fix(backend): remove unnecessary f-strings in documentation generation

## Background

When using chat to run blocks/agents that support multiple credential
types (e.g., GitHub blocks support both `api_key` and `oauth2`), users
reported that the credentials setup UI would randomly show either "Add
API key" or "Connect account (OAuth)" - seemingly at random between
requests or server restarts.

## Root Cause

The bug was in how the backend selected which credential type to return
when building the missing credentials response:

```python
cred_type = next(iter(field_info.supported_types), "api_key")
```

The problem is that `supported_types` is a **frozenset**. When you call
`iter()` on a frozenset and take `next()`, the iteration order is
**non-deterministic** due to Python's hash randomization. This means:
- `frozenset({'api_key', 'oauth2'})` could iterate as either
`['api_key', 'oauth2']` or `['oauth2', 'api_key']`
- The order varies between Python process restarts and sometimes between
requests
- This caused the UI to randomly show different credential options

### Changes 🏗️

**Backend (`utils.py`, `run_block.py`, `run_agent.py`):**
- Added `_serialize_missing_credential()` helper that uses `sorted()`
for deterministic ordering
- Added `build_missing_credentials_from_graph()` and
`build_missing_credentials_from_field_info()` utilities
- Now returns both `type` (first sorted type, for backwards compat) and
`types` (full array with ALL supported types)

**Frontend (`helpers.ts`, `ChatCredentialsSetup.tsx`,
`useChatMessage.ts`):**
- Updated to read the `types` array from backend response
- Changed `credentialType` (single) to `credentialTypes` (array)
throughout the chat credentials flow
- Passes all supported types to `CredentialsInput` via
`credentials_types` schema field

### Result

Now `useCredentials.ts` correctly sets both `supportsApiKey=true` AND
`supportsOAuth2=true` when both are supported, ensuring:
1. **Deterministic behavior** - no more random type selection
2. **All saved credentials shown** - credentials of any supported type
appear in the selection list

### Checklist 📋

#### For code changes:
- [x] I have clearly listed my changes in the PR description
- [x] I have made a test plan
- [x] I have tested my changes according to the test plan:
- [x] Verified GitHub block shows consistent credential options across
page reloads
- [x] Verified both OAuth and API key credentials appear in selection
when user has both saved
- [x] Verified backend returns `types: ["api_key", "oauth2"]` array
(checked via Python REPL)

<!-- CURSOR_SUMMARY -->
---

> [!NOTE]
> Ensures deterministic credential type selection and surfaces all
supported types end-to-end.
> 
> - Backend: add `_serialize_missing_credential`,
`build_missing_credentials_from_graph/field_info`;
`run_agent`/`run_block` now return missing credentials with stable
ordering and both `type` (first) and `types` (all).
> - Frontend: chat helpers and UI (`helpers.ts`,
`ChatCredentialsSetup.tsx`, `useChatMessage.ts`) now read `types`,
switch from single `credentialType` to `credentialTypes`, and pass all
supported `credentials_types` in schemas.
> 
> <sup>Written by [Cursor
Bugbot](https://cursor.com/dashboard?tab=bugbot) for commit
7d80f4f0e0. This will update automatically
on new commits. Configure
[here](https://cursor.com/dashboard?tab=bugbot).</sup>
<!-- /CURSOR_SUMMARY -->

---------

Co-authored-by: Claude Opus 4.5 <noreply@anthropic.com>
Co-authored-by: claude[bot] <41898282+claude[bot]@users.noreply.github.com>
Co-authored-by: Nicholas Tindle <ntindle@users.noreply.github.com>

.github/workflows/classic-autogpt-ci.yml

@@ -83,7 +83,7 @@ jobs:
       - name: Set up Python dependency cache
         # On Windows, unpacking cached dependencies takes longer than just installing them
         if: runner.os != 'Windows'
-        uses: actions/cache@v5
+        uses: actions/cache@v4
         with:
           path: ${{ runner.os == 'macOS' && '~/Library/Caches/pypoetry' || '~/.cache/pypoetry' }}
           key: poetry-${{ runner.os }}-${{ hashFiles('classic/original_autogpt/poetry.lock') }}

.github/workflows/classic-benchmark-ci.yml

@@ -55,7 +55,7 @@ jobs:
       - name: Set up Python dependency cache
         # On Windows, unpacking cached dependencies takes longer than just installing them
         if: runner.os != 'Windows'
-        uses: actions/cache@v5
+        uses: actions/cache@v4
         with:
           path: ${{ runner.os == 'macOS' && '~/Library/Caches/pypoetry' || '~/.cache/pypoetry' }}
           key: poetry-${{ runner.os }}-${{ hashFiles('classic/benchmark/poetry.lock') }}

.github/workflows/classic-forge-ci.yml

@@ -107,7 +107,7 @@ jobs:
       - name: Set up Python dependency cache
         # On Windows, unpacking cached dependencies takes longer than just installing them
         if: runner.os != 'Windows'
-        uses: actions/cache@v5
+        uses: actions/cache@v4
         with:
           path: ${{ runner.os == 'macOS' && '~/Library/Caches/pypoetry' || '~/.cache/pypoetry' }}
           key: poetry-${{ runner.os }}-${{ hashFiles('classic/forge/poetry.lock') }}

.github/workflows/classic-python-checks.yml

@@ -78,7 +78,7 @@ jobs:
           python-version: ${{ env.min-python-version }}
 
       - name: Set up Python dependency cache
-        uses: actions/cache@v5
+        uses: actions/cache@v4
         with:
           path: ~/.cache/pypoetry
           key: ${{ runner.os }}-poetry-${{ hashFiles(format('{0}/poetry.lock', matrix.sub-package)) }}
@@ -130,7 +130,7 @@ jobs:
           python-version: ${{ env.min-python-version }}
 
       - name: Set up Python dependency cache
-        uses: actions/cache@v5
+        uses: actions/cache@v4
         with:
           path: ~/.cache/pypoetry
           key: ${{ runner.os }}-poetry-${{ hashFiles(format('{0}/poetry.lock', matrix.sub-package)) }}

.github/workflows/claude-dependabot.yml

@@ -41,7 +41,7 @@ jobs:
           python-version: "3.11"  # Use standard version matching CI
 
