:
-            messages.append(
-                {
-                    "role": "tool",
-                    "tool_call_id": tr.tool_call_id,
-                    "content": tr.content,
-                }
-            )
-    else:
-        if response.response_text:
-            messages.append({"role": "assistant", "content": response.response_text})
-
-
 async def _update_title_async(
     session_id: str, message: str, user_id: str | None
 ) -> None:
@@ -473,32 +219,191 @@ async def stream_chat_completion_baseline(
     except Exception:
         logger.warning("[Baseline] Langfuse trace context setup failed")
 
+    assistant_text = ""
+    text_block_id = str(uuid.uuid4())
+    text_started = False
+    step_open = False
+    # Token usage accumulators — populated from streaming chunks
+    turn_prompt_tokens = 0
+    turn_completion_tokens = 0
     _stream_error = False  # Track whether an error occurred during streaming
-    state = _BaselineStreamState()
-
-    # Bind extracted module-level callbacks to this request's state/session
-    # using functools.partial so they satisfy the Protocol signatures.
-    _bound_llm_caller = partial(_baseline_llm_caller, state=state)
-    _bound_tool_executor = partial(
-        _baseline_tool_executor, state=state, user_id=user_id, session=session
-    )
-
     try:
-        loop_result = None
-        async for loop_result in tool_call_loop(
-            messages=openai_messages,
-            tools=tools,
-            llm_call=_bound_llm_caller,
-            execute_tool=_bound_tool_executor,
-            update_conversation=_baseline_conversation_updater,
-            max_iterations=_MAX_TOOL_ROUNDS,
-        ):
-            # Drain buffered events after each iteration (real-time streaming)
-            for evt in state.pending_events:
-                yield evt
-            state.pending_events.clear()
+        for _round in range(_MAX_TOOL_ROUNDS):
+            # Open a new step for each LLM round
+            yield StreamStartStep()
+            step_open = True
 
-        if loop_result and not loop_result.finished_naturally:
+            # Stream a response from the model
+            create_kwargs: dict[str, Any] = dict(
+                model=config.model,
+                messages=openai_messages,
+                stream=True,
+                stream_options={"include_usage": True},
+            )
+            if tools:
+                create_kwargs["tools"] = tools
+            response = await _get_openai_client().chat.completions.create(**create_kwargs)  # type: ignore[arg-type]  # dynamic kwargs
+
+            # Accumulate streamed response (text + tool calls)
+            round_text = ""
+            tool_calls_by_index: dict[int, dict[str, str]] = {}
+
+            async for chunk in response:
+                # Capture token usage from the streaming chunk.
+                # OpenRouter normalises all providers into OpenAI format
+                # where prompt_tokens already includes cached tokens
+                # (unlike Anthropic's native API). Use += to sum all
+                # tool-call rounds since each API call is independent.
+                # NOTE: stream_options={"include_usage": True} is not
+                # universally supported — some providers (Mistral, Llama
+                # via OpenRouter) always return chunk.usage=None. When
+                # that happens, tokens stay 0 and the tiktoken fallback
+                # below activates. Fail-open: one round is estimated.
+                if chunk.usage:
+                    turn_prompt_tokens += chunk.usage.prompt_tokens or 0
+                    turn_completion_tokens += chunk.usage.completion_tokens or 0
+
+                delta = chunk.choices[0].delta if chunk.choices else None
+                if not delta:
+                    continue
+
+                # Text content
+                if delta.content:
+                    if not text_started:
+                        yield StreamTextStart(id=text_block_id)
+                        text_started = True
+                    round_text += delta.content
+                    yield StreamTextDelta(id=text_block_id, delta=delta.content)
+
+                # Tool call fragments (streamed incrementally)
+                if delta.tool_calls:
+                    for tc in delta.tool_calls:
+                        idx = tc.index
+                        if idx not in tool_calls_by_index:
+                            tool_calls_by_index[idx] = {
+                                "id": "",
+                                "name": "",
+                                "arguments": "",
+                            }
+                        entry = tool_calls_by_index[idx]
+                        if tc.id:
+                            entry["id"] = tc.id
+                        if tc.function and tc.function.name:
+                            entry["name"] = tc.function.name
+                        if tc.function and tc.function.arguments:
+                            entry["arguments"] += tc.function.arguments
+
+            # Close text block if we had one this round
+            if text_started:
+                yield StreamTextEnd(id=text_block_id)
+                text_started = False
+                text_block_id = str(uuid.uuid4())
+
+            # Accumulate text for session persistence
+            assistant_text += round_text
+
+            # No tool calls -> model is done
+            if not tool_calls_by_index:
+                yield StreamFinishStep()
+                step_open = False
+                break
+
+            # Close step before tool execution
+            yield StreamFinishStep()
+            step_open = False
+
+            # Append the assistant message with tool_calls to context.
+            assistant_msg: dict[str, Any] = {"role": "assistant"}
+            if round_text:
+                assistant_msg["content"] = round_text
+            assistant_msg["tool_calls"] = [
+                {
+                    "id": tc["id"],
+                    "type": "function",
+                    "function": {
+                        "name": tc["name"],
+                        "arguments": tc["arguments"] or "{}",
+                    },
+                }
+                for tc in tool_calls_by_index.values()
+            ]
+            openai_messages.append(assistant_msg)
+
+            # Execute each tool call and stream events
+            for tc in tool_calls_by_index.values():
+                tool_call_id = tc["id"]
+                tool_name = tc["name"]
+                raw_args = tc["arguments"] or "{}"
+                try:
+                    tool_args = orjson.loads(raw_args)
+                except orjson.JSONDecodeError as parse_err:
+                    parse_error = (
+                        f"Invalid JSON arguments for tool '{tool_name}': {parse_err}"
+                    )
+                    logger.warning("[Baseline] %s", parse_error)
+                    yield StreamToolOutputAvailable(
+                        toolCallId=tool_call_id,
+                        toolName=tool_name,
+                        output=parse_error,
+                        success=False,
+                    )
+                    openai_messages.append(
+                        {
+                            "role": "tool",
+                            "tool_call_id": tool_call_id,
+                            "content": parse_error,
+                        }
+                    )
+                    continue
+
+                yield StreamToolInputStart(toolCallId=tool_call_id, toolName=tool_name)
+                yield StreamToolInputAvailable(
+                    toolCallId=tool_call_id,
+                    toolName=tool_name,
+                    input=tool_args,
+                )
+
+                # Execute via shared tool registry
+                try:
+                    result: StreamToolOutputAvailable = await execute_tool(
+                        tool_name=tool_name,
+                        parameters=tool_args,
+                        user_id=user_id,
+                        session=session,
+                        tool_call_id=tool_call_id,
+                    )
+                    yield result
+                    tool_output = (
+                        result.output
+                        if isinstance(result.output, str)
+                        else str(result.output)
+                    )
+                except Exception as e:
+                    error_output = f"Tool execution error: {e}"
+                    logger.error(
+                        "[Baseline] Tool %s failed: %s",
+                        tool_name,
+                        error_output,
+                        exc_info=True,
+                    )
+                    yield StreamToolOutputAvailable(
+                        toolCallId=tool_call_id,
+                        toolName=tool_name,
+                        output=error_output,
+                        success=False,
+                    )
+                    tool_output = error_output
+
+                # Append tool result to context for next round
+                openai_messages.append(
+                    {
+                        "role": "tool",
+                        "tool_call_id": tool_call_id,
+                        "content": tool_output,
+                    }
+                )
+        else:
+            # for-loop exhausted without break -> tool-round limit hit
             limit_msg = (
                 f"Exceeded {_MAX_TOOL_ROUNDS} tool-call rounds "
                 "without a final response."
@@ -513,28 +418,11 @@ async def stream_chat_completion_baseline(
         _stream_error = True
         error_msg = str(e) or type(e).__name__
         logger.error("[Baseline] Streaming error: %s", error_msg, exc_info=True)
-        # Close any open text block.  The llm_caller's finally block
-        # already appended StreamFinishStep to pending_events, so we must
-        # insert StreamTextEnd *before* StreamFinishStep to preserve the
-        # protocol ordering:
-        #   StreamStartStep -> StreamTextStart -> ...deltas... ->
-        #   StreamTextEnd -> StreamFinishStep
-        # Appending (or yielding directly) would place it after
-        # StreamFinishStep, violating the protocol.
-        if state.text_started:
-            # Find the last StreamFinishStep and insert before it.
-            insert_pos = len(state.pending_events)
-            for i in range(len(state.pending_events) - 1, -1, -1):
-                if isinstance(state.pending_events[i], StreamFinishStep):
-                    insert_pos = i
-                    break
-            state.pending_events.insert(
-                insert_pos, StreamTextEnd(id=state.text_block_id)
-            )
-        # Drain pending events in correct order
-        for evt in state.pending_events:
-            yield evt
-        state.pending_events.clear()
+        # Close any open text/step before emitting error
+        if text_started:
+            yield StreamTextEnd(id=text_block_id)
+        if step_open:
+            yield StreamFinishStep()
         yield StreamError(errorText=error_msg, code="baseline_error")
         # Still persist whatever we got
     finally:
@@ -554,21 +442,26 @@ async def stream_chat_completion_baseline(
         # Skip fallback when an error occurred and no output was produced —
         # charging rate-limit tokens for completely failed requests is unfair.
         if (
-            state.turn_prompt_tokens == 0
-            and state.turn_completion_tokens == 0
-            and not (_stream_error and not state.assistant_text)
+            turn_prompt_tokens == 0
+            and turn_completion_tokens == 0
+            and not (_stream_error and not assistant_text)
         ):
-            state.turn_prompt_tokens = max(
+            from backend.util.prompt import (
+                estimate_token_count,
+                estimate_token_count_str,
+            )
+
+            turn_prompt_tokens = max(
                 estimate_token_count(openai_messages, model=config.model), 1
             )
-            state.turn_completion_tokens = estimate_token_count_str(
-                state.assistant_text, model=config.model
+            turn_completion_tokens = estimate_token_count_str(
+                assistant_text, model=config.model
             )
             logger.info(
                 "[Baseline] No streaming usage reported; estimated tokens: "
                 "prompt=%d, completion=%d",
-                state.turn_prompt_tokens,
-                state.turn_completion_tokens,
+                turn_prompt_tokens,
+                turn_completion_tokens,
             )
 
         # Persist token usage to session and record for rate limiting.
@@ -578,15 +471,15 @@ async def stream_chat_completion_baseline(
         await persist_and_record_usage(
             session=session,
             user_id=user_id,
-            prompt_tokens=state.turn_prompt_tokens,
-            completion_tokens=state.turn_completion_tokens,
+            prompt_tokens=turn_prompt_tokens,
+            completion_tokens=turn_completion_tokens,
             log_prefix="[Baseline]",
         )
 
         # Persist assistant response
-        if state.assistant_text:
+        if assistant_text:
             session.messages.append(
-                ChatMessage(role="assistant", content=state.assistant_text)
+                ChatMessage(role="assistant", content=assistant_text)
             )
         try:
             await upsert_chat_session(session)
@@ -598,11 +491,11 @@ async def stream_chat_completion_baseline(
     # aclose() — doing so raises RuntimeError on client disconnect.
     # On GeneratorExit the client is already gone, so unreachable yields
     # are harmless; on normal completion they reach the SSE stream.
-    if state.turn_prompt_tokens > 0 or state.turn_completion_tokens > 0:
+    if turn_prompt_tokens > 0 or turn_completion_tokens > 0:
         yield StreamUsage(
-            prompt_tokens=state.turn_prompt_tokens,
-            completion_tokens=state.turn_completion_tokens,
-            total_tokens=state.turn_prompt_tokens + state.turn_completion_tokens,
+            prompt_tokens=turn_prompt_tokens,
+            completion_tokens=turn_completion_tokens,
+            total_tokens=turn_prompt_tokens + turn_completion_tokens,
         )
 
     yield StreamFinish()

autogpt_platform/backend/backend/copilot/config.py

@@ -91,20 +91,6 @@ class ChatConfig(BaseSettings):
         description="Max tokens per week, resets Monday 00:00 UTC (0 = unlimited)",
     )
 
-    # Cost (in credits / cents) to reset the daily rate limit using credits.
-    # When a user hits their daily limit, they can spend this amount to reset
-    # the daily counter and keep working.  Set to 0 to disable the feature.
-    rate_limit_reset_cost: int = Field(
-        default=500,
-        ge=0,
-        description="Credit cost (in cents) for resetting the daily rate limit. 0 = disabled.",
-    )
-    max_daily_resets: int = Field(
-        default=5,
-        ge=0,
-        description="Maximum number of credit-based rate limit resets per user per day. 0 = unlimited.",
-    )
-
     # Claude Agent SDK Configuration
     use_claude_agent_sdk: bool = Field(
         default=True,
@@ -178,7 +164,7 @@ class ChatConfig(BaseSettings):
 
         Single source of truth for "will the SDK route through OpenRouter?".
         Checks the flag *and* that ``api_key`` + a valid ``base_url`` are
-        present — mirrors the fallback logic in ``build_sdk_env``.
+        present — mirrors the fallback logic in ``_build_sdk_env``.
         """
         if not self.use_openrouter:
             return False

autogpt_platform/backend/backend/copilot/db.py

@@ -18,7 +18,7 @@ from prisma.types import (
 from backend.data import db
 from backend.util.json import SafeJson, sanitize_string
 
-from .model import ChatMessage, ChatSession, ChatSessionInfo, invalidate_session_cache
+from .model import ChatMessage, ChatSession, ChatSessionInfo
 
 logger = logging.getLogger(__name__)
 
@@ -217,9 +217,6 @@ async def add_chat_messages_batch(
                     if msg.get("function_call") is not None:
                         data["functionCall"] = SafeJson(msg["function_call"])
 
-                    if msg.get("duration_ms") is not None:
-                        data["durationMs"] = msg["duration_ms"]
-
                     messages_data.append(data)
 
                 # Run create_many and session update in parallel within transaction
@@ -362,22 +359,3 @@ async def update_tool_message_content(
             f"tool_call_id {tool_call_id}: {e}"
         )
         return False
-
-
-async def set_turn_duration(session_id: str, duration_ms: int) -> None:
-    """Set durationMs on the last assistant message in a session.
-
-    Also invalidates the Redis session cache so the next GET returns
-    the updated duration.
-    """
-    last_msg = await PrismaChatMessage.prisma().find_first(
-        where={"sessionId": session_id, "role": "assistant"},
-        order={"sequence": "desc"},
-    )
-    if last_msg:
-        await PrismaChatMessage.prisma().update(
-            where={"id": last_msg.id},
-            data={"durationMs": duration_ms},
-        )
-        # Invalidate cache so the session is re-fetched from DB with durationMs
-        await invalidate_session_cache(session_id)

autogpt_platform/backend/backend/copilot/model.py

@@ -54,7 +54,6 @@ class ChatMessage(BaseModel):
     refusal: str | None = None
     tool_calls: list[dict] | None = None
     function_call: dict | None = None
-    duration_ms: int | None = None
 
     @staticmethod
     def from_db(prisma_message: PrismaChatMessage) -> "ChatMessage":
@@ -67,7 +66,6 @@ class ChatMessage(BaseModel):
             refusal=prisma_message.refusal,
             tool_calls=_parse_json_field(prisma_message.toolCalls),
             function_call=_parse_json_field(prisma_message.functionCall),
-            duration_ms=prisma_message.durationMs,
         )
 
 

autogpt_platform/backend/backend/copilot/prompting.py

@@ -205,10 +205,9 @@ Important files (code, configs, outputs) should be saved to workspace to ensure
 ### SDK tool-result files
 When tool outputs are large, the SDK truncates them and saves the full output to
 a local file under `~/.claude/projects/.../tool-results/`. To read these files,
-always use `Read` (NOT `bash_exec`, NOT `read_workspace_file`).
-These files are on the host filesystem — `bash_exec` runs in the sandbox and
-CANNOT access them. `read_workspace_file` reads from cloud workspace storage,
-where SDK tool-results are NOT stored.
+always use `read_file` or `Read` (NOT `read_workspace_file`).
+`read_workspace_file` reads from cloud workspace storage, where SDK
+tool-results are NOT stored.
 {_SHARED_TOOL_NOTES}{extra_notes}"""
 
 

autogpt_platform/backend/backend/copilot/rate_limit.py

@@ -36,10 +36,6 @@ class CoPilotUsageStatus(BaseModel):
 
     daily: UsageWindow
     weekly: UsageWindow
-    reset_cost: int = Field(
-        default=0,
-        description="Credit cost (in cents) to reset the daily limit. 0 = feature disabled.",
-    )
 
 
 class RateLimitExceeded(Exception):
@@ -65,7 +61,6 @@ async def get_usage_status(
     user_id: str,
     daily_token_limit: int,
     weekly_token_limit: int,
-    rate_limit_reset_cost: int = 0,
 ) -> CoPilotUsageStatus:
     """Get current usage status for a user.
 
@@ -73,7 +68,6 @@ async def get_usage_status(
         user_id: The user's ID.
         daily_token_limit: Max tokens per day (0 = unlimited).
         weekly_token_limit: Max tokens per week (0 = unlimited).
-        rate_limit_reset_cost: Credit cost (cents) to reset daily limit (0 = disabled).
 
     Returns:
         CoPilotUsageStatus with current usage and limits.
@@ -103,7 +97,6 @@ async def get_usage_status(
             limit=weekly_token_limit,
             resets_at=_weekly_reset_time(now=now),
         ),
-        reset_cost=rate_limit_reset_cost,
     )
 
 
@@ -148,110 +141,6 @@ async def check_rate_limit(
         raise RateLimitExceeded("weekly", _weekly_reset_time(now=now))
 
 
-async def reset_daily_usage(user_id: str, daily_token_limit: int = 0) -> bool:
-    """Reset a user's daily token usage counter in Redis.
-
-    Called after a user pays credits to extend their daily limit.
-    Also reduces the weekly usage counter by ``daily_token_limit`` tokens
-    (clamped to 0) so the user effectively gets one extra day's worth of
-    weekly capacity.
-
-    Args:
-        user_id: The user's ID.
-        daily_token_limit: The configured daily token limit. When positive,
-            the weekly counter is reduced by this amount.
-
-    Fails open: returns False if Redis is unavailable (consistent with
-    the fail-open design of this module).
-    """
-    now = datetime.now(UTC)
-    try:
-        redis = await get_redis_async()
-
-        # Use a MULTI/EXEC transaction so that DELETE (daily) and DECRBY
-        # (weekly) either both execute or neither does.  This prevents the
-        # scenario where the daily counter is cleared but the weekly
-        # counter is not decremented — which would let the caller refund
-        # credits even though the daily limit was already reset.
-        d_key = _daily_key(user_id, now=now)
-        w_key = _weekly_key(user_id, now=now) if daily_token_limit > 0 else None
-
-        pipe = redis.pipeline(transaction=True)
-        pipe.delete(d_key)
-        if w_key is not None:
-            pipe.decrby(w_key, daily_token_limit)
-        results = await pipe.execute()
-
-        # Clamp negative weekly counter to 0 (best-effort; not critical).
-        if w_key is not None:
-            new_val = results[1]  # DECRBY result
-            if new_val < 0:
-                await redis.set(w_key, 0, keepttl=True)
-
-        logger.info("Reset daily usage for user %s", user_id[:8])
-        return True
-    except (RedisError, ConnectionError, OSError):
-        logger.warning("Redis unavailable for resetting daily usage")
-        return False
-
-
-_RESET_LOCK_PREFIX = "copilot:reset_lock"
-_RESET_COUNT_PREFIX = "copilot:reset_count"
-
-
-async def acquire_reset_lock(user_id: str, ttl_seconds: int = 10) -> bool:
-    """Acquire a short-lived lock to serialize rate limit resets per user."""
-    try:
-        redis = await get_redis_async()
-        key = f"{_RESET_LOCK_PREFIX}:{user_id}"
-        return bool(await redis.set(key, "1", nx=True, ex=ttl_seconds))
-    except (RedisError, ConnectionError, OSError) as exc:
-        logger.warning("Redis unavailable for reset lock, rejecting reset: %s", exc)
-        return False
-
-
-async def release_reset_lock(user_id: str) -> None:
-    """Release the per-user reset lock."""
-    try:
-        redis = await get_redis_async()
-        await redis.delete(f"{_RESET_LOCK_PREFIX}:{user_id}")
-    except (RedisError, ConnectionError, OSError):
-        pass  # Lock will expire via TTL
-
-
-async def get_daily_reset_count(user_id: str) -> int | None:
-    """Get how many times the user has reset today.
-
-    Returns None when Redis is unavailable so callers can fail-closed
-    for billed operations (as opposed to failing open for read-only
-    rate-limit checks).
-    """
-    now = datetime.now(UTC)
-    try:
-        redis = await get_redis_async()
-        key = f"{_RESET_COUNT_PREFIX}:{user_id}:{now.strftime('%Y-%m-%d')}"
-        val = await redis.get(key)
-        return int(val or 0)
-    except (RedisError, ConnectionError, OSError):
-        logger.warning("Redis unavailable for reading daily reset count")
-        return None
-
-
-async def increment_daily_reset_count(user_id: str) -> None:
-    """Increment and track how many resets this user has done today."""
-    now = datetime.now(UTC)
-    try:
-        redis = await get_redis_async()
-        key = f"{_RESET_COUNT_PREFIX}:{user_id}:{now.strftime('%Y-%m-%d')}"
-        pipe = redis.pipeline(transaction=True)
-        pipe.incr(key)
-        seconds_until_reset = int((_daily_reset_time(now=now) - now).total_seconds())
-        pipe.expire(key, max(seconds_until_reset, 1))
-        await pipe.execute()
-    except (RedisError, ConnectionError, OSError):
-        logger.warning("Redis unavailable for tracking reset count")
-
-
 async def record_token_usage(
     user_id: str,
     prompt_tokens: int,
@@ -342,67 +231,6 @@ async def record_token_usage(
         )
 
 
-async def get_global_rate_limits(
-    user_id: str,
-    config_daily: int,
-    config_weekly: int,
-) -> tuple[int, int]:
-    """Resolve global rate limits from LaunchDarkly, falling back to config.
-
-    Args:
-        user_id: User ID for LD flag evaluation context.
-        config_daily: Fallback daily limit from ChatConfig.
-        config_weekly: Fallback weekly limit from ChatConfig.
-
-    Returns:
-        (daily_token_limit, weekly_token_limit) tuple.
-    """
-    # Lazy import to avoid circular dependency:
-    # rate_limit -> feature_flag -> settings -> ... -> rate_limit
-    from backend.util.feature_flag import Flag, get_feature_flag_value
-
-    daily_raw = await get_feature_flag_value(
-        Flag.COPILOT_DAILY_TOKEN_LIMIT.value, user_id, config_daily
-    )
-    weekly_raw = await get_feature_flag_value(
-        Flag.COPILOT_WEEKLY_TOKEN_LIMIT.value, user_id, config_weekly
-    )
-    try:
-        daily = max(0, int(daily_raw))
-    except (TypeError, ValueError):
-        logger.warning("Invalid LD value for daily token limit: %r", daily_raw)
-        daily = config_daily
-    try:
-        weekly = max(0, int(weekly_raw))
-    except (TypeError, ValueError):
-        logger.warning("Invalid LD value for weekly token limit: %r", weekly_raw)
-        weekly = config_weekly
-    return daily, weekly
-
-
-async def reset_user_usage(user_id: str, *, reset_weekly: bool = False) -> None:
-    """Reset a user's usage counters.
-
-    Always deletes the daily Redis key.  When *reset_weekly* is ``True``,
-    the weekly key is deleted as well.
-
-    Unlike read paths (``get_usage_status``, ``check_rate_limit``) which
-    fail-open on Redis errors, resets intentionally re-raise so the caller
-    knows the operation did not succeed.  A silent failure here would leave
-    the admin believing the counters were zeroed when they were not.
-    """
-    now = datetime.now(UTC)
-    keys_to_delete = [_daily_key(user_id, now=now)]
-    if reset_weekly:
-        keys_to_delete.append(_weekly_key(user_id, now=now))
-    try:
-        redis = await get_redis_async()
-        await redis.delete(*keys_to_delete)
-    except (RedisError, ConnectionError, OSError):
-        logger.warning("Redis unavailable for resetting user usage")
-        raise
-
-
 # ---------------------------------------------------------------------------
 # Private helpers
 # ---------------------------------------------------------------------------

autogpt_platform/backend/backend/copilot/rate_limit_test.py

@@ -12,7 +12,6 @@ from .rate_limit import (
     check_rate_limit,
     get_usage_status,
     record_token_usage,
-    reset_daily_usage,
 )
 
 _USER = "test-user-rl"
@@ -333,91 +332,3 @@ class TestRecordTokenUsage:
         ):
             # Should not raise — fail-open
             await record_token_usage(_USER, prompt_tokens=100, completion_tokens=50)
-
-
-# ---------------------------------------------------------------------------
-# reset_daily_usage
-# ---------------------------------------------------------------------------
-
-
-class TestResetDailyUsage:
-    @staticmethod
-    def _make_pipeline_mock(decrby_result: int = 0) -> MagicMock:
-        """Create a pipeline mock that returns [delete_result, decrby_result]."""
-        pipe = MagicMock()
-        pipe.execute = AsyncMock(return_value=[1, decrby_result])
-        return pipe
-
-    @pytest.mark.asyncio
-    async def test_deletes_daily_key(self):
-        mock_pipe = self._make_pipeline_mock(decrby_result=0)
-        mock_redis = AsyncMock()
-        mock_redis.pipeline = lambda **_kw: mock_pipe
-
-        with patch(
-            "backend.copilot.rate_limit.get_redis_async",
-            return_value=mock_redis,
-        ):
-            result = await reset_daily_usage(_USER, daily_token_limit=10000)
-
-        assert result is True
-        mock_pipe.delete.assert_called_once()
-
-    @pytest.mark.asyncio
-    async def test_reduces_weekly_usage_via_decrby(self):
-        """Weekly counter should be reduced via DECRBY in the pipeline."""
-        mock_pipe = self._make_pipeline_mock(decrby_result=35000)
-        mock_redis = AsyncMock()
-        mock_redis.pipeline = lambda **_kw: mock_pipe
-
-        with patch(
-            "backend.copilot.rate_limit.get_redis_async",
-            return_value=mock_redis,
-        ):
-            await reset_daily_usage(_USER, daily_token_limit=10000)
-
-        mock_pipe.decrby.assert_called_once()
-        mock_redis.set.assert_not_called()  # 35000 > 0, no clamp needed
-
-    @pytest.mark.asyncio
-    async def test_clamps_negative_weekly_to_zero(self):
-        """If DECRBY goes negative, SET to 0 (outside the pipeline)."""
-        mock_pipe = self._make_pipeline_mock(decrby_result=-5000)
-        mock_redis = AsyncMock()
-        mock_redis.pipeline = lambda **_kw: mock_pipe
-
-        with patch(
-            "backend.copilot.rate_limit.get_redis_async",
-            return_value=mock_redis,
-        ):
-            await reset_daily_usage(_USER, daily_token_limit=10000)
-
-        mock_pipe.decrby.assert_called_once()
-        mock_redis.set.assert_called_once()
-
-    @pytest.mark.asyncio
-    async def test_no_weekly_reduction_when_daily_limit_zero(self):
-        """When daily_token_limit is 0, weekly counter should not be touched."""
-        mock_pipe = self._make_pipeline_mock()
-        mock_pipe.execute = AsyncMock(return_value=[1])  # only delete result
-        mock_redis = AsyncMock()
-        mock_redis.pipeline = lambda **_kw: mock_pipe
-
-        with patch(
-            "backend.copilot.rate_limit.get_redis_async",
-            return_value=mock_redis,
-        ):
-            await reset_daily_usage(_USER, daily_token_limit=0)
-
-        mock_pipe.delete.assert_called_once()
-        mock_pipe.decrby.assert_not_called()
-
-    @pytest.mark.asyncio
-    async def test_returns_false_when_redis_unavailable(self):
-        with patch(
-            "backend.copilot.rate_limit.get_redis_async",
-            side_effect=ConnectionError("Redis down"),
-        ):
-            result = await reset_daily_usage(_USER, daily_token_limit=10000)
-
-        assert result is False