       - name: Set up Python dependency cache
-        uses: actions/cache@v5
+        uses: actions/cache@v4
         with:
           path: ~/.cache/pypoetry
           key: poetry-${{ runner.os }}-${{ hashFiles('autogpt_platform/backend/poetry.lock') }}
@@ -91,7 +91,7 @@ jobs:
           echo "PNPM_HOME=$HOME/.pnpm-store" >> $GITHUB_ENV
 
       - name: Cache frontend dependencies
-        uses: actions/cache@v5
+        uses: actions/cache@v4
         with:
           path: ~/.pnpm-store
           key: ${{ runner.os }}-pnpm-${{ hashFiles('autogpt_platform/frontend/pnpm-lock.yaml', 'autogpt_platform/frontend/package.json') }}
@@ -124,7 +124,7 @@ jobs:
       # Phase 1: Cache and load Docker images for faster setup
       - name: Set up Docker image cache
         id: docker-cache
-        uses: actions/cache@v5
+        uses: actions/cache@v4
         with:
           path: ~/docker-cache
           # Use a versioned key for cache invalidation when image list changes

.github/workflows/claude.yml

@@ -57,7 +57,7 @@ jobs:
           python-version: "3.11"  # Use standard version matching CI
 
       - name: Set up Python dependency cache
-        uses: actions/cache@v5
+        uses: actions/cache@v4
         with:
           path: ~/.cache/pypoetry
           key: poetry-${{ runner.os }}-${{ hashFiles('autogpt_platform/backend/poetry.lock') }}
@@ -107,7 +107,7 @@ jobs:
           echo "PNPM_HOME=$HOME/.pnpm-store" >> $GITHUB_ENV
 
       - name: Cache frontend dependencies
-        uses: actions/cache@v5
+        uses: actions/cache@v4
         with:
           path: ~/.pnpm-store
           key: ${{ runner.os }}-pnpm-${{ hashFiles('autogpt_platform/frontend/pnpm-lock.yaml', 'autogpt_platform/frontend/package.json') }}
@@ -140,7 +140,7 @@ jobs:
       # Phase 1: Cache and load Docker images for faster setup
       - name: Set up Docker image cache
         id: docker-cache
-        uses: actions/cache@v5
+        uses: actions/cache@v4
         with:
           path: ~/docker-cache
           # Use a versioned key for cache invalidation when image list changes

.github/workflows/copilot-setup-steps.yml

@@ -39,7 +39,7 @@ jobs:
           python-version: "3.11"  # Use standard version matching CI
 
       - name: Set up Python dependency cache
-        uses: actions/cache@v5
+        uses: actions/cache@v4
         with:
           path: ~/.cache/pypoetry
           key: poetry-${{ runner.os }}-${{ hashFiles('autogpt_platform/backend/poetry.lock') }}
@@ -89,7 +89,7 @@ jobs:
           echo "PNPM_HOME=$HOME/.pnpm-store" >> $GITHUB_ENV
 
       - name: Cache frontend dependencies
-        uses: actions/cache@v5
+        uses: actions/cache@v4
         with:
           path: ~/.pnpm-store
           key: ${{ runner.os }}-pnpm-${{ hashFiles('autogpt_platform/frontend/pnpm-lock.yaml', 'autogpt_platform/frontend/package.json') }}
@@ -132,7 +132,7 @@ jobs:
       # Phase 1: Cache and load Docker images for faster setup
       - name: Set up Docker image cache
         id: docker-cache
-        uses: actions/cache@v5
+        uses: actions/cache@v4
         with:
           path: ~/docker-cache
           # Use a versioned key for cache invalidation when image list changes

.github/workflows/docs-block-sync.yml

@@ -33,7 +33,7 @@ jobs:
           python-version: "3.11"
 
       - name: Set up Python dependency cache
-        uses: actions/cache@v5
+        uses: actions/cache@v4
         with:
           path: ~/.cache/pypoetry
           key: poetry-${{ runner.os }}-${{ hashFiles('autogpt_platform/backend/poetry.lock') }}

.github/workflows/docs-claude-review.yml

@@ -33,7 +33,7 @@ jobs:
           python-version: "3.11"
 
       - name: Set up Python dependency cache
-        uses: actions/cache@v5
+        uses: actions/cache@v4
         with:
           path: ~/.cache/pypoetry
           key: poetry-${{ runner.os }}-${{ hashFiles('autogpt_platform/backend/poetry.lock') }}

.github/workflows/docs-enhance.yml

@@ -38,7 +38,7 @@ jobs:
           python-version: "3.11"
 
       - name: Set up Python dependency cache
-        uses: actions/cache@v5
+        uses: actions/cache@v4
         with:
           path: ~/.cache/pypoetry
           key: poetry-${{ runner.os }}-${{ hashFiles('autogpt_platform/backend/poetry.lock') }}

.github/workflows/platform-backend-ci.yml

@@ -88,7 +88,7 @@ jobs:
         run: echo "date=$(date +'%Y-%m-%d')" >> $GITHUB_OUTPUT
 
       - name: Set up Python dependency cache
-        uses: actions/cache@v5
+        uses: actions/cache@v4
         with:
           path: ~/.cache/pypoetry
           key: poetry-${{ runner.os }}-${{ hashFiles('autogpt_platform/backend/poetry.lock') }}

.github/workflows/platform-frontend-ci.yml

@@ -45,7 +45,7 @@ jobs:
         run: echo "key=${{ runner.os }}-pnpm-${{ hashFiles('autogpt_platform/frontend/pnpm-lock.yaml', 'autogpt_platform/frontend/package.json') }}" >> $GITHUB_OUTPUT
 
       - name: Cache dependencies
-        uses: actions/cache@v5
+        uses: actions/cache@v4
         with:
           path: ~/.pnpm-store
           key: ${{ steps.cache-key.outputs.key }}
@@ -73,7 +73,7 @@ jobs:
         run: corepack enable
 
       - name: Restore dependencies cache
-        uses: actions/cache@v5
+        uses: actions/cache@v4
         with:
           path: ~/.pnpm-store
           key: ${{ needs.setup.outputs.cache-key }}
@@ -108,7 +108,7 @@ jobs:
         run: corepack enable
 
       - name: Restore dependencies cache
-        uses: actions/cache@v5
+        uses: actions/cache@v4
         with:
           path: ~/.pnpm-store
           key: ${{ needs.setup.outputs.cache-key }}
@@ -164,7 +164,7 @@ jobs:
         uses: docker/setup-buildx-action@v3
 