autogpt_platform/backend/backend/copilot/reset_usage_test.py

@@ -1,294 +0,0 @@
-"""Unit tests for the POST /usage/reset endpoint."""
-
-from __future__ import annotations
-
-from datetime import UTC, datetime, timedelta
-from unittest.mock import AsyncMock, MagicMock, patch
-
-import pytest
-from fastapi import HTTPException
-
-from backend.api.features.chat.routes import reset_copilot_usage
-from backend.copilot.rate_limit import CoPilotUsageStatus, UsageWindow
-from backend.util.exceptions import InsufficientBalanceError
-
-
-# Minimal config mock matching ChatConfig fields used by the endpoint.
-def _make_config(
-    rate_limit_reset_cost: int = 500,
-    daily_token_limit: int = 2_500_000,
-    weekly_token_limit: int = 12_500_000,
-    max_daily_resets: int = 5,
-):
-    cfg = MagicMock()
-    cfg.rate_limit_reset_cost = rate_limit_reset_cost
-    cfg.daily_token_limit = daily_token_limit
-    cfg.weekly_token_limit = weekly_token_limit
-    cfg.max_daily_resets = max_daily_resets
-    return cfg
-
-
-def _usage(daily_used: int = 3_000_000, daily_limit: int = 2_500_000):
-    return CoPilotUsageStatus(
-        daily=UsageWindow(
-            used=daily_used,
-            limit=daily_limit,
-            resets_at=datetime.now(UTC) + timedelta(hours=6),
-        ),
-        weekly=UsageWindow(
-            used=5_000_000,
-            limit=12_500_000,
-            resets_at=datetime.now(UTC) + timedelta(days=3),
-        ),
-    )
-
-
-_MODULE = "backend.api.features.chat.routes"
-
-
-def _mock_settings(enable_credit: bool = True):
-    """Return a mock Settings object with the given enable_credit flag."""
-    mock = MagicMock()
-    mock.config.enable_credit = enable_credit
-    return mock
-
-
-@pytest.mark.asyncio
-class TestResetCopilotUsage:
-    async def test_feature_disabled_returns_400(self):
-        """When rate_limit_reset_cost=0, endpoint returns 400."""
-
-        with patch(f"{_MODULE}.config", _make_config(rate_limit_reset_cost=0)):
-            with pytest.raises(HTTPException) as exc_info:
-                await reset_copilot_usage(user_id="user-1")
-            assert exc_info.value.status_code == 400
-            assert "not available" in exc_info.value.detail
-
-    async def test_no_daily_limit_returns_400(self):
-        """When daily_token_limit=0 (unlimited), endpoint returns 400."""
-
-        with (
-            patch(f"{_MODULE}.config", _make_config(daily_token_limit=0)),
-            patch(f"{_MODULE}.settings", _mock_settings()),
-        ):
-            with pytest.raises(HTTPException) as exc_info:
-                await reset_copilot_usage(user_id="user-1")
-            assert exc_info.value.status_code == 400
-            assert "nothing to reset" in exc_info.value.detail.lower()
-
-    async def test_not_at_limit_returns_400(self):
-        """When user hasn't hit their daily limit, returns 400."""
-
-        cfg = _make_config()
-        with (
-            patch(f"{_MODULE}.config", cfg),
-            patch(f"{_MODULE}.settings", _mock_settings()),
-            patch(f"{_MODULE}.get_daily_reset_count", AsyncMock(return_value=0)),
-            patch(f"{_MODULE}.acquire_reset_lock", AsyncMock(return_value=True)),
-            patch(f"{_MODULE}.release_reset_lock", AsyncMock()) as mock_release,
-            patch(
-                f"{_MODULE}.get_usage_status",
-                AsyncMock(return_value=_usage(daily_used=1_000_000)),
-            ),
-        ):
-            with pytest.raises(HTTPException) as exc_info:
-                await reset_copilot_usage(user_id="user-1")
-            assert exc_info.value.status_code == 400
-            assert "not reached" in exc_info.value.detail
-            mock_release.assert_awaited_once()
-
-    async def test_insufficient_credits_returns_402(self):
-        """When user doesn't have enough credits, returns 402."""
-
-        mock_credit_model = AsyncMock()
-        mock_credit_model.spend_credits.side_effect = InsufficientBalanceError(
-            message="Insufficient balance",
-            user_id="user-1",
-            balance=50,
-            amount=200,
-        )
-
-        cfg = _make_config()
-        with (
-            patch(f"{_MODULE}.config", cfg),
-            patch(f"{_MODULE}.settings", _mock_settings()),
-            patch(f"{_MODULE}.get_daily_reset_count", AsyncMock(return_value=0)),
-            patch(f"{_MODULE}.acquire_reset_lock", AsyncMock(return_value=True)),
-            patch(f"{_MODULE}.release_reset_lock", AsyncMock()) as mock_release,
-            patch(
-                f"{_MODULE}.get_usage_status",
-                AsyncMock(return_value=_usage()),
-            ),
-            patch(
-                f"{_MODULE}.get_user_credit_model",
-                AsyncMock(return_value=mock_credit_model),
-            ),
-        ):
-            with pytest.raises(HTTPException) as exc_info:
-                await reset_copilot_usage(user_id="user-1")
-            assert exc_info.value.status_code == 402
-            mock_release.assert_awaited_once()
-
-    async def test_happy_path(self):
-        """Successful reset: charges credits, resets usage, returns response."""
-
-        mock_credit_model = AsyncMock()
-        mock_credit_model.spend_credits.return_value = 1500  # remaining balance
-
-        cfg = _make_config()
-        updated_usage = _usage(daily_used=0)
-
-        with (
-            patch(f"{_MODULE}.config", cfg),
-            patch(f"{_MODULE}.settings", _mock_settings()),
-            patch(f"{_MODULE}.get_daily_reset_count", AsyncMock(return_value=0)),
-            patch(f"{_MODULE}.acquire_reset_lock", AsyncMock(return_value=True)),
-            patch(f"{_MODULE}.release_reset_lock", AsyncMock()),
-            patch(
-                f"{_MODULE}.get_usage_status",
-                AsyncMock(side_effect=[_usage(), updated_usage]),
-            ),
-            patch(
-                f"{_MODULE}.get_user_credit_model",
-                AsyncMock(return_value=mock_credit_model),
-            ),
-            patch(
-                f"{_MODULE}.reset_daily_usage", AsyncMock(return_value=True)
-            ) as mock_reset,
-            patch(f"{_MODULE}.increment_daily_reset_count", AsyncMock()) as mock_incr,
-        ):
-            result = await reset_copilot_usage(user_id="user-1")
-            assert result.success is True
-            assert result.credits_charged == 500
-            assert result.remaining_balance == 1500
-            mock_reset.assert_awaited_once()
-            mock_incr.assert_awaited_once()
-
-    async def test_max_daily_resets_exceeded(self):
-        """When user has exhausted daily resets, returns 429."""
-
-        cfg = _make_config(max_daily_resets=3)
-        with (
-            patch(f"{_MODULE}.config", cfg),
-            patch(f"{_MODULE}.settings", _mock_settings()),
-            patch(f"{_MODULE}.get_daily_reset_count", AsyncMock(return_value=3)),
-        ):
-            with pytest.raises(HTTPException) as exc_info:
-                await reset_copilot_usage(user_id="user-1")
-            assert exc_info.value.status_code == 429
-
-    async def test_credit_system_disabled_returns_400(self):
-        """When enable_credit=False, endpoint returns 400."""
-
-        with (
-            patch(f"{_MODULE}.config", _make_config()),
-            patch(f"{_MODULE}.settings", _mock_settings(enable_credit=False)),
-        ):
-            with pytest.raises(HTTPException) as exc_info:
-                await reset_copilot_usage(user_id="user-1")
-            assert exc_info.value.status_code == 400
-            assert "credit system is disabled" in exc_info.value.detail.lower()
-
-    async def test_weekly_limit_exhausted_returns_400(self):
-        """When the weekly limit is also exhausted, resetting daily won't help."""
-
-        cfg = _make_config()
-        weekly_exhausted = CoPilotUsageStatus(
-            daily=UsageWindow(
-                used=3_000_000,
-                limit=2_500_000,
-                resets_at=datetime.now(UTC) + timedelta(hours=6),
-            ),
-            weekly=UsageWindow(
-                used=12_500_000,
-                limit=12_500_000,
-                resets_at=datetime.now(UTC) + timedelta(days=3),
-            ),
-        )
-        with (
-            patch(f"{_MODULE}.config", cfg),
-            patch(f"{_MODULE}.settings", _mock_settings()),
-            patch(f"{_MODULE}.get_daily_reset_count", AsyncMock(return_value=0)),
-            patch(f"{_MODULE}.acquire_reset_lock", AsyncMock(return_value=True)),
-            patch(f"{_MODULE}.release_reset_lock", AsyncMock()) as mock_release,
-            patch(
-                f"{_MODULE}.get_usage_status",
-                AsyncMock(return_value=weekly_exhausted),
-            ),
-        ):
-            with pytest.raises(HTTPException) as exc_info:
-                await reset_copilot_usage(user_id="user-1")
-            assert exc_info.value.status_code == 400
-            assert "weekly" in exc_info.value.detail.lower()
-            mock_release.assert_awaited_once()
-
-    async def test_redis_failure_for_reset_count_returns_503(self):
-        """When Redis is unavailable for get_daily_reset_count, returns 503."""
-
-        with (
-            patch(f"{_MODULE}.config", _make_config()),
-            patch(f"{_MODULE}.settings", _mock_settings()),
-            patch(f"{_MODULE}.get_daily_reset_count", AsyncMock(return_value=None)),
-        ):
-            with pytest.raises(HTTPException) as exc_info:
-                await reset_copilot_usage(user_id="user-1")
-            assert exc_info.value.status_code == 503
-            assert "verify" in exc_info.value.detail.lower()
-
-    async def test_redis_reset_failure_refunds_credits(self):
-        """When reset_daily_usage fails, credits are refunded and 503 returned."""
-
-        mock_credit_model = AsyncMock()
-        mock_credit_model.spend_credits.return_value = 1500
-
-        cfg = _make_config()
-        with (
-            patch(f"{_MODULE}.config", cfg),
-            patch(f"{_MODULE}.settings", _mock_settings()),
-            patch(f"{_MODULE}.get_daily_reset_count", AsyncMock(return_value=0)),
-            patch(f"{_MODULE}.acquire_reset_lock", AsyncMock(return_value=True)),
-            patch(f"{_MODULE}.release_reset_lock", AsyncMock()),
-            patch(
-                f"{_MODULE}.get_usage_status",
-                AsyncMock(return_value=_usage()),
-            ),
-            patch(
-                f"{_MODULE}.get_user_credit_model",
-                AsyncMock(return_value=mock_credit_model),
-            ),
-            patch(f"{_MODULE}.reset_daily_usage", AsyncMock(return_value=False)),
-        ):
-            with pytest.raises(HTTPException) as exc_info:
-                await reset_copilot_usage(user_id="user-1")
-            assert exc_info.value.status_code == 503
-            assert "not been charged" in exc_info.value.detail
-            mock_credit_model.top_up_credits.assert_awaited_once()
-
-    async def test_redis_reset_failure_refund_also_fails(self):
-        """When both reset and refund fail, error message reflects the truth."""
-
-        mock_credit_model = AsyncMock()
-        mock_credit_model.spend_credits.return_value = 1500
-        mock_credit_model.top_up_credits.side_effect = RuntimeError("db down")
-
-        cfg = _make_config()
-        with (
-            patch(f"{_MODULE}.config", cfg),
-            patch(f"{_MODULE}.settings", _mock_settings()),
-            patch(f"{_MODULE}.get_daily_reset_count", AsyncMock(return_value=0)),
-            patch(f"{_MODULE}.acquire_reset_lock", AsyncMock(return_value=True)),
-            patch(f"{_MODULE}.release_reset_lock", AsyncMock()),
-            patch(
-                f"{_MODULE}.get_usage_status",
-                AsyncMock(return_value=_usage()),
-            ),
-            patch(
-                f"{_MODULE}.get_user_credit_model",
-                AsyncMock(return_value=mock_credit_model),
-            ),
-            patch(f"{_MODULE}.reset_daily_usage", AsyncMock(return_value=False)),
-        ):
-            with pytest.raises(HTTPException) as exc_info:
-                await reset_copilot_usage(user_id="user-1")
-            assert exc_info.value.status_code == 503
-            assert "contact support" in exc_info.value.detail.lower()

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

@@ -67,17 +67,9 @@ 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`
+- Optional: `title`, `description`, `placeholder_values` (for dropdowns)
 - Output: `result` — the user-provided value at runtime
 - Create one AgentInputBlock per distinct input the agent needs
-- For dropdown/select inputs, use **AgentDropdownInputBlock** instead (see below)
-
-**AgentDropdownInputBlock** (ID: `655d6fdf-a334-421c-b733-520549c07cd1`):
-- Specialized input block that presents a dropdown/select to the user
-- Required `input_default` fields: `name` (str), `placeholder_values` (list of options, must have at least one)
-- Optional: `title`, `description`, `value` (default selection)
-- Output: `result` — the user-selected value at runtime
-- Use this instead of AgentInputBlock when the user should pick from a fixed set of options
 
 **AgentOutputBlock** (ID: `363ae599-353e-4804-937e-b2ee3cef3da4`):
 - Defines a user-facing output displayed after the agent runs

autogpt_platform/backend/backend/copilot/sdk/conftest.py

@@ -25,64 +25,24 @@ def build_test_transcript(pairs: list[tuple[str, str]]) -> str:
 
     Use this helper in any copilot SDK test that needs a well-formed
     transcript without hitting the real storage layer.
-
-    Delegates to ``build_structured_transcript`` — plain content strings
-    are automatically wrapped in ``[{"type": "text", "text": ...}]`` for
-    assistant messages.
-    """
-    # Cast widening: tuple[str, str] is structurally compatible with
-    # tuple[str, str | list[dict]] but list invariance requires explicit
-    # annotation.
-    widened: list[tuple[str, str | list[dict]]] = list(pairs)
-    return build_structured_transcript(widened)
-
-
-def build_structured_transcript(
-    entries: list[tuple[str, str | list[dict]]],
-) -> str:
-    """Build a JSONL transcript with structured content blocks.
-
-    Each entry is (role, content) where content is either a plain string
-    (for user messages) or a list of content block dicts (for assistant
-    messages with thinking/tool_use/text blocks).
-
-    Example::
-
-        build_structured_transcript([
-            ("user", "Hello"),
-            ("assistant", [
-                {"type": "thinking", "thinking": "...", "signature": "sig1"},
-                {"type": "text", "text": "Hi there"},
-            ]),
-        ])
     """
     lines: list[str] = []
     last_uuid: str | None = None
-    for role, content in entries:
+    for role, content in pairs:
         uid = str(uuid4())
         entry_type = "assistant" if role == "assistant" else "user"
-        if role == "assistant" and isinstance(content, list):
-            msg: dict = {
-                "role": "assistant",
-                "model": "claude-test",
-                "id": f"msg_{uid[:8]}",
-                "type": "message",
-                "content": content,
-                "stop_reason": "end_turn",
-                "stop_sequence": None,
-            }
-        elif role == "assistant":
-            msg = {
-                "role": "assistant",
-                "model": "claude-test",
-                "id": f"msg_{uid[:8]}",
-                "type": "message",
-                "content": [{"type": "text", "text": content}],
-                "stop_reason": "end_turn",
-                "stop_sequence": None,
-            }
-        else:
-            msg = {"role": role, "content": content}
+        msg: dict = {"role": role, "content": content}
+        if role == "assistant":
+            msg.update(
+                {
+                    "model": "",
+                    "id": f"msg_{uid[:8]}",
+                    "type": "message",
+                    "content": [{"type": "text", "text": content}],
+                    "stop_reason": "end_turn",
+                    "stop_sequence": None,
+                }
+            )
         entry = {
             "type": entry_type,
             "uuid": uid,

autogpt_platform/backend/backend/copilot/sdk/env.py

@@ -1,68 +0,0 @@
-"""SDK environment variable builder — importable without circular deps.
-
-Extracted from ``service.py`` so that ``backend.blocks.orchestrator``
-can reuse the same subscription / OpenRouter / direct-Anthropic logic
-without pulling in the full copilot service module (which would create a
-circular import through ``executor`` → ``credit`` → ``block_cost_config``).
-"""
-
-from __future__ import annotations
-
-from backend.copilot.config import ChatConfig
-from backend.copilot.sdk.subscription import validate_subscription
-
-# ChatConfig is stateless (reads env vars) — a separate instance is fine.
-# A singleton would require importing service.py which causes the circular dep
-# this module was created to avoid.
-config = ChatConfig()
-
-
-def build_sdk_env(
-    session_id: str | None = None,
-    user_id: str | None = None,
-) -> dict[str, str]:
-    """Build env vars for the SDK CLI subprocess.
-
-    Three modes (checked in order):
-    1. **Subscription** — clears all keys; CLI uses ``claude login`` auth.
-    2. **Direct Anthropic** — returns ``{}``; subprocess inherits
-       ``ANTHROPIC_API_KEY`` from the parent environment.
-    3. **OpenRouter** (default) — overrides base URL and auth token to
-       route through the proxy, with Langfuse trace headers.
-    """
-    # --- Mode 1: Claude Code subscription auth ---
-    if config.use_claude_code_subscription:
-        validate_subscription()
-        return {
-            "ANTHROPIC_API_KEY": "",
-            "ANTHROPIC_AUTH_TOKEN": "",
-            "ANTHROPIC_BASE_URL": "",
-        }
-
-    # --- Mode 2: Direct Anthropic (no proxy hop) ---
-    if not config.openrouter_active:
-        return {}
-
-    # --- Mode 3: OpenRouter proxy ---
-    base = (config.base_url or "").rstrip("/")
-    if base.endswith("/v1"):
-        base = base[:-3]
-    env: dict[str, str] = {
-        "ANTHROPIC_BASE_URL": base,
-        "ANTHROPIC_AUTH_TOKEN": config.api_key or "",
-        "ANTHROPIC_API_KEY": "",  # force CLI to use AUTH_TOKEN
-    }
-
-    # Inject broadcast headers so OpenRouter forwards traces to Langfuse.
-    def _safe(v: str) -> str:
-        return v.replace("\r", "").replace("\n", "").strip()[:128]
-
-    parts = []
-    if session_id:
-        parts.append(f"x-session-id: {_safe(session_id)}")
-    if user_id:
-        parts.append(f"x-user-id: {_safe(user_id)}")
-    if parts:
-        env["ANTHROPIC_CUSTOM_HEADERS"] = "\n".join(parts)
-
-    return env

autogpt_platform/backend/backend/copilot/sdk/env_test.py

@@ -1,242 +0,0 @@
-"""Tests for build_sdk_env() — the SDK subprocess environment builder."""
-
-from unittest.mock import patch
-
-import pytest
-
-from backend.copilot.config import ChatConfig
-
-# ---------------------------------------------------------------------------
-# Helpers — build a ChatConfig with explicit field values so tests don't
-# depend on real environment variables.
-# ---------------------------------------------------------------------------
-
-
-def _make_config(**overrides) -> ChatConfig:
-    """Create a ChatConfig with safe defaults, applying *overrides*."""
-    defaults = {
-        "use_claude_code_subscription": False,
-        "use_openrouter": False,
-        "api_key": None,
-        "base_url": None,
-    }
-    defaults.update(overrides)
-    return ChatConfig(**defaults)
-
-
-# ---------------------------------------------------------------------------
-# Mode 1 — Subscription auth
-# ---------------------------------------------------------------------------
-
-
-class TestBuildSdkEnvSubscription:
-    """When ``use_claude_code_subscription`` is True, keys are blanked."""
-
-    @patch("backend.copilot.sdk.env.validate_subscription")
-    def test_returns_blanked_keys(self, mock_validate):
-        """Subscription mode clears API_KEY, AUTH_TOKEN, and BASE_URL."""
-        cfg = _make_config(use_claude_code_subscription=True)
-        with patch("backend.copilot.sdk.env.config", cfg):
-            from backend.copilot.sdk.env import build_sdk_env
-
-            result = build_sdk_env()
-
-        assert result == {
-            "ANTHROPIC_API_KEY": "",
-            "ANTHROPIC_AUTH_TOKEN": "",
-            "ANTHROPIC_BASE_URL": "",
-        }
-        mock_validate.assert_called_once()
-
-    @patch(
-        "backend.copilot.sdk.env.validate_subscription",
-        side_effect=RuntimeError("CLI not found"),
-    )
-    def test_propagates_validation_error(self, mock_validate):
-        """If validate_subscription fails, the error bubbles up."""
-        cfg = _make_config(use_claude_code_subscription=True)
-        with patch("backend.copilot.sdk.env.config", cfg):
-            from backend.copilot.sdk.env import build_sdk_env
-
-            with pytest.raises(RuntimeError, match="CLI not found"):
-                build_sdk_env()
-
-
-# ---------------------------------------------------------------------------
-# Mode 2 — Direct Anthropic (no OpenRouter)
-# ---------------------------------------------------------------------------
-
-
-class TestBuildSdkEnvDirectAnthropic:
-    """When OpenRouter is inactive, return empty dict (inherit parent env)."""
-
-    def test_returns_empty_dict_when_openrouter_inactive(self):
-        cfg = _make_config(use_openrouter=False)
-        with patch("backend.copilot.sdk.env.config", cfg):
-            from backend.copilot.sdk.env import build_sdk_env
-
-            result = build_sdk_env()
-
-        assert result == {}
-
-    def test_returns_empty_dict_when_openrouter_flag_true_but_no_key(self):
-        """OpenRouter flag is True but no api_key => openrouter_active is False."""
-        cfg = _make_config(use_openrouter=True, base_url="https://openrouter.ai/api/v1")
-        # Force api_key to None after construction (field_validator may pick up env vars)
-        object.__setattr__(cfg, "api_key", None)
-        assert not cfg.openrouter_active
-        with patch("backend.copilot.sdk.env.config", cfg):
-            from backend.copilot.sdk.env import build_sdk_env
-
-            result = build_sdk_env()
-
-        assert result == {}
-
-
-# ---------------------------------------------------------------------------
-# Mode 3 — OpenRouter proxy
-# ---------------------------------------------------------------------------
-
-
-class TestBuildSdkEnvOpenRouter:
-    """When OpenRouter is active, return proxy env vars."""
-
-    def _openrouter_config(self, **overrides):
-        defaults = {
-            "use_openrouter": True,
-            "api_key": "sk-or-test-key",
-            "base_url": "https://openrouter.ai/api/v1",
-        }
-        defaults.update(overrides)
-        return _make_config(**defaults)
-
-    def test_basic_openrouter_env(self):
-        cfg = self._openrouter_config()
-        with patch("backend.copilot.sdk.env.config", cfg):
-            from backend.copilot.sdk.env import build_sdk_env
-
-            result = build_sdk_env()
-
-        assert result["ANTHROPIC_BASE_URL"] == "https://openrouter.ai/api"
-        assert result["ANTHROPIC_AUTH_TOKEN"] == "sk-or-test-key"
-        assert result["ANTHROPIC_API_KEY"] == ""
-        assert "ANTHROPIC_CUSTOM_HEADERS" not in result
-
-    def test_strips_trailing_v1(self):
-        """The /v1 suffix is stripped from the base URL."""
-        cfg = self._openrouter_config(base_url="https://openrouter.ai/api/v1")
-        with patch("backend.copilot.sdk.env.config", cfg):
-            from backend.copilot.sdk.env import build_sdk_env
-
-            result = build_sdk_env()
-
-        assert result["ANTHROPIC_BASE_URL"] == "https://openrouter.ai/api"
-
-    def test_strips_trailing_v1_and_slash(self):
-        """Trailing slash before /v1 strip is handled."""
-        cfg = self._openrouter_config(base_url="https://openrouter.ai/api/v1/")
-        with patch("backend.copilot.sdk.env.config", cfg):
-            from backend.copilot.sdk.env import build_sdk_env
-
-            result = build_sdk_env()
-
-        # rstrip("/") first, then remove /v1
-        assert result["ANTHROPIC_BASE_URL"] == "https://openrouter.ai/api"
-
-    def test_no_v1_suffix_left_alone(self):
-        """A base URL without /v1 is used as-is."""
-        cfg = self._openrouter_config(base_url="https://custom-proxy.example.com")
-        with patch("backend.copilot.sdk.env.config", cfg):
-            from backend.copilot.sdk.env import build_sdk_env
-
-            result = build_sdk_env()
-
-        assert result["ANTHROPIC_BASE_URL"] == "https://custom-proxy.example.com"
-
-    def test_session_id_header(self):
-        cfg = self._openrouter_config()
-        with patch("backend.copilot.sdk.env.config", cfg):
-            from backend.copilot.sdk.env import build_sdk_env
-
-            result = build_sdk_env(session_id="sess-123")
-
-        assert "ANTHROPIC_CUSTOM_HEADERS" in result
-        assert "x-session-id: sess-123" in result["ANTHROPIC_CUSTOM_HEADERS"]
-
-    def test_user_id_header(self):
-        cfg = self._openrouter_config()
-        with patch("backend.copilot.sdk.env.config", cfg):
-            from backend.copilot.sdk.env import build_sdk_env
-
-            result = build_sdk_env(user_id="user-456")
-
-        assert "x-user-id: user-456" in result["ANTHROPIC_CUSTOM_HEADERS"]
-
-    def test_both_headers(self):
-        cfg = self._openrouter_config()
-        with patch("backend.copilot.sdk.env.config", cfg):
-            from backend.copilot.sdk.env import build_sdk_env
-
-            result = build_sdk_env(session_id="s1", user_id="u2")
-
-        headers = result["ANTHROPIC_CUSTOM_HEADERS"]
-        assert "x-session-id: s1" in headers
-        assert "x-user-id: u2" in headers
-        # They should be newline-separated
-        assert "\n" in headers
-
-    def test_header_sanitisation_strips_newlines(self):
-        """Newlines/carriage-returns in header values are stripped."""
-        cfg = self._openrouter_config()
-        with patch("backend.copilot.sdk.env.config", cfg):
-            from backend.copilot.sdk.env import build_sdk_env
-
-            result = build_sdk_env(session_id="bad\r\nvalue")
-
-        header_val = result["ANTHROPIC_CUSTOM_HEADERS"]
-        # The _safe helper removes \r and \n
-        assert "\r" not in header_val.split(": ", 1)[1]
-        assert "badvalue" in header_val
-
-    def test_header_value_truncated_to_128_chars(self):
-        """Header values are truncated to 128 characters."""
-        cfg = self._openrouter_config()
-        with patch("backend.copilot.sdk.env.config", cfg):
-            from backend.copilot.sdk.env import build_sdk_env
-
-            long_id = "x" * 200
-            result = build_sdk_env(session_id=long_id)
-
-        # The value after "x-session-id: " should be at most 128 chars
-        header_line = result["ANTHROPIC_CUSTOM_HEADERS"]
-        value = header_line.split(": ", 1)[1]
-        assert len(value) == 128
-
-
-# ---------------------------------------------------------------------------
-# Mode priority
-# ---------------------------------------------------------------------------
-
-
-class TestBuildSdkEnvModePriority:
-    """Subscription mode takes precedence over OpenRouter."""
-
-    @patch("backend.copilot.sdk.env.validate_subscription")
-    def test_subscription_overrides_openrouter(self, mock_validate):
-        cfg = _make_config(
-            use_claude_code_subscription=True,
-            use_openrouter=True,
-            api_key="sk-or-key",
-            base_url="https://openrouter.ai/api/v1",
-        )
-        with patch("backend.copilot.sdk.env.config", cfg):
-            from backend.copilot.sdk.env import build_sdk_env
-
-            result = build_sdk_env()
-
-        # Should get subscription result, not OpenRouter
-        assert result == {
-            "ANTHROPIC_API_KEY": "",
-            "ANTHROPIC_AUTH_TOKEN": "",
-            "ANTHROPIC_BASE_URL": "",
-        }

autogpt_platform/backend/backend/copilot/sdk/prompt_too_long_test.py

@@ -442,11 +442,8 @@ class TestCompactTranscript:
         assert result is not None
         assert validate_transcript(result)
         msgs = _transcript_to_messages(result)
-        # 3 messages: compressed prefix (2) + preserved last assistant (1)
-        assert len(msgs) == 3
+        assert len(msgs) == 2
         assert msgs[1]["content"] == "Summarized response"
-        # The last assistant entry is preserved verbatim from original
-        assert msgs[2]["content"] == "Details"
 
     @pytest.mark.asyncio
     async def test_returns_none_on_compression_failure(self, mock_chat_config):

autogpt_platform/backend/backend/copilot/sdk/response_adapter.py

@@ -15,7 +15,6 @@ from claude_agent_sdk import (
     ResultMessage,
     SystemMessage,
     TextBlock,
-    ThinkingBlock,
     ToolResultBlock,
     ToolUseBlock,
     UserMessage,
@@ -101,11 +100,6 @@ class SDKResponseAdapter:
                             StreamTextDelta(id=self.text_block_id, delta=block.text)
                         )
 
-                elif isinstance(block, ThinkingBlock):
-                    # Thinking blocks are preserved in the transcript but
-                    # not streamed to the frontend — skip silently.
-                    pass
-
                 elif isinstance(block, ToolUseBlock):
                     self._end_text_if_open(responses)
 

autogpt_platform/backend/backend/copilot/sdk/retry_scenarios_test.py

@@ -124,11 +124,8 @@ class TestScenarioCompactAndRetry:
         assert result != original  # Must be different
         assert validate_transcript(result)
         msgs = _transcript_to_messages(result)
-        # 3 messages: compressed prefix (2) + preserved last assistant (1)
-        assert len(msgs) == 3
+        assert len(msgs) == 2
         assert msgs[0]["content"] == "[summary of conversation]"
-        # Last assistant preserved verbatim
-        assert msgs[2]["content"] == "Long answer 2"
 
     def test_compacted_transcript_loads_into_builder(self):
         """TranscriptBuilder can load a compacted transcript and continue."""
@@ -740,10 +737,7 @@ class TestRetryEdgeCases:
         assert result is not None
         assert result != transcript
         msgs = _transcript_to_messages(result)
-        # 3 messages: compressed prefix (2) + preserved last assistant (1)
-        assert len(msgs) == 3
-        # Last assistant preserved verbatim
-        assert msgs[2]["content"] == "Answer 19"
+        assert len(msgs) == 2
 
     def test_messages_to_transcript_roundtrip_preserves_content(self):
         """Verify messages → transcript → messages preserves all content."""
@@ -1010,7 +1004,7 @@ def _make_sdk_patches(
         (f"{_SVC}.create_security_hooks", dict(return_value=MagicMock())),
         (f"{_SVC}.get_copilot_tool_names", dict(return_value=[])),
         (f"{_SVC}.get_sdk_disallowed_tools", dict(return_value=[])),
-        (f"{_SVC}.build_sdk_env", dict(return_value=None)),
+        (f"{_SVC}._build_sdk_env", dict(return_value=None)),
         (f"{_SVC}._resolve_sdk_model", dict(return_value=None)),
         (f"{_SVC}.set_execution_context", {}),
         (

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

@@ -77,9 +77,9 @@ from ..tools.e2b_sandbox import get_or_create_sandbox, pause_sandbox_direct
 from ..tools.sandbox import WORKSPACE_PREFIX, make_session_path
 from ..tracking import track_user_message
 from .compaction import CompactionTracker, filter_compaction_messages
-from .env import build_sdk_env  # noqa: F401 — re-export for backward compat
 from .response_adapter import SDKResponseAdapter
 from .security_hooks import create_security_hooks
+from .subscription import validate_subscription as _validate_claude_code_subscription
 from .tool_adapter import (
     cancel_pending_tool_tasks,
     create_copilot_mcp_server,
@@ -185,24 +185,6 @@ def _is_prompt_too_long(err: BaseException) -> bool:
     return False
 
 
-def _is_sdk_disconnect_error(exc: BaseException) -> bool:
-    """Return True if *exc* is an expected SDK cleanup error from client disconnect.
-
-    Two known patterns occur when ``GeneratorExit`` tears down the async
-    generator and the SDK's ``__aexit__`` runs in a different context/task:
-
-    * ``RuntimeError``: cancel scope exited in wrong task (anyio)
-    * ``ValueError``: ContextVar token created in a different Context (OTEL)
-
-    These are suppressed to avoid polluting Sentry with non-actionable noise.
-    """
-    if isinstance(exc, RuntimeError) and "cancel scope" in str(exc):
-        return True
-    if isinstance(exc, ValueError) and "was created in a different Context" in str(exc):
-        return True
-    return False
-
-
 def _is_tool_only_message(sdk_msg: object) -> bool:
     """Return True if *sdk_msg* is an AssistantMessage containing only ToolUseBlocks.
 
@@ -427,63 +409,6 @@ _HEARTBEAT_INTERVAL = 10.0  # seconds
 STREAM_LOCK_PREFIX = "copilot:stream:lock:"
 
 
-async def _safe_close_sdk_client(
-    sdk_client: ClaudeSDKClient,
-    log_prefix: str,
-) -> None:
-    """Close a ClaudeSDKClient, suppressing errors from client disconnect.
-
-    When the SSE client disconnects mid-stream, ``GeneratorExit`` propagates
-    through the async generator stack and causes ``ClaudeSDKClient.__aexit__``
-    to run in a different async context or task than where the client was
-    opened.  This triggers two known error classes:
-
-    * ``ValueError``: ``<Token var=<ContextVar name='current_context'>>
-      was created in a different Context`` — OpenTelemetry's
-      ``context.detach()`` fails because the OTEL context token was
-      created in the original generator coroutine but detach runs in
-      the GC / cleanup coroutine (Sentry: AUTOGPT-SERVER-8BT).
-
-    * ``RuntimeError``: ``Attempted to exit cancel scope in a different
-      task than it was entered in`` — anyio's ``TaskGroup.__aexit__``
-      detects that the cancel scope was entered in one task but is
-      being exited in another (Sentry: AUTOGPT-SERVER-8BW).
-
-    Both are harmless — the TCP connection is already dead and no
-    resources leak.  Logging them at ``debug`` level keeps observability
-    without polluting Sentry.
-    """
-    try:
-        await sdk_client.__aexit__(None, None, None)
-    except (ValueError, RuntimeError) as exc:
-        if _is_sdk_disconnect_error(exc):
-            # Expected during client disconnect — suppress to avoid Sentry noise.
-            logger.debug(
-                "%s SDK client cleanup error suppressed (client disconnect): %s: %s",
-                log_prefix,
-                type(exc).__name__,
-                exc,
-            )
-        else:
-            raise
-    except GeneratorExit:
-        # GeneratorExit can propagate through __aexit__ — suppress it here
-        # since the generator is already being torn down.
-        logger.debug(
-            "%s SDK client cleanup GeneratorExit suppressed (client disconnect)",
-            log_prefix,
-        )
-    except Exception:
-        # Unexpected cleanup error — log at error level so Sentry captures it
-        # (via its logging integration), but don't propagate since we're in
-        # teardown and the caller cannot meaningfully handle this.
-        logger.error(
-            "%s Unexpected SDK client cleanup error",
-            log_prefix,
-            exc_info=True,
-        )
-
-
 async def _iter_sdk_messages(
     client: ClaudeSDKClient,
 ) -> AsyncGenerator[Any, None]:
@@ -567,6 +492,60 @@ def _resolve_sdk_model() -> str | None:
     return model
 
 
+def _build_sdk_env(
+    session_id: str | None = None,
+    user_id: str | None = None,
+) -> dict[str, str]:
+    """Build env vars for the SDK CLI subprocess.
+
+    Three modes (checked in order):
+    1. **Subscription** — clears all keys; CLI uses `claude login` auth.
+    2. **Direct Anthropic** — returns `{}`; subprocess inherits
+       `ANTHROPIC_API_KEY` from the parent environment.
+    3. **OpenRouter** (default) — overrides base URL and auth token to
+       route through the proxy, with Langfuse trace headers.
+    """
+    # --- Mode 1: Claude Code subscription auth ---
+    if config.use_claude_code_subscription:
+        _validate_claude_code_subscription()
+        return {
+            "ANTHROPIC_API_KEY": "",
+            "ANTHROPIC_AUTH_TOKEN": "",
+            "ANTHROPIC_BASE_URL": "",
+        }
+
+    # --- Mode 2: Direct Anthropic (no proxy hop) ---
+    # `openrouter_active` checks the flag *and* credential presence.
+    if not config.openrouter_active:
+        return {}
+
+    # --- Mode 3: OpenRouter proxy ---
+    # Strip /v1 suffix — SDK expects the base URL without a version path.
+    base = (config.base_url or "").rstrip("/")
+    if base.endswith("/v1"):
+        base = base[:-3]
+    env: dict[str, str] = {
+        "ANTHROPIC_BASE_URL": base,
+        "ANTHROPIC_AUTH_TOKEN": config.api_key or "",
+        "ANTHROPIC_API_KEY": "",  # force CLI to use AUTH_TOKEN
+    }
+
+    # Inject broadcast headers so OpenRouter forwards traces to Langfuse.
+    def _safe(v: str) -> str:
+        """Sanitise a header value: strip newlines/whitespace and cap length."""
+        return v.replace("\r", "").replace("\n", "").strip()[:128]
+
+    parts = []
+    if session_id:
+        parts.append(f"x-session-id: {_safe(session_id)}")
+    if user_id:
+        parts.append(f"x-user-id: {_safe(user_id)}")
+    if parts:
+        env["ANTHROPIC_CUSTOM_HEADERS"] = "\n".join(parts)
+
+    return env
+
+
 def _make_sdk_cwd(session_id: str) -> str:
     """Create a safe, session-specific working directory path.
 
@@ -616,9 +595,7 @@ def _format_sdk_content_blocks(blocks: list) -> list[dict[str, Any]]:
     """Convert SDK content blocks to transcript format.
 