       - name: Cache Docker layers
-        uses: actions/cache@v5
+        uses: actions/cache@v4
         with:
           path: /tmp/.buildx-cache
           key: ${{ runner.os }}-buildx-frontend-test-${{ hashFiles('autogpt_platform/docker-compose.yml', 'autogpt_platform/backend/Dockerfile', 'autogpt_platform/backend/pyproject.toml', 'autogpt_platform/backend/poetry.lock') }}
@@ -219,7 +219,7 @@ jobs:
           fi
 
       - name: Restore dependencies cache
-        uses: actions/cache@v5
+        uses: actions/cache@v4
         with:
           path: ~/.pnpm-store
           key: ${{ needs.setup.outputs.cache-key }}

.github/workflows/platform-fullstack-ci.yml

@@ -44,7 +44,7 @@ jobs:
         run: echo "key=${{ runner.os }}-pnpm-${{ hashFiles('autogpt_platform/frontend/pnpm-lock.yaml', 'autogpt_platform/frontend/package.json') }}" >> $GITHUB_OUTPUT
 
       - name: Cache dependencies
-        uses: actions/cache@v5
+        uses: actions/cache@v4
         with:
           path: ~/.pnpm-store
           key: ${{ steps.cache-key.outputs.key }}
@@ -88,7 +88,7 @@ jobs:
           docker compose -f ../docker-compose.yml --profile local --profile deps_backend up -d
 
       - name: Restore dependencies cache
-        uses: actions/cache@v5
+        uses: actions/cache@v4
         with:
           path: ~/.pnpm-store
           key: ${{ needs.setup.outputs.cache-key }}

AGENTS.md

@@ -16,6 +16,20 @@ See `docs/content/platform/getting-started.md` for setup instructions.
 - Format Python code with `poetry run format`.
 - Format frontend code using `pnpm format`.
 
+## Frontend-specific guidelines
+
+**When working on files in `autogpt_platform/frontend/`, always read and follow the conventions in `autogpt_platform/frontend/CONTRIBUTING.md`.**
+
+Key frontend conventions:
+- Component props should be `interface Props { ... }` (not exported) unless the interface needs to be used outside the component
+- Separate render logic from business logic (component.tsx + useComponent.ts + helpers.ts)
+- Colocate state when possible and avoid create large components, use sub-components ( local `/components` folder next to the parent component ) when sensible
+- Avoid large hooks, abstract logic into `helpers.ts` files when sensible
+- Use function declarations for components and handlers, arrow functions only for small inline callbacks
+- No barrel files or `index.ts` re-exports
+
+See `autogpt_platform/frontend/CONTRIBUTING.md` for complete frontend architecture, patterns, and conventions.
+
 ## Testing
 
 - Backend: `poetry run test` (runs pytest with a docker based postgres + prisma).

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

@@ -161,7 +161,7 @@ async def create_session(
 async def get_session(
     session_id: str,
     user_id: Annotated[str | None, Depends(auth.get_user_id)],
-) -> SessionDetailResponse:
+) -> SessionDetailResponse | None:
     """
     Retrieve the details of a specific chat session.
 
@@ -172,12 +172,12 @@ async def get_session(
         user_id: The optional authenticated user ID, or None for anonymous access.
 
     Returns:
-        SessionDetailResponse: Details for the requested session; raises NotFoundError if not found.
+        SessionDetailResponse: Details for the requested session, or None if not found.
 
     """
     session = await get_chat_session(session_id, user_id)
     if not session:
-        raise NotFoundError(f"Session {session_id} not found")
+        return None
 
     messages = [message.model_dump() for message in session.messages]
     logger.info(

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

@@ -4,14 +4,9 @@ from collections.abc import AsyncGenerator
 from typing import Any
 
 import orjson
-from langfuse import Langfuse
-from openai import (
-    APIConnectionError,
-    APIError,
-    APIStatusError,
-    AsyncOpenAI,
-    RateLimitError,
-)
+from langfuse import get_client, propagate_attributes
+from langfuse.openai import openai  # type: ignore
+from openai import APIConnectionError, APIError, APIStatusError, RateLimitError
 from openai.types.chat import ChatCompletionChunk, ChatCompletionToolParam
 
 from backend.data.understanding import (
@@ -21,7 +16,6 @@ from backend.data.understanding import (
 from backend.util.exceptions import NotFoundError
 from backend.util.settings import Settings
 
-from . import db as chat_db
 from .config import ChatConfig
 from .model import (
     ChatMessage,
@@ -50,10 +44,10 @@ logger = logging.getLogger(__name__)
 
 config = ChatConfig()
 settings = Settings()
-client = AsyncOpenAI(api_key=config.api_key, base_url=config.base_url)
+client = openai.AsyncOpenAI(api_key=config.api_key, base_url=config.base_url)
 
-# Langfuse client (lazy initialization)
-_langfuse_client: Langfuse | None = None
+
+langfuse = get_client()
 
 
 class LangfuseNotConfiguredError(Exception):
@@ -69,65 +63,6 @@ def _is_langfuse_configured() -> bool:
     )
 
 
-def _get_langfuse_client() -> Langfuse:
-    """Get or create the Langfuse client for prompt management and tracing."""
-    global _langfuse_client
-    if _langfuse_client is None:
-        if not _is_langfuse_configured():
-            raise LangfuseNotConfiguredError(
-                "Langfuse is not configured. The chat feature requires Langfuse for prompt management. "
-                "Please set the LANGFUSE_PUBLIC_KEY and LANGFUSE_SECRET_KEY environment variables."
-            )
-        _langfuse_client = Langfuse(
-            public_key=settings.secrets.langfuse_public_key,
-            secret_key=settings.secrets.langfuse_secret_key,
-            host=settings.secrets.langfuse_host or "https://cloud.langfuse.com",
-        )
-    return _langfuse_client
-
-
-def _get_environment() -> str:
-    """Get the current environment name for Langfuse tagging."""
-    return settings.config.app_env.value
-
-
-def _get_langfuse_prompt() -> str:
-    """Fetch the latest production prompt from Langfuse.
-
-    Returns:
-        The compiled prompt text from Langfuse.
-
-    Raises:
-        Exception: If Langfuse is unavailable or prompt fetch fails.
-    """
-    try:
-        langfuse = _get_langfuse_client()
-        # cache_ttl_seconds=0 disables SDK caching to always get the latest prompt
-        prompt = langfuse.get_prompt(config.langfuse_prompt_name, cache_ttl_seconds=0)
-        compiled = prompt.compile()
-        logger.info(
-            f"Fetched prompt '{config.langfuse_prompt_name}' from Langfuse "
-            f"(version: {prompt.version})"
-        )
-        return compiled
-    except Exception as e:
-        logger.error(f"Failed to fetch prompt from Langfuse: {e}")
-        raise
-
-
-async def _is_first_session(user_id: str) -> bool:
-    """Check if this is the user's first chat session.
-
-    Returns True if the user has 1 or fewer sessions (meaning this is their first).
-    """
-    try:
-        session_count = await chat_db.get_user_session_count(user_id)
-        return session_count <= 1
-    except Exception as e:
-        logger.warning(f"Failed to check session count for user {user_id}: {e}")
-        return False  # Default to non-onboarding if we can't check
-
-
 async def _build_system_prompt(user_id: str | None) -> tuple[str, Any]:
     """Build the full system prompt including business understanding if available.
 