     Handles TextBlock, ToolUseBlock, ToolResultBlock, and ThinkingBlock.
-    Raw dicts (e.g. ``redacted_thinking`` blocks that the SDK may not have
-    a typed class for) are passed through verbatim to preserve them in the
-    transcript.  Unknown typed block objects are logged and skipped.
+    Unknown block types are logged and skipped.
     """
     result: list[dict[str, Any]] = []
     for block in blocks or []:
@@ -650,9 +627,6 @@ def _format_sdk_content_blocks(blocks: list) -> list[dict[str, Any]]:
                     "signature": block.signature,
                 }
             )
-        elif isinstance(block, dict) and "type" in block:
-            # Preserve raw dict blocks (e.g. redacted_thinking) verbatim.
-            result.append(block)
         else:
             logger.warning(
                 f"[SDK] Unknown content block type: {type(block).__name__}. "
@@ -1214,17 +1188,7 @@ async def _run_stream_attempt(
 
     consecutive_empty_tool_calls = 0
 
-    # Use manual __aenter__/__aexit__ instead of ``async with`` so we can
-    # suppress SDK cleanup errors that occur when the SSE client disconnects
-    # mid-stream.  GeneratorExit causes the SDK's ``__aexit__`` to run in a
-    # different async context/task than where the client was opened, which
-    # triggers:
-    #   - ValueError: ContextVar token mismatch (AUTOGPT-SERVER-8BT)
-    #   - RuntimeError: cancel scope in wrong task  (AUTOGPT-SERVER-8BW)
-    # Both are harmless — the TCP connection is already dead.
-    sdk_client = ClaudeSDKClient(options=state.options)
-    client = await sdk_client.__aenter__()
-    try:
+    async with ClaudeSDKClient(options=state.options) as client:
         logger.info(
             "%s Sending query — resume=%s, total_msgs=%d, "
             "query_len=%d, attached_files=%d, image_blocks=%d",
@@ -1484,8 +1448,6 @@ async def _run_stream_attempt(
 
             if acc.stream_completed:
                 break
-    finally:
-        await _safe_close_sdk_client(sdk_client, ctx.log_prefix)
 
     # --- Post-stream processing (only on success) ---
     if state.adapter.has_unresolved_tool_calls:
@@ -1813,7 +1775,7 @@ async def stream_chat_completion_sdk(
         )
 
         # Fail fast when no API credentials are available at all.
-        sdk_env = build_sdk_env(session_id=session_id, user_id=user_id)
+        sdk_env = _build_sdk_env(session_id=session_id, user_id=user_id)
         if not config.api_key and not config.use_claude_code_subscription:
             raise RuntimeError(
                 "No API key configured. Set OPEN_ROUTER_API_KEY, "
@@ -2207,16 +2169,9 @@ async def stream_chat_completion_sdk(
             error_msg = "Operation cancelled"
         else:
             error_msg = str(e) or type(e).__name__
-            # SDK cleanup errors are expected during client disconnect —
-            # log as warning rather than error to reduce Sentry noise.
-            # These are normally caught by _safe_close_sdk_client but
-            # can escape in edge cases (e.g. GeneratorExit timing).
-            if _is_sdk_disconnect_error(e):
-                logger.warning(
-                    "%s SDK cleanup error (client disconnect): %s",
-                    log_prefix,
-                    error_msg,
-                )
+            # SDK cleanup RuntimeError is expected during cancellation, log as warning
+            if isinstance(e, RuntimeError) and "cancel scope" in str(e):
+                logger.warning("%s SDK cleanup error: %s", log_prefix, error_msg)
             else:
                 logger.error("%s Error: %s", log_prefix, error_msg, exc_info=True)
 
@@ -2238,11 +2193,10 @@ async def stream_chat_completion_sdk(
             )
 
         # Yield StreamError for immediate feedback (only for non-cancellation errors)
-        # Skip for CancelledError and SDK disconnect cleanup errors — these
-        # are not actionable by the user and the SSE connection is already dead.
-        is_cancellation = isinstance(
-            e, asyncio.CancelledError
-        ) or _is_sdk_disconnect_error(e)
+        # Skip for CancelledError and RuntimeError cleanup issues (both are cancellations)
+        is_cancellation = isinstance(e, asyncio.CancelledError) or (
+            isinstance(e, RuntimeError) and "cancel scope" in str(e)
+        )
         if not is_cancellation:
             yield StreamError(errorText=display_msg, code=code)
 

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

@@ -8,12 +8,7 @@ from unittest.mock import AsyncMock, MagicMock, patch
 
 import pytest
 
-from .service import (
-    _is_sdk_disconnect_error,
-    _prepare_file_attachments,
-    _resolve_sdk_model,
-    _safe_close_sdk_client,
-)
+from .service import _prepare_file_attachments, _resolve_sdk_model
 
 
 @dataclass
@@ -504,111 +499,3 @@ class TestResolveSdkModel:
         )
         monkeypatch.setattr("backend.copilot.sdk.service.config", cfg)
         assert _resolve_sdk_model() == "claude-opus-4-6"
-
-
-# ---------------------------------------------------------------------------
-# _is_sdk_disconnect_error — classify client disconnect cleanup errors
-# ---------------------------------------------------------------------------
-
-
-class TestIsSdkDisconnectError:
-    """Tests for _is_sdk_disconnect_error — identifies expected SDK cleanup errors."""
-
-    def test_cancel_scope_runtime_error(self):
-        """RuntimeError about cancel scope in wrong task is a disconnect error."""
-        exc = RuntimeError(
-            "Attempted to exit cancel scope in a different task than it was entered in"
-        )
-        assert _is_sdk_disconnect_error(exc) is True
-
-    def test_context_var_value_error(self):
-        """ValueError about ContextVar token mismatch is a disconnect error."""
-        exc = ValueError(
-            "<Token var=<ContextVar name='current_context'>> "
-            "was created in a different Context"
-        )
-        assert _is_sdk_disconnect_error(exc) is True
-
-    def test_unrelated_runtime_error(self):
-        """Unrelated RuntimeError should NOT be classified as disconnect error."""
-        exc = RuntimeError("something else went wrong")
-        assert _is_sdk_disconnect_error(exc) is False
-
-    def test_unrelated_value_error(self):
-        """Unrelated ValueError should NOT be classified as disconnect error."""
-        exc = ValueError("invalid argument")
-        assert _is_sdk_disconnect_error(exc) is False
-
-    def test_other_exception_types(self):
-        """Non-RuntimeError/ValueError should NOT be classified as disconnect error."""
-        assert _is_sdk_disconnect_error(TypeError("bad type")) is False
-        assert _is_sdk_disconnect_error(OSError("network down")) is False
-        assert _is_sdk_disconnect_error(asyncio.CancelledError()) is False
-
-
-# ---------------------------------------------------------------------------
-# _safe_close_sdk_client — suppress cleanup errors during disconnect
-# ---------------------------------------------------------------------------
-
-
-class TestSafeCloseSdkClient:
-    """Tests for _safe_close_sdk_client — suppresses expected SDK cleanup errors."""
-
-    @pytest.mark.asyncio
-    async def test_clean_exit(self):
-        """Normal __aexit__ (no error) should succeed silently."""
-        client = AsyncMock()
-        client.__aexit__ = AsyncMock(return_value=None)
-        await _safe_close_sdk_client(client, "[test]")
-        client.__aexit__.assert_awaited_once_with(None, None, None)
-
-    @pytest.mark.asyncio
-    async def test_cancel_scope_runtime_error_suppressed(self):
-        """RuntimeError from cancel scope mismatch should be suppressed."""
-        client = AsyncMock()
-        client.__aexit__ = AsyncMock(
-            side_effect=RuntimeError(
-                "Attempted to exit cancel scope in a different task"
-            )
-        )
-        # Should NOT raise
-        await _safe_close_sdk_client(client, "[test]")
-
-    @pytest.mark.asyncio
-    async def test_context_var_value_error_suppressed(self):
-        """ValueError from ContextVar token mismatch should be suppressed."""
-        client = AsyncMock()
-        client.__aexit__ = AsyncMock(
-            side_effect=ValueError(
-                "<Token var=<ContextVar name='current_context'>> "
-                "was created in a different Context"
-            )
-        )
-        # Should NOT raise
-        await _safe_close_sdk_client(client, "[test]")
-
-    @pytest.mark.asyncio
-    async def test_unexpected_exception_suppressed_with_error_log(self):
-        """Unexpected exceptions should be caught (not propagated) but logged at error."""
-        client = AsyncMock()
-        client.__aexit__ = AsyncMock(side_effect=OSError("unexpected"))
-        # Should NOT raise — unexpected errors are also suppressed to
-        # avoid crashing the generator during teardown.  Logged at error
-        # level so Sentry captures them via its logging integration.
-        await _safe_close_sdk_client(client, "[test]")
-
-    @pytest.mark.asyncio
-    async def test_unrelated_runtime_error_propagates(self):
-        """Non-cancel-scope RuntimeError should propagate (not suppressed)."""
-        client = AsyncMock()
-        client.__aexit__ = AsyncMock(side_effect=RuntimeError("something unrelated"))
-        with pytest.raises(RuntimeError, match="something unrelated"):
-            await _safe_close_sdk_client(client, "[test]")
-
-    @pytest.mark.asyncio
-    async def test_unrelated_value_error_propagates(self):
-        """Non-disconnect ValueError should propagate (not suppressed)."""
-        client = AsyncMock()
-        client.__aexit__ = AsyncMock(side_effect=ValueError("invalid argument"))
-        with pytest.raises(ValueError, match="invalid argument"):
-            await _safe_close_sdk_client(client, "[test]")

autogpt_platform/backend/backend/copilot/sdk/thinking_blocks_test.py

@@ -1,822 +0,0 @@
-"""Tests for thinking/redacted_thinking block preservation.
-
-Validates the fix for the Anthropic API error:
-    "thinking or redacted_thinking blocks in the latest assistant message
-    cannot be modified. These blocks must remain as they were in the
-    original response."
-
-The API requires that thinking blocks in the LAST assistant message are
-preserved value-identical. Older assistant messages may have thinking blocks
-stripped entirely. This test suite covers:
-
-  1. _flatten_assistant_content — strips thinking from older messages
-  2. compact_transcript — preserves last assistant's thinking blocks
-  3. response_adapter — handles ThinkingBlock without error
-  4. _format_sdk_content_blocks — preserves redacted_thinking blocks
-"""
-
-from __future__ import annotations
-
-from unittest.mock import AsyncMock, patch
-
-import pytest
-from claude_agent_sdk import AssistantMessage, TextBlock, ThinkingBlock
-
-from backend.copilot.response_model import (
-    StreamStartStep,
-    StreamTextDelta,
-    StreamTextStart,
-)
-from backend.util import json
-
-from .conftest import build_structured_transcript
-from .response_adapter import SDKResponseAdapter
-from .service import _format_sdk_content_blocks
-from .transcript import (
-    _find_last_assistant_entry,
-    _flatten_assistant_content,
-    _messages_to_transcript,
-    _rechain_tail,
-    _transcript_to_messages,
-    compact_transcript,
-    validate_transcript,
-)
-
-# ---------------------------------------------------------------------------
-# Fixtures: realistic thinking block content
-# ---------------------------------------------------------------------------
-
-THINKING_BLOCK = {
-    "type": "thinking",
-    "thinking": "Let me analyze the user's request carefully...",
-    "signature": "ErUBCkYIAxgCIkD0V2MsRXPkuGolGexaW9V1kluijxXGF",
-}
-
-REDACTED_THINKING_BLOCK = {
-    "type": "redacted_thinking",
-    "data": "EmwKAhgBEgy2VEE8PJaS2oLJCPkaT...",
-}
-
-
-def _make_thinking_transcript() -> str:
-    """Build a transcript with thinking blocks in multiple assistant turns.
-
-    Layout:
-      User 1 → Assistant 1 (thinking + text + tool_use)
-      User 2 (tool_result) → Assistant 2 (thinking + text)
-      User 3 → Assistant 3 (thinking + redacted_thinking + text) ← LAST
-    """
-    return build_structured_transcript(
-        [
-            ("user", "What files are in this project?"),
-            (
-                "assistant",
-                [
-                    {
-                        "type": "thinking",
-                        "thinking": "I should list the files.",
-                        "signature": "sig_old_1",
-                    },
-                    {"type": "text", "text": "Let me check the files."},
-                    {
-                        "type": "tool_use",
-                        "id": "tu1",
-                        "name": "list_files",
-                        "input": {"path": "/"},
-                    },
-                ],
-            ),
-            ("user", "Here are the files: a.py, b.py"),
-            (
-                "assistant",
-                [
-                    {
-                        "type": "thinking",
-                        "thinking": "Good, I see two Python files.",
-                        "signature": "sig_old_2",
-                    },
-                    {"type": "text", "text": "I found a.py and b.py."},
-                ],
-            ),
-            ("user", "Tell me about a.py"),
-            (
-                "assistant",
-                [
-                    THINKING_BLOCK,
-                    REDACTED_THINKING_BLOCK,
-                    {"type": "text", "text": "a.py contains the main entry point."},
-                ],
-            ),
-        ]
-    )
-
-
-def _last_assistant_content(transcript_jsonl: str) -> list[dict] | None:
-    """Extract the content blocks of the last assistant entry in a transcript."""
-    last_content = None
-    for line in transcript_jsonl.strip().split("\n"):
-        entry = json.loads(line)
-        msg = entry.get("message", {})
-        if msg.get("role") == "assistant":
-            last_content = msg.get("content")
-    return last_content
-
-
-# ---------------------------------------------------------------------------
-# _find_last_assistant_entry — unit tests
-# ---------------------------------------------------------------------------
-
-
-class TestFindLastAssistantEntry:
-    def test_splits_at_last_assistant(self):
-        """Prefix contains everything before last assistant; tail starts at it."""
-        transcript = build_structured_transcript(
-            [
-                ("user", "Hello"),
-                ("assistant", [{"type": "text", "text": "Hi"}]),
-                ("user", "More"),
-                ("assistant", [{"type": "text", "text": "Details"}]),
-            ]
-        )
-        prefix, tail = _find_last_assistant_entry(transcript)
-        # 3 entries in prefix (user, assistant, user), 1 in tail (last assistant)
-        assert len(prefix) == 3
-        assert len(tail) == 1
-
-    def test_no_assistant_returns_all_in_prefix(self):
-        """When there's no assistant, all lines are in prefix, tail is empty."""
-        transcript = build_structured_transcript(
-            [("user", "Hello"), ("user", "Another question")]
-        )
-        prefix, tail = _find_last_assistant_entry(transcript)
-        assert len(prefix) == 2
-        assert tail == []
-
-    def test_assistant_at_index_zero(self):
-        """When assistant is the first entry, prefix is empty."""
-        transcript = build_structured_transcript(
-            [("assistant", [{"type": "text", "text": "Start"}])]
-        )
-        prefix, tail = _find_last_assistant_entry(transcript)
-        assert prefix == []
-        assert len(tail) == 1
-
-    def test_trailing_user_included_in_tail(self):
-        """User message after last assistant is part of the tail."""
-        transcript = build_structured_transcript(
-            [
-                ("user", "Q1"),
-                ("assistant", [{"type": "text", "text": "A1"}]),
-                ("user", "Q2"),
-            ]
-        )
-        prefix, tail = _find_last_assistant_entry(transcript)
-        assert len(prefix) == 1  # first user
-        assert len(tail) == 2  # last assistant + trailing user
-
-    def test_multi_entry_turn_fully_preserved(self):
-        """An assistant turn spanning multiple JSONL entries (same message.id)
-        must be entirely in the tail, not split across prefix and tail."""
-        # Build manually because build_structured_transcript generates unique ids
-        lines = [
-            json.dumps(
-                {
-                    "type": "user",
-                    "uuid": "u1",
-                    "parentUuid": "",
-                    "message": {"role": "user", "content": "Hello"},
-                }
-            ),
-            json.dumps(
-                {
-                    "type": "assistant",
-                    "uuid": "a1-think",
-                    "parentUuid": "u1",
-                    "message": {
-                        "role": "assistant",
-                        "id": "msg_same_turn",
-                        "type": "message",
-                        "content": [THINKING_BLOCK],
-                        "stop_reason": None,
-                        "stop_sequence": None,
-                    },
-                }
-            ),
-            json.dumps(
-                {
-                    "type": "assistant",
-                    "uuid": "a1-tool",
-                    "parentUuid": "u1",
-                    "message": {
-                        "role": "assistant",
-                        "id": "msg_same_turn",
-                        "type": "message",
-                        "content": [
-                            {
-                                "type": "tool_use",
-                                "id": "tu1",
-                                "name": "Bash",
-                                "input": {},
-                            },
-                        ],
-                        "stop_reason": "tool_use",
-                        "stop_sequence": None,
-                    },
-                }
-            ),
-        ]
-        transcript = "\n".join(lines) + "\n"
-        prefix, tail = _find_last_assistant_entry(transcript)
-        # Both assistant entries share msg_same_turn → both in tail
-        assert len(prefix) == 1  # only the user entry
-        assert len(tail) == 2  # both assistant entries (thinking + tool_use)
-
-    def test_no_message_id_preserves_last_assistant(self):
-        """When the last assistant entry has no message.id, it should still
-        be preserved in the tail (fail closed) rather than being compressed."""
-        lines = [
-            json.dumps(
-                {
-                    "type": "user",
-                    "uuid": "u1",
-                    "parentUuid": "",
-                    "message": {"role": "user", "content": "Hello"},
-                }
-            ),
-            json.dumps(
-                {
-                    "type": "assistant",
-                    "uuid": "a1",
-                    "parentUuid": "u1",
-                    "message": {
-                        "role": "assistant",
-                        "content": [THINKING_BLOCK, {"type": "text", "text": "Hi"}],
-                    },
-                }
-            ),
-        ]
-        transcript = "\n".join(lines) + "\n"
-        prefix, tail = _find_last_assistant_entry(transcript)
-        assert len(prefix) == 1  # user entry
-        assert len(tail) == 1  # assistant entry preserved
-
-
-# ---------------------------------------------------------------------------
-# _rechain_tail — UUID chain patching
-# ---------------------------------------------------------------------------
-
-
-class TestRechainTail:
-    def test_patches_first_entry_parentuuid(self):
-        """First tail entry's parentUuid should point to last prefix uuid."""
-        prefix = _messages_to_transcript(
-            [
-                {"role": "user", "content": "Hello"},
-                {"role": "assistant", "content": "Hi"},
-            ]
-        )
-        # Get the last uuid from the prefix
-        last_prefix_uuid = None
-        for line in prefix.strip().split("\n"):
-            entry = json.loads(line)
-            last_prefix_uuid = entry.get("uuid")
-
-        tail_lines = [
-            json.dumps(
-                {
-                    "type": "assistant",
-                    "uuid": "tail-a1",
-                    "parentUuid": "old-parent",
-                    "message": {
-                        "role": "assistant",
-                        "content": [{"type": "text", "text": "Tail msg"}],
-                    },
-                }
-            )
-        ]
-        result = _rechain_tail(prefix, tail_lines)
-        entry = json.loads(result.strip())
-        assert entry["parentUuid"] == last_prefix_uuid
-        assert entry["uuid"] == "tail-a1"  # uuid preserved
-
-    def test_chains_multiple_tail_entries(self):
-        """Subsequent tail entries chain to each other."""
-        prefix = _messages_to_transcript([{"role": "user", "content": "Hi"}])
-        tail_lines = [
-            json.dumps(
-                {
-                    "type": "assistant",
-                    "uuid": "t1",
-                    "parentUuid": "old1",
-                    "message": {"role": "assistant", "content": []},
-                }
-            ),
-            json.dumps(
-                {
-                    "type": "user",
-                    "uuid": "t2",
-                    "parentUuid": "old2",
-                    "message": {"role": "user", "content": "Follow-up"},
-                }
-            ),
-        ]
-        result = _rechain_tail(prefix, tail_lines)
-        entries = [json.loads(ln) for ln in result.strip().split("\n")]
-        assert len(entries) == 2
-        # Second entry's parentUuid should be first entry's uuid
-        assert entries[1]["parentUuid"] == "t1"
-
-    def test_empty_tail_returns_empty(self):
-        """No tail entries → empty string."""
-        prefix = _messages_to_transcript([{"role": "user", "content": "Hi"}])
-        assert _rechain_tail(prefix, []) == ""
-
-    def test_preserves_message_content_verbatim(self):
-        """Tail message content (including thinking blocks) must not be modified."""
-        prefix = _messages_to_transcript([{"role": "user", "content": "Hi"}])
-        original_content = [
-            THINKING_BLOCK,
-            REDACTED_THINKING_BLOCK,
-            {"type": "text", "text": "Response"},
-        ]
-        tail_lines = [
-            json.dumps(
-                {
-                    "type": "assistant",
-                    "uuid": "t1",
-                    "parentUuid": "old",
-                    "message": {
-                        "role": "assistant",
-                        "content": original_content,
-                    },
-                }
-            )
-        ]
-        result = _rechain_tail(prefix, tail_lines)
-        entry = json.loads(result.strip())
-        assert entry["message"]["content"] == original_content
-
-
-# ---------------------------------------------------------------------------
-# _flatten_assistant_content — thinking blocks
-# ---------------------------------------------------------------------------
-
-
-class TestFlattenThinkingBlocks:
-    def test_thinking_blocks_are_stripped(self):
-        """Thinking blocks should not appear in flattened text for compression."""
-        blocks = [
-            {"type": "thinking", "thinking": "secret thoughts", "signature": "sig"},
-            {"type": "text", "text": "Hello user"},
-        ]
-        result = _flatten_assistant_content(blocks)
-        assert "secret thoughts" not in result
-        assert "Hello user" in result
-
-    def test_redacted_thinking_blocks_are_stripped(self):
-        """Redacted thinking blocks should not appear in flattened text."""
-        blocks = [
-            {"type": "redacted_thinking", "data": "encrypted_data"},
-            {"type": "text", "text": "Response text"},
-        ]
-        result = _flatten_assistant_content(blocks)
-        assert "encrypted_data" not in result
-        assert "Response text" in result
-
-    def test_thinking_only_message_flattens_to_empty(self):
-        """A message with only thinking blocks flattens to empty string."""
-        blocks = [
-            {"type": "thinking", "thinking": "just thinking...", "signature": "sig"},
-        ]
-        result = _flatten_assistant_content(blocks)
-        assert result == ""
-
-    def test_mixed_thinking_text_tool(self):
-        """Mixed blocks: only text and tool_use survive flattening."""
-        blocks = [
-            {"type": "thinking", "thinking": "hmm", "signature": "sig"},
-            {"type": "redacted_thinking", "data": "xyz"},
-            {"type": "text", "text": "I'll read the file."},
-            {"type": "tool_use", "name": "Read", "input": {"path": "/x"}},
-        ]
-        result = _flatten_assistant_content(blocks)
-        assert "hmm" not in result
-        assert "xyz" not in result
-        assert "I'll read the file." in result
-        assert "[tool_use: Read]" in result
-
-
-# ---------------------------------------------------------------------------
-# compact_transcript — thinking block preservation
-# ---------------------------------------------------------------------------
-
-
-class TestCompactTranscriptThinkingBlocks:
-    """Verify that compact_transcript preserves thinking blocks in the
-    last assistant message while stripping them from older messages."""
-
-    @pytest.mark.asyncio
-    async def test_last_assistant_thinking_blocks_preserved(self, mock_chat_config):
-        """After compaction, the last assistant entry must retain its
-        original thinking and redacted_thinking blocks verbatim."""
-        transcript = _make_thinking_transcript()
-
-        compacted_msgs = [
-            {"role": "user", "content": "[conversation summary]"},
-            {"role": "assistant", "content": "Summarized response"},
-        ]
-        mock_result = type(
-            "CompressResult",
-            (),
-            {
-                "was_compacted": True,
-                "messages": compacted_msgs,
-                "original_token_count": 800,
-                "token_count": 200,
-                "messages_summarized": 4,
-                "messages_dropped": 0,
-            },
-        )()
-        with patch(
-            "backend.copilot.sdk.transcript._run_compression",
-            new_callable=AsyncMock,
-            return_value=mock_result,
-        ):
-            result = await compact_transcript(transcript, model="test-model")
-
-        assert result is not None
-        assert validate_transcript(result)
-
-        last_content = _last_assistant_content(result)
-        assert last_content is not None, "No assistant entry found"
-        assert isinstance(last_content, list)
-
-        # The last assistant must have the thinking blocks preserved
-        block_types = [b["type"] for b in last_content]
-        assert (
-            "thinking" in block_types
-        ), "thinking block missing from last assistant message"
-        assert (
-            "redacted_thinking" in block_types
-        ), "redacted_thinking block missing from last assistant message"
-        assert "text" in block_types
-
-        # Verify the thinking block content is value-identical
-        thinking_blocks = [b for b in last_content if b["type"] == "thinking"]
-        assert len(thinking_blocks) == 1
-        assert thinking_blocks[0]["thinking"] == THINKING_BLOCK["thinking"]
-        assert thinking_blocks[0]["signature"] == THINKING_BLOCK["signature"]
-
-        redacted_blocks = [b for b in last_content if b["type"] == "redacted_thinking"]
-        assert len(redacted_blocks) == 1
-        assert redacted_blocks[0]["data"] == REDACTED_THINKING_BLOCK["data"]
-
-    @pytest.mark.asyncio
-    async def test_older_assistant_thinking_blocks_stripped(self, mock_chat_config):
-        """Older assistant messages should NOT retain thinking blocks
-        after compaction (they're compressed into summaries)."""
-        transcript = _make_thinking_transcript()
-
-        # The compressor will receive messages where older assistant
-        # entries have already had thinking blocks stripped.
-        captured_messages: list[dict] = []
-
-        async def mock_compression(messages, model, log_prefix):
-            captured_messages.extend(messages)
-            return type(
-                "CompressResult",
-                (),
-                {
-                    "was_compacted": True,
-                    "messages": messages,
-                    "original_token_count": 800,
-                    "token_count": 400,
-                    "messages_summarized": 2,
-                    "messages_dropped": 0,
-                },
-            )()
-
-        with patch(
-            "backend.copilot.sdk.transcript._run_compression",
-            side_effect=mock_compression,
-        ):
-            await compact_transcript(transcript, model="test-model")
-
-        # Check that the messages sent to compression don't contain
-        # thinking content from older assistant messages
-        for msg in captured_messages:
-            if msg["role"] == "assistant":
-                content = msg.get("content", "")
-                assert (
-                    "I should list the files." not in content
-                ), "Old thinking block content leaked into compression input"
-                assert (
-                    "Good, I see two Python files." not in content
-                ), "Old thinking block content leaked into compression input"
-
-    @pytest.mark.asyncio
-    async def test_trailing_user_message_after_last_assistant(self, mock_chat_config):
-        """When the last entry is a user message, the last *assistant*
-        message's thinking blocks should still be preserved."""
-        transcript = build_structured_transcript(
-            [
-                ("user", "Hello"),
-                (
-                    "assistant",
-                    [
-                        THINKING_BLOCK,
-                        {"type": "text", "text": "Hi there"},
-                    ],
-                ),
-                ("user", "Follow-up question"),
-            ]
-        )
-
-        # The compressor only receives the prefix (1 user message); the
-        # tail (assistant + trailing user) is preserved verbatim.
-        compacted_msgs = [
-            {"role": "user", "content": "Hello"},
-        ]
-        mock_result = type(
-            "CompressResult",
-            (),
-            {
-                "was_compacted": True,
-                "messages": compacted_msgs,
-                "original_token_count": 400,
-                "token_count": 100,
-                "messages_summarized": 0,
-                "messages_dropped": 0,
-            },
-        )()
-        with patch(
-            "backend.copilot.sdk.transcript._run_compression",
-            new_callable=AsyncMock,
-            return_value=mock_result,
-        ):
-            result = await compact_transcript(transcript, model="test-model")
-
-        assert result is not None
-
-        last_content = _last_assistant_content(result)
-        assert last_content is not None
-        assert isinstance(last_content, list)
-        block_types = [b["type"] for b in last_content]
-        assert (
-            "thinking" in block_types
-        ), "thinking block lost from last assistant despite trailing user msg"
-
-    @pytest.mark.asyncio
-    async def test_single_assistant_with_thinking_preserved(self, mock_chat_config):
-        """When there's only one assistant message (which is also the last),
-        its thinking blocks must be preserved."""
-        transcript = build_structured_transcript(
-            [
-                ("user", "Hello"),
-                (
-                    "assistant",
-                    [
-                        THINKING_BLOCK,
-                        {"type": "text", "text": "World"},
-                    ],
-                ),
-            ]
-        )
-
-        compacted_msgs = [
-            {"role": "user", "content": "Hello"},
-            {"role": "assistant", "content": "World"},
-        ]
-        mock_result = type(
-            "CompressResult",
-            (),
-            {
-                "was_compacted": True,
-                "messages": compacted_msgs,
-                "original_token_count": 200,
-                "token_count": 100,
-                "messages_summarized": 0,
-                "messages_dropped": 0,
-            },
-        )()
-        with patch(
-            "backend.copilot.sdk.transcript._run_compression",
-            new_callable=AsyncMock,
-            return_value=mock_result,
-        ):
-            result = await compact_transcript(transcript, model="test-model")
-
-        assert result is not None
-
-        last_content = _last_assistant_content(result)
-        assert last_content is not None
-        assert isinstance(last_content, list)
-        block_types = [b["type"] for b in last_content]
-        assert "thinking" in block_types
-
-    @pytest.mark.asyncio
-    async def test_tail_parentuuid_rewired_to_prefix(self, mock_chat_config):
-        """After compaction, the first tail entry's parentUuid must point to
-        the last entry in the compressed prefix — not its original parent."""
-        transcript = _make_thinking_transcript()
-
-        compacted_msgs = [
-            {"role": "user", "content": "[conversation summary]"},
-            {"role": "assistant", "content": "Summarized response"},
-        ]
-        mock_result = type(
-            "CompressResult",
-            (),
-            {
-                "was_compacted": True,
-                "messages": compacted_msgs,
-                "original_token_count": 800,
-                "token_count": 200,
-                "messages_summarized": 4,
-                "messages_dropped": 0,
-            },
-        )()
-        with patch(
-            "backend.copilot.sdk.transcript._run_compression",
-            new_callable=AsyncMock,
-            return_value=mock_result,
-        ):
-            result = await compact_transcript(transcript, model="test-model")
-
-        assert result is not None
-        lines = [ln for ln in result.strip().split("\n") if ln.strip()]
-        entries = [json.loads(ln) for ln in lines]
-
-        # Find the boundary: the compressed prefix ends just before the
-        # first tail entry (last assistant in original transcript).
-        tail_start = None
-        for i, entry in enumerate(entries):
-            msg = entry.get("message", {})
-            if isinstance(msg.get("content"), list):
-                # Structured content = preserved tail entry
-                tail_start = i
-                break
-
-        assert tail_start is not None, "Could not find preserved tail entry"
-        assert tail_start > 0, "Tail should not be the first entry"
-
-        # The tail entry's parentUuid must be the uuid of the preceding entry
-        prefix_last_uuid = entries[tail_start - 1]["uuid"]
-        tail_first_parent = entries[tail_start]["parentUuid"]
-        assert tail_first_parent == prefix_last_uuid, (
-            f"Tail parentUuid {tail_first_parent!r} != "
-            f"last prefix uuid {prefix_last_uuid!r}"
-        )
-
-    @pytest.mark.asyncio
-    async def test_no_thinking_blocks_still_works(self, mock_chat_config):
-        """Compaction should still work normally when there are no thinking
-        blocks in the transcript."""
-        transcript = build_structured_transcript(
-            [
-                ("user", "Hello"),
-                ("assistant", [{"type": "text", "text": "Hi"}]),
-                ("user", "More"),
-                ("assistant", [{"type": "text", "text": "Details"}]),
-            ]
-        )
-
-        compacted_msgs = [
-            {"role": "user", "content": "[summary]"},
-            {"role": "assistant", "content": "Summary"},
-        ]
-        mock_result = type(
-            "CompressResult",
-            (),
-            {
-                "was_compacted": True,
-                "messages": compacted_msgs,
-                "original_token_count": 200,
-                "token_count": 50,
-                "messages_summarized": 2,
-                "messages_dropped": 0,
-            },
-        )()
-        with patch(
-            "backend.copilot.sdk.transcript._run_compression",
-            new_callable=AsyncMock,
-            return_value=mock_result,
-        ):
-            result = await compact_transcript(transcript, model="test-model")
-
-        assert result is not None
-        assert validate_transcript(result)
-        # Verify last assistant content is preserved even without thinking blocks
-        last_content = _last_assistant_content(result)
-        assert last_content is not None
-        assert last_content == [{"type": "text", "text": "Details"}]
-
-
-# ---------------------------------------------------------------------------
-# _transcript_to_messages — thinking block handling
-# ---------------------------------------------------------------------------
-
-
-class TestTranscriptToMessagesThinking:
-    def test_thinking_blocks_excluded_from_flattened_content(self):
-        """When _transcript_to_messages flattens content, thinking block
-        text should not leak into the message content string."""
-        transcript = build_structured_transcript(
-            [
-                ("user", "Hello"),
-                (
-                    "assistant",
-                    [
-                        {
-                            "type": "thinking",
-                            "thinking": "SECRET_THOUGHT",
-                            "signature": "sig",
-                        },
-                        {"type": "text", "text": "Visible response"},
-                    ],
-                ),
-            ]
-        )
-        messages = _transcript_to_messages(transcript)
-        assistant_msg = [m for m in messages if m["role"] == "assistant"][0]
-        assert "SECRET_THOUGHT" not in assistant_msg["content"]
-        assert "Visible response" in assistant_msg["content"]
-
-
-# ---------------------------------------------------------------------------
-# response_adapter — ThinkingBlock handling
-# ---------------------------------------------------------------------------
-
-
-class TestResponseAdapterThinkingBlock:
-    def test_thinking_block_does_not_crash(self):
-        """ThinkingBlock in AssistantMessage should not cause an error."""
-        adapter = SDKResponseAdapter(message_id="msg-1", session_id="sess-1")
-        msg = AssistantMessage(
-            content=[
-                ThinkingBlock(
-                    thinking="Let me think about this...",
-                    signature="sig_test_123",
-                ),
-                TextBlock(text="Here is my response."),
-            ],
-            model="claude-test",
-        )
-        results = adapter.convert_message(msg)
-        # Should produce stream events for text only, no crash
-        types = [type(r) for r in results]
-        assert StreamStartStep in types
-        assert StreamTextStart in types or StreamTextDelta in types
-
-    def test_thinking_block_does_not_emit_stream_events(self):
-        """ThinkingBlock should NOT produce any StreamTextDelta events
-        containing thinking content."""
-        adapter = SDKResponseAdapter(message_id="msg-1", session_id="sess-1")
-        msg = AssistantMessage(
-            content=[
-                ThinkingBlock(
-                    thinking="My secret thoughts",
-                    signature="sig_test_456",
-                ),
-                TextBlock(text="Public response"),
-            ],
-            model="claude-test",
-        )
-        results = adapter.convert_message(msg)
-        text_deltas = [r for r in results if isinstance(r, StreamTextDelta)]
-        for delta in text_deltas:
-            assert "secret thoughts" not in (delta.delta or "")
-
-
-# ---------------------------------------------------------------------------
-# _format_sdk_content_blocks — redacted_thinking handling
-# ---------------------------------------------------------------------------
-
-
-class TestFormatSdkContentBlocks:
-    def test_thinking_block_preserved(self):
-        """ThinkingBlock should be serialized with type, thinking, and signature."""
-        blocks = [
-            ThinkingBlock(thinking="My thoughts", signature="sig123"),
-            TextBlock(text="Response"),
-        ]
-        result = _format_sdk_content_blocks(blocks)
-        assert len(result) == 2
-        assert result[0] == {
-            "type": "thinking",
-            "thinking": "My thoughts",
-            "signature": "sig123",
-        }
-        assert result[1] == {"type": "text", "text": "Response"}
-
-    def test_raw_dict_redacted_thinking_preserved(self):
-        """Raw dict blocks (e.g. redacted_thinking) pass through unchanged."""
-        raw_block = {"type": "redacted_thinking", "data": "EmwKAh...encrypted"}
-        blocks = [
-            raw_block,
-            TextBlock(text="Response"),
-        ]
-        result = _format_sdk_content_blocks(blocks)
-        assert len(result) == 2
-        assert result[0] == raw_block
-        assert result[1] == {"type": "text", "text": "Response"}

autogpt_platform/backend/backend/copilot/sdk/transcript.py

@@ -605,31 +605,20 @@ COMPACT_MSG_ID_PREFIX = "msg_compact_"
 ENTRY_TYPE_MESSAGE = "message"
 
 
-_THINKING_BLOCK_TYPES = frozenset({"thinking", "redacted_thinking"})
-
-
 def _flatten_assistant_content(blocks: list) -> str:
     """Flatten assistant content blocks into a single plain-text string.
 
     Structured ``tool_use`` blocks are converted to ``[tool_use: name]``
-    placeholders.  ``thinking`` and ``redacted_thinking`` blocks are
-    silently dropped — they carry no useful context for compression
-    summaries and must not leak into compacted transcripts (the Anthropic
-    API requires thinking blocks in the last assistant message to be
-    value-identical to the original response; including stale thinking
-    text would violate that constraint).
-
-    This is intentional: ``compress_context`` requires plain text for
-    token counting and LLM summarization.  The structural loss is
-    acceptable because compaction only runs when the original transcript
-    was already too large for the model.
+    placeholders.  This is intentional: ``compress_context`` requires plain
+    text for token counting and LLM summarization.  The structural loss is
+    acceptable because compaction only runs when the original transcript was
+    already too large for the model — a summarized plain-text version is
+    better than no context at all.
     """
     parts: list[str] = []
     for block in blocks:
         if isinstance(block, dict):
             btype = block.get("type", "")
-            if btype in _THINKING_BLOCK_TYPES:
-                continue
             if btype == "text":
                 parts.append(block.get("text", ""))
             elif btype == "tool_use":
@@ -816,68 +805,6 @@ async def _run_compression(
         )
 
 
-def _find_last_assistant_entry(
-    content: str,
-) -> tuple[list[str], list[str]]:
-    """Split JSONL lines into (compressible_prefix, preserved_tail).
-
-    The tail starts at the **first** entry of the last assistant turn and
-    includes everything after it (typically trailing user messages).  An
-    assistant turn can span multiple consecutive JSONL entries sharing the
-    same ``message.id`` (e.g., a thinking entry followed by a tool_use
-    entry).  All entries of the turn are preserved verbatim.
-
-    The Anthropic API requires that ``thinking`` and ``redacted_thinking``
-    blocks in the **last** assistant message remain value-identical to the
-    original response (the API validates parsed signature values, not raw
-    JSON bytes).  By excluding the entire turn from compression we
-    guarantee those blocks are never altered.
-
-    Returns ``(all_lines, [])`` when no assistant entry is found.
-    """
-    lines = [ln for ln in content.strip().split("\n") if ln.strip()]
-
-    # Parse all lines once to avoid double JSON deserialization.
-    # json.loads with fallback=None returns Any; non-dict entries are
-    # safely skipped by the isinstance(entry, dict) guards below.
-    parsed: list = [json.loads(ln, fallback=None) for ln in lines]
-
-    # Reverse scan: find the message.id and index of the last assistant entry.
-    last_asst_msg_id: str | None = None
-    last_asst_idx: int | None = None
-    for i in range(len(parsed) - 1, -1, -1):
-        entry = parsed[i]
-        if not isinstance(entry, dict):
-            continue
-        msg = entry.get("message", {})
-        if msg.get("role") == "assistant":
-            last_asst_idx = i
-            last_asst_msg_id = msg.get("id")
-            break
-
-    if last_asst_idx is None:
-        return lines, []
-
-    # If the assistant entry has no message.id, fall back to preserving
-    # from that single entry onward — safer than compressing everything.
-    if last_asst_msg_id is None:
-        return lines[:last_asst_idx], lines[last_asst_idx:]
-
-    # Forward scan: find the first entry of this turn (same message.id).
-    first_turn_idx: int | None = None
-    for i, entry in enumerate(parsed):
-        if not isinstance(entry, dict):
-            continue
-        msg = entry.get("message", {})
-        if msg.get("role") == "assistant" and msg.get("id") == last_asst_msg_id:
-            first_turn_idx = i
-            break
-
-    if first_turn_idx is None:
-        return lines, []
-    return lines[:first_turn_idx], lines[first_turn_idx:]
-
-
 async def compact_transcript(
     content: str,
     *,
@@ -889,50 +816,42 @@ async def compact_transcript(
     Converts transcript entries to plain messages, runs ``compress_context``
     (the same compressor used for pre-query history), and rebuilds JSONL.
 
-    The **last assistant entry** (and any entries after it) are preserved
-    verbatim — never flattened or compressed.  The Anthropic API requires
-    ``thinking`` and ``redacted_thinking`` blocks in the latest assistant
-    message to be value-identical to the original response (the API
-    validates parsed signature values, not raw JSON bytes); compressing
-    them would destroy the cryptographic signatures and cause
-    ``invalid_request_error``.
+    Structured content (``tool_use`` blocks, ``tool_result`` nesting, images)
+    is flattened to plain text for compression.  This matches the fidelity of
+    the Plan C (DB compression) fallback path, where
+    ``_format_conversation_context`` similarly renders tool calls as
+    ``You called tool: name(args)`` and results as ``Tool result: ...``.
+    Neither path preserves structured API content blocks — the compacted
+    context serves as text history for the LLM, which creates proper
+    structured tool calls going forward.
 
-    Structured content in *older* assistant entries (``tool_use`` blocks,
-    ``thinking`` blocks, ``tool_result`` nesting, images) is flattened to
-    plain text for compression.  This matches the fidelity of the Plan C
-    (DB compression) fallback path.
+    Images are per-turn attachments loaded from workspace storage by file ID
+    (via ``_prepare_file_attachments``), not part of the conversation history.
+    They are re-attached each turn and are unaffected by compaction.
 
     Returns the compacted JSONL string, or ``None`` on failure.
 
     See also:
         ``_compress_messages`` in ``service.py`` — compresses ``ChatMessage``
-        lists for pre-query DB history.
+        lists for pre-query DB history.  Both share ``compress_context()``
+        but operate on different input formats (JSONL transcript entries
+        here vs. ChatMessage dicts there).
     """
-    prefix_lines, tail_lines = _find_last_assistant_entry(content)
-
-    # Build the JSONL string for the compressible prefix
-    prefix_content = "\n".join(prefix_lines) + "\n" if prefix_lines else ""
-    messages = _transcript_to_messages(prefix_content) if prefix_content else []
-
-    if len(messages) + len(tail_lines) < 2:
-        total = len(messages) + len(tail_lines)
-        logger.warning("%s Too few messages to compact (%d)", log_prefix, total)
-        return None
-    if not messages:
-        logger.warning("%s Nothing to compress (only tail entries remain)", log_prefix)
+    messages = _transcript_to_messages(content)
+    if len(messages) < 2:
+        logger.warning("%s Too few messages to compact (%d)", log_prefix, len(messages))
         return None
     try:
         result = await _run_compression(messages, model, log_prefix)
         if not result.was_compacted:
+            # Compressor says it's within budget, but the SDK rejected it.
+            # Return None so the caller falls through to DB fallback.
             logger.warning(
                 "%s Compressor reports within budget but SDK rejected — "
                 "signalling failure",
                 log_prefix,
             )
             return None
-        if not result.messages:
-            logger.warning("%s Compressor returned empty messages", log_prefix)
-            return None
         logger.info(
             "%s Compacted transcript: %d->%d tokens (%d summarized, %d dropped)",
             log_prefix,
@@ -941,29 +860,7 @@ async def compact_transcript(
             result.messages_summarized,
             result.messages_dropped,
         )
-        compressed_part = _messages_to_transcript(result.messages)
-
-        # Re-append the preserved tail (last assistant + trailing entries)
-        # with parentUuid patched to chain onto the compressed prefix.
-        tail_part = _rechain_tail(compressed_part, tail_lines)
-        compacted = compressed_part + tail_part
-
-        if len(compacted) >= len(content):
-            # Byte count can increase due to preserved tail entries
-            # (thinking blocks, JSON overhead) even when token count
-            # decreased.  Log a warning but still return — the API
-            # validates tokens not bytes, and the caller falls through
-            # to DB fallback if the transcript is still too large.
-            logger.warning(
-                "%s Compacted transcript (%d bytes) is not smaller than "
-                "original (%d bytes) — may still reduce token count",
-                log_prefix,
-                len(compacted),
-                len(content),
-            )
-        # Authoritative validation — the caller (_reduce_context) also
-        # validates, but this is the canonical check that guarantees we
-        # never return a malformed transcript from this function.
+        compacted = _messages_to_transcript(result.messages)
         if not validate_transcript(compacted):
             logger.warning("%s Compacted transcript failed validation", log_prefix)
             return None
@@ -973,43 +870,3 @@ async def compact_transcript(
             "%s Transcript compaction failed: %s", log_prefix, e, exc_info=True
         )
         return None
-
-
-def _rechain_tail(compressed_prefix: str, tail_lines: list[str]) -> str:
-    """Patch tail entries so their parentUuid chain links to the compressed prefix.
-
-    The first tail entry's ``parentUuid`` is set to the ``uuid`` of the
-    last entry in the compressed prefix.  Subsequent tail entries are
-    rechained to point to their predecessor in the tail — their original
-    ``parentUuid`` values may reference entries that were compressed away.
-    """
-    if not tail_lines:
-        return ""
-    # Find the last uuid in the compressed prefix
-    last_prefix_uuid = ""
-    for line in reversed(compressed_prefix.strip().split("\n")):
-        if not line.strip():
-            continue
-        entry = json.loads(line, fallback=None)
-        if isinstance(entry, dict) and "uuid" in entry:
-            last_prefix_uuid = entry["uuid"]
-            break
-
-    result_lines: list[str] = []
-    prev_uuid: str | None = None
-    for i, line in enumerate(tail_lines):
-        entry = json.loads(line, fallback=None)
-        if not isinstance(entry, dict):
-            # Safety guard: _find_last_assistant_entry already filters empty
-            # lines, and well-formed JSONL always parses to dicts.  Non-dict
-            # lines are passed through unchanged; prev_uuid is intentionally
-            # NOT updated so the next dict entry chains to the last known uuid.
-            result_lines.append(line)
-            continue
-        if i == 0:
-            entry["parentUuid"] = last_prefix_uuid
-        elif prev_uuid is not None:
-            entry["parentUuid"] = prev_uuid
-        prev_uuid = entry.get("uuid")
-        result_lines.append(json.dumps(entry, separators=(",", ":")))
-    return "\n".join(result_lines) + "\n"

autogpt_platform/backend/backend/copilot/stream_registry.py

@@ -26,7 +26,6 @@ import orjson
 from redis.exceptions import RedisError
 
 from backend.api.model import CopilotCompletionPayload
-from backend.data.db_accessors import chat_db
 from backend.data.notification_bus import (
     AsyncRedisNotificationEventBus,
     NotificationEvent,
@@ -112,14 +111,6 @@ def _parse_session_meta(meta: dict[Any, Any], session_id: str = "") -> ActiveSes
     ``session_id`` is used as a fallback for ``turn_id`` when the meta hash
     pre-dates the turn_id field (backward compat for in-flight sessions).
     """
-    created_at = datetime.now(timezone.utc)
-    created_at_raw = meta.get("created_at")
-    if created_at_raw:
-        try:
-            created_at = datetime.fromisoformat(str(created_at_raw))
-        except (ValueError, TypeError):
-            pass
-
     return ActiveSession(
         session_id=meta.get("session_id", "") or session_id,
         user_id=meta.get("user_id", "") or None,
@@ -128,7 +119,6 @@ def _parse_session_meta(meta: dict[Any, Any], session_id: str = "") -> ActiveSes
         turn_id=meta.get("turn_id", "") or session_id,
         blocking=meta.get("blocking") == "1",
         status=meta.get("status", "running"),  # type: ignore[arg-type]
-        created_at=created_at,
     )
 
 
@@ -812,33 +802,6 @@ async def mark_session_completed(
                 f"Failed to publish error event for session {session_id}: {e}"
             )
 
-    # Compute wall-clock duration from session created_at.
-    # Only persist when (a) the session completed successfully and
-    # (b) created_at was actually present in Redis meta (not a fallback).
-    duration_ms: int | None = None
-    if meta and not error_message:
-        created_at_raw = meta.get("created_at")
-        if created_at_raw:
-            try:
-                created_at = datetime.fromisoformat(str(created_at_raw))
-                if created_at.tzinfo is None:
-                    created_at = created_at.replace(tzinfo=timezone.utc)
-                elapsed = datetime.now(timezone.utc) - created_at
-                duration_ms = max(0, int(elapsed.total_seconds() * 1000))
-            except (ValueError, TypeError):
-                logger.warning(
-                    "Failed to compute session duration for %s (created_at=%r)",
-                    session_id,
-                    created_at_raw,
-                )
-
-    # Persist duration on the last assistant message
-    if duration_ms is not None:
-        try:
-            await chat_db().set_turn_duration(session_id, duration_ms)
-        except Exception as e:
-            logger.warning(f"Failed to save turn duration for {session_id}: {e}")
-
     # Publish StreamFinish AFTER status is set to "completed"/"failed".
     # This is the SINGLE place that publishes StreamFinish — services and
     # the processor must NOT publish it themselves.

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

@@ -102,6 +102,7 @@ async def setup_test_data(server):
             "value": "",
             "advanced": False,
             "description": "Test input field",
+            "placeholder_values": [],
         },
         metadata={"position": {"x": 0, "y": 0}},
     )
@@ -241,6 +242,7 @@ async def setup_llm_test_data(server):
             "value": "",
             "advanced": False,
             "description": "Prompt for the LLM",
+            "placeholder_values": [],
         },
         metadata={"position": {"x": 0, "y": 0}},
     )
@@ -394,6 +396,7 @@ async def setup_firecrawl_test_data(server):
             "value": "",
             "advanced": False,
             "description": "URL for Firecrawl to scrape",
+            "placeholder_values": [],
         },
         metadata={"position": {"x": 0, "y": 0}},
     )

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

@@ -4,8 +4,6 @@ import logging
 import re
 from typing import Any
 
-from backend.data.dynamic_fields import DICT_SPLIT
-
 from .helpers import (
     AGENT_EXECUTOR_BLOCK_ID,
     MCP_TOOL_BLOCK_ID,
@@ -1538,8 +1536,8 @@ class AgentFixer:
         for link in links:
             sink_name = link.get("sink_name", "")
 
-            if DICT_SPLIT in sink_name:
-                parent, child = sink_name.split(DICT_SPLIT, 1)
+            if "_#_" in sink_name:
+                parent, child = sink_name.split("_#_", 1)
 
                 # Check if child is a numeric index (invalid for _#_ notation)
                 if child.isdigit():

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

@@ -4,8 +4,6 @@ import re
 import uuid
 from typing import Any
 
-from backend.data.dynamic_fields import DICT_SPLIT
-
 from .blocks import get_blocks_as_dicts
 
 __all__ = [
@@ -53,8 +51,8 @@ def generate_uuid() -> str:
 
 def get_defined_property_type(schema: dict[str, Any], name: str) -> str | None:
     """Get property type from a schema, handling nested `_#_` notation."""
-    if DICT_SPLIT in name:
-        parent, child = name.split(DICT_SPLIT, 1)
+    if "_#_" in name:
+        parent, child = name.split("_#_", 1)
         parent_schema = schema.get(parent, {})
         if "properties" in parent_schema and isinstance(
             parent_schema["properties"], dict

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

@@ -5,8 +5,6 @@ import logging
 import re
 from typing import Any
 
-from backend.data.dynamic_fields import DICT_SPLIT
-
 from .helpers import (
     AGENT_EXECUTOR_BLOCK_ID,
     AGENT_INPUT_BLOCK_ID,
@@ -258,6 +256,95 @@ class AgentValidator:
 
         return valid
 
+    def validate_nested_sink_links(
+        self,
+        agent: AgentDict,
+        blocks: list[dict[str, Any]],
+        node_lookup: dict[str, dict[str, Any]] | None = None,
+    ) -> 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
+        }
+        if node_lookup is None:
+            node_lookup = self._build_node_lookup(agent)
+
+        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
@@ -384,8 +471,8 @@ class AgentValidator:
                 output_props = block_output_schemas.get(block_id, {})
 
             # Handle nested source names (with _#_ notation)
-            if DICT_SPLIT in source_name:
-                parent, child = source_name.split(DICT_SPLIT, 1)
+            if "_#_" in source_name:
+                parent, child = source_name.split("_#_", 1)
 
                 parent_schema = output_props.get(parent)
                 if not parent_schema:
@@ -466,195 +553,6 @@ class AgentValidator:
 
         return valid
 
-    def validate_sink_input_existence(
-        self,
-        agent: AgentDict,
-        blocks: list[dict[str, Any]],
-        node_lookup: dict[str, dict[str, Any]] | None = None,
-    ) -> bool:
-        """
-        Validate that all sink_names in links and input_default keys in nodes
-        exist in the corresponding block's input schema.
-
-        Checks that for each link the sink_name references a valid input
-        property in the sink block's inputSchema, and that every key in a
-        node's input_default is a recognised input property. Also handles
-        nested inputs with _#_ notation and dynamic schemas for
-        AgentExecutorBlock.
-
-        Args:
-            agent: The agent dictionary to validate
-            blocks: List of available blocks with their schemas
-            node_lookup: Optional pre-built node-id → node dict
-
-        Returns:
-            True if all sink input fields exist, 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
-        }
-        if node_lookup is None:
-            node_lookup = self._build_node_lookup(agent)
-
-        def get_input_props(node: dict[str, Any]) -> dict[str, Any]:
-            block_id = node.get("block_id", "")
-            if block_id == AGENT_EXECUTOR_BLOCK_ID:
-                input_default = node.get("input_default", {})
-                dynamic_input_schema = input_default.get("input_schema", {})
-                if not isinstance(dynamic_input_schema, dict):
-                    dynamic_input_schema = {}
-                dynamic_props = dynamic_input_schema.get("properties", {})
-                if not isinstance(dynamic_props, dict):
-                    dynamic_props = {}
-                static_props = block_input_schemas.get(block_id, {})
-                return {**static_props, **dynamic_props}
-            return block_input_schemas.get(block_id, {})
-
-        def check_nested_input(
-            input_props: dict[str, Any],
-            field_name: str,
-            context: str,
-            block_name: str,
-            block_id: str,
-        ) -> bool:
-            parent, child = field_name.split(DICT_SPLIT, 1)
-            parent_schema = input_props.get(parent)
-            if not parent_schema:
-                self.add_error(
-                    f"{context}: Parent property '{parent}' does not "
-                    f"exist in block '{block_name}' ({block_id}) input "
-                    f"schema."
-                )
-                return False
-
-            allows_additional = parent_schema.get("additionalProperties", False)
-            # Only anyOf is checked here because Pydantic's JSON schema
-            # emits optional/union fields via anyOf. allOf and oneOf are
-            # not currently used by any block's dict-typed inputs, so
-            # false positives from them are not a concern in practice.
-            if not allows_additional and "anyOf" in parent_schema:
-                for schema_option in parent_schema.get("anyOf", []):
-                    if not isinstance(schema_option, dict):
-                        continue
-                    if schema_option.get("additionalProperties"):
-                        allows_additional = True
-                        break
-                    items_schema = schema_option.get("items")
-                    if isinstance(items_schema, dict) and items_schema.get(
-                        "additionalProperties"
-                    ):
-                        allows_additional = True
-                        break
-
-            if not allows_additional:
-                if not (
-                    isinstance(parent_schema, dict)
-                    and "properties" in parent_schema
-                    and isinstance(parent_schema["properties"], dict)
-                    and child in parent_schema["properties"]
-                ):
-                    available = (
-                        list(parent_schema.get("properties", {}).keys())
-                        if isinstance(parent_schema, dict)
-                        else []
-                    )
-                    self.add_error(
-                        f"{context}: Child property '{child}' does not "
-                        f"exist in parent '{parent}' of block "
-                        f"'{block_name}' ({block_id}) input schema. "
-                        f"Available properties: {available}"
-                    )
-                    return False
-            return True
-
-        for link in agent.get("links", []):
-            sink_id = link.get("sink_id")
-            sink_name = link.get("sink_name", "")
-            link_id = link.get("id", "Unknown")
-
-            if not sink_name:
-                # Missing sink_name is caught by validate_data_type_compatibility
-                continue
-
-            sink_node = node_lookup.get(sink_id)
-            if not sink_node:
-                # Already caught by validate_link_node_references
-                continue
-
-            block_id = sink_node.get("block_id", "")
-            block_name = block_names.get(block_id, "Unknown Block")
-            input_props = get_input_props(sink_node)
-
-            context = (
-                f"Invalid sink input field '{sink_name}' in link "
-                f"'{link_id}' to node '{sink_id}'"
-            )
-
-            if DICT_SPLIT in sink_name:
-                if not check_nested_input(
-                    input_props, sink_name, context, block_name, block_id
-                ):
-                    valid = False
-            else:
-                if sink_name not in input_props:
-                    available_inputs = list(input_props.keys())
-                    self.add_error(
-                        f"{context} (block '{block_name}' - {block_id}): "
-                        f"Input property '{sink_name}' does not exist in "
-                        f"the block's input schema. "
-                        f"Available inputs: {available_inputs}"
-                    )
-                    valid = False
-
-        for node in agent.get("nodes", []):
-            node_id = node.get("id")
-            block_id = node.get("block_id", "")
-            block_name = block_names.get(block_id, "Unknown Block")
-            input_default = node.get("input_default", {})
-
-            if not isinstance(input_default, dict) or not input_default:
-                continue
-
-            if (
-                block_id not in block_input_schemas
-                and block_id != AGENT_EXECUTOR_BLOCK_ID
-            ):
-                continue
-
-            input_props = get_input_props(node)
-
-            for key in input_default:
-                if key == "credentials":
-                    continue
-
-                context = (
-                    f"Node '{node_id}' (block '{block_name}' - {block_id}) "
-                    f"has unknown input_default key '{key}'"
-                )
-
-                if DICT_SPLIT in key:
-                    if not check_nested_input(
-                        input_props, key, context, block_name, block_id
-                    ):
-                        valid = False
-                else:
-                    if key not in input_props:
-                        available_inputs = list(input_props.keys())
-                        self.add_error(
-                            f"{context} which does not exist in the "
-                            f"block's input schema. "
-                            f"Available inputs: {available_inputs}"
-                        )
-                        valid = False
-
-        return valid
-
     def validate_io_blocks(self, agent: AgentDict) -> bool:
         """
         Validate that the agent has at least one AgentInputBlock and one
@@ -1101,12 +999,12 @@ class AgentValidator:
                 self.validate_data_type_compatibility(agent, blocks, node_lookup),
             ),
             (
-                "Source output existence",
-                self.validate_source_output_existence(agent, blocks, node_lookup),
+                "Nested sink links",
+                self.validate_nested_sink_links(agent, blocks, node_lookup),
             ),
             (
-                "Sink input existence",
-                self.validate_sink_input_existence(agent, blocks, node_lookup),
+                "Source output existence",
+                self.validate_source_output_existence(agent, blocks, node_lookup),
             ),
             (
                 "Prompt double curly braces spaces",

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

@@ -331,6 +331,43 @@ class TestValidatePromptDoubleCurlyBracesSpaces:
         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
 # ============================================================================
@@ -558,28 +595,11 @@ class TestValidate:
         input_block = _make_block(
             block_id=AGENT_INPUT_BLOCK_ID,
             name="AgentInputBlock",
-            input_schema={
-                "properties": {
-                    "name": {"type": "string"},
-                    "title": {"type": "string"},
-                    "value": {},
-                    "description": {"type": "string"},
-                },
-                "required": ["name"],
-            },
             output_schema={"properties": {"result": {}}},
         )
         output_block = _make_block(
             block_id=AGENT_OUTPUT_BLOCK_ID,
             name="AgentOutputBlock",
-            input_schema={
-                "properties": {
-                    "name": {"type": "string"},
-                    "title": {"type": "string"},
-                    "value": {},
-                },
-                "required": ["name"],
-            },
         )
         input_node = _make_node(
             node_id="n-in",
@@ -630,201 +650,6 @@ class TestValidate:
         assert "AgentOutputBlock" in error_message
 
 
-class TestValidateSinkInputExistence:
-    """Tests for validate_sink_input_existence."""
-
-    def test_valid_sink_name_passes(self):
-        v = AgentValidator()
-        block = _make_block(
-            block_id="b1",
-            input_schema={"properties": {"url": {"type": "string"}}, "required": []},
-        )
-        node = _make_node(node_id="n1", block_id="b1")
-        link = _make_link(
-            source_id="src", source_name="out", sink_id="n1", sink_name="url"
-        )
-        agent = _make_agent(nodes=[node], links=[link])
-
-        assert v.validate_sink_input_existence(agent, [block]) is True
-
-    def test_invalid_sink_name_fails(self):
-        v = AgentValidator()
-        block = _make_block(
-            block_id="b1",
-            input_schema={"properties": {"url": {"type": "string"}}, "required": []},
-        )
-        node = _make_node(node_id="n1", block_id="b1")
-        link = _make_link(
-            source_id="src", source_name="out", sink_id="n1", sink_name="nonexistent"
-        )
-        agent = _make_agent(nodes=[node], links=[link])
-
-        assert v.validate_sink_input_existence(agent, [block]) is False
-        assert any("nonexistent" in e for e in v.errors)
-
-    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(
-            source_id="src",
-            source_name="out",
-            sink_id="n1",
-            sink_name="config_#_key",
-        )
-        agent = _make_agent(nodes=[node], links=[link])
-
-        assert v.validate_sink_input_existence(agent, [block]) is True
-
-    def test_invalid_nested_child_fails(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(
-            source_id="src",
-            source_name="out",
-            sink_id="n1",
-            sink_name="config_#_missing",
-        )
-        agent = _make_agent(nodes=[node], links=[link])
-
-        assert v.validate_sink_input_existence(agent, [block]) is False
-
-    def test_unknown_input_default_key_fails(self):
-        v = AgentValidator()
-        block = _make_block(
-            block_id="b1",
-            input_schema={"properties": {"url": {"type": "string"}}, "required": []},
-        )
-        node = _make_node(
-            node_id="n1", block_id="b1", input_default={"nonexistent_key": "value"}
-        )
-        agent = _make_agent(nodes=[node])
-
-        assert v.validate_sink_input_existence(agent, [block]) is False
-        assert any("nonexistent_key" in e for e in v.errors)
-
-    def test_credentials_key_skipped(self):
-        v = AgentValidator()
-        block = _make_block(
-            block_id="b1",
-            input_schema={"properties": {"url": {"type": "string"}}, "required": []},
-        )
-        node = _make_node(
-            node_id="n1",
-            block_id="b1",
-            input_default={
-                "url": "http://example.com",
-                "credentials": {"api_key": "x"},
-            },
-        )
-        agent = _make_agent(nodes=[node])
-
-        assert v.validate_sink_input_existence(agent, [block]) is True
-
-    def test_agent_executor_dynamic_schema_passes(self):
-        v = AgentValidator()
-        block = _make_block(
-            block_id=AGENT_EXECUTOR_BLOCK_ID,
-            input_schema={
-                "properties": {
-                    "graph_id": {"type": "string"},
-                    "input_schema": {"type": "object"},
-                },
-                "required": ["graph_id"],
-            },
-        )
-        node = _make_node(
-            node_id="n1",
-            block_id=AGENT_EXECUTOR_BLOCK_ID,
-            input_default={
-                "graph_id": "abc",
-                "input_schema": {
-                    "properties": {"query": {"type": "string"}},
-                    "required": [],
-                },
-            },
-        )
-        link = _make_link(
-            source_id="src",
-            source_name="out",
-            sink_id="n1",
-            sink_name="query",
-        )
-        agent = _make_agent(nodes=[node], links=[link])
-
-        assert v.validate_sink_input_existence(agent, [block]) is True
-
-    def test_input_default_nested_invalid_child_fails(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",
-            input_default={"config_#_invalid_child": "value"},
-        )
-        agent = _make_agent(nodes=[node])
-
-        assert v.validate_sink_input_existence(agent, [block]) is False
-        assert any("invalid_child" in e for e in v.errors)
-
-    def test_input_default_nested_valid_child_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",
-            input_default={"config_#_key": "value"},
-        )
-        agent = _make_agent(nodes=[node])
-
-        assert v.validate_sink_input_existence(agent, [block]) is True
-
-
 class TestValidateMCPToolBlocks:
     """Tests for validate_mcp_tool_blocks."""
 