@@ -139,8 +74,6 @@ async def _build_system_prompt(user_id: str | None) -> tuple[str, Any]:
         Tuple of (compiled prompt string, Langfuse prompt object for tracing)
     """
 
-    langfuse = _get_langfuse_client()
-
     # cache_ttl_seconds=0 disables SDK caching to always get the latest prompt
     prompt = langfuse.get_prompt(config.langfuse_prompt_name, cache_ttl_seconds=0)
 
@@ -158,7 +91,7 @@ async def _build_system_prompt(user_id: str | None) -> tuple[str, Any]:
         context = "This is the first time you are meeting the user. Greet them and introduce them to the platform"
 
     compiled = prompt.compile(users_information=context)
-    return compiled, prompt
+    return compiled, understanding
 
 
 async def _generate_session_title(message: str) -> str | None:
@@ -217,6 +150,7 @@ async def assign_user_to_session(
 async def stream_chat_completion(
     session_id: str,
     message: str | None = None,
+    tool_call_response: str | None = None,
     is_user_message: bool = True,
     user_id: str | None = None,
     retry_count: int = 0,
@@ -256,11 +190,6 @@ async def stream_chat_completion(
         yield StreamFinish()
         return
 
-    # Langfuse observations will be created after session is loaded (need messages for input)
-    # Initialize to None so finally block can safely check and end them
-    trace = None
-    generation = None
-
     # Only fetch from Redis if session not provided (initial call)
     if session is None:
         session = await get_chat_session(session_id, user_id)
@@ -336,297 +265,295 @@ async def stream_chat_completion(
             asyncio.create_task(_update_title())
 
     # Build system prompt with business understanding
-    system_prompt, langfuse_prompt = await _build_system_prompt(user_id)
-
-    # Build input messages including system prompt for complete Langfuse logging
-    trace_input_messages = [{"role": "system", "content": system_prompt}] + [
-        m.model_dump() for m in session.messages
-    ]
+    system_prompt, understanding = await _build_system_prompt(user_id)
 
     # Create Langfuse trace for this LLM call (each call gets its own trace, grouped by session_id)
     # Using v3 SDK: start_observation creates a root span, update_trace sets trace-level attributes
-    try:
-        langfuse = _get_langfuse_client()
-        env = _get_environment()
-        trace = langfuse.start_observation(
-            name="chat_completion",
-            input={"messages": trace_input_messages},
-            metadata={
-                "environment": env,
-                "model": config.model,
-                "message_count": len(session.messages),
-                "prompt_name": langfuse_prompt.name if langfuse_prompt else None,
-                "prompt_version": langfuse_prompt.version if langfuse_prompt else None,
-            },
-        )
-        # Set trace-level attributes (session_id, user_id, tags)
-        trace.update_trace(
+    input = message
+    if not message and tool_call_response:
+        input = tool_call_response
+
+    langfuse = get_client()
+    with langfuse.start_as_current_observation(
+        as_type="span",
+        name="user-copilot-request",
+        input=input,
+    ) as span:
+        with propagate_attributes(
             session_id=session_id,
             user_id=user_id,
-            tags=[env, "copilot"],
-        )
-    except Exception as e:
-        logger.warning(f"Failed to create Langfuse trace: {e}")
+            tags=["copilot"],
+            metadata={
+                "users_information": format_understanding_for_prompt(understanding)[
+                    :200
+                ]  # langfuse only accepts upto to 200 chars
+            },
+        ):
 
-    # Initialize variables that will be used in finally block (must be defined before try)
-    assistant_response = ChatMessage(
-        role="assistant",
-        content="",
-    )
-    accumulated_tool_calls: list[dict[str, Any]] = []
-
-    # Wrap main logic in try/finally to ensure Langfuse observations are always ended
-    try:
-        has_yielded_end = False
-        has_yielded_error = False
-        has_done_tool_call = False
-        has_received_text = False
-        text_streaming_ended = False
-        tool_response_messages: list[ChatMessage] = []
-        should_retry = False
-
-        # Generate unique IDs for AI SDK protocol
-        import uuid as uuid_module
-
-        message_id = str(uuid_module.uuid4())
-        text_block_id = str(uuid_module.uuid4())
-
-        # Yield message start
-        yield StreamStart(messageId=message_id)
-
-        # Create Langfuse generation for each LLM call, linked to the prompt
-        # Using v3 SDK: start_observation with as_type="generation"
-        generation = (
-            trace.start_observation(
-                as_type="generation",
-                name="llm_call",
-                model=config.model,
-                input={"messages": trace_input_messages},
-                prompt=langfuse_prompt,
+            # Initialize variables that will be used in finally block (must be defined before try)
+            assistant_response = ChatMessage(
+                role="assistant",
+                content="",
             )
-            if trace
-            else None
-        )
+            accumulated_tool_calls: list[dict[str, Any]] = []
+            has_saved_assistant_message = False
 
-        try:
-            async for chunk in _stream_chat_chunks(
-                session=session,
-                tools=tools,
-                system_prompt=system_prompt,
-                text_block_id=text_block_id,
-            ):
+            # Wrap main logic in try/finally to ensure Langfuse observations are always ended
+            has_yielded_end = False
+            has_yielded_error = False
+            has_done_tool_call = False
+            has_received_text = False
+            text_streaming_ended = False
+            tool_response_messages: list[ChatMessage] = []
+            should_retry = False
 
-                if isinstance(chunk, StreamTextStart):
-                    # Emit text-start before first text delta
-                    if not has_received_text:
+            # Generate unique IDs for AI SDK protocol
+            import uuid as uuid_module
+
+            message_id = str(uuid_module.uuid4())
+            text_block_id = str(uuid_module.uuid4())
+
+            # Yield message start
+            yield StreamStart(messageId=message_id)
+
+            try:
+                async for chunk in _stream_chat_chunks(
+                    session=session,
+                    tools=tools,
+                    system_prompt=system_prompt,
+                    text_block_id=text_block_id,
+                ):
+
+                    if isinstance(chunk, StreamTextStart):
+                        # Emit text-start before first text delta
+                        if not has_received_text:
+                            yield chunk
+                    elif isinstance(chunk, StreamTextDelta):
+                        delta = chunk.delta or ""
+                        assert assistant_response.content is not None
+                        assistant_response.content += delta
+                        has_received_text = True
                         yield chunk
-                elif isinstance(chunk, StreamTextDelta):
-                    delta = chunk.delta or ""
-                    assert assistant_response.content is not None
-                    assistant_response.content += delta
-                    has_received_text = True
-                    yield chunk
-                elif isinstance(chunk, StreamTextEnd):
-                    # Emit text-end after text completes
-                    if has_received_text and not text_streaming_ended:
-                        text_streaming_ended = True
-                        yield chunk
-                elif isinstance(chunk, StreamToolInputStart):
-                    # Emit text-end before first tool call, but only if we've received text
-                    if has_received_text and not text_streaming_ended:
-                        yield StreamTextEnd(id=text_block_id)
-                        text_streaming_ended = True
-                    yield chunk
-                elif isinstance(chunk, StreamToolInputAvailable):
-                    # Accumulate tool calls in OpenAI format
-                    accumulated_tool_calls.append(
-                        {
-                            "id": chunk.toolCallId,
-                            "type": "function",
-                            "function": {
-                                "name": chunk.toolName,
-                                "arguments": orjson.dumps(chunk.input).decode("utf-8"),
-                            },
-                        }
-                    )
-                elif isinstance(chunk, StreamToolOutputAvailable):
-                    result_content = (
-                        chunk.output
-                        if isinstance(chunk.output, str)
-                        else orjson.dumps(chunk.output).decode("utf-8")
-                    )
-                    tool_response_messages.append(
-                        ChatMessage(
-                            role="tool",
-                            content=result_content,
-                            tool_call_id=chunk.toolCallId,
-                        )
-                    )
-                    has_done_tool_call = True
-                    # Track if any tool execution failed
-                    if not chunk.success:
-                        logger.warning(
-                            f"Tool {chunk.toolName} (ID: {chunk.toolCallId}) execution failed"
-                        )
-                    yield chunk
-                elif isinstance(chunk, StreamFinish):
-                    if not has_done_tool_call:
-                        # Emit text-end before finish if we received text but haven't closed it
+                    elif isinstance(chunk, StreamTextEnd):
+                        # Emit text-end after text completes
+                        if has_received_text and not text_streaming_ended:
+                            text_streaming_ended = True
+                            if assistant_response.content:
+                                logger.warn(
+                                    f"StreamTextEnd: Attempting to set output {assistant_response.content}"
+                                )
+                                span.update_trace(output=assistant_response.content)
+                                span.update(output=assistant_response.content)
+                            yield chunk
+                    elif isinstance(chunk, StreamToolInputStart):
+                        # Emit text-end before first tool call, but only if we've received text
                         if has_received_text and not text_streaming_ended:
                             yield StreamTextEnd(id=text_block_id)
                             text_streaming_ended = True
-                        has_yielded_end = True
                         yield chunk
-                elif isinstance(chunk, StreamError):
-                    has_yielded_error = True
-                elif isinstance(chunk, StreamUsage):
-                    session.usage.append(
-                        Usage(
-                            prompt_tokens=chunk.promptTokens,
-                            completion_tokens=chunk.completionTokens,
-                            total_tokens=chunk.totalTokens,
+                    elif isinstance(chunk, StreamToolInputAvailable):
+                        # Accumulate tool calls in OpenAI format
+                        accumulated_tool_calls.append(
+                            {
+                                "id": chunk.toolCallId,
+                                "type": "function",
+                                "function": {
+                                    "name": chunk.toolName,
+                                    "arguments": orjson.dumps(chunk.input).decode(
+                                        "utf-8"
+                                    ),
+                                },
+                            }
                         )
-                    )
-                else:
-                    logger.error(f"Unknown chunk type: {type(chunk)}", exc_info=True)
-        except Exception as e:
-            logger.error(f"Error during stream: {e!s}", exc_info=True)
+                    elif isinstance(chunk, StreamToolOutputAvailable):
+                        result_content = (
+                            chunk.output
+                            if isinstance(chunk.output, str)
+                            else orjson.dumps(chunk.output).decode("utf-8")
+                        )
+                        tool_response_messages.append(
+                            ChatMessage(
+                                role="tool",
+                                content=result_content,
+                                tool_call_id=chunk.toolCallId,
+                            )
+                        )
+                        has_done_tool_call = True
+                        # Track if any tool execution failed
+                        if not chunk.success:
+                            logger.warning(
+                                f"Tool {chunk.toolName} (ID: {chunk.toolCallId}) execution failed"
+                            )
+                        yield chunk
+                    elif isinstance(chunk, StreamFinish):
+                        if not has_done_tool_call:
+                            # Emit text-end before finish if we received text but haven't closed it
+                            if has_received_text and not text_streaming_ended:
+                                yield StreamTextEnd(id=text_block_id)
+                                text_streaming_ended = True
 
-            # Check if this is a retryable error (JSON parsing, incomplete tool calls, etc.)
-            is_retryable = isinstance(e, (orjson.JSONDecodeError, KeyError, TypeError))
+                            # Save assistant message before yielding finish to ensure it's persisted
+                            # even if client disconnects immediately after receiving StreamFinish
+                            if not has_saved_assistant_message:
+                                messages_to_save_early: list[ChatMessage] = []
+                                if accumulated_tool_calls:
+                                    assistant_response.tool_calls = (
+                                        accumulated_tool_calls
+                                    )
+                                if (
+                                    assistant_response.content
+                                    or assistant_response.tool_calls
+                                ):
+                                    messages_to_save_early.append(assistant_response)
+                                messages_to_save_early.extend(tool_response_messages)
 