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

@@ -537,7 +537,7 @@ async def check_hitl_review(
         )
 
     synthetic_node_exec_id = (
-        f"{synthetic_node_id}{COPILOT_NODE_EXEC_ID_SEPARATOR}{uuid.uuid4().hex[:8]}"
+        f"{synthetic_node_id}{COPILOT_NODE_EXEC_ID_SEPARATOR}" f"{uuid.uuid4().hex[:8]}"
     )
 
     review_context = ExecutionContext(
@@ -582,16 +582,7 @@ def _resolve_discriminated_credentials(
     block: AnyBlockSchema,
     input_data: dict[str, Any],
 ) -> dict[str, CredentialsFieldInfo]:
-    """Resolve credential requirements, applying discriminator logic where needed.
-
-    Handles two discrimination modes:
-    1. **Provider-based** (``discriminator_mapping`` is set): the discriminator
-       field value selects the provider (e.g. an AI model name -> provider).
-    2. **URL/host-based** (``discriminator`` is set but ``discriminator_mapping``
-       is ``None``): the discriminator field value (typically a URL) is added to
-       ``discriminator_values`` so that host-scoped credential matching can
-       compare the credential's host against the target URL.
-    """
+    """Resolve credential requirements, applying discriminator logic where needed."""
     credentials_fields_info = block.input_schema.get_credentials_fields_info()
     if not credentials_fields_info:
         return {}
@@ -601,42 +592,25 @@ def _resolve_discriminated_credentials(
     for field_name, field_info in credentials_fields_info.items():
         effective_field_info = field_info
 
-        if field_info.discriminator:
+        if field_info.discriminator and field_info.discriminator_mapping:
             discriminator_value = input_data.get(field_info.discriminator)
             if discriminator_value is None:
                 field = block.input_schema.model_fields.get(field_info.discriminator)
                 if field and field.default is not PydanticUndefined:
                     discriminator_value = field.default
 
-            if discriminator_value is not None:
-                if field_info.discriminator_mapping:
-                    # Provider-based discrimination (e.g. model -> provider)
-                    if discriminator_value in field_info.discriminator_mapping:
-                        effective_field_info = field_info.discriminate(
-                            discriminator_value
-                        )
-                        effective_field_info.discriminator_values.add(
-                            discriminator_value
-                        )
-                        # Model names are safe to log (not PII); URLs are
-                        # intentionally omitted in the host-based branch below.
-                        logger.debug(
-                            "Discriminated provider for %s: %s -> %s",
-                            field_name,
-                            discriminator_value,
-                            effective_field_info.provider,
-                        )
-                else:
-                    # URL/host-based discrimination (e.g. url -> host matching).
-                    # Deep copy to avoid mutating the cached schema-level
-                    # field_info (model_copy() is shallow — the mutable set
-                    # would be shared).
-                    effective_field_info = field_info.model_copy(deep=True)
-                    effective_field_info.discriminator_values.add(discriminator_value)
-                    logger.debug(
-                        "Added discriminator value for host matching on %s",
-                        field_name,
-                    )
+            if (
+                discriminator_value
+                and discriminator_value in field_info.discriminator_mapping
+            ):
+                effective_field_info = field_info.discriminate(discriminator_value)
+                effective_field_info.discriminator_values.add(discriminator_value)
+                logger.debug(
+                    "Discriminated provider for %s: %s -> %s",
+                    field_name,
+                    discriminator_value,
+                    effective_field_info.provider,
+                )
 
         resolved[field_name] = effective_field_info
 

autogpt_platform/backend/backend/copilot/tools/http_credentials_test.py

@@ -1,916 +0,0 @@
-"""Tests for credential resolution across all credential types in the CoPilot.
-
-These tests verify that:
-1. `_resolve_discriminated_credentials` correctly populates discriminator_values
-   for URL-based (host-scoped) and provider-based (api_key) credential fields.
-2. `find_matching_credential` correctly matches credentials for all types:
-   APIKeyCredentials, OAuth2Credentials, UserPasswordCredentials, and
-   HostScopedCredentials.
-3. The full `resolve_block_credentials` flow correctly resolves matching
-   credentials or reports them as missing for each credential type.
-4. `RunBlockTool._execute` end-to-end tests return correct response types.
-"""
-
-from unittest.mock import AsyncMock, patch
-
-from pydantic import SecretStr
-
-from backend.blocks.http import SendAuthenticatedWebRequestBlock
-from backend.data.model import (
-    APIKeyCredentials,
-    CredentialsFieldInfo,
-    CredentialsType,
-    HostScopedCredentials,
-    OAuth2Credentials,
-    UserPasswordCredentials,
-)
-from backend.integrations.providers import ProviderName
-
-from ._test_data import make_session
-from .helpers import _resolve_discriminated_credentials, resolve_block_credentials
-from .models import BlockDetailsResponse, SetupRequirementsResponse
-from .run_block import RunBlockTool
-from .utils import find_matching_credential
-
-_TEST_USER_ID = "test-user-http-cred"
-
-# Properly typed constants to avoid type: ignore on CredentialsFieldInfo construction.
-_HOST_SCOPED_TYPES: frozenset[CredentialsType] = frozenset(["host_scoped"])
-_API_KEY_TYPES: frozenset[CredentialsType] = frozenset(["api_key"])
-_OAUTH2_TYPES: frozenset[CredentialsType] = frozenset(["oauth2"])
-_USER_PASSWORD_TYPES: frozenset[CredentialsType] = frozenset(["user_password"])
-
-# ---------------------------------------------------------------------------
-# _resolve_discriminated_credentials tests
-# ---------------------------------------------------------------------------
-
-
-class TestResolveDiscriminatedCredentials:
-    """Tests for _resolve_discriminated_credentials with URL-based discrimination."""
-
-    def _get_auth_block(self):
-        return SendAuthenticatedWebRequestBlock()
-
-    def test_url_discriminator_populates_discriminator_values(self):
-        """When input_data contains a URL, discriminator_values should include it."""
-        block = self._get_auth_block()
-        input_data = {"url": "https://api.example.com/v1/data"}
-
-        result = _resolve_discriminated_credentials(block, input_data)
-
-        assert "credentials" in result
-        field_info = result["credentials"]
-        assert "https://api.example.com/v1/data" in field_info.discriminator_values
-
-    def test_url_discriminator_without_url_keeps_empty_values(self):
-        """When no URL is provided, discriminator_values should remain empty."""
-        block = self._get_auth_block()
-        input_data = {}
-
-        result = _resolve_discriminated_credentials(block, input_data)
-
-        assert "credentials" in result
-        field_info = result["credentials"]
-        assert len(field_info.discriminator_values) == 0
-
-    def test_url_discriminator_does_not_mutate_original_field_info(self):
-        """The original block schema field_info must not be mutated."""
-        block = self._get_auth_block()
-
-        # Grab a reference to the original schema-level field_info
-        original_info = block.input_schema.get_credentials_fields_info()["credentials"]
-
-        # Call with a URL, which adds to discriminator_values on the copy
-        _resolve_discriminated_credentials(
-            block, {"url": "https://api.example.com/v1/data"}
-        )
-
-        # The original object must remain unchanged
-        assert len(original_info.discriminator_values) == 0
-
-        # And a fresh call without URL should also return empty values
-        result = _resolve_discriminated_credentials(block, {})
-        field_info = result["credentials"]
-        assert len(field_info.discriminator_values) == 0
-
-    def test_url_discriminator_preserves_provider_and_type(self):
-        """Provider and supported_types should be preserved after URL discrimination."""
-        block = self._get_auth_block()
-        input_data = {"url": "https://api.example.com/v1/data"}
-
-        result = _resolve_discriminated_credentials(block, input_data)
-
-        field_info = result["credentials"]
-        assert ProviderName.HTTP in field_info.provider
-        assert "host_scoped" in field_info.supported_types
-
-    def test_provider_discriminator_still_works(self):
-        """Verify provider-based discrimination (e.g. model -> provider) is preserved.
-
-        The refactored conditional in _resolve_discriminated_credentials split the
-        original single ``if`` into nested ``if/else`` branches. This test ensures
-        the provider-based path still narrows the provider correctly.
-        """
-        from backend.blocks.llm import AITextGeneratorBlock
-
-        block = AITextGeneratorBlock()
-        input_data = {"model": "gpt-4o-mini"}
-
-        result = _resolve_discriminated_credentials(block, input_data)
-
-        assert "credentials" in result
-        field_info = result["credentials"]
-        # Should narrow provider to openai
-        assert ProviderName.OPENAI in field_info.provider
-        assert "gpt-4o-mini" in field_info.discriminator_values
-
-
-# ---------------------------------------------------------------------------
-# find_matching_credential tests (host-scoped)
-# ---------------------------------------------------------------------------
-
-
-class TestFindMatchingHostScopedCredential:
-    """Tests for find_matching_credential with host-scoped credentials."""
-
-    def _make_host_scoped_cred(
-        self, host: str, cred_id: str = "test-cred-id"
-    ) -> HostScopedCredentials:
-        return HostScopedCredentials(
-            id=cred_id,
-            provider="http",
-            host=host,
-            headers={"Authorization": SecretStr("Bearer test-token")},
-            title=f"Cred for {host}",
-        )
-
-    def _make_field_info(
-        self, discriminator_values: set | None = None
-    ) -> CredentialsFieldInfo:
-        return CredentialsFieldInfo(
-            credentials_provider=frozenset([ProviderName.HTTP]),
-            credentials_types=_HOST_SCOPED_TYPES,
-            credentials_scopes=None,
-            discriminator="url",
-            discriminator_values=discriminator_values or set(),
-        )
-
-    def test_matches_credential_for_correct_host(self):
-        """A host-scoped credential matching the URL host should be returned."""
-        cred = self._make_host_scoped_cred("api.example.com")
-        field_info = self._make_field_info({"https://api.example.com/v1/data"})
-
-        result = find_matching_credential([cred], field_info)
-        assert result is not None
-        assert result.id == cred.id
-
-    def test_rejects_credential_for_wrong_host(self):
-        """A host-scoped credential for a different host should not match."""
-        cred = self._make_host_scoped_cred("api.github.com")
-        field_info = self._make_field_info({"https://api.stripe.com/v1/charges"})
-
-        result = find_matching_credential([cred], field_info)
-        assert result is None
-
-    def test_matches_any_when_no_discriminator_values(self):
-        """With empty discriminator_values, any host-scoped credential matches.
-
-        Note: this tests the current fallback behavior in _credential_is_for_host()
-        where empty discriminator_values means "no host constraint" and any
-        host-scoped credential is accepted. This is by design for the case where
-        the target URL is not yet known (e.g. schema preview with empty input).
-        """
-        cred = self._make_host_scoped_cred("api.anything.com")
-        field_info = self._make_field_info(set())
-
-        result = find_matching_credential([cred], field_info)
-        assert result is not None
-
-    def test_wildcard_host_matching(self):
-        """Wildcard host (*.example.com) should match subdomains."""
-        cred = self._make_host_scoped_cred("*.example.com")
-        field_info = self._make_field_info({"https://api.example.com/v1/data"})
-
-        result = find_matching_credential([cred], field_info)
-        assert result is not None
-
-    def test_selects_correct_credential_from_multiple(self):
-        """When multiple host-scoped credentials exist, the correct one is selected."""
-        cred_github = self._make_host_scoped_cred("api.github.com", "github-cred")
-        cred_stripe = self._make_host_scoped_cred("api.stripe.com", "stripe-cred")
-        field_info = self._make_field_info({"https://api.stripe.com/v1/charges"})
-
-        result = find_matching_credential([cred_github, cred_stripe], field_info)
-        assert result is not None
-        assert result.id == "stripe-cred"
-
-
-# ---------------------------------------------------------------------------
-# find_matching_credential tests (api_key)
-# ---------------------------------------------------------------------------
-
-
-class TestFindMatchingAPIKeyCredential:
-    """Tests for find_matching_credential with API key credentials."""
-
-    def _make_api_key_cred(
-        self, provider: str = "google_maps", cred_id: str = "test-api-key-id"
-    ) -> APIKeyCredentials:
-        return APIKeyCredentials(
-            id=cred_id,
-            provider=provider,
-            api_key=SecretStr("sk-test-key-123"),
-            title=f"API key for {provider}",
-            expires_at=None,
-        )
-
-    def _make_field_info(
-        self, provider: ProviderName = ProviderName.GOOGLE_MAPS
-    ) -> CredentialsFieldInfo:
-        return CredentialsFieldInfo(
-            credentials_provider=frozenset([provider]),
-            credentials_types=_API_KEY_TYPES,
-            credentials_scopes=None,
-        )
-
-    def test_matches_credential_for_correct_provider(self):
-        """An API key credential matching the provider should be returned."""
-        cred = self._make_api_key_cred("google_maps")
-        field_info = self._make_field_info(ProviderName.GOOGLE_MAPS)
-
-        result = find_matching_credential([cred], field_info)
-        assert result is not None
-        assert result.id == cred.id
-
-    def test_rejects_credential_for_wrong_provider(self):
-        """An API key credential for a different provider should not match."""
-        cred = self._make_api_key_cred("openai")
-        field_info = self._make_field_info(ProviderName.GOOGLE_MAPS)
-
-        result = find_matching_credential([cred], field_info)
-        assert result is None
-
-    def test_rejects_credential_for_wrong_type(self):
-        """An OAuth2 credential should not match an api_key requirement."""
-        oauth_cred = OAuth2Credentials(
-            id="oauth-cred-id",
-            provider="google_maps",
-            access_token=SecretStr("mock-token"),
-            scopes=[],
-            title="OAuth cred (wrong type)",
-        )
-        field_info = self._make_field_info(ProviderName.GOOGLE_MAPS)
-
-        result = find_matching_credential([oauth_cred], field_info)
-        assert result is None
-
-    def test_selects_correct_credential_from_multiple(self):
-        """When multiple API key credentials exist, the correct provider is selected."""
-        cred_maps = self._make_api_key_cred("google_maps", "maps-key")
-        cred_openai = self._make_api_key_cred("openai", "openai-key")
-        field_info = self._make_field_info(ProviderName.OPENAI)
-
-        result = find_matching_credential([cred_maps, cred_openai], field_info)
-        assert result is not None
-        assert result.id == "openai-key"
-
-    def test_returns_none_when_no_credentials(self):
-        """Should return None when the credential list is empty."""
-        field_info = self._make_field_info(ProviderName.GOOGLE_MAPS)
-
-        result = find_matching_credential([], field_info)
-        assert result is None
-
-
-# ---------------------------------------------------------------------------
-# find_matching_credential tests (oauth2)
-# ---------------------------------------------------------------------------
-
-
-class TestFindMatchingOAuth2Credential:
-    """Tests for find_matching_credential with OAuth2 credentials."""
-
-    def _make_oauth2_cred(
-        self,
-        provider: str = "google",
-        scopes: list[str] | None = None,
-        cred_id: str = "test-oauth2-id",
-    ) -> OAuth2Credentials:
-        return OAuth2Credentials(
-            id=cred_id,
-            provider=provider,
-            access_token=SecretStr("mock-access-token"),
-            refresh_token=SecretStr("mock-refresh-token"),
-            access_token_expires_at=1234567890,
-            scopes=scopes or [],
-            title=f"OAuth2 cred for {provider}",
-        )
-
-    def _make_field_info(
-        self,
-        provider: ProviderName = ProviderName.GOOGLE,
-        required_scopes: frozenset[str] | None = None,
-    ) -> CredentialsFieldInfo:
-        return CredentialsFieldInfo(
-            credentials_provider=frozenset([provider]),
-            credentials_types=_OAUTH2_TYPES,
-            credentials_scopes=required_scopes,
-        )
-
-    def test_matches_credential_for_correct_provider(self):
-        """An OAuth2 credential matching the provider should be returned."""
-        cred = self._make_oauth2_cred("google")
-        field_info = self._make_field_info(ProviderName.GOOGLE)
-
-        result = find_matching_credential([cred], field_info)
-        assert result is not None
-        assert result.id == cred.id
-
-    def test_rejects_credential_for_wrong_provider(self):
-        """An OAuth2 credential for a different provider should not match."""
-        cred = self._make_oauth2_cred("github")
-        field_info = self._make_field_info(ProviderName.GOOGLE)
-
-        result = find_matching_credential([cred], field_info)
-        assert result is None
-
-    def test_matches_credential_with_required_scopes(self):
-        """An OAuth2 credential with all required scopes should match."""
-        cred = self._make_oauth2_cred(
-            "google",
-            scopes=[
-                "https://www.googleapis.com/auth/gmail.readonly",
-                "https://www.googleapis.com/auth/gmail.send",
-            ],
-        )
-        field_info = self._make_field_info(
-            ProviderName.GOOGLE,
-            required_scopes=frozenset(
-                ["https://www.googleapis.com/auth/gmail.readonly"]
-            ),
-        )
-
-        result = find_matching_credential([cred], field_info)
-        assert result is not None
-
-    def test_rejects_credential_with_insufficient_scopes(self):
-        """An OAuth2 credential missing required scopes should not match."""
-        cred = self._make_oauth2_cred(
-            "google",
-            scopes=["https://www.googleapis.com/auth/gmail.readonly"],
-        )
-        field_info = self._make_field_info(
-            ProviderName.GOOGLE,
-            required_scopes=frozenset(
-                [
-                    "https://www.googleapis.com/auth/gmail.readonly",
-                    "https://www.googleapis.com/auth/gmail.send",
-                ]
-            ),
-        )
-
-        result = find_matching_credential([cred], field_info)
-        assert result is None
-
-    def test_matches_credential_when_no_scopes_required(self):
-        """An OAuth2 credential should match when no scopes are required."""
-        cred = self._make_oauth2_cred("google", scopes=[])
-        field_info = self._make_field_info(ProviderName.GOOGLE)
-
-        result = find_matching_credential([cred], field_info)
-        assert result is not None
-
-    def test_selects_correct_credential_from_multiple(self):
-        """When multiple OAuth2 credentials exist, the correct one is selected."""
-        cred_google = self._make_oauth2_cred("google", cred_id="google-cred")
-        cred_github = self._make_oauth2_cred("github", cred_id="github-cred")
-        field_info = self._make_field_info(ProviderName.GITHUB)
-
-        result = find_matching_credential([cred_google, cred_github], field_info)
-        assert result is not None
-        assert result.id == "github-cred"
-
-    def test_returns_none_when_no_credentials(self):
-        """Should return None when the credential list is empty."""
-        field_info = self._make_field_info(ProviderName.GOOGLE)
-
-        result = find_matching_credential([], field_info)
-        assert result is None
-
-
-# ---------------------------------------------------------------------------
-# find_matching_credential tests (user_password)
-# ---------------------------------------------------------------------------
-
-
-class TestFindMatchingUserPasswordCredential:
-    """Tests for find_matching_credential with user/password credentials."""
-
-    def _make_user_password_cred(
-        self, provider: str = "smtp", cred_id: str = "test-userpass-id"
-    ) -> UserPasswordCredentials:
-        return UserPasswordCredentials(
-            id=cred_id,
-            provider=provider,
-            username=SecretStr("test-user"),
-            password=SecretStr("test-pass"),
-            title=f"Credentials for {provider}",
-        )
-
-    def _make_field_info(
-        self, provider: ProviderName = ProviderName.SMTP
-    ) -> CredentialsFieldInfo:
-        return CredentialsFieldInfo(
-            credentials_provider=frozenset([provider]),
-            credentials_types=_USER_PASSWORD_TYPES,
-            credentials_scopes=None,
-        )
-
-    def test_matches_credential_for_correct_provider(self):
-        """A user/password credential matching the provider should be returned."""
-        cred = self._make_user_password_cred("smtp")
-        field_info = self._make_field_info(ProviderName.SMTP)
-
-        result = find_matching_credential([cred], field_info)
-        assert result is not None
-        assert result.id == cred.id
-
-    def test_rejects_credential_for_wrong_provider(self):
-        """A user/password credential for a different provider should not match."""
-        cred = self._make_user_password_cred("smtp")
-        field_info = self._make_field_info(ProviderName.HUBSPOT)
-
-        result = find_matching_credential([cred], field_info)
-        assert result is None
-
-    def test_rejects_credential_for_wrong_type(self):
-        """An API key credential should not match a user_password requirement."""
-        api_key_cred = APIKeyCredentials(
-            id="api-key-cred-id",
-            provider="smtp",
-            api_key=SecretStr("wrong-type-key"),
-            title="API key cred (wrong type)",
-        )
-        field_info = self._make_field_info(ProviderName.SMTP)
-
-        result = find_matching_credential([api_key_cred], field_info)
-        assert result is None
-
-    def test_selects_correct_credential_from_multiple(self):
-        """When multiple user/password credentials exist, the correct one is selected."""
-        cred_smtp = self._make_user_password_cred("smtp", "smtp-cred")
-        cred_hubspot = self._make_user_password_cred("hubspot", "hubspot-cred")
-        field_info = self._make_field_info(ProviderName.HUBSPOT)
-
-        result = find_matching_credential([cred_smtp, cred_hubspot], field_info)
-        assert result is not None
-        assert result.id == "hubspot-cred"
-
-    def test_returns_none_when_no_credentials(self):
-        """Should return None when the credential list is empty."""
-        field_info = self._make_field_info(ProviderName.SMTP)
-
-        result = find_matching_credential([], field_info)
-        assert result is None
-
-
-# ---------------------------------------------------------------------------
-# find_matching_credential tests (mixed credential types)
-# ---------------------------------------------------------------------------
-
-
-class TestFindMatchingCredentialMixedTypes:
-    """Tests that find_matching_credential correctly filters by type in a mixed list."""
-
-    def test_selects_api_key_from_mixed_list(self):
-        """API key requirement should skip OAuth2 and user_password credentials."""
-        oauth_cred = OAuth2Credentials(
-            id="oauth-id",
-            provider="openai",
-            access_token=SecretStr("token"),
-            scopes=[],
-        )
-        userpass_cred = UserPasswordCredentials(
-            id="userpass-id",
-            provider="openai",
-            username=SecretStr("user"),
-            password=SecretStr("pass"),
-        )
-        api_key_cred = APIKeyCredentials(
-            id="apikey-id",
-            provider="openai",
-            api_key=SecretStr("sk-key"),
-        )
-        field_info = CredentialsFieldInfo(
-            credentials_provider=frozenset([ProviderName.OPENAI]),
-            credentials_types=_API_KEY_TYPES,
-            credentials_scopes=None,
-        )
-
-        result = find_matching_credential(
-            [oauth_cred, userpass_cred, api_key_cred], field_info
-        )
-        assert result is not None
-        assert result.id == "apikey-id"
-
-    def test_selects_oauth2_from_mixed_list(self):
-        """OAuth2 requirement should skip API key and user_password credentials."""
-        api_key_cred = APIKeyCredentials(
-            id="apikey-id",
-            provider="google",
-            api_key=SecretStr("key"),
-        )
-        userpass_cred = UserPasswordCredentials(
-            id="userpass-id",
-            provider="google",
-            username=SecretStr("user"),
-            password=SecretStr("pass"),
-        )
-        oauth_cred = OAuth2Credentials(
-            id="oauth-id",
-            provider="google",
-            access_token=SecretStr("token"),
-            scopes=["https://www.googleapis.com/auth/gmail.readonly"],
-        )
-        field_info = CredentialsFieldInfo(
-            credentials_provider=frozenset([ProviderName.GOOGLE]),
-            credentials_types=_OAUTH2_TYPES,
-            credentials_scopes=frozenset(
-                ["https://www.googleapis.com/auth/gmail.readonly"]
-            ),
-        )
-
-        result = find_matching_credential(
-            [api_key_cred, userpass_cred, oauth_cred], field_info
-        )
-        assert result is not None
-        assert result.id == "oauth-id"
-
-    def test_selects_user_password_from_mixed_list(self):
-        """User/password requirement should skip API key and OAuth2 credentials."""
-        api_key_cred = APIKeyCredentials(
-            id="apikey-id",
-            provider="smtp",
-            api_key=SecretStr("key"),
-        )
-        oauth_cred = OAuth2Credentials(
-            id="oauth-id",
-            provider="smtp",
-            access_token=SecretStr("token"),
-            scopes=[],
-        )
-        userpass_cred = UserPasswordCredentials(
-            id="userpass-id",
-            provider="smtp",
-            username=SecretStr("user"),
-            password=SecretStr("pass"),
-        )
-        field_info = CredentialsFieldInfo(
-            credentials_provider=frozenset([ProviderName.SMTP]),
-            credentials_types=_USER_PASSWORD_TYPES,
-            credentials_scopes=None,
-        )
-
-        result = find_matching_credential(
-            [api_key_cred, oauth_cred, userpass_cred], field_info
-        )
-        assert result is not None
-        assert result.id == "userpass-id"
-
-    def test_returns_none_when_only_wrong_types_available(self):
-        """Should return None when all available creds have the wrong type."""
-        oauth_cred = OAuth2Credentials(
-            id="oauth-id",
-            provider="google_maps",
-            access_token=SecretStr("token"),
-            scopes=[],
-        )
-        field_info = CredentialsFieldInfo(
-            credentials_provider=frozenset([ProviderName.GOOGLE_MAPS]),
-            credentials_types=_API_KEY_TYPES,
-            credentials_scopes=None,
-        )
-
-        result = find_matching_credential([oauth_cred], field_info)
-        assert result is None
-
-
-# ---------------------------------------------------------------------------
-# resolve_block_credentials tests (integration — all credential types)
-# ---------------------------------------------------------------------------
-
-
-class TestResolveBlockCredentials:
-    """Integration tests for resolve_block_credentials across credential types."""
-
-    async def test_matches_host_scoped_credential_for_url(self):
-        """resolve_block_credentials should match a host-scoped cred for the given URL."""
-        block = SendAuthenticatedWebRequestBlock()
-        input_data = {"url": "https://api.example.com/v1/data"}
-
-        mock_cred = HostScopedCredentials(
-            id="matching-cred-id",
-            provider="http",
-            host="api.example.com",
-            headers={"Authorization": SecretStr("Bearer token")},
-            title="Example API Cred",
-        )
-
-        with patch(
-            "backend.copilot.tools.utils.get_user_credentials",
-            new_callable=AsyncMock,
-            return_value=[mock_cred],
-        ):
-            matched, missing = await resolve_block_credentials(
-                _TEST_USER_ID, block, input_data
-            )
-
-        assert "credentials" in matched
-        assert matched["credentials"].id == "matching-cred-id"
-        assert len(missing) == 0
-
-    async def test_reports_missing_when_no_matching_host(self):
-        """resolve_block_credentials should report missing creds when host doesn't match."""
-        block = SendAuthenticatedWebRequestBlock()
-        input_data = {"url": "https://api.stripe.com/v1/charges"}
-
-        wrong_host_cred = HostScopedCredentials(
-            id="wrong-cred-id",
-            provider="http",
-            host="api.github.com",
-            headers={"Authorization": SecretStr("Bearer token")},
-            title="GitHub API Cred",
-        )
-
-        with patch(
-            "backend.copilot.tools.utils.get_user_credentials",
-            new_callable=AsyncMock,
-            return_value=[wrong_host_cred],
-        ):
-            matched, missing = await resolve_block_credentials(
-                _TEST_USER_ID, block, input_data
-            )
-
-        assert len(matched) == 0
-        assert len(missing) == 1
-
-    async def test_reports_missing_when_no_credentials(self):
-        """resolve_block_credentials should report missing when user has no creds at all."""
-        block = SendAuthenticatedWebRequestBlock()
-        input_data = {"url": "https://api.example.com/v1/data"}
-
-        with patch(
-            "backend.copilot.tools.utils.get_user_credentials",
-            new_callable=AsyncMock,
-            return_value=[],
-        ):
-            matched, missing = await resolve_block_credentials(
-                _TEST_USER_ID, block, input_data
-            )
-
-        assert len(matched) == 0
-        assert len(missing) == 1
-
-    async def test_matches_api_key_credential_for_llm_block(self):
-        """resolve_block_credentials should match an API key cred for an LLM block."""
-        from backend.blocks.llm import AITextGeneratorBlock
-
-        block = AITextGeneratorBlock()
-        input_data = {"model": "gpt-4o-mini"}
-
-        mock_cred = APIKeyCredentials(
-            id="openai-key-id",
-            provider="openai",
-            api_key=SecretStr("sk-test-key"),
-            title="OpenAI API Key",
-        )
-
-        with patch(
-            "backend.copilot.tools.utils.get_user_credentials",
-            new_callable=AsyncMock,
-            return_value=[mock_cred],
-        ):
-            matched, missing = await resolve_block_credentials(
-                _TEST_USER_ID, block, input_data
-            )
-
-        assert "credentials" in matched
-        assert matched["credentials"].id == "openai-key-id"
-        assert len(missing) == 0
-
-    async def test_reports_missing_api_key_for_wrong_provider(self):
-        """resolve_block_credentials should report missing when API key provider mismatches."""
-        from backend.blocks.llm import AITextGeneratorBlock
-
-        block = AITextGeneratorBlock()
-        input_data = {"model": "gpt-4o-mini"}
-
-        wrong_provider_cred = APIKeyCredentials(
-            id="wrong-key-id",
-            provider="google_maps",
-            api_key=SecretStr("sk-wrong"),
-            title="Google Maps Key",
-        )
-
-        with patch(
-            "backend.copilot.tools.utils.get_user_credentials",
-            new_callable=AsyncMock,
-            return_value=[wrong_provider_cred],
-        ):
-            matched, missing = await resolve_block_credentials(
-                _TEST_USER_ID, block, input_data
-            )
-
-        assert len(matched) == 0
-        assert len(missing) == 1
-
-    async def test_matches_oauth2_credential_for_google_block(self):
-        """resolve_block_credentials should match an OAuth2 cred for a Google block."""
-        from backend.blocks.google.gmail import GmailReadBlock
-
-        block = GmailReadBlock()
-        input_data = {}
-
-        mock_cred = OAuth2Credentials(
-            id="google-oauth-id",
-            provider="google",
-            access_token=SecretStr("mock-token"),
-            refresh_token=SecretStr("mock-refresh"),
-            access_token_expires_at=9999999999,
-            scopes=["https://www.googleapis.com/auth/gmail.readonly"],
-            title="Google OAuth",
-        )
-
-        with patch(
-            "backend.copilot.tools.utils.get_user_credentials",
-            new_callable=AsyncMock,
-            return_value=[mock_cred],
-        ):
-            matched, missing = await resolve_block_credentials(
-                _TEST_USER_ID, block, input_data
-            )
-
-        assert "credentials" in matched
-        assert matched["credentials"].id == "google-oauth-id"
-        assert len(missing) == 0
-
-    async def test_reports_missing_oauth2_with_insufficient_scopes(self):
-        """resolve_block_credentials should report missing when OAuth2 scopes are insufficient."""
-        from backend.blocks.google.gmail import GmailSendBlock
-
-        block = GmailSendBlock()
-        input_data = {}
-
-        # GmailSendBlock requires gmail.send scope; provide only readonly
-        insufficient_cred = OAuth2Credentials(
-            id="limited-oauth-id",
-            provider="google",
-            access_token=SecretStr("mock-token"),
-            scopes=["https://www.googleapis.com/auth/gmail.readonly"],
-            title="Google OAuth (limited)",
-        )
-
-        with patch(
-            "backend.copilot.tools.utils.get_user_credentials",
-            new_callable=AsyncMock,
-            return_value=[insufficient_cred],
-        ):
-            matched, missing = await resolve_block_credentials(
-                _TEST_USER_ID, block, input_data
-            )
-
-        assert len(matched) == 0
-        assert len(missing) == 1
-
-    async def test_matches_user_password_credential_for_email_block(self):
-        """resolve_block_credentials should match a user/password cred for an SMTP block."""
-        from backend.blocks.email_block import SendEmailBlock
-
-        block = SendEmailBlock()
-        input_data = {}
-
-        mock_cred = UserPasswordCredentials(
-            id="smtp-cred-id",
-            provider="smtp",
-            username=SecretStr("test-user"),
-            password=SecretStr("test-pass"),
-            title="SMTP Credentials",
-        )
-
-        with patch(
-            "backend.copilot.tools.utils.get_user_credentials",
-            new_callable=AsyncMock,
-            return_value=[mock_cred],
-        ):
-            matched, missing = await resolve_block_credentials(
-                _TEST_USER_ID, block, input_data
-            )
-
-        assert "credentials" in matched
-        assert matched["credentials"].id == "smtp-cred-id"
-        assert len(missing) == 0
-
-    async def test_reports_missing_user_password_for_wrong_provider(self):
-        """resolve_block_credentials should report missing when user/password provider mismatches."""
-        from backend.blocks.email_block import SendEmailBlock
-
-        block = SendEmailBlock()
-        input_data = {}
-
-        wrong_cred = UserPasswordCredentials(
-            id="wrong-cred-id",
-            provider="dataforseo",
-            username=SecretStr("user"),
-            password=SecretStr("pass"),
-            title="DataForSEO Creds",
-        )
-
-        with patch(
-            "backend.copilot.tools.utils.get_user_credentials",
-            new_callable=AsyncMock,
-            return_value=[wrong_cred],
-        ):
-            matched, missing = await resolve_block_credentials(
-                _TEST_USER_ID, block, input_data
-            )
-
-        assert len(matched) == 0
-        assert len(missing) == 1
-
-
-# ---------------------------------------------------------------------------
-# RunBlockTool integration tests for authenticated HTTP
-# ---------------------------------------------------------------------------
-
-
-class TestRunBlockToolAuthenticatedHttp:
-    """End-to-end tests for RunBlockTool with SendAuthenticatedWebRequestBlock."""
-
-    async def test_returns_setup_requirements_when_creds_missing(self):
-        """When no matching host-scoped credential exists, return SetupRequirementsResponse."""
-        session = make_session(user_id=_TEST_USER_ID)
-        block = SendAuthenticatedWebRequestBlock()
-
-        with patch(
-            "backend.copilot.tools.helpers.get_block",
-            return_value=block,
-        ):
-            with patch(
-                "backend.copilot.tools.utils.get_user_credentials",
-                new_callable=AsyncMock,
-                return_value=[],
-            ):
-                tool = RunBlockTool()
-                response = await tool._execute(
-                    user_id=_TEST_USER_ID,
-                    session=session,
-                    block_id=block.id,
-                    input_data={"url": "https://api.example.com/data", "method": "GET"},
-                )
-
-        assert isinstance(response, SetupRequirementsResponse)
-        assert "credentials" in response.message.lower()
-
-    async def test_returns_details_when_creds_matched_but_missing_required_inputs(self):
-        """When creds present + required inputs missing -> BlockDetailsResponse.
-
-        Note: with input_data={}, no URL is provided so discriminator_values is
-        empty, meaning _credential_is_for_host() matches any host-scoped
-        credential vacuously. This test exercises the "creds present + inputs
-        missing" branch, not host-based matching (which is covered by
-        TestFindMatchingHostScopedCredential and TestResolveBlockCredentials).
-        """
-        session = make_session(user_id=_TEST_USER_ID)
-        block = SendAuthenticatedWebRequestBlock()
-
-        mock_cred = HostScopedCredentials(
-            id="matching-cred-id",
-            provider="http",
-            host="api.example.com",
-            headers={"Authorization": SecretStr("Bearer token")},
-            title="Example API Cred",
-        )
-
-        with patch(
-            "backend.copilot.tools.helpers.get_block",
-            return_value=block,
-        ):
-            with patch(
-                "backend.copilot.tools.utils.get_user_credentials",
-                new_callable=AsyncMock,
-                return_value=[mock_cred],
-            ):
-                tool = RunBlockTool()
-                # Call with empty input to get schema
-                response = await tool._execute(
-                    user_id=_TEST_USER_ID,
-                    session=session,
-                    block_id=block.id,
-                    input_data={},
-                )
-
-        assert isinstance(response, BlockDetailsResponse)
-        assert response.block.name == block.name
-        # The matched credential should be included in the details
-        assert len(response.block.credentials) > 0
-        assert response.block.credentials[0].id == "matching-cred-id"

autogpt_platform/backend/backend/copilot/tools/utils.py

@@ -121,7 +121,7 @@ def _serialize_missing_credential(
     provider = next(iter(field_info.provider), "unknown")
     scopes = sorted(field_info.required_scopes or [])
 
-    result: dict[str, Any] = {
+    return {
         "id": field_key,
         "title": field_key.replace("_", " ").title(),
         "provider": provider,
@@ -131,17 +131,6 @@ def _serialize_missing_credential(
         "scopes": scopes,
     }
 