-            if is_retryable and retry_count < config.max_retries:
-                logger.info(
-                    f"Retryable error encountered. Attempt {retry_count + 1}/{config.max_retries}"
+                                if messages_to_save_early:
+                                    session.messages.extend(messages_to_save_early)
+                                    logger.info(
+                                        f"Saving assistant message before StreamFinish: "
+                                        f"content_len={len(assistant_response.content or '')}, "
+                                        f"tool_calls={len(assistant_response.tool_calls or [])}, "
+                                        f"tool_responses={len(tool_response_messages)}"
+                                    )
+                                    await upsert_chat_session(session)
+                                    has_saved_assistant_message = True
+
+                            has_yielded_end = True
+                            yield chunk
+                    elif isinstance(chunk, StreamError):
+                        has_yielded_error = True
+                    elif isinstance(chunk, StreamUsage):
+                        session.usage.append(
+                            Usage(
+                                prompt_tokens=chunk.promptTokens,
+                                completion_tokens=chunk.completionTokens,
+                                total_tokens=chunk.totalTokens,
+                            )
+                        )
+                    else:
+                        logger.error(
+                            f"Unknown chunk type: {type(chunk)}", exc_info=True
+                        )
+                if assistant_response.content:
+                    langfuse.update_current_trace(output=assistant_response.content)
+                    langfuse.update_current_span(output=assistant_response.content)
+                elif tool_response_messages:
+                    langfuse.update_current_trace(output=str(tool_response_messages))
+                    langfuse.update_current_span(output=str(tool_response_messages))
+
+            except Exception as e:
+                logger.error(f"Error during stream: {e!s}", exc_info=True)
+
+                # Check if this is a retryable error (JSON parsing, incomplete tool calls, etc.)
+                is_retryable = isinstance(
+                    e, (orjson.JSONDecodeError, KeyError, TypeError)
                 )
-                should_retry = True
-            else:
-                # Non-retryable error or max retries exceeded
-                # Save any partial progress before reporting error
+
+                if is_retryable and retry_count < config.max_retries:
+                    logger.info(
+                        f"Retryable error encountered. Attempt {retry_count + 1}/{config.max_retries}"
+                    )
+                    should_retry = True
+                else:
+                    # Non-retryable error or max retries exceeded
+                    # Save any partial progress before reporting error
+                    messages_to_save: list[ChatMessage] = []
+
+                    # Add assistant message if it has content or tool calls
+                    if accumulated_tool_calls:
+                        assistant_response.tool_calls = accumulated_tool_calls
+                    if assistant_response.content or assistant_response.tool_calls:
+                        messages_to_save.append(assistant_response)
+
+                    # Add tool response messages after assistant message
+                    messages_to_save.extend(tool_response_messages)
+
+                    session.messages.extend(messages_to_save)
+                    await upsert_chat_session(session)
+
+                    if not has_yielded_error:
+                        error_message = str(e)
+                        if not is_retryable:
+                            error_message = f"Non-retryable error: {error_message}"
+                        elif retry_count >= config.max_retries:
+                            error_message = f"Max retries ({config.max_retries}) exceeded: {error_message}"
+
+                        error_response = StreamError(errorText=error_message)
+                        yield error_response
+                    if not has_yielded_end:
+                        yield StreamFinish()
+                    return
+
+            # Handle retry outside of exception handler to avoid nesting
+            if should_retry and retry_count < config.max_retries:
+                logger.info(
+                    f"Retrying stream_chat_completion for session {session_id}, attempt {retry_count + 1}"
+                )
+                async for chunk in stream_chat_completion(
+                    session_id=session.session_id,
+                    user_id=user_id,
+                    retry_count=retry_count + 1,
+                    session=session,
+                    context=context,
+                ):
+                    yield chunk
+                return  # Exit after retry to avoid double-saving in finally block
+
+            # Normal completion path - save session and handle tool call continuation
+            # Only save if we haven't already saved when StreamFinish was received
+            if not has_saved_assistant_message:
+                logger.info(
+                    f"Normal completion path: session={session.session_id}, "
+                    f"current message_count={len(session.messages)}"
+                )
+
+                # Build the messages list in the correct order
                 messages_to_save: list[ChatMessage] = []
 
-                # Add assistant message if it has content or tool calls
+                # Add assistant message with tool_calls if any
                 if accumulated_tool_calls:
                     assistant_response.tool_calls = accumulated_tool_calls
+                    logger.info(
+                        f"Added {len(accumulated_tool_calls)} tool calls to assistant message"
+                    )
                 if assistant_response.content or assistant_response.tool_calls:
                     messages_to_save.append(assistant_response)
+                    logger.info(
+                        f"Saving assistant message with content_len={len(assistant_response.content or '')}, tool_calls={len(assistant_response.tool_calls or [])}"
+                    )
 
                 # Add tool response messages after assistant message
                 messages_to_save.extend(tool_response_messages)
-
-                session.messages.extend(messages_to_save)
-                await upsert_chat_session(session)
-
-                if not has_yielded_error:
-                    error_message = str(e)
-                    if not is_retryable:
-                        error_message = f"Non-retryable error: {error_message}"
-                    elif retry_count >= config.max_retries:
-                        error_message = f"Max retries ({config.max_retries}) exceeded: {error_message}"
-
-                    error_response = StreamError(errorText=error_message)
-                    yield error_response
-                if not has_yielded_end:
-                    yield StreamFinish()
-                return
-
-        # Handle retry outside of exception handler to avoid nesting
-        if should_retry and retry_count < config.max_retries:
-            logger.info(
-                f"Retrying stream_chat_completion for session {session_id}, attempt {retry_count + 1}"
-            )
-            async for chunk in stream_chat_completion(
-                session_id=session.session_id,
-                user_id=user_id,
-                retry_count=retry_count + 1,
-                session=session,
-                context=context,
-            ):
-                yield chunk
-            return  # Exit after retry to avoid double-saving in finally block
-
-        # Normal completion path - save session and handle tool call continuation
-        logger.info(
-            f"Normal completion path: session={session.session_id}, "
-            f"current message_count={len(session.messages)}"
-        )
-
-        # Build the messages list in the correct order
-        messages_to_save: list[ChatMessage] = []
-
-        # Add assistant message with tool_calls if any
-        if accumulated_tool_calls:
-            assistant_response.tool_calls = accumulated_tool_calls
-            logger.info(
-                f"Added {len(accumulated_tool_calls)} tool calls to assistant message"
-            )
-        if assistant_response.content or assistant_response.tool_calls:
-            messages_to_save.append(assistant_response)
-            logger.info(
-                f"Saving assistant message with content_len={len(assistant_response.content or '')}, tool_calls={len(assistant_response.tool_calls or [])}"
-            )
-
-        # Add tool response messages after assistant message
-        messages_to_save.extend(tool_response_messages)
-        logger.info(
-            f"Saving {len(tool_response_messages)} tool response messages, "
-            f"total_to_save={len(messages_to_save)}"
-        )
-
-        session.messages.extend(messages_to_save)
-        logger.info(
-            f"Extended session messages, new message_count={len(session.messages)}"
-        )
-        await upsert_chat_session(session)
-
-        # If we did a tool call, stream the chat completion again to get the next response
-        if has_done_tool_call:
-            logger.info(
-                "Tool call executed, streaming chat completion again to get assistant response"
-            )
-            async for chunk in stream_chat_completion(
-                session_id=session.session_id,
-                user_id=user_id,
-                session=session,  # Pass session object to avoid Redis refetch
-                context=context,
-            ):
-                yield chunk
-
-    finally:
-        # Always end Langfuse observations to prevent resource leaks
-        # Guard against None and catch errors to avoid masking original exceptions
-        if generation is not None:
-            try:
-                latest_usage = session.usage[-1] if session.usage else None
-                generation.update(
-                    model=config.model,
-                    output={
-                        "content": assistant_response.content,
-                        "tool_calls": accumulated_tool_calls or None,
-                    },
-                    usage_details=(
-                        {
-                            "input": latest_usage.prompt_tokens,
-                            "output": latest_usage.completion_tokens,
-                            "total": latest_usage.total_tokens,
-                        }
-                        if latest_usage
-                        else None
-                    ),
+                logger.info(
+                    f"Saving {len(tool_response_messages)} tool response messages, "
+                    f"total_to_save={len(messages_to_save)}"
                 )
-                generation.end()
-            except Exception as e:
-                logger.warning(f"Failed to end Langfuse generation: {e}")
 
-        if trace is not None:
-            try:
-                if accumulated_tool_calls:
-                    trace.update_trace(output={"tool_calls": accumulated_tool_calls})
-                else:
-                    trace.update_trace(output={"response": assistant_response.content})
-                trace.end()
-            except Exception as e:
-                logger.warning(f"Failed to end Langfuse trace: {e}")
+                if messages_to_save:
+                    session.messages.extend(messages_to_save)
+                    logger.info(
+                        f"Extended session messages, new message_count={len(session.messages)}"
+                    )
+                    await upsert_chat_session(session)
+            else:
+                logger.info(
+                    "Assistant message already saved when StreamFinish was received, "
+                    "skipping duplicate save"
+                )
+
+            # If we did a tool call, stream the chat completion again to get the next response
+            if has_done_tool_call:
+                logger.info(
+                    "Tool call executed, streaming chat completion again to get assistant response"
+                )
+                async for chunk in stream_chat_completion(
+                    session_id=session.session_id,
+                    user_id=user_id,
+                    session=session,  # Pass session object to avoid Redis refetch
+                    context=context,
+                    tool_call_response=str(tool_response_messages),
+                ):
+                    yield chunk
 
 
 # Retry configuration for OpenAI API calls
@@ -900,5 +827,4 @@ async def _yield_tool_call(
         session=session,
     )
 
-    logger.info(f"Yielding Tool execution response: {tool_execution_response}")
     yield tool_execution_response

autogpt_platform/backend/backend/api/features/chat/tools/__init__.py

@@ -30,7 +30,7 @@ TOOL_REGISTRY: dict[str, BaseTool] = {
     "find_library_agent": FindLibraryAgentTool(),
     "run_agent": RunAgentTool(),
     "run_block": RunBlockTool(),
-    "agent_output": AgentOutputTool(),
+    "view_agent_output": AgentOutputTool(),
     "search_docs": SearchDocsTool(),
     "get_doc_page": GetDocPageTool(),
 }

autogpt_platform/backend/backend/api/features/chat/tools/add_understanding.py

@@ -3,6 +3,8 @@
 import logging
 from typing import Any
 
+from langfuse import observe
+
 from backend.api.features.chat.model import ChatSession
 from backend.data.understanding import (
     BusinessUnderstandingInput,
@@ -59,6 +61,7 @@ and automations for the user's specific needs."""
         """Requires authentication to store user-specific data."""
         return True
 
+    @observe(as_type="tool", name="add_understanding")
     async def _execute(
         self,
         user_id: str | None,

autogpt_platform/backend/backend/api/features/chat/tools/agent_output.py

@@ -5,6 +5,7 @@ import re
 from datetime import datetime, timedelta, timezone
 from typing import Any
 
+from langfuse import observe
 from pydantic import BaseModel, field_validator
 
 from backend.api.features.chat.model import ChatSession
@@ -103,7 +104,7 @@ class AgentOutputTool(BaseTool):
 
     @property
     def name(self) -> str:
-        return "agent_output"
+        return "view_agent_output"
 
     @property
     def description(self) -> str:
@@ -328,6 +329,7 @@ class AgentOutputTool(BaseTool):
             total_executions=len(available_executions) if available_executions else 1,
         )
 
+    @observe(as_type="tool", name="view_agent_output")
     async def _execute(
         self,
         user_id: str | None,

autogpt_platform/backend/backend/api/features/chat/tools/create_agent.py

@@ -3,6 +3,8 @@
 import logging
 from typing import Any
 
+from langfuse import observe
+
 from backend.api.features.chat.model import ChatSession
 
 from .agent_generator import (
@@ -78,6 +80,7 @@ class CreateAgentTool(BaseTool):
             "required": ["description"],
         }
 
+    @observe(as_type="tool", name="create_agent")
     async def _execute(
         self,
         user_id: str | None,

autogpt_platform/backend/backend/api/features/chat/tools/edit_agent.py

@@ -3,6 +3,8 @@
 import logging
 from typing import Any
 
+from langfuse import observe
+
 from backend.api.features.chat.model import ChatSession
 
 from .agent_generator import (
@@ -85,6 +87,7 @@ class EditAgentTool(BaseTool):
             "required": ["agent_id", "changes"],
         }
 