-    # Include discriminator info so the frontend can auto-match
-    # host-scoped credentials (e.g. SendAuthenticatedWebRequestBlock).
-    if field_info.discriminator:
-        result["discriminator"] = field_info.discriminator
-    if field_info.discriminator_values:
-        result["discriminator_values"] = sorted(
-            str(v) for v in field_info.discriminator_values
-        )
-
-    return result
-
 
 def build_missing_credentials_from_graph(
     graph: GraphModel, matched_credentials: dict[str, CredentialsMetaInput] | None

autogpt_platform/backend/backend/data/db_manager.py

@@ -344,7 +344,6 @@ class DatabaseManager(AppService):
     get_next_sequence = _(chat_db.get_next_sequence)
     update_tool_message_content = _(chat_db.update_tool_message_content)
     update_chat_session_title = _(chat_db.update_chat_session_title)
-    set_turn_duration = _(chat_db.set_turn_duration)
 
 
 class DatabaseManagerClient(AppServiceClient):
@@ -541,4 +540,3 @@ class DatabaseManagerAsyncClient(AppServiceClient):
     get_next_sequence = d.get_next_sequence
     update_tool_message_content = d.update_tool_message_content
     update_chat_session_title = d.update_chat_session_title
-    set_turn_duration = d.set_turn_duration

autogpt_platform/backend/backend/data/execution.py

@@ -342,7 +342,6 @@ class GraphExecution(GraphExecutionMeta):
                     if (
                         (block := get_block(exec.block_id))
                         and block.block_type == BlockType.INPUT
-                        and "name" in exec.input_data
                     )
                 }
             ),
@@ -361,10 +360,8 @@ class GraphExecution(GraphExecutionMeta):
         outputs: CompletedBlockOutput = defaultdict(list)
         for exec in complete_node_executions:
             if (
-                (block := get_block(exec.block_id))
-                and block.block_type == BlockType.OUTPUT
-                and "name" in exec.input_data
-            ):
+                block := get_block(exec.block_id)
+            ) and block.block_type == BlockType.OUTPUT:
                 outputs[exec.input_data["name"]].append(exec.input_data.get("value"))
 
         return GraphExecution(

autogpt_platform/backend/backend/data/graph.py

@@ -581,6 +581,7 @@ class GraphModel(Graph, GraphMeta):
                     field_name,
                     field_info,
                 ) in node.block.input_schema.get_credentials_fields_info().items():
+
                     discriminator = field_info.discriminator
                     if not discriminator:
                         node_credential_data.append((field_info, (node.id, field_name)))
@@ -1528,28 +1529,6 @@ async def fork_graph(graph_id: str, graph_version: int, user_id: str) -> GraphMo
 async def __create_graph(tx, graph: Graph, user_id: str):
     graphs = [graph] + graph.sub_graphs
 
-    # Auto-increment version for any graph entry (parent or sub-graph) whose
-    # (id, version) already exists.  This prevents UniqueViolationError when
-    # the copilot re-saves an agent that already exists at the requested version.
-    # NOTE: This issues one find_first query per graph entry (N+1 pattern).
-    # Sub-graph counts are typically small (< 5), so the overhead is negligible.
-    for g in graphs:
-        existing = await AgentGraph.prisma(tx).find_first(
-            where={"id": g.id},
-            order={"version": "desc"},
-        )
-        if existing and existing.version >= g.version:
-            old_version = g.version
-            g.version = existing.version + 1
-            logger.warning(
-                "Auto-incremented graph %s version from %d to %d "
-                "(version %d already exists)",
-                g.id,
-                old_version,
-                g.version,
-                existing.version,
-            )
-
     await AgentGraph.prisma(tx).create_many(
         data=[
             AgentGraphCreateInput(

autogpt_platform/backend/backend/data/model.py

@@ -325,8 +325,6 @@ class _BaseCredentials(BaseModel):
     id: str = Field(default_factory=lambda: str(uuid4()))
     provider: str
     title: Optional[str] = None
-    is_managed: bool = False
-    metadata: dict[str, Any] = Field(default_factory=dict)
 
     @field_serializer("*")
     def dump_secret_strings(value: Any, _info):
@@ -346,6 +344,7 @@ class OAuth2Credentials(_BaseCredentials):
     refresh_token_expires_at: Optional[int] = None
     """Unix timestamp (seconds) indicating when the refresh token expires (if at all)"""
     scopes: list[str]
+    metadata: dict[str, Any] = Field(default_factory=dict)
 
     def auth_header(self) -> str:
         return f"Bearer {self.access_token.get_secret_value()}"
@@ -723,7 +722,7 @@ class CredentialsFieldInfo(BaseModel, Generic[CP, CT]):
             credentials_scopes=self.required_scopes,
             discriminator=self.discriminator,
             discriminator_mapping=self.discriminator_mapping,
-            discriminator_values=set(self.discriminator_values),  # defensive copy
+            discriminator_values=self.discriminator_values,
         )
 
 

autogpt_platform/backend/backend/data/tally.py

@@ -40,9 +40,6 @@ _MAX_PAGES = 100
 # LLM extraction timeout (seconds)
 _LLM_TIMEOUT = 30
 
-SUGGESTION_THEMES = ["Learn", "Create", "Automate", "Organize"]
-PROMPTS_PER_THEME = 5
-
 
 def _mask_email(email: str) -> str:
     """Mask an email for safe logging: 'alice@example.com' -> 'a***e@example.com'."""
@@ -335,11 +332,6 @@ Fields:
 - current_software (list of strings): software/tools currently used
 - existing_automation (list of strings): existing automations
 - additional_notes (string): any additional context
-- suggested_prompts (object with keys "Learn", "Create", "Automate", "Organize"): for each key, \
-provide a list of 5 short action prompts (each under 20 words) that would help this person. \
-"Learn" = questions about AutoGPT features; "Create" = content/document generation tasks; \
-"Automate" = recurring workflow automation ideas; "Organize" = structuring/prioritizing tasks. \
-Should be specific to their industry, role, and pain points; actionable and conversational in tone.
 
 Form data:
 """
@@ -386,29 +378,6 @@ async def extract_business_understanding(
 
     # Filter out null values before constructing
     cleaned = {k: v for k, v in data.items() if v is not None}
-
-    # Validate suggested_prompts: themed dict, filter >20 words, cap at 5 per theme
-    raw_prompts = cleaned.get("suggested_prompts", {})
-    if isinstance(raw_prompts, dict):
-        themed: dict[str, list[str]] = {}
-        for theme in SUGGESTION_THEMES:
-            theme_prompts = raw_prompts.get(theme, [])
-            if not isinstance(theme_prompts, list):
-                continue
-            valid = [
-                s
-                for p in theme_prompts
-                if isinstance(p, str) and (s := p.strip()) and len(s.split()) <= 20
-            ]
-            if valid:
-                themed[theme] = valid[:PROMPTS_PER_THEME]
-        if themed:
-            cleaned["suggested_prompts"] = themed
-        else:
-            cleaned.pop("suggested_prompts", None)
-    else:
-        cleaned.pop("suggested_prompts", None)
-
     return BusinessUnderstandingInput(**cleaned)
 
 

autogpt_platform/backend/backend/data/tally_test.py

@@ -284,7 +284,6 @@ async def test_populate_understanding_full_flow():
         ],
     }
     mock_input = MagicMock()
-    mock_input.suggested_prompts = {"Learn": ["P1"], "Create": ["P2"]}
 
     with (
         patch(
@@ -398,25 +397,15 @@ def test_extraction_prompt_no_format_placeholders():
 
 
 @pytest.mark.asyncio
-async def test_extract_business_understanding_themed_prompts():
-    """Happy path: LLM returns themed prompts as dict."""
+async def test_extract_business_understanding_success():
+    """Happy path: LLM returns valid JSON that maps to BusinessUnderstandingInput."""
     mock_choice = MagicMock()
     mock_choice.message.content = json.dumps(
         {
             "user_name": "Alice",
             "business_name": "Acme Corp",
-            "suggested_prompts": {
-                "Learn": ["Learn 1", "Learn 2", "Learn 3", "Learn 4", "Learn 5"],
-                "Create": [
-                    "Create 1",
-                    "Create 2",
-                    "Create 3",
-                    "Create 4",
-                    "Create 5",
-                ],
-                "Automate": ["Auto 1", "Auto 2", "Auto 3", "Auto 4", "Auto 5"],
-                "Organize": ["Org 1", "Org 2", "Org 3", "Org 4", "Org 5"],
-            },
+            "industry": "Technology",
+            "pain_points": ["manual reporting"],
         }
     )
     mock_response = MagicMock()
@@ -429,42 +418,9 @@ async def test_extract_business_understanding_themed_prompts():
         result = await extract_business_understanding("Q: Name?\nA: Alice")
 
     assert result.user_name == "Alice"
-    assert result.suggested_prompts is not None
-    assert len(result.suggested_prompts) == 4
-    assert len(result.suggested_prompts["Learn"]) == 5
-
-
-@pytest.mark.asyncio
-async def test_extract_themed_prompts_filters_long_and_unknown_keys():
-    """Long prompts are filtered, unknown keys are dropped, each theme capped at 5."""
-    long_prompt = " ".join(["word"] * 21)
-    mock_choice = MagicMock()
-    mock_choice.message.content = json.dumps(
-        {
-            "user_name": "Alice",
-            "suggested_prompts": {
-                "Learn": [long_prompt, "Valid learn 1", "Valid learn 2"],
-                "UnknownTheme": ["Should be dropped"],
-                "Automate": ["A1", "A2", "A3", "A4", "A5", "A6"],
-            },
-        }
-    )
-    mock_response = MagicMock()
-    mock_response.choices = [mock_choice]
-
-    mock_client = AsyncMock()
-    mock_client.chat.completions.create.return_value = mock_response
-
-    with patch("backend.data.tally.AsyncOpenAI", return_value=mock_client):
-        result = await extract_business_understanding("Q: Name?\nA: Alice")
-
-    assert result.suggested_prompts is not None
-    # Unknown key dropped
-    assert "UnknownTheme" not in result.suggested_prompts
-    # Long prompt filtered
-    assert result.suggested_prompts["Learn"] == ["Valid learn 1", "Valid learn 2"]
-    # Capped at 5
-    assert result.suggested_prompts["Automate"] == ["A1", "A2", "A3", "A4", "A5"]
+    assert result.business_name == "Acme Corp"
+    assert result.industry == "Technology"
+    assert result.pain_points == ["manual reporting"]
 
 
 @pytest.mark.asyncio

autogpt_platform/backend/backend/data/understanding.py

@@ -49,25 +49,6 @@ def _json_to_list(value: Any) -> list[str]:
     return []
 
 
-def _json_to_themed_prompts(value: Any) -> dict[str, list[str]]:
-    """Convert Json field to themed prompts dict.
-
-    Handles both the new ``dict[str, list[str]]`` format and the legacy
-    ``list[str]`` format.  Legacy rows are placed under a ``"General"`` key so
-    existing personalised prompts remain readable until a backfill regenerates
-    them into the proper themed shape.
-    """
-    if isinstance(value, dict):
-        return {
-            k: [i for i in v if isinstance(i, str)]
-            for k, v in value.items()
-            if isinstance(k, str) and isinstance(v, list)
-        }
-    if isinstance(value, list) and value:
-        return {"General": [str(p) for p in value if isinstance(p, str)]}
-    return {}
-
-
 class BusinessUnderstandingInput(pydantic.BaseModel):
     """Input model for updating business understanding - all fields optional for incremental updates."""
 
@@ -123,11 +104,6 @@ class BusinessUnderstandingInput(pydantic.BaseModel):
         None, description="Any additional context"
     )
 
-    # Suggested prompts (UI-only, not included in system prompt)
-    suggested_prompts: Optional[dict[str, list[str]]] = pydantic.Field(
-        None, description="LLM-generated suggested prompts grouped by theme"
-    )
-
 
 class BusinessUnderstanding(pydantic.BaseModel):
     """Full business understanding model returned from database."""
@@ -164,9 +140,6 @@ class BusinessUnderstanding(pydantic.BaseModel):
     # Additional context
     additional_notes: Optional[str] = None
 
-    # Suggested prompts (UI-only, not included in system prompt)
-    suggested_prompts: dict[str, list[str]] = pydantic.Field(default_factory=dict)
-
     @classmethod
     def from_db(cls, db_record: CoPilotUnderstanding) -> "BusinessUnderstanding":
         """Convert database record to Pydantic model."""
@@ -194,7 +167,6 @@ class BusinessUnderstanding(pydantic.BaseModel):
             current_software=_json_to_list(business.get("current_software")),
             existing_automation=_json_to_list(business.get("existing_automation")),
             additional_notes=business.get("additional_notes"),
-            suggested_prompts=_json_to_themed_prompts(data.get("suggested_prompts")),
         )
 
 
@@ -274,22 +246,33 @@ async def get_business_understanding(
     return understanding
 
 
-def merge_business_understanding_data(
-    existing_data: dict[str, Any],
+async def upsert_business_understanding(
+    user_id: str,
     input_data: BusinessUnderstandingInput,
-) -> dict[str, Any]:
-    """Merge new input into existing data dict using incremental strategy.
+) -> BusinessUnderstanding:
+    """
+    Create or update business understanding with incremental merge strategy.
 
     - String fields: new value overwrites if provided (not None)
     - List fields: new items are appended to existing (deduplicated)
-    - suggested_prompts: fully replaced if provided (not None)
 
-    Returns the merged data dict (mutates and returns *existing_data*).
+    Data is stored as: {name: ..., business: {version: 1, ...}}
     """
+    # Get existing record for merge
+    existing = await CoPilotUnderstanding.prisma().find_unique(
+        where={"userId": user_id}
+    )
+
+    # Get existing data structure or start fresh
+    existing_data: dict[str, Any] = {}
+    if existing and isinstance(existing.data, dict):
+        existing_data = dict(existing.data)
+
     existing_business: dict[str, Any] = {}
     if isinstance(existing_data.get("business"), dict):
         existing_business = dict(existing_data["business"])
 
+    # Business fields (stored inside business object)
     business_string_fields = [
         "job_title",
         "business_name",
@@ -327,48 +310,16 @@ def merge_business_understanding_data(
             merged = _merge_lists(existing_list, value)
             existing_business[field] = merged
 
-    # Suggested prompts - fully replace if provided
-    if input_data.suggested_prompts is not None:
-        existing_data["suggested_prompts"] = input_data.suggested_prompts
-
     # Set version and nest business data
     existing_business["version"] = 1
     existing_data["business"] = existing_business
 
-    return existing_data
-
-
-async def upsert_business_understanding(
-    user_id: str,
-    input_data: BusinessUnderstandingInput,
-) -> BusinessUnderstanding:
-    """
-    Create or update business understanding with incremental merge strategy.
-
-    - String fields: new value overwrites if provided (not None)
-    - List fields: new items are appended to existing (deduplicated)
-    - suggested_prompts: fully replaced if provided (not None)
-
-    Data is stored as: {name: ..., business: {version: 1, ...}}
-    """
-    # Get existing record for merge
-    existing = await CoPilotUnderstanding.prisma().find_unique(
-        where={"userId": user_id}
-    )
-
-    # Get existing data structure or start fresh
-    existing_data: dict[str, Any] = {}
-    if existing and isinstance(existing.data, dict):
-        existing_data = dict(existing.data)
-
-    merged_data = merge_business_understanding_data(existing_data, input_data)
-
     # Upsert with the merged data
     record = await CoPilotUnderstanding.prisma().upsert(
         where={"userId": user_id},
         data={
-            "create": {"userId": user_id, "data": SafeJson(merged_data)},
-            "update": {"data": SafeJson(merged_data)},
+            "create": {"userId": user_id, "data": SafeJson(existing_data)},
+            "update": {"data": SafeJson(existing_data)},
         },
     )
 

autogpt_platform/backend/backend/data/understanding_test.py

@@ -1,148 +0,0 @@
-"""Tests for business understanding merge and format logic."""
-
-from datetime import datetime, timezone
-from typing import Any
-from unittest.mock import MagicMock
-
-from backend.data.understanding import (
-    BusinessUnderstanding,
-    BusinessUnderstandingInput,
-    _json_to_themed_prompts,
-    format_understanding_for_prompt,
-    merge_business_understanding_data,
-)
-
-
-def _make_input(**kwargs: Any) -> BusinessUnderstandingInput:
-    """Create a BusinessUnderstandingInput with only the specified fields."""
-    return BusinessUnderstandingInput.model_validate(kwargs)
-
-
-# ─── merge_business_understanding_data: themed prompts ─────────────────
-
-
-def test_merge_themed_prompts_overwrites_existing():
-    """New themed prompts should fully replace existing ones (not merge)."""
-    existing = {
-        "name": "Alice",
-        "business": {"industry": "Tech", "version": 1},
-        "suggested_prompts": {
-            "Learn": ["Old learn prompt"],
-            "Create": ["Old create prompt"],
-        },
-    }
-    new_prompts = {
-        "Automate": ["Schedule daily reports", "Set up email alerts"],
-        "Organize": ["Sort inbox by priority"],
-    }
-    input_data = _make_input(suggested_prompts=new_prompts)
-
-    result = merge_business_understanding_data(existing, input_data)
-
-    assert result["suggested_prompts"] == new_prompts
-
-
-def test_merge_themed_prompts_none_preserves_existing():
-    """When input has suggested_prompts=None, existing themed prompts are preserved."""
-    existing_prompts = {
-        "Learn": ["How to automate?"],
-        "Create": ["Build a chatbot"],
-    }
-    existing = {
-        "name": "Alice",
-        "business": {"industry": "Tech", "version": 1},
-        "suggested_prompts": existing_prompts,
-    }
-    input_data = _make_input(industry="Finance")
-
-    result = merge_business_understanding_data(existing, input_data)
-
-    assert result["suggested_prompts"] == existing_prompts
-    assert result["business"]["industry"] == "Finance"
-
-
-# ─── from_db: themed prompts deserialization ───────────────────────────
-
-
-def test_from_db_themed_prompts():
-    """from_db correctly deserializes a themed dict for suggested_prompts."""
-    themed = {
-        "Learn": ["What can I automate?"],
-        "Create": ["Build a workflow"],
-    }
-    db_record = MagicMock()
-    db_record.id = "test-id"
-    db_record.userId = "user-1"
-    db_record.createdAt = datetime.now(tz=timezone.utc)
-    db_record.updatedAt = datetime.now(tz=timezone.utc)
-    db_record.data = {
-        "name": "Alice",
-        "business": {"industry": "Tech", "version": 1},
-        "suggested_prompts": themed,
-    }
-
-    result = BusinessUnderstanding.from_db(db_record)
-
-    assert result.suggested_prompts == themed
-
-
-def test_from_db_legacy_list_prompts_preserved_under_general():
-    """from_db preserves legacy list[str] prompts under a 'General' key."""
-    db_record = MagicMock()
-    db_record.id = "test-id"
-    db_record.userId = "user-1"
-    db_record.createdAt = datetime.now(tz=timezone.utc)
-    db_record.updatedAt = datetime.now(tz=timezone.utc)
-    db_record.data = {
-        "name": "Alice",
-        "business": {"industry": "Tech", "version": 1},
-        "suggested_prompts": ["Old prompt 1", "Old prompt 2"],
-    }
-
-    result = BusinessUnderstanding.from_db(db_record)
-
-    assert result.suggested_prompts == {"General": ["Old prompt 1", "Old prompt 2"]}
-
-
-# ─── _json_to_themed_prompts helper ───────────────────────────────────
-
-
-def test_json_to_themed_prompts_with_dict():
-    value = {"Learn": ["a", "b"], "Create": ["c"]}
-    assert _json_to_themed_prompts(value) == {"Learn": ["a", "b"], "Create": ["c"]}
-
-
-def test_json_to_themed_prompts_with_list_returns_general():
-    assert _json_to_themed_prompts(["a", "b"]) == {"General": ["a", "b"]}
-
-
-def test_json_to_themed_prompts_with_none_returns_empty():
-    assert _json_to_themed_prompts(None) == {}
-
-
-# ─── format_understanding_for_prompt: excludes themed prompts ──────────
-
-
-def test_format_understanding_excludes_themed_prompts():
-    """Themed suggested_prompts are UI-only and must NOT appear in the system prompt."""
-    understanding = BusinessUnderstanding(
-        id="test-id",
-        user_id="user-1",
-        created_at=datetime.now(tz=timezone.utc),
-        updated_at=datetime.now(tz=timezone.utc),
-        user_name="Alice",
-        industry="Technology",
-        suggested_prompts={
-            "Learn": ["Automate reports"],
-            "Create": ["Set up alerts", "Track KPIs"],
-        },
-    )
-
-    formatted = format_understanding_for_prompt(understanding)
-
-    assert "Alice" in formatted
-    assert "Technology" in formatted
-    assert "suggested_prompts" not in formatted
-    assert "Automate reports" not in formatted
-    assert "Set up alerts" not in formatted
-    assert "Track KPIs" not in formatted

autogpt_platform/backend/backend/data/user.py

@@ -3,7 +3,7 @@ import hashlib
 import hmac
 import logging
 from datetime import datetime, timedelta
-from typing import TYPE_CHECKING, Optional, cast
+from typing import Optional, cast
 from urllib.parse import quote_plus
 
 from autogpt_libs.auth.models import DEFAULT_USER_ID
@@ -21,9 +21,6 @@ from backend.util.exceptions import DatabaseError
 from backend.util.json import SafeJson
 from backend.util.settings import Settings
 
-if TYPE_CHECKING:
-    from backend.integrations.credentials_store import IntegrationCredentialsStore
-
 logger = logging.getLogger(__name__)
 settings = Settings()
 
@@ -456,27 +453,6 @@ async def unsubscribe_user_by_token(token: str) -> None:
         raise DatabaseError(f"Failed to unsubscribe user by token {token}: {e}") from e
 
 
-async def cleanup_user_managed_credentials(
-    user_id: str,
-    store: Optional["IntegrationCredentialsStore"] = None,
-) -> None:
-    """Revoke all externally-provisioned managed credentials for *user_id*.
-
-    Call this before deleting a user account so that external resources
-    (e.g. AgentMail pods, pod-scoped API keys) are properly cleaned up.
-    The credential rows themselves are cascade-deleted with the User row.
-
-    Pass an existing *store* for testability; when omitted a fresh instance
-    is created.
-    """
-    from backend.integrations.credentials_store import IntegrationCredentialsStore
-    from backend.integrations.managed_credentials import cleanup_managed_credentials
-
-    if store is None:
-        store = IntegrationCredentialsStore()
-    await cleanup_managed_credentials(user_id, store)
-
-
 async def update_user_timezone(user_id: str, timezone: str) -> User:
     """Update a user's timezone setting."""
     try:

autogpt_platform/backend/backend/data/workspace.py

@@ -76,24 +76,20 @@ async def get_or_create_workspace(user_id: str) -> Workspace:
     """
     Get user's workspace, creating one if it doesn't exist.
 
-    Uses upsert to atomically handle concurrent creation attempts.
-
     Args:
         user_id: The user's ID
 
     Returns:
         Workspace instance
     """
+    workspace = await UserWorkspace.prisma().find_unique(where={"userId": user_id})
+    if workspace:
+        return Workspace.from_db(workspace)
+
     try:
-        workspace = await UserWorkspace.prisma().upsert(
-            where={"userId": user_id},
-            data={
-                "create": {"userId": user_id},
-                "update": {},  # No-op update; workspace already exists
-            },
-        )
+        workspace = await UserWorkspace.prisma().create(data={"userId": user_id})
     except UniqueViolationError:
-        # Defense-in-depth: should not happen with upsert, but handle gracefully
+        # Concurrent request already created it
         workspace = await UserWorkspace.prisma().find_unique(where={"userId": user_id})
         if workspace is None:
             raise
@@ -129,13 +125,6 @@ async def create_workspace_file(
     """
     Create a new workspace file record.
 
-    Raises ``UniqueViolationError`` if a record with the same
-    ``(workspaceId, path)`` already exists.  The caller
-    (``WorkspaceManager._persist_db_record``) relies on this to trigger
-    its delete-old-file-then-retry flow, which cleans up the old storage
-    blob before re-creating the DB record.  Using ``upsert`` here would
-    silently overwrite ``storagePath`` and orphan the old blob in storage.
-
     Args:
         workspace_id: The workspace ID
         file_id: The file ID (same as used in storage path for consistency)

autogpt_platform/backend/backend/integrations/credentials_store.py

@@ -1,6 +1,5 @@
 import base64
 import hashlib
-import logging
 import secrets
 from contextlib import asynccontextmanager
 from datetime import datetime, timedelta, timezone
@@ -22,7 +21,6 @@ from backend.data.redis_client import get_redis_async
 from backend.util.settings import Settings
 
 settings = Settings()
-logger = logging.getLogger(__name__)
 
 
 def provider_matches(stored: str, expected: str) -> bool:
@@ -286,7 +284,6 @@ DEFAULT_CREDENTIALS = [
     elevenlabs_credentials,
 ]
 
-
 SYSTEM_CREDENTIAL_IDS = {cred.id for cred in DEFAULT_CREDENTIALS}
 
 # Set of providers that have system credentials available
@@ -326,45 +323,20 @@ class IntegrationCredentialsStore:
             return get_database_manager_async_client()
 
     # =============== USER-MANAGED CREDENTIALS =============== #
-
-    async def _get_persisted_user_creds_unlocked(
-        self, user_id: str
-    ) -> list[Credentials]:
-        """Return only the persisted (user-stored) credentials — no side effects.
-
-        **Caller must already hold ``locked_user_integrations(user_id)``.**
-        """
-        return list((await self._get_user_integrations(user_id)).credentials)
-
     async def add_creds(self, user_id: str, credentials: Credentials) -> None:
         async with await self.locked_user_integrations(user_id):
-            # Check system/managed IDs without triggering provisioning
-            if credentials.id in SYSTEM_CREDENTIAL_IDS:
+            if await self.get_creds_by_id(user_id, credentials.id):
                 raise ValueError(
                     f"Can not re-create existing credentials #{credentials.id} "
                     f"for user #{user_id}"
                 )
-            persisted = await self._get_persisted_user_creds_unlocked(user_id)
-            if any(c.id == credentials.id for c in persisted):
-                raise ValueError(
-                    f"Can not re-create existing credentials #{credentials.id} "
-                    f"for user #{user_id}"
-                )
-            await self._set_user_integration_creds(user_id, [*persisted, credentials])
+            await self._set_user_integration_creds(
+                user_id, [*(await self.get_all_creds(user_id)), credentials]
+            )
 
     async def get_all_creds(self, user_id: str) -> list[Credentials]:
-        """Public entry point — acquires lock, then delegates."""
-        async with await self.locked_user_integrations(user_id):
-            return await self._get_all_creds_unlocked(user_id)
-
-    async def _get_all_creds_unlocked(self, user_id: str) -> list[Credentials]:
-        """Return all credentials for *user_id*.
-
-        **Caller must already hold ``locked_user_integrations(user_id)``.**
-        """
-        user_integrations = await self._get_user_integrations(user_id)
-        all_credentials = list(user_integrations.credentials)
-
+        users_credentials = (await self._get_user_integrations(user_id)).credentials
+        all_credentials = users_credentials
         # These will always be added
         all_credentials.append(ollama_credentials)
 
@@ -445,22 +417,13 @@ class IntegrationCredentialsStore:
         return list(set(c.provider for c in credentials))
 
     async def update_creds(self, user_id: str, updated: Credentials) -> None:
-        if updated.id in SYSTEM_CREDENTIAL_IDS:
-            raise ValueError(
-                f"System credential #{updated.id} cannot be updated directly"
-            )
         async with await self.locked_user_integrations(user_id):
-            persisted = await self._get_persisted_user_creds_unlocked(user_id)
-            current = next((c for c in persisted if c.id == updated.id), None)
+            current = await self.get_creds_by_id(user_id, updated.id)
             if not current:
                 raise ValueError(
                     f"Credentials with ID {updated.id} "
                     f"for user with ID {user_id} not found"
                 )
-            if current.is_managed:
-                raise ValueError(
-                    f"AutoGPT-managed credential #{updated.id} cannot be updated"
-                )
             if type(current) is not type(updated):
                 raise TypeError(
                     f"Can not update credentials with ID {updated.id} "
@@ -480,53 +443,22 @@ class IntegrationCredentialsStore:
                     f"to more restrictive set of scopes {updated.scopes}"
                 )
 
-            # Update only persisted credentials — no side-effectful provisioning
+            # Update the credentials
             updated_credentials_list = [
-                updated if c.id == updated.id else c for c in persisted
+                updated if c.id == updated.id else c
+                for c in await self.get_all_creds(user_id)
             ]
             await self._set_user_integration_creds(user_id, updated_credentials_list)
 
     async def delete_creds_by_id(self, user_id: str, credentials_id: str) -> None:
-        if credentials_id in SYSTEM_CREDENTIAL_IDS:
-            raise ValueError(f"System credential #{credentials_id} cannot be deleted")
         async with await self.locked_user_integrations(user_id):
-            persisted = await self._get_persisted_user_creds_unlocked(user_id)
-            target = next((c for c in persisted if c.id == credentials_id), None)
-            if target and target.is_managed:
-                raise ValueError(
-                    f"AutoGPT-managed credential #{credentials_id} cannot be deleted"
-                )
-            filtered_credentials = [c for c in persisted if c.id != credentials_id]
+            filtered_credentials = [
+                c for c in await self.get_all_creds(user_id) if c.id != credentials_id
+            ]
             await self._set_user_integration_creds(user_id, filtered_credentials)
 
     # ============== SYSTEM-MANAGED CREDENTIALS ============== #
 
-    async def has_managed_credential(self, user_id: str, provider: str) -> bool:
-        """Check if a managed credential exists for *provider*."""
-        user_integrations = await self._get_user_integrations(user_id)
-        return any(
-            c.provider == provider and c.is_managed
-            for c in user_integrations.credentials
-        )
-
-    async def add_managed_credential(
-        self, user_id: str, credential: Credentials
-    ) -> None:
-        """Upsert a managed credential.
-
-        Removes any existing managed credential for the same provider,
-        then appends the new one. The credential MUST have is_managed=True.
-        """
-        if not credential.is_managed:
-            raise ValueError("credential.is_managed must be True")
-        async with self.edit_user_integrations(user_id) as user_integrations:
-            user_integrations.credentials = [
-                c
-                for c in user_integrations.credentials
-                if not (c.provider == credential.provider and c.is_managed)
-            ]
-            user_integrations.credentials.append(credential)
-
     async def set_ayrshare_profile_key(self, user_id: str, profile_key: str) -> None:
         """Set the Ayrshare profile key for a user.
 

autogpt_platform/backend/backend/integrations/managed_credentials.py

@@ -1,188 +0,0 @@
-"""Generic infrastructure for system-provided, per-user managed credentials.
-
-Managed credentials are provisioned automatically by the platform (e.g. an
-AgentMail pod-scoped API key) and stored alongside regular user credentials
-with ``is_managed=True``.  Users cannot update or delete them.
-
-New integrations register a :class:`ManagedCredentialProvider` at import time;
-the two entry-points consumed by the rest of the application are:
-
-* :func:`ensure_managed_credentials` – fired as a background task from the
-  credential-listing endpoints (non-blocking).
-* :func:`cleanup_managed_credentials` – called during account deletion to
-  revoke external resources (API keys, pods, etc.).
-"""
-
-from __future__ import annotations
-
-import asyncio
-import logging
-from abc import ABC, abstractmethod
-from typing import TYPE_CHECKING
-
-from cachetools import TTLCache
-
-if TYPE_CHECKING:
-    from backend.data.model import Credentials
-    from backend.integrations.credentials_store import IntegrationCredentialsStore
-
-logger = logging.getLogger(__name__)
-
-# ---------------------------------------------------------------------------
-# Abstract provider
-# ---------------------------------------------------------------------------
-
-
-class ManagedCredentialProvider(ABC):
-    """Base class for integrations that auto-provision per-user credentials."""
-
-    provider_name: str
-    """Must match the ``provider`` field on the resulting credential."""
-
-    @abstractmethod
-    async def is_available(self) -> bool:
-        """Return ``True`` when the org-level configuration is present."""
-
-    @abstractmethod
-    async def provision(self, user_id: str) -> Credentials:
-        """Create external resources and return a credential.
-
-        The returned credential **must** have ``is_managed=True``.
-        """
-
-    @abstractmethod
-    async def deprovision(self, user_id: str, credential: Credentials) -> None:
-        """Revoke external resources during account deletion."""
-
-
-# ---------------------------------------------------------------------------
-# Registry
-# ---------------------------------------------------------------------------
-
-_PROVIDERS: dict[str, ManagedCredentialProvider] = {}
-
-# Users whose managed credentials have already been verified recently.
-# Avoids redundant DB checks on every GET /credentials call.
-# maxsize caps memory; TTL re-checks periodically (e.g. when new providers
-# are added).  ~100K entries ≈ 4-8 MB.
-_provisioned_users: TTLCache[str, bool] = TTLCache(maxsize=100_000, ttl=3600)
-
-
-def register_managed_provider(provider: ManagedCredentialProvider) -> None:
-    _PROVIDERS[provider.provider_name] = provider
-
-
-def get_managed_provider(name: str) -> ManagedCredentialProvider | None:
-    return _PROVIDERS.get(name)
-
-
-def get_managed_providers() -> dict[str, ManagedCredentialProvider]:
-    return dict(_PROVIDERS)
-
-
-# ---------------------------------------------------------------------------
-# Public helpers
-# ---------------------------------------------------------------------------
-
-
-async def _ensure_one(
-    user_id: str,
-    store: IntegrationCredentialsStore,
-    name: str,
-    provider: ManagedCredentialProvider,
-) -> bool:
-    """Provision a single managed credential under a distributed Redis lock.
-
-    Returns ``True`` if the credential already exists or was successfully
-    provisioned, ``False`` on transient failure so the caller knows not to
-    cache the user as fully provisioned.
-    """
-    try:
-        if not await provider.is_available():
-            return True
-        # Use a distributed Redis lock so the check-then-provision operation
-        # is atomic across all workers, preventing duplicate external
-        # resource provisioning (e.g. AgentMail API keys).
-        locks = await store.locks()
-        key = (f"user:{user_id}", f"managed-provision:{name}")
-        async with locks.locked(key):
-            # Re-check under lock to avoid duplicate provisioning.
-            if await store.has_managed_credential(user_id, name):
-                return True
-            credential = await provider.provision(user_id)
-            await store.add_managed_credential(user_id, credential)
-            logger.info(
-                "Provisioned managed credential for provider=%s user=%s",
-                name,
-                user_id,
-            )
-            return True
-    except Exception:
-        logger.warning(
-            "Failed to provision managed credential for provider=%s user=%s",
-            name,
-            user_id,
-            exc_info=True,
-        )
-        return False
-
-
-async def ensure_managed_credentials(
-    user_id: str,
-    store: IntegrationCredentialsStore,
-) -> None:
-    """Provision missing managed credentials for *user_id*.
-
-    Fired as a non-blocking background task from the credential-listing
-    endpoints.  Failures are logged but never propagated — the user simply
-    will not see the managed credential until the next page load.
-
-    Skips entirely if this user has already been checked during the current
-    process lifetime (in-memory cache).  Resets on restart — just a
-    performance optimisation, not a correctness guarantee.
-
-    Providers are checked concurrently via ``asyncio.gather``.
-    """
-    if user_id in _provisioned_users:
-        return
-
-    results = await asyncio.gather(
-        *(_ensure_one(user_id, store, n, p) for n, p in _PROVIDERS.items())
-    )
-
-    # Only cache the user as provisioned when every provider succeeded or
-    # was already present.  A transient failure (network timeout, Redis
-    # blip) returns False, so the next page load will retry.
-    if all(results):
-        _provisioned_users[user_id] = True
-
-
-async def cleanup_managed_credentials(
-    user_id: str,
-    store: IntegrationCredentialsStore,
-) -> None:
-    """Revoke all external managed resources for a user being deleted."""
-    all_creds = await store.get_all_creds(user_id)
-    managed = [c for c in all_creds if c.is_managed]
-    for cred in managed:
-        provider = _PROVIDERS.get(cred.provider)
-        if not provider:
-            logger.warning(
-                "No managed provider registered for %s — skipping cleanup",
-                cred.provider,
-            )
-            continue
-        try:
-            await provider.deprovision(user_id, cred)
-            logger.info(
-                "Deprovisioned managed credential for provider=%s user=%s",
-                cred.provider,
-                user_id,
-            )
-        except Exception:
-            logger.error(
-                "Failed to deprovision %s for user %s",
-                cred.provider,
-                user_id,
-                exc_info=True,
-            )

autogpt_platform/backend/backend/integrations/managed_providers/__init__.py

@@ -1,17 +0,0 @@
-"""Managed credential providers.
-
-Call :func:`register_all` at application startup (e.g. in ``rest_api.py``)
-to populate the provider registry before any requests are processed.
-"""
-
-from backend.integrations.managed_credentials import (
-    get_managed_provider,
-    register_managed_provider,
-)
-from backend.integrations.managed_providers.agentmail import AgentMailManagedProvider
-
-
-def register_all() -> None:
-    """Register every built-in managed credential provider (idempotent)."""
-    if get_managed_provider(AgentMailManagedProvider.provider_name) is None:
-        register_managed_provider(AgentMailManagedProvider())

autogpt_platform/backend/backend/integrations/managed_providers/agentmail.py

@@ -1,90 +0,0 @@
-"""AgentMail managed credential provider.
-
-Uses the org-level AgentMail API key to create a per-user pod and a
-pod-scoped API key.  The pod key is stored as an ``is_managed``
-credential so it appears automatically in block credential dropdowns.
-"""
-
-from __future__ import annotations
-
-import logging
-
-from pydantic import SecretStr
-
-from backend.data.model import APIKeyCredentials, Credentials
-from backend.integrations.managed_credentials import ManagedCredentialProvider
-from backend.util.settings import Settings
-
-logger = logging.getLogger(__name__)
-settings = Settings()
-
-
-class AgentMailManagedProvider(ManagedCredentialProvider):
-    provider_name = "agent_mail"
-
-    async def is_available(self) -> bool:
-        return bool(settings.secrets.agentmail_api_key)
-
-    async def provision(self, user_id: str) -> Credentials:
-        from agentmail import AsyncAgentMail
-
-        client = AsyncAgentMail(api_key=settings.secrets.agentmail_api_key)
-
-        # client_id makes pod creation idempotent — if a pod already exists
-        # for this user_id the SDK returns the existing pod.
-        pod = await client.pods.create(client_id=user_id, name=f"{user_id}-pod")
-
-        # NOTE: api_keys.create() is NOT idempotent.  If the caller retries
-        # after a partial failure (pod created, key created, but store write
-        # failed), a second key will be created and the first becomes orphaned
-        # on AgentMail's side.  The double-check pattern in _ensure_one
-        # (has_managed_credential under lock) prevents this in normal flow;
-        # only a crash between key creation and store write can cause it.
-        api_key_obj = await client.pods.api_keys.create(
-            pod_id=pod.pod_id, name=f"{user_id}-agpt-managed"
-        )
-
-        return APIKeyCredentials(
-            provider=self.provider_name,
-            title="AgentMail (managed by AutoGPT)",
-            api_key=SecretStr(api_key_obj.api_key),
-            expires_at=None,
-            is_managed=True,
-            metadata={"pod_id": pod.pod_id},
-        )
-
-    async def deprovision(self, user_id: str, credential: Credentials) -> None:
-        from agentmail import AsyncAgentMail
-
-        pod_id = credential.metadata.get("pod_id")
-        if not pod_id:
-            logger.warning(
-                "Managed credential for user %s has no pod_id in metadata — "
-                "skipping AgentMail cleanup",
-                user_id,
-            )
-            return
-
-        client = AsyncAgentMail(api_key=settings.secrets.agentmail_api_key)
-        try:
-            # Verify the pod actually belongs to this user before deleting,
-            # as a safety measure against cross-user deletion via the
-            # org-level API key.
-            pod = await client.pods.get(pod_id=pod_id)
-            if getattr(pod, "client_id", None) and pod.client_id != user_id:
-                logger.error(
-                    "Pod %s client_id=%s does not match user %s — "
-                    "refusing to delete",
-                    pod_id,
-                    pod.client_id,
-                    user_id,
-                )
-                return
-            await client.pods.delete(pod_id=pod_id)
-        except Exception:
-            logger.warning(
-                "Failed to delete AgentMail pod %s for user %s",
-                pod_id,
-                user_id,
-                exc_info=True,
-            )

autogpt_platform/backend/backend/util/feature_flag.py

@@ -39,8 +39,6 @@ class Flag(str, Enum):
     ENABLE_PLATFORM_PAYMENT = "enable-platform-payment"
     CHAT = "chat"
     COPILOT_SDK = "copilot-sdk"
-    COPILOT_DAILY_TOKEN_LIMIT = "copilot-daily-token-limit"
-    COPILOT_WEEKLY_TOKEN_LIMIT = "copilot-weekly-token-limit"
 
 
 def is_configured() -> bool:

autogpt_platform/backend/backend/util/metrics.py

@@ -84,14 +84,6 @@ def _before_send(event, hint):
         ):
             return None
 
-        # Prisma UniqueViolationError — always caught and handled in our codebase.
-        # These arise from concurrent create operations racing on unique constraints
-        # (workspace files, credits, library folders, store listings, chat messages).
-        # Every call site has an except handler; the global FastAPI handler also
-        # catches them and returns 400.  Safe to drop unconditionally.
-        if exc_type and exc_type.__name__ == "UniqueViolationError":
-            return None
-
         # Google metadata DNS errors — expected in non-GCP environments
         if (
             "metadata.google.internal" in exc_msg

autogpt_platform/backend/backend/util/security.py

@@ -1,20 +0,0 @@
-"""Shared security constants for field-level filtering.
-
-Other modules (e.g. orchestrator, future blocks) import from here so the
-sensitive-field list stays in one place.
-"""
-
-# Field names to exclude from hardcoded-defaults descriptions (case-insensitive).
-SENSITIVE_FIELD_NAMES: frozenset[str] = frozenset(
-    {
-        "credentials",
-        "api_key",
-        "password",
-        "secret",
-        "token",
-        "auth",
-        "authorization",
-        "access_token",
-        "refresh_token",
-    }
-)

autogpt_platform/backend/backend/util/service.py

@@ -227,16 +227,10 @@ class AppService(BaseAppService, ABC):
     def _handle_internal_http_error(status_code: int = 500, log_error: bool = True):
         def handler(request: Request, exc: Exception):
             if log_error:
-                if status_code >= 500:
-                    logger.error(
-                        f"{request.method} {request.url.path} failed: {exc}",
-                        exc_info=exc,
-                    )
-                else:
-                    logger.warning(
-                        f"{request.method} {request.url.path} failed: {exc}",
-                        exc_info=exc,
-                    )
+                logger.error(
+                    f"{request.method} {request.url.path} failed: {exc}",
+                    exc_info=exc if status_code == 500 else None,
+                )
             return responses.JSONResponse(
                 status_code=status_code,
                 content=RemoteCallError(
@@ -569,6 +563,7 @@ def get_service_client(
                 self._connection_failure_count >= 3
                 and current_time - self._last_client_reset > 30
             ):
+
                 logger.warning(
                     f"Connection failures detected ({self._connection_failure_count}), recreating HTTP clients"
                 )

autogpt_platform/backend/backend/util/settings.py

@@ -708,8 +708,6 @@ class Secrets(UpdateTrackingModel["Secrets"], BaseSettings):
         description="The LaunchDarkly SDK key for feature flag management",
     )
 
-    agentmail_api_key: str = Field(default="", description="AgentMail API Key")
-
     ayrshare_api_key: str = Field(default="", description="Ayrshare API Key")
     ayrshare_jwt_key: str = Field(default="", description="Ayrshare private Key")
 

autogpt_platform/backend/backend/util/tool_call_loop.py

@@ -1,281 +0,0 @@
-"""Shared tool-calling conversation loop.
-
-Provides a generic, provider-agnostic conversation loop that both
-the OrchestratorBlock and copilot baseline can use. The loop:
-
-1. Calls the LLM with tool definitions
-2. Extracts tool calls from the response
-3. Executes tools via a caller-supplied callback
-4. Appends results to the conversation
-5. Repeats until no more tool calls or max iterations reached
-
-Callers provide callbacks for LLM calling, tool execution, and
-conversation updating.
-"""
-
-from __future__ import annotations
-
-import asyncio
-import logging
-from collections.abc import AsyncGenerator, Sequence
-from dataclasses import dataclass, field
-from typing import Any, Protocol, TypedDict
-
-logger = logging.getLogger(__name__)
-
-
-# ---------------------------------------------------------------------------
-# Typed dict definitions for tool definitions and conversation messages.
-# These document the expected shapes and allow callers to pass TypedDict
-# subclasses (e.g. ``ChatCompletionToolParam``) without ``type: ignore``.
-# ---------------------------------------------------------------------------
-
-
-class FunctionParameters(TypedDict, total=False):
-    """JSON Schema object describing a tool function's parameters."""
-
-    type: str
-    properties: dict[str, Any]
-    required: list[str]
-    additionalProperties: bool
-
-
-class FunctionDefinition(TypedDict, total=False):
-    """Function definition within a tool definition."""
-
-    name: str
-    description: str
-    parameters: FunctionParameters
-
-
-class ToolDefinition(TypedDict):
-    """OpenAI-compatible tool definition (function-calling format).
-
-    Compatible with ``openai.types.chat.ChatCompletionToolParam`` and the
-    dict-based tool definitions built by ``OrchestratorBlock``.
-    """
-
-    type: str
-    function: FunctionDefinition
-
-
-class ConversationMessage(TypedDict, total=False):
-    """A single message in the conversation (OpenAI chat format).
-
-    Primarily for documentation; at runtime plain dicts are used because
-    messages from different providers carry varying keys.
-    """
-
-    role: str
-    content: str | list[Any] | None
-    tool_calls: list[dict[str, Any]]
-    tool_call_id: str
-    name: str
-
-
-@dataclass
-class ToolCallResult:
-    """Result of a single tool execution."""
-
-    tool_call_id: str
-    tool_name: str
-    content: str
-    is_error: bool = False
-
-
-@dataclass
-class LLMToolCall:
-    """A tool call extracted from an LLM response."""
-
-    id: str
-    name: str
-    arguments: str  # JSON string
-
-
-@dataclass
-class LLMLoopResponse:
-    """Response from a single LLM call in the loop.
-
-    ``raw_response`` is typed as ``Any`` intentionally: the loop itself
-    never inspects it — it is an opaque pass-through that the caller's
-    ``ConversationUpdater`` uses to rebuild provider-specific message
-    history (OpenAI ChatCompletion, Anthropic Message, Ollama str, etc.).
-    """
-
-    response_text: str | None
-    tool_calls: list[LLMToolCall]
-    raw_response: Any
-    prompt_tokens: int = 0
-    completion_tokens: int = 0
-    reasoning: str | None = None
-
-
-class LLMCaller(Protocol):
-    """Protocol for LLM call functions."""
-
-    async def __call__(
-        self,
-        messages: list[dict[str, Any]],
-        tools: Sequence[Any],
-    ) -> LLMLoopResponse: ...
-
-
-class ToolExecutor(Protocol):
-    """Protocol for tool execution functions."""
-
-    async def __call__(
-        self,
-        tool_call: LLMToolCall,
-        tools: Sequence[Any],
-    ) -> ToolCallResult: ...
-
-
-class ConversationUpdater(Protocol):
-    """Protocol for updating conversation history after an LLM response."""
-
-    def __call__(
-        self,
-        messages: list[dict[str, Any]],
-        response: LLMLoopResponse,
-        tool_results: list[ToolCallResult] | None = None,
-    ) -> None: ...
-
-
-@dataclass
-class ToolCallLoopResult:
-    """Final result of the tool-calling loop."""
-
-    response_text: str
-    messages: list[dict[str, Any]]
-    total_prompt_tokens: int = 0
-    total_completion_tokens: int = 0
-    iterations: int = 0
-    finished_naturally: bool = True  # False if hit max iterations
-    last_tool_calls: list[LLMToolCall] = field(default_factory=list)
-
-
-async def tool_call_loop(
-    *,
-    messages: list[dict[str, Any]],
-    tools: Sequence[Any],
-    llm_call: LLMCaller,
-    execute_tool: ToolExecutor,
-    update_conversation: ConversationUpdater,
-    max_iterations: int = -1,
-    last_iteration_message: str | None = None,
-    parallel_tool_calls: bool = True,
-) -> AsyncGenerator[ToolCallLoopResult, None]:
-    """Run a tool-calling conversation loop as an async generator.
-
-    Yields a ``ToolCallLoopResult`` after each iteration so callers can
-    drain buffered events (e.g. streaming text deltas) between iterations.
-    The **final** yielded result has ``finished_naturally`` set and contains
-    the complete response text.
-
-    Args:
-        messages: Initial conversation messages (modified in-place).
-        tools: Tool function definitions (OpenAI format).  Accepts any
-            sequence of tool dicts, including ``ChatCompletionToolParam``.
-        llm_call: Async function to call the LLM. The callback can
-            perform streaming internally (e.g. accumulate text deltas
-            and collect events) — it just needs to return the final
-            ``LLMLoopResponse`` with extracted tool calls.
-        execute_tool: Async function to execute a tool call.
-        update_conversation: Function to update messages with LLM
-            response and tool results.
-        max_iterations: Max iterations. -1 = infinite, 0 = no loop
-            (immediately yields a "max reached" result).
-        last_iteration_message: Optional message to append on the last
-            iteration to encourage the model to finish.
-        parallel_tool_calls: If True (default), execute multiple tool
-            calls from a single LLM response concurrently via
-            ``asyncio.gather``.  Set to False when tool calls may have
-            ordering dependencies or mutate shared state.
-
-    Yields:
-        ToolCallLoopResult after each iteration. Check ``finished_naturally``
-        to determine if the loop completed or is still running.
-    """
-    total_prompt_tokens = 0
-    total_completion_tokens = 0
-    iteration = 0
-
-    while max_iterations < 0 or iteration < max_iterations:
-        iteration += 1
-
-        # On last iteration, add a hint to finish.  Only copy the list
-        # when the hint needs to be appended to avoid per-iteration overhead
-        # on long conversations.
-        is_last = (
-            last_iteration_message
-            and max_iterations > 0
-            and iteration == max_iterations
-        )
-        if is_last:
-            iteration_messages = list(messages)
-            iteration_messages.append(
-                {"role": "system", "content": last_iteration_message}
-            )
-        else:
-            iteration_messages = messages
-
-        # Call LLM
-        response = await llm_call(iteration_messages, tools)
-        total_prompt_tokens += response.prompt_tokens
-        total_completion_tokens += response.completion_tokens
-
-        # No tool calls = done
-        if not response.tool_calls:
-            update_conversation(messages, response)
-            yield ToolCallLoopResult(
-                response_text=response.response_text or "",
-                messages=messages,
-                total_prompt_tokens=total_prompt_tokens,
-                total_completion_tokens=total_completion_tokens,
-                iterations=iteration,
-                finished_naturally=True,
-            )
-            return
-
-        # Execute tools — parallel or sequential depending on caller preference.
-        # NOTE: asyncio.gather does not cancel sibling tasks when one raises.
-        # Callers should handle errors inside execute_tool (return error
-        # ToolCallResult) rather than letting exceptions propagate.
-        if parallel_tool_calls and len(response.tool_calls) > 1:
-            # Parallel: side-effects from different tool executors (e.g.
-            # streaming events appended to a shared list) may interleave
-            # nondeterministically.  Each event carries its own tool-call
-            # identifier, so consumers must correlate by ID.
-            tool_results: list[ToolCallResult] = list(
-                await asyncio.gather(
-                    *(execute_tool(tc, tools) for tc in response.tool_calls)
-                )
-            )
-        else:
-            # Sequential: preserves ordering guarantees for callers that
-            # need deterministic execution order.
-            tool_results = [await execute_tool(tc, tools) for tc in response.tool_calls]
-
-        # Update conversation with response + tool results
-        update_conversation(messages, response, tool_results)
-
-        # Yield a fresh result so callers can drain buffered events
-        yield ToolCallLoopResult(
-            response_text="",
-            messages=messages,
-            total_prompt_tokens=total_prompt_tokens,
-            total_completion_tokens=total_completion_tokens,
-            iterations=iteration,
-            finished_naturally=False,
-            last_tool_calls=list(response.tool_calls),
-        )
-
-    # Hit max iterations
-    yield ToolCallLoopResult(
-        response_text=f"Completed after {max_iterations} iterations (limit reached)",
-        messages=messages,
-        total_prompt_tokens=total_prompt_tokens,
-        total_completion_tokens=total_completion_tokens,
-        iterations=iteration,
-        finished_naturally=False,
-    )

autogpt_platform/backend/backend/util/tool_call_loop_test.py

@@ -1,554 +0,0 @@
-"""Unit tests for tool_call_loop shared abstraction.
-
-Covers:
-- Happy path with tool calls (single and multi-round)
-- Final text response (no tool calls)
-- Max iterations reached
-- No tools scenario
-- Exception propagation from tool executor
-- Parallel tool execution
-"""
-
-from __future__ import annotations
-
-import asyncio
-from collections.abc import Sequence
-from typing import Any
-
-import pytest
-
-from backend.util.tool_call_loop import (
-    LLMLoopResponse,
-    LLMToolCall,
-    ToolCallLoopResult,
-    ToolCallResult,
-    tool_call_loop,
-)
-
-# ---------------------------------------------------------------------------
-# Helpers
-# ---------------------------------------------------------------------------
-
-TOOL_DEFS: list[dict[str, Any]] = [
-    {
-        "type": "function",
-        "function": {
-            "name": "get_weather",
-            "description": "Get weather for a city",
-            "parameters": {
-                "type": "object",
-                "properties": {"city": {"type": "string"}},
-                "required": ["city"],
-            },
-        },
-    }
-]
-
-
-def _make_response(
-    text: str | None = None,
-    tool_calls: list[LLMToolCall] | None = None,
-    prompt_tokens: int = 10,
-    completion_tokens: int = 5,
-) -> LLMLoopResponse:
-    return LLMLoopResponse(
-        response_text=text,
-        tool_calls=tool_calls or [],
-        raw_response={"mock": True},
-        prompt_tokens=prompt_tokens,
-        completion_tokens=completion_tokens,
-    )
-
-
-# ---------------------------------------------------------------------------
-# Tests
-# ---------------------------------------------------------------------------
-
-
-@pytest.mark.asyncio
-async def test_text_response_no_tool_calls():
-    """LLM responds with text only -- loop should yield once and finish."""
-
-    async def llm_call(
-        messages: list[dict[str, Any]], tools: Sequence[Any]
-    ) -> LLMLoopResponse:
-        return _make_response(text="Hello world")
-
-    async def execute_tool(
-        tool_call: LLMToolCall, tools: Sequence[Any]
-    ) -> ToolCallResult:
-        raise AssertionError("Should not be called")
-
-    def update_conversation(
-        messages: list[dict[str, Any]],
-        response: LLMLoopResponse,
-        tool_results: list[ToolCallResult] | None = None,
-    ) -> None:
-        messages.append({"role": "assistant", "content": response.response_text})
-
-    msgs: list[dict[str, Any]] = [{"role": "user", "content": "Hi"}]
-    results: list[ToolCallLoopResult] = []
-    async for r in tool_call_loop(
-        messages=msgs,
-        tools=TOOL_DEFS,
-        llm_call=llm_call,
-        execute_tool=execute_tool,
-        update_conversation=update_conversation,
-    ):
-        results.append(r)
-
-    assert len(results) == 1
-    assert results[0].finished_naturally is True
-    assert results[0].response_text == "Hello world"
-    assert results[0].iterations == 1
-    assert results[0].total_prompt_tokens == 10
-    assert results[0].total_completion_tokens == 5
-
-
-@pytest.mark.asyncio
-async def test_single_tool_call_then_text():
-    """LLM makes one tool call, then responds with text on second round."""
-    call_count = 0
-
-    async def llm_call(
-        messages: list[dict[str, Any]], tools: Sequence[Any]
-    ) -> LLMLoopResponse:
-        nonlocal call_count
-        call_count += 1
-        if call_count == 1:
-            return _make_response(
-                tool_calls=[
-                    LLMToolCall(
-                        id="tc_1", name="get_weather", arguments='{"city":"NYC"}'
-                    )
-                ]
-            )
-        return _make_response(text="It's sunny in NYC")
-
-    async def execute_tool(
-        tool_call: LLMToolCall, tools: Sequence[Any]
-    ) -> ToolCallResult:
-        return ToolCallResult(
-            tool_call_id=tool_call.id,
-            tool_name=tool_call.name,
-            content='{"temp": 72}',
-        )
-
-    def update_conversation(
-        messages: list[dict[str, Any]],
-        response: LLMLoopResponse,
-        tool_results: list[ToolCallResult] | None = None,
-    ) -> None:
-        messages.append({"role": "assistant", "content": response.response_text})
-        if tool_results:
-            for tr in tool_results:
-                messages.append(
-                    {
-                        "role": "tool",
-                        "tool_call_id": tr.tool_call_id,
-                        "content": tr.content,
-                    }
-                )
-
-    msgs: list[dict[str, Any]] = [{"role": "user", "content": "Weather?"}]
-    results: list[ToolCallLoopResult] = []
-    async for r in tool_call_loop(
-        messages=msgs,
-        tools=TOOL_DEFS,
-        llm_call=llm_call,
-        execute_tool=execute_tool,
-        update_conversation=update_conversation,
-    ):
-        results.append(r)
-
-    # First yield: tool call iteration (not finished)
-    # Second yield: text response (finished)
-    assert len(results) == 2
-    assert results[0].finished_naturally is False
-    assert results[0].iterations == 1
-    assert len(results[0].last_tool_calls) == 1
-    assert results[1].finished_naturally is True
-    assert results[1].response_text == "It's sunny in NYC"
-    assert results[1].iterations == 2
-    assert results[1].total_prompt_tokens == 20
-    assert results[1].total_completion_tokens == 10
-
-
-@pytest.mark.asyncio
-async def test_max_iterations_reached():
-    """Loop should stop after max_iterations even if LLM keeps calling tools."""
-
-    async def llm_call(
-        messages: list[dict[str, Any]], tools: Sequence[Any]
-    ) -> LLMLoopResponse:
-        return _make_response(
-            tool_calls=[
-                LLMToolCall(id="tc_x", name="get_weather", arguments='{"city":"X"}')
-            ]
-        )
-
-    async def execute_tool(
-        tool_call: LLMToolCall, tools: Sequence[Any]
-    ) -> ToolCallResult:
-        return ToolCallResult(
-            tool_call_id=tool_call.id, tool_name=tool_call.name, content="result"
-        )
-
-    def update_conversation(
-        messages: list[dict[str, Any]],
-        response: LLMLoopResponse,
-        tool_results: list[ToolCallResult] | None = None,
-    ) -> None:
-        pass
-
-    msgs: list[dict[str, Any]] = [{"role": "user", "content": "Go"}]
-    results: list[ToolCallLoopResult] = []
-    async for r in tool_call_loop(
-        messages=msgs,
-        tools=TOOL_DEFS,
-        llm_call=llm_call,
-        execute_tool=execute_tool,
-        update_conversation=update_conversation,
-        max_iterations=3,
-    ):
-        results.append(r)
-
-    # 3 tool-call iterations + 1 final "max reached"
-    assert len(results) == 4
-    for r in results[:3]:
-        assert r.finished_naturally is False
-    final = results[-1]
-    assert final.finished_naturally is False
-    assert "3 iterations" in final.response_text
-    assert final.iterations == 3
-
-
-@pytest.mark.asyncio
-async def test_no_tools_first_response_text():
-    """When LLM immediately responds with text (empty tools list), finishes."""
-
-    async def llm_call(
-        messages: list[dict[str, Any]], tools: Sequence[Any]
-    ) -> LLMLoopResponse:
-        return _make_response(text="No tools needed")
-
-    async def execute_tool(
-        tool_call: LLMToolCall, tools: Sequence[Any]
-    ) -> ToolCallResult:
-        raise AssertionError("Should not be called")
-
-    def update_conversation(
-        messages: list[dict[str, Any]],
-        response: LLMLoopResponse,
-        tool_results: list[ToolCallResult] | None = None,
-    ) -> None:
-        pass
-
-    msgs: list[dict[str, Any]] = [{"role": "user", "content": "Hi"}]
-    results: list[ToolCallLoopResult] = []
-    async for r in tool_call_loop(
-        messages=msgs,
-        tools=[],
-        llm_call=llm_call,
-        execute_tool=execute_tool,
-        update_conversation=update_conversation,
-    ):
-        results.append(r)
-
-    assert len(results) == 1
-    assert results[0].finished_naturally is True
-    assert results[0].response_text == "No tools needed"
-
-
-@pytest.mark.asyncio
-async def test_tool_executor_exception_propagates():
-    """Exception in execute_tool should propagate out of the loop."""
-
-    async def llm_call(
-        messages: list[dict[str, Any]], tools: Sequence[Any]
-    ) -> LLMLoopResponse:
-        return _make_response(
-            tool_calls=[LLMToolCall(id="tc_err", name="get_weather", arguments="{}")]
-        )
-
-    async def execute_tool(
-        tool_call: LLMToolCall, tools: Sequence[Any]
-    ) -> ToolCallResult:
-        raise RuntimeError("Tool execution failed!")
-
-    def update_conversation(
-        messages: list[dict[str, Any]],
-        response: LLMLoopResponse,
-        tool_results: list[ToolCallResult] | None = None,
-    ) -> None:
-        pass
-
-    msgs: list[dict[str, Any]] = [{"role": "user", "content": "Go"}]
-    with pytest.raises(RuntimeError, match="Tool execution failed!"):
-        async for _ in tool_call_loop(
-            messages=msgs,
-            tools=TOOL_DEFS,
-            llm_call=llm_call,
-            execute_tool=execute_tool,
-            update_conversation=update_conversation,
-        ):
-            pass
-
-
-@pytest.mark.asyncio
-async def test_parallel_tool_execution():
-    """Multiple tool calls in one response should execute concurrently."""
-    execution_order: list[str] = []
-
-    async def llm_call(
-        messages: list[dict[str, Any]], tools: Sequence[Any]
-    ) -> LLMLoopResponse:
-        if len(messages) == 1:
-            return _make_response(
-                tool_calls=[
-                    LLMToolCall(id="tc_a", name="tool_a", arguments="{}"),
-                    LLMToolCall(id="tc_b", name="tool_b", arguments="{}"),
-                ]
-            )
-        return _make_response(text="Done")
-
-    async def execute_tool(
-        tool_call: LLMToolCall, tools: Sequence[Any]
-    ) -> ToolCallResult:
-        # tool_b starts instantly, tool_a has a small delay.
-        # With parallel execution, both should overlap.
-        if tool_call.name == "tool_a":
-            await asyncio.sleep(0.05)
-        execution_order.append(tool_call.name)
-        return ToolCallResult(
-            tool_call_id=tool_call.id, tool_name=tool_call.name, content="ok"
-        )
-
-    def update_conversation(
-        messages: list[dict[str, Any]],
-        response: LLMLoopResponse,
-        tool_results: list[ToolCallResult] | None = None,
-    ) -> None:
-        messages.append({"role": "assistant", "content": "called tools"})
-        if tool_results:
-            for tr in tool_results:
-                messages.append(
-                    {
-                        "role": "tool",
-                        "tool_call_id": tr.tool_call_id,
-                        "content": tr.content,
-                    }
-                )
-
-    msgs: list[dict[str, Any]] = [{"role": "user", "content": "Run both"}]
-    async for _ in tool_call_loop(
-        messages=msgs,
-        tools=TOOL_DEFS,
-        llm_call=llm_call,
-        execute_tool=execute_tool,
-        update_conversation=update_conversation,
-    ):
-        pass
-
-    # With parallel execution, tool_b (no delay) finishes before tool_a
-    assert execution_order == ["tool_b", "tool_a"]
-
-
-@pytest.mark.asyncio
-async def test_sequential_tool_execution():
-    """With parallel_tool_calls=False, tools execute in order regardless of speed."""
-    execution_order: list[str] = []
-
-    async def llm_call(
-        messages: list[dict[str, Any]], tools: Sequence[Any]
-    ) -> LLMLoopResponse:
-        if len(messages) == 1:
-            return _make_response(
-                tool_calls=[
-                    LLMToolCall(id="tc_a", name="tool_a", arguments="{}"),
-                    LLMToolCall(id="tc_b", name="tool_b", arguments="{}"),
-                ]
-            )
-        return _make_response(text="Done")
-
-    async def execute_tool(
-        tool_call: LLMToolCall, tools: Sequence[Any]
-    ) -> ToolCallResult:
-        # tool_b would finish first if parallel, but sequential should keep order
-        if tool_call.name == "tool_a":
-            await asyncio.sleep(0.05)
-        execution_order.append(tool_call.name)
-        return ToolCallResult(
-            tool_call_id=tool_call.id, tool_name=tool_call.name, content="ok"
-        )
-
-    def update_conversation(
-        messages: list[dict[str, Any]],
-        response: LLMLoopResponse,
-        tool_results: list[ToolCallResult] | None = None,
-    ) -> None:
-        messages.append({"role": "assistant", "content": "called tools"})
-        if tool_results:
-            for tr in tool_results:
-                messages.append(
-                    {
-                        "role": "tool",
-                        "tool_call_id": tr.tool_call_id,
-                        "content": tr.content,
-                    }
-                )
-
-    msgs: list[dict[str, Any]] = [{"role": "user", "content": "Run both"}]
-    async for _ in tool_call_loop(
-        messages=msgs,
-        tools=TOOL_DEFS,
-        llm_call=llm_call,
-        execute_tool=execute_tool,
-        update_conversation=update_conversation,
-        parallel_tool_calls=False,
-    ):
-        pass
-
-    # With sequential execution, tool_a runs first despite being slower
-    assert execution_order == ["tool_a", "tool_b"]
-
-
-@pytest.mark.asyncio
-async def test_last_iteration_message_appended():
-    """On the final iteration, last_iteration_message should be appended."""
-    captured_messages: list[list[dict[str, Any]]] = []
-
-    async def llm_call(
-        messages: list[dict[str, Any]], tools: Sequence[Any]
-    ) -> LLMLoopResponse:
-        captured_messages.append(list(messages))
-        return _make_response(
-            tool_calls=[LLMToolCall(id="tc_1", name="get_weather", arguments="{}")]
-        )
-
-    async def execute_tool(
-        tool_call: LLMToolCall, tools: Sequence[Any]
-    ) -> ToolCallResult:
-        return ToolCallResult(
-            tool_call_id=tool_call.id, tool_name=tool_call.name, content="ok"
-        )
-
-    def update_conversation(
-        messages: list[dict[str, Any]],
-        response: LLMLoopResponse,
-        tool_results: list[ToolCallResult] | None = None,
-    ) -> None:
-        pass
-
-    msgs: list[dict[str, Any]] = [{"role": "user", "content": "Go"}]
-    async for _ in tool_call_loop(
-        messages=msgs,
-        tools=TOOL_DEFS,
-        llm_call=llm_call,
-        execute_tool=execute_tool,
-        update_conversation=update_conversation,
-        max_iterations=2,
-        last_iteration_message="Please finish now.",
-    ):
-        pass
-
-    # First iteration: no extra message
-    assert len(captured_messages[0]) == 1
-    # Second (last) iteration: should have the hint appended
-    last_call_msgs = captured_messages[1]
-    assert any(
-        m.get("role") == "system" and "Please finish now." in m.get("content", "")
-        for m in last_call_msgs
-    )
-
-
-@pytest.mark.asyncio
-async def test_token_accumulation():
-    """Tokens should accumulate across iterations."""
-    call_count = 0
-
-    async def llm_call(
-        messages: list[dict[str, Any]], tools: Sequence[Any]
-    ) -> LLMLoopResponse:
-        nonlocal call_count
-        call_count += 1
-        if call_count <= 2:
-            return _make_response(
-                tool_calls=[
-                    LLMToolCall(
-                        id=f"tc_{call_count}", name="get_weather", arguments="{}"
-                    )
-                ],
-                prompt_tokens=100,
-                completion_tokens=50,
-            )
-        return _make_response(text="Final", prompt_tokens=100, completion_tokens=50)
-
-    async def execute_tool(
-        tool_call: LLMToolCall, tools: Sequence[Any]
-    ) -> ToolCallResult:
-        return ToolCallResult(
-            tool_call_id=tool_call.id, tool_name=tool_call.name, content="ok"
-        )
-
-    def update_conversation(
-        messages: list[dict[str, Any]],
-        response: LLMLoopResponse,
-        tool_results: list[ToolCallResult] | None = None,
-    ) -> None:
-        pass
-
-    msgs: list[dict[str, Any]] = [{"role": "user", "content": "Go"}]
-    final_result = None
-    async for r in tool_call_loop(
-        messages=msgs,
-        tools=TOOL_DEFS,
-        llm_call=llm_call,
-        execute_tool=execute_tool,
-        update_conversation=update_conversation,
-    ):
-        final_result = r
-
-    assert final_result is not None
-    assert final_result.total_prompt_tokens == 300  # 3 calls * 100
-    assert final_result.total_completion_tokens == 150  # 3 calls * 50
-    assert final_result.iterations == 3
-
-
-@pytest.mark.asyncio
-async def test_max_iterations_zero_no_loop():
-    """max_iterations=0 should immediately yield a 'max reached' result without calling LLM."""
-
-    async def llm_call(
-        messages: list[dict[str, Any]], tools: Sequence[Any]
-    ) -> LLMLoopResponse:
-        raise AssertionError("LLM should not be called when max_iterations=0")
-
-    async def execute_tool(
-        tool_call: LLMToolCall, tools: Sequence[Any]
-    ) -> ToolCallResult:
-        raise AssertionError("Tool should not be called when max_iterations=0")
-
-    def update_conversation(
-        messages: list[dict[str, Any]],
-        response: LLMLoopResponse,
-        tool_results: list[ToolCallResult] | None = None,
-    ) -> None:
-        raise AssertionError("Updater should not be called when max_iterations=0")
-
-    msgs: list[dict[str, Any]] = [{"role": "user", "content": "Go"}]
-    results: list[ToolCallLoopResult] = []
-    async for r in tool_call_loop(
-        messages=msgs,
-        tools=TOOL_DEFS,
-        llm_call=llm_call,
-        execute_tool=execute_tool,
-        update_conversation=update_conversation,
-        max_iterations=0,
-    ):
-        results.append(r)
-
-    assert len(results) == 1
-    assert results[0].finished_naturally is False
-    assert results[0].iterations == 0
-    assert "0 iterations" in results[0].response_text

autogpt_platform/backend/backend/util/virus_scanner.py

@@ -108,9 +108,6 @@ class VirusScannerService:
             return VirusScanResult(
                 is_clean=True, scan_time_ms=0, file_size=len(content)
             )
-        if len(content) == 0:
-            logger.debug(f"Skipping virus scan for empty file {filename}")
-            return VirusScanResult(is_clean=True, scan_time_ms=0, file_size=0)
         if len(content) > self.settings.max_scan_size:
             logger.warning(
                 f"File {filename} ({len(content)} bytes) exceeds client max scan size ({self.settings.max_scan_size}); Stopping virus scan"
@@ -126,7 +123,7 @@ class VirusScannerService:
             raise RuntimeError("ClamAV service is unreachable")
 
         start = time.monotonic()
-        chunk_size = max(1, len(content))  # Start with full content length
+        chunk_size = len(content)  # Start with full content length
         for retry in range(self.settings.max_retries):
             # For small files, don't check min_chunk_size limit
             if chunk_size < self.settings.min_chunk_size and chunk_size < len(content):
@@ -215,5 +212,5 @@ async def scan_content_safe(content: bytes, *, filename: str = "unknown") -> Non
     except VirusDetectedError:
         raise
     except Exception as e:
-        logger.warning(f"Virus scanning failed for {filename}: {str(e)}")
+        logger.error(f"Virus scanning failed for {filename}: {str(e)}")
         raise VirusScanError(f"Virus scanning failed: {str(e)}") from e

autogpt_platform/backend/backend/util/virus_scanner_test.py

@@ -85,36 +85,7 @@ class TestVirusScannerService:
         )
         assert result_dirty.is_clean is False
 
-    @pytest.mark.asyncio
-    async def test_scan_empty_file(self, scanner):
-        """Empty files (0 bytes) should be accepted without hitting ClamAV."""
-        content = b""
-        result = await scanner.scan_file(content, filename="empty.png")
-
-        assert result.is_clean is True
-        assert result.threat_name is None
-        assert result.file_size == 0
-        assert result.scan_time_ms == 0
-
-    @pytest.mark.asyncio
-    async def test_scan_single_byte_file(self, scanner):
-        """A 1-byte file should be scanned normally (regression: chunk_size must not be 0)."""
-
-        async def mock_instream(_):
-            await asyncio.sleep(0.001)
-            return None
-
-        mock_client = Mock()
-        mock_client.ping = AsyncMock(return_value=True)
-        mock_client.instream = AsyncMock(side_effect=mock_instream)
-        scanner._client = mock_client
-
-        content = b"\x00"
-        result = await scanner.scan_file(content, filename="tiny.bin")
-
-        assert result.is_clean is True
-        assert result.file_size == 1
-        assert result.scan_time_ms > 0
+    # Note: ping method was removed from current implementation
 
     @pytest.mark.asyncio
     async def test_scan_clean_file(self, scanner):
@@ -280,27 +251,3 @@ class TestHelperFunctions:
 
             with pytest.raises(VirusScanError, match="Virus scanning failed"):
                 await scan_content_safe(b"test content", filename="test.txt")
-
-    @pytest.mark.asyncio
-    async def test_scan_content_safe_logs_warning_not_error_on_failure(self):
-        """Scan failures should log at WARNING level, not ERROR, to avoid paging on-call."""
-        with patch("backend.util.virus_scanner.get_virus_scanner") as mock_get_scanner:
-            mock_scanner = Mock()
-            mock_scanner.scan_file = AsyncMock()
-            mock_scanner.scan_file.side_effect = Exception(
-                "range() arg 3 must not be zero"
-            )
-            mock_get_scanner.return_value = mock_scanner
-
-            with (
-                pytest.raises(VirusScanError),
-                patch("backend.util.virus_scanner.logger") as mock_logger,
-            ):
-                await scan_content_safe(b"test", filename="screenshot.png")
-
-            mock_logger.warning.assert_called_once()
-            # Check the formatted log message contains the error text.
-            # Use str() to handle both f-string and %-style logging formats.
-            log_msg = str(mock_logger.warning.call_args)
-            assert "range()" in log_msg
-            mock_logger.error.assert_not_called()

autogpt_platform/backend/migrations/20260326120000_add_chat_message_duration_ms/migration.sql

@@ -1,2 +0,0 @@
--- Add durationMs column to ChatMessage for persisting turn elapsed time.
-ALTER TABLE "ChatMessage" ADD COLUMN "durationMs" INTEGER;

autogpt_platform/backend/pyproject.toml

@@ -155,7 +155,6 @@ asyncio_default_fixture_loop_scope = "session"
 addopts = "-p no:syrupy"
 markers = [
     "supplementary: tests kept for coverage but superseded by integration tests",
-    "integration: end-to-end tests that require a live database (skipped in CI)",
 ]
 filterwarnings = [
     "ignore:'audioop' is deprecated:DeprecationWarning:discord.player",

autogpt_platform/backend/schema.prisma

@@ -246,8 +246,7 @@ model ChatMessage {
   functionCall Json? // Deprecated but kept for compatibility
 
   // Ordering within session
-  sequence   Int
-  durationMs Int? // Wall-clock milliseconds for this assistant turn
+  sequence Int
 
   @@unique([sessionId, sequence])
 }

autogpt_platform/backend/snapshots/get_rate_limit

@@ -1,8 +0,0 @@
-{
-  "daily_token_limit": 2500000,
-  "daily_tokens_used": 500000,
-  "user_email": "target@example.com",
-  "user_id": "5e53486c-cf57-477e-ba2a-cb02dc828e1c",
-  "weekly_token_limit": 12500000,
-  "weekly_tokens_used": 3000000
-}

autogpt_platform/backend/snapshots/reset_user_usage_daily_and_weekly

@@ -1,8 +0,0 @@
-{
-  "daily_token_limit": 2500000,
-  "daily_tokens_used": 0,
-  "user_email": "target@example.com",
-  "user_id": "5e53486c-cf57-477e-ba2a-cb02dc828e1c",
-  "weekly_token_limit": 12500000,
-  "weekly_tokens_used": 0
-}

autogpt_platform/backend/snapshots/reset_user_usage_daily_only

@@ -1,8 +0,0 @@
-{
-  "daily_token_limit": 2500000,
-  "daily_tokens_used": 0,
-  "user_email": "target@example.com",
-  "user_id": "5e53486c-cf57-477e-ba2a-cb02dc828e1c",
-  "weekly_token_limit": 12500000,
-  "weekly_tokens_used": 3000000
-}

autogpt_platform/backend/test/agent_generator/test_orchestrator.py

@@ -526,12 +526,7 @@ class TestValidateOrchestratorBlocks:
                 "id": AGENT_INPUT_BLOCK_ID,
                 "name": "AgentInputBlock",
                 "inputSchema": {
-                    "properties": {
-                        "name": {"type": "string"},
-                        "title": {"type": "string"},
-                        "value": {},
-                        "description": {"type": "string"},
-                    },
+                    "properties": {"name": {"type": "string"}},
                     "required": ["name"],
                 },
                 "outputSchema": {"properties": {"result": {}}},
@@ -542,7 +537,6 @@ class TestValidateOrchestratorBlocks:
                 "inputSchema": {
                     "properties": {
                         "name": {"type": "string"},
-                        "title": {"type": "string"},
                         "value": {},
                     },
                     "required": ["name"],
@@ -689,12 +683,7 @@ class TestOrchestratorE2EPipeline:
                 "id": AGENT_INPUT_BLOCK_ID,
                 "name": "AgentInputBlock",
                 "inputSchema": {
-                    "properties": {
-                        "name": {"type": "string"},
-                        "title": {"type": "string"},
-                        "value": {},
-                        "description": {"type": "string"},
-                    },
+                    "properties": {"name": {"type": "string"}},
                     "required": ["name"],
                 },
                 "outputSchema": {"properties": {"result": {}}},
@@ -705,7 +694,6 @@ class TestOrchestratorE2EPipeline:
                 "inputSchema": {
                     "properties": {
                         "name": {"type": "string"},
-                        "title": {"type": "string"},
                         "value": {},
                     },
                     "required": ["name"],

autogpt_platform/backend/test/blocks/test_gmail.py

@@ -1,20 +1,9 @@
 import base64
-from types import SimpleNamespace
-from typing import cast
 from unittest.mock import Mock, patch
 
 import pytest
 
-from backend.blocks.google.gmail import (
-    GmailForwardBlock,
-    GmailReadBlock,
-    HasRecipients,
-    _build_reply_message,
-    create_mime_message,
-    validate_all_recipients,
-    validate_email_recipients,
-)
-from backend.data.execution import ExecutionContext
+from backend.blocks.google.gmail import GmailReadBlock
 
 
 class TestGmailReadBlock:
@@ -261,244 +250,3 @@ class TestGmailReadBlock:
 
         result = await self.gmail_block._get_email_body(msg, self.mock_service)
         assert result == "This email does not contain a readable body."
-
-
-class TestValidateEmailRecipients:
-    """Test cases for validate_email_recipients."""
-
-    def test_valid_single_email(self):
-        validate_email_recipients(["user@example.com"])
-
-    def test_valid_multiple_emails(self):
-        validate_email_recipients(["a@b.com", "x@y.org", "test@sub.domain.co"])
-
-    def test_invalid_missing_at(self):
-        with pytest.raises(ValueError, match="Invalid email address"):
-            validate_email_recipients(["not-an-email"])
-
-    def test_invalid_missing_domain_dot(self):
-        with pytest.raises(ValueError, match="Invalid email address"):
-            validate_email_recipients(["user@localhost"])
-
-    def test_invalid_empty_string(self):
-        with pytest.raises(ValueError, match="Invalid email address"):
-            validate_email_recipients([""])
-
-    def test_invalid_json_object_string(self):
-        with pytest.raises(ValueError, match="Invalid email address"):
-            validate_email_recipients(['{"email": "user@example.com"}'])
-
-    def test_mixed_valid_and_invalid(self):
-        with pytest.raises(ValueError, match="'bad-addr'"):
-            validate_email_recipients(["good@example.com", "bad-addr"])
-
-    def test_field_name_in_error(self):
-        with pytest.raises(ValueError, match="'cc'"):
-            validate_email_recipients(["nope"], field_name="cc")
-
-    def test_whitespace_trimmed(self):
-        validate_email_recipients(["  user@example.com  "])
-
-    def test_empty_list_passes(self):
-        validate_email_recipients([])
-
-
-class TestValidateAllRecipients:
-    """Test cases for validate_all_recipients."""
-
-    def test_valid_all_fields(self):
-        data = cast(
-            HasRecipients,
-            SimpleNamespace(to=["a@b.com"], cc=["c@d.com"], bcc=["e@f.com"]),
-        )
-        validate_all_recipients(data)
-
-    def test_invalid_to_raises(self):
-        data = cast(HasRecipients, SimpleNamespace(to=["bad"], cc=[], bcc=[]))
-        with pytest.raises(ValueError, match="'to'"):
-            validate_all_recipients(data)
-
-    def test_invalid_cc_raises(self):
-        data = cast(HasRecipients, SimpleNamespace(to=["a@b.com"], cc=["bad"], bcc=[]))
-        with pytest.raises(ValueError, match="'cc'"):
-            validate_all_recipients(data)
-
-    def test_invalid_bcc_raises(self):
-        data = cast(
-            HasRecipients,
-            SimpleNamespace(to=["a@b.com"], cc=["c@d.com"], bcc=["bad"]),
-        )
-        with pytest.raises(ValueError, match="'bcc'"):
-            validate_all_recipients(data)
-
-    def test_empty_cc_bcc_skipped(self):
-        data = cast(HasRecipients, SimpleNamespace(to=["a@b.com"], cc=[], bcc=[]))
-        validate_all_recipients(data)
-
-
-class TestCreateMimeMessageValidation:
-    """Integration tests verifying validation hooks in create_mime_message()."""
-
-    @pytest.mark.asyncio
-    async def test_invalid_to_raises_before_mime_construction(self):
-        """Invalid 'to' recipients should raise ValueError before any MIME work."""
-        input_data = SimpleNamespace(
-            to=["not-an-email"],
-            cc=[],
-            bcc=[],
-            subject="Test",
-            body="Hello",
-            attachments=[],
-        )
-        exec_ctx = cast(ExecutionContext, SimpleNamespace(graph_exec_id="test-exec-id"))
-
-        with pytest.raises(ValueError, match="Invalid email address"):
-            await create_mime_message(input_data, exec_ctx)
-
-    @pytest.mark.asyncio
-    async def test_invalid_cc_raises_before_mime_construction(self):
-        """Invalid 'cc' recipients should raise ValueError."""
-        input_data = SimpleNamespace(
-            to=["valid@example.com"],
-            cc=["bad-addr"],
-            bcc=[],
-            subject="Test",
-            body="Hello",
-            attachments=[],
-        )
-        exec_ctx = cast(ExecutionContext, SimpleNamespace(graph_exec_id="test-exec-id"))
-
-        with pytest.raises(ValueError, match="'cc'"):
-            await create_mime_message(input_data, exec_ctx)
-
-    @pytest.mark.asyncio
-    async def test_valid_recipients_passes_validation(self):
-        """Valid recipients should not raise during validation."""
-        input_data = SimpleNamespace(
-            to=["user@example.com"],
-            cc=["other@example.com"],
-            bcc=[],
-            subject="Test",
-            body="Hello",
-            attachments=[],
-        )
-        exec_ctx = cast(ExecutionContext, SimpleNamespace(graph_exec_id="test-exec-id"))
-
-        # Should succeed without raising
-        result = await create_mime_message(input_data, exec_ctx)
-        assert isinstance(result, str)
-
-
-class TestBuildReplyMessageValidation:
-    """Integration tests verifying validation hooks in _build_reply_message()."""
-
-    @pytest.mark.asyncio
-    async def test_invalid_to_raises_before_reply_construction(self):
-        """Invalid 'to' in reply should raise ValueError before MIME work."""
-        mock_service = Mock()
-        mock_parent = {
-            "threadId": "thread-1",
-            "payload": {
-                "headers": [
-                    {"name": "Subject", "value": "Original"},
-                    {"name": "Message-ID", "value": "<msg@example.com>"},
-                    {"name": "From", "value": "sender@example.com"},
-                ]
-            },
-        }
-        mock_service.users().messages().get().execute.return_value = mock_parent
-
-        input_data = SimpleNamespace(
-            parentMessageId="msg-1",
-            to=["not-valid"],
-            cc=[],
-            bcc=[],
-            subject="",
-            body="Reply body",
-            replyAll=False,
-            attachments=[],
-        )
-        exec_ctx = cast(ExecutionContext, SimpleNamespace(graph_exec_id="test-exec-id"))
-
-        with pytest.raises(ValueError, match="Invalid email address"):
-            await _build_reply_message(mock_service, input_data, exec_ctx)
-
-
-class TestForwardMessageValidation:
-    """Test that _forward_message() raises ValueError for invalid recipients."""
-
-    @staticmethod
-    def _make_input(
-        to: list[str] | None = None,
-        cc: list[str] | None = None,
-        bcc: list[str] | None = None,
-    ) -> "GmailForwardBlock.Input":
-        mock = Mock(spec=GmailForwardBlock.Input)
-        mock.messageId = "m1"
-        mock.to = to or []
-        mock.cc = cc or []
-        mock.bcc = bcc or []
-        mock.subject = ""
-        mock.forwardMessage = "FYI"
-        mock.includeAttachments = False
-        mock.content_type = None
-        mock.additionalAttachments = []
-        mock.credentials = None
-        return mock
-
-    @staticmethod
-    def _exec_ctx():
-        return ExecutionContext(user_id="u1", graph_exec_id="g1")
-
-    @staticmethod
-    def _mock_service():
-        """Build a mock Gmail service that returns a parent message."""
-        parent_message = {
-            "id": "m1",
-            "payload": {
-                "headers": [
-                    {"name": "Subject", "value": "Original subject"},
-                    {"name": "From", "value": "sender@example.com"},
-                    {"name": "To", "value": "me@example.com"},
-                    {"name": "Date", "value": "Mon, 31 Mar 2026 00:00:00 +0000"},
-                ],
-                "mimeType": "text/plain",
-                "body": {
-                    "data": base64.urlsafe_b64encode(b"Hello world").decode(),
-                },
-                "parts": [],
-            },
-        }
-        svc = Mock()
-        svc.users().messages().get().execute.return_value = parent_message
-        return svc
-
-    @pytest.mark.asyncio
-    async def test_invalid_to_raises(self):
-        block = GmailForwardBlock()
-        with pytest.raises(ValueError, match="Invalid email address.*'to'"):
-            await block._forward_message(
-                self._mock_service(),
-                self._make_input(to=["bad-addr"]),
-                self._exec_ctx(),
-            )
-
-    @pytest.mark.asyncio
-    async def test_invalid_cc_raises(self):
-        block = GmailForwardBlock()
-        with pytest.raises(ValueError, match="Invalid email address.*'cc'"):
-            await block._forward_message(
-                self._mock_service(),
-                self._make_input(to=["valid@example.com"], cc=["not-valid"]),
-                self._exec_ctx(),
-            )
-
-    @pytest.mark.asyncio
-    async def test_invalid_bcc_raises(self):
-        block = GmailForwardBlock()
-        with pytest.raises(ValueError, match="Invalid email address.*'bcc'"):
-            await block._forward_message(
-                self._mock_service(),
-                self._make_input(to=["valid@example.com"], bcc=["nope"]),
-                self._exec_ctx(),
-            )

autogpt_platform/backend/test/e2e_test_data.py

@@ -254,6 +254,7 @@ class TestDataCreator:
                             "value": "",
                             "advanced": False,
                             "description": None,
+                            "placeholder_values": [],
                         },
                         metadata={"position": {"x": -1012, "y": 674}},
                     )
@@ -273,6 +274,7 @@ class TestDataCreator:
                             "value": "",
                             "advanced": False,
                             "description": None,
+                            "placeholder_values": [],
                         },
                         metadata={"position": {"x": -1117, "y": 78}},
                     )

autogpt_platform/backend/test/test_data_creator.py

@@ -17,7 +17,6 @@ images: {
 """
 
 import asyncio
-import os
 import random
 from datetime import datetime
 
@@ -570,10 +569,6 @@ async def main():
 
 @pytest.mark.asyncio
 @pytest.mark.integration
-@pytest.mark.skipif(
-    os.getenv("CI") == "true",
-    reason="Data seeding test requires a dedicated database; not for CI",
-)
 async def test_main_function_runs_without_errors():
     await main()
 

autogpt_platform/frontend/.storybook/main.ts

@@ -7,7 +7,6 @@ const config: StorybookConfig = {
     "../src/components/atoms/**/*.stories.@(js|jsx|mjs|ts|tsx)",
     "../src/components/molecules/**/*.stories.@(js|jsx|mjs|ts|tsx)",
     "../src/components/ai-elements/**/*.stories.@(js|jsx|mjs|ts|tsx)",
-    "../src/components/renderers/**/*.stories.@(js|jsx|mjs|ts|tsx)",
   ],
   addons: [
     "@storybook/addon-a11y",

autogpt_platform/frontend/instrumentation-client.ts

@@ -25,11 +25,7 @@ Sentry.init({
   // Suppress cross-origin stylesheet errors from Sentry Replay (rrweb)
   // serializing DOM snapshots with cross-origin stylesheets
   // (e.g., from browser extensions or CDN-loaded CSS)
-  ignoreErrors: [
-    /Not allowed to access cross-origin stylesheet/,
-    // Sentry SDK internal issue on some mobile browsers
-    /Error invoking postEvent: Method not found/,
-  ],
+  ignoreErrors: [/Not allowed to access cross-origin stylesheet/],
 
   // Add optional integrations for additional features
   integrations: [

autogpt_platform/frontend/src/app/(platform)/admin/components/AdminUserSearch.tsx

@@ -1,71 +0,0 @@
-"use client";
-
-import { useState } from "react";
-import { Input } from "@/components/__legacy__/ui/input";
-import { Button } from "@/components/atoms/Button/Button";
-import { MagnifyingGlass } from "@phosphor-icons/react";
-
-export interface AdminUserSearchProps {
-  /** Current search query value (controlled). Falls back to internal state if omitted. */
-  value?: string;
-  /** Called when the input text changes */
-  onChange?: (value: string) => void;
-  /** Called when the user presses Enter or clicks the search button */
-  onSearch: (query: string) => void;
-  /** Placeholder text for the input */
-  placeholder?: string;
-  /** Disables the input and button while a search is in progress */
-  isLoading?: boolean;
-}
-
-/**
- * Shared admin user search input.
- * Supports searching users by name, email, or partial/fuzzy text.
- * Can be used as controlled (value + onChange) or uncontrolled (internal state).
- */
-export function AdminUserSearch({
-  value: controlledValue,
-  onChange,
-  onSearch,
-  placeholder = "Search users by Name or Email...",
-  isLoading = false,
-}: AdminUserSearchProps) {
-  const [internalValue, setInternalValue] = useState("");
-
-  const isControlled = controlledValue !== undefined;
-  const currentValue = isControlled ? controlledValue : internalValue;
-
-  function handleChange(newValue: string) {
-    if (isControlled) {
-      onChange?.(newValue);
-    } else {
-      setInternalValue(newValue);
-    }
-  }
-
-  function handleSearch() {
-    onSearch(currentValue.trim());
-  }
-
-  return (
-    <div className="flex w-full items-center gap-2">
-      <Input
-        placeholder={placeholder}
-        aria-label={placeholder}
-        value={currentValue}
-        onChange={(e) => handleChange(e.target.value)}
-        onKeyDown={(e) => e.key === "Enter" && handleSearch()}
-        disabled={isLoading}
-      />
-      <Button
-        variant="outline"
-        size="small"
-        onClick={handleSearch}
-        disabled={isLoading || !currentValue.trim()}
-        loading={isLoading}
-      >
-        {isLoading ? "Searching..." : <MagnifyingGlass size={16} />}
-      </Button>
-    </div>
-  );
-}

autogpt_platform/frontend/src/app/(platform)/admin/components/UsageBar.tsx

@@ -1,34 +0,0 @@
-"use client";
-
-export function formatTokens(tokens: number): string {
-  if (tokens >= 1_000_000) return `${(tokens / 1_000_000).toFixed(1)}M`;
-  if (tokens >= 1_000) return `${(tokens / 1_000).toFixed(0)}K`;
-  return tokens.toString();
-}
-
-export function UsageBar({ used, limit }: { used: number; limit: number }) {
-  if (limit === 0) {
-    return <span className="text-sm text-gray-500">Unlimited</span>;
-  }
-  const pct = Math.min(Math.max(0, (used / limit) * 100), 100);
-  const color =
-    pct >= 90 ? "bg-red-500" : pct >= 70 ? "bg-yellow-500" : "bg-green-500";
-
-  return (
-    <div className="space-y-1">
-      <div className="flex justify-between text-sm">
-        <span>{formatTokens(used)} used</span>
-        <span>{formatTokens(limit)} limit</span>
-      </div>
-      <div className="h-2 w-full rounded-full bg-gray-200">
-        <div
-          className={`h-2 rounded-full ${color}`}
-          style={{ width: `${pct}%` }}
-        />
-      </div>
-      <div className="text-right text-xs text-gray-500">
-        {pct.toFixed(1)}% used
-      </div>
-    </div>
-  );
-}

autogpt_platform/frontend/src/app/(platform)/admin/layout.tsx

@@ -1,6 +1,5 @@
 import { Sidebar } from "@/components/__legacy__/Sidebar";
 import { Users, DollarSign, UserSearch, FileText } from "lucide-react";
-import { Gauge } from "@phosphor-icons/react/dist/ssr";
 
 import { IconSliders } from "@/components/__legacy__/ui/icons";
 
@@ -22,11 +21,6 @@ const sidebarLinkGroups = [
         href: "/admin/impersonation",
         icon: <UserSearch className="h-6 w-6" />,
       },
-      {
-        text: "Rate Limits",
-        href: "/admin/rate-limits",
-        icon: <Gauge className="h-6 w-6" />,
-      },
       {
         text: "Execution Analytics",
         href: "/admin/execution-analytics",

autogpt_platform/frontend/src/app/(platform)/admin/rate-limits/components/RateLimitDisplay.tsx

@@ -1,85 +0,0 @@
-"use client";
-
-import { useState } from "react";
-import { Button } from "@/components/atoms/Button/Button";
-import type { UserRateLimitResponse } from "@/app/api/__generated__/models/userRateLimitResponse";
-import { UsageBar } from "../../components/UsageBar";
-
-interface Props {
-  data: UserRateLimitResponse;
-  onReset: (resetWeekly: boolean) => Promise<void>;
-  /** Override the outer container classes (default: bordered card). */
-  className?: string;
-}
-
-export function RateLimitDisplay({ data, onReset, className }: Props) {
-  const [isResetting, setIsResetting] = useState(false);
-  const [resetWeekly, setResetWeekly] = useState(false);
-
-  async function handleReset() {
-    const msg = resetWeekly
-      ? "Reset both daily and weekly usage counters to zero?"
-      : "Reset daily usage counter to zero?";
-    if (!window.confirm(msg)) return;
-
-    setIsResetting(true);
-    try {
-      await onReset(resetWeekly);
-    } finally {
-      setIsResetting(false);
-    }
-  }
-
-  const nothingToReset = resetWeekly
-    ? data.daily_tokens_used === 0 && data.weekly_tokens_used === 0
-    : data.daily_tokens_used === 0;
-
-  return (
-    <div className={className ?? "rounded-md border bg-white p-6"}>
-      <h2 className="mb-1 text-lg font-semibold">
-        Rate Limits for {data.user_email ?? data.user_id}
-      </h2>
-      {data.user_email && (
-        <p className="mb-4 text-xs text-gray-500">User ID: {data.user_id}</p>
-      )}
-      {!data.user_email && <div className="mb-4" />}
-
-      <div className="grid grid-cols-2 gap-6">
-        <div className="space-y-2">
-          <h3 className="text-sm font-medium text-gray-700">Daily Usage</h3>
-          <UsageBar
-            used={data.daily_tokens_used}
-            limit={data.daily_token_limit}
-          />
-        </div>
-        <div className="space-y-2">
-          <h3 className="text-sm font-medium text-gray-700">Weekly Usage</h3>
-          <UsageBar
-            used={data.weekly_tokens_used}
-            limit={data.weekly_token_limit}
-          />
-        </div>
-      </div>
-
-      <div className="mt-6 flex items-center gap-3 border-t pt-4">
-        <select
-          aria-label="Reset scope"
-          value={resetWeekly ? "both" : "daily"}
-          onChange={(e) => setResetWeekly(e.target.value === "both")}
-          className="rounded-md border bg-white px-3 py-1.5 text-sm"
-          disabled={isResetting}
-        >
-          <option value="daily">Reset daily only</option>
-          <option value="both">Reset daily + weekly</option>
-        </select>
-        <Button
-          variant="outline"
-          onClick={handleReset}
-          disabled={isResetting || nothingToReset}
-        >
-          {isResetting ? "Resetting..." : "Reset Usage"}
-        </Button>
-      </div>
-    </div>
-  );
-}

autogpt_platform/frontend/src/app/(platform)/admin/rate-limits/components/RateLimitManager.tsx

@@ -1,81 +0,0 @@
-"use client";
-
-import { AdminUserSearch } from "../../components/AdminUserSearch";
-import { RateLimitDisplay } from "./RateLimitDisplay";
-import { useRateLimitManager } from "./useRateLimitManager";
-
-export function RateLimitManager() {
-  const {
-    isSearching,
-    isLoadingRateLimit,
-    searchResults,
-    selectedUser,
-    rateLimitData,
-    handleSearch,
-    handleSelectUser,
-    handleReset,
-  } = useRateLimitManager();
-
-  return (
-    <div className="space-y-6">
-      <div className="rounded-md border bg-white p-6">
-        <label className="mb-2 block text-sm font-medium">Search User</label>
-        <AdminUserSearch
-          onSearch={handleSearch}
-          placeholder="Search by name, email, or user ID..."
-          isLoading={isSearching}
-        />
-        <p className="mt-1.5 text-xs text-gray-500">
-          Exact email or user ID does a direct lookup. Partial text searches
-          user history.
-        </p>
-      </div>
-
-      {/* User selection list -- always require explicit selection */}
-      {searchResults.length >= 1 && !selectedUser && (
-        <div className="rounded-md border bg-white p-4">
-          <h3 className="mb-2 text-sm font-medium text-gray-700">
-            Select a user ({searchResults.length}{" "}
-            {searchResults.length === 1 ? "result" : "results"})
-          </h3>
-          <ul className="divide-y">
-            {searchResults.map((user) => (
-              <li key={user.user_id}>
-                <button
-                  className="w-full px-2 py-2 text-left text-sm hover:bg-gray-100"
-                  onClick={() => handleSelectUser(user)}
-                >
-                  <span className="font-medium">{user.user_email}</span>
-                  <span className="ml-2 text-xs text-gray-500">
-                    {user.user_id}
-                  </span>
-                </button>
-              </li>
-            ))}
-          </ul>
-        </div>
-      )}
-
-      {/* Show selected user */}
-      {selectedUser && searchResults.length >= 1 && (
-        <div className="rounded-md border border-blue-200 bg-blue-50 px-4 py-2 text-sm">
-          Selected:{" "}
-          <span className="font-medium">{selectedUser.user_email}</span>
-          <span className="ml-2 text-xs text-gray-500">
-            {selectedUser.user_id}
-          </span>
-        </div>
-      )}
-
-      {isLoadingRateLimit && (
-        <div className="py-4 text-center text-sm text-gray-500">
-          Loading rate limits...
-        </div>
-      )}
-
-      {rateLimitData && (
-        <RateLimitDisplay data={rateLimitData} onReset={handleReset} />
-      )}
-    </div>
-  );
-}