+    @observe(as_type="tool", name="edit_agent")
     async def _execute(
         self,
         user_id: str | None,

autogpt_platform/backend/backend/api/features/chat/tools/find_agent.py

@@ -2,6 +2,8 @@
 
 from typing import Any
 
+from langfuse import observe
+
 from backend.api.features.chat.model import ChatSession
 
 from .agent_search import search_agents
@@ -35,6 +37,7 @@ class FindAgentTool(BaseTool):
             "required": ["query"],
         }
 
+    @observe(as_type="tool", name="find_agent")
     async def _execute(
         self, user_id: str | None, session: ChatSession, **kwargs
     ) -> ToolResponseBase:

autogpt_platform/backend/backend/api/features/chat/tools/find_block.py

@@ -1,6 +1,7 @@
 import logging
 from typing import Any
 
+from langfuse import observe
 from prisma.enums import ContentType
 
 from backend.api.features.chat.model import ChatSession
@@ -55,6 +56,7 @@ class FindBlockTool(BaseTool):
     def requires_auth(self) -> bool:
         return True
 
+    @observe(as_type="tool", name="find_block")
     async def _execute(
         self,
         user_id: str | None,

autogpt_platform/backend/backend/api/features/chat/tools/find_library_agent.py

@@ -2,6 +2,8 @@
 
 from typing import Any
 
+from langfuse import observe
+
 from backend.api.features.chat.model import ChatSession
 
 from .agent_search import search_agents
@@ -41,6 +43,7 @@ class FindLibraryAgentTool(BaseTool):
     def requires_auth(self) -> bool:
         return True
 
+    @observe(as_type="tool", name="find_library_agent")
     async def _execute(
         self, user_id: str | None, session: ChatSession, **kwargs
     ) -> ToolResponseBase:

autogpt_platform/backend/backend/api/features/chat/tools/get_doc_page.py

@@ -4,6 +4,8 @@ import logging
 from pathlib import Path
 from typing import Any
 
+from langfuse import observe
+
 from backend.api.features.chat.model import ChatSession
 from backend.api.features.chat.tools.base import BaseTool
 from backend.api.features.chat.tools.models import (
@@ -71,6 +73,7 @@ class GetDocPageTool(BaseTool):
         url_path = path.rsplit(".", 1)[0] if "." in path else path
         return f"{DOCS_BASE_URL}/{url_path}"
 
+    @observe(as_type="tool", name="get_doc_page")
     async def _execute(
         self,
         user_id: str | None,

autogpt_platform/backend/backend/api/features/chat/tools/run_agent.py

@@ -3,6 +3,7 @@
 import logging
 from typing import Any
 
+from langfuse import observe
 from pydantic import BaseModel, Field, field_validator
 
 from backend.api.features.chat.config import ChatConfig
@@ -32,7 +33,7 @@ from .models import (
     UserReadiness,
 )
 from .utils import (
-    check_user_has_required_credentials,
+    build_missing_credentials_from_graph,
     extract_credentials_from_schema,
     fetch_graph_from_store_slug,
     get_or_create_library_agent,
@@ -154,6 +155,7 @@ class RunAgentTool(BaseTool):
         """All operations require authentication."""
         return True
 
+    @observe(as_type="tool", name="run_agent")
     async def _execute(
         self,
         user_id: str | None,
@@ -235,15 +237,13 @@ class RunAgentTool(BaseTool):
                 # Return credentials needed response with input data info
                 # The UI handles credential setup automatically, so the message
                 # focuses on asking about input data
-                credentials = extract_credentials_from_schema(
-                    graph.credentials_input_schema
+                requirements_creds_dict = build_missing_credentials_from_graph(
+                    graph, None
                 )
-                missing_creds_check = await check_user_has_required_credentials(
-                    user_id, credentials
+                missing_credentials_dict = build_missing_credentials_from_graph(
+                    graph, graph_credentials
                 )
-                missing_credentials_dict = {
-                    c.id: c.model_dump() for c in missing_creds_check
-                }
+                requirements_creds_list = list(requirements_creds_dict.values())
 
                 return SetupRequirementsResponse(
                     message=self._build_inputs_message(graph, MSG_WHAT_VALUES_TO_USE),
@@ -257,7 +257,7 @@ class RunAgentTool(BaseTool):
                             ready_to_run=False,
                         ),
                         requirements={
-                            "credentials": [c.model_dump() for c in credentials],
+                            "credentials": requirements_creds_list,
                             "inputs": self._get_inputs_list(graph.input_schema),
                             "execution_modes": self._get_execution_modes(graph),
                         },

autogpt_platform/backend/backend/api/features/chat/tools/run_block.py

@@ -4,6 +4,8 @@ import logging
 from collections import defaultdict
 from typing import Any
 
+from langfuse import observe
+
 from backend.api.features.chat.model import ChatSession
 from backend.data.block import get_block
 from backend.data.execution import ExecutionContext
@@ -20,6 +22,7 @@ from .models import (
     ToolResponseBase,
     UserReadiness,
 )
+from .utils import build_missing_credentials_from_field_info
 
 logger = logging.getLogger(__name__)
 
@@ -127,6 +130,7 @@ class RunBlockTool(BaseTool):
 
         return matched_credentials, missing_credentials
 
+    @observe(as_type="tool", name="run_block")
     async def _execute(
         self,
         user_id: str | None,
@@ -186,7 +190,11 @@ class RunBlockTool(BaseTool):
 
         if missing_credentials:
             # Return setup requirements response with missing credentials
-            missing_creds_dict = {c.id: c.model_dump() for c in missing_credentials}
+            credentials_fields_info = block.input_schema.get_credentials_fields_info()
+            missing_creds_dict = build_missing_credentials_from_field_info(
+                credentials_fields_info, set(matched_credentials.keys())
+            )
+            missing_creds_list = list(missing_creds_dict.values())
 
             return SetupRequirementsResponse(
                 message=(
@@ -203,7 +211,7 @@ class RunBlockTool(BaseTool):
                         ready_to_run=False,
                     ),
                     requirements={
-                        "credentials": [c.model_dump() for c in missing_credentials],
+                        "credentials": missing_creds_list,
                         "inputs": self._get_inputs_list(block),
                         "execution_modes": ["immediate"],
                     },

autogpt_platform/backend/backend/api/features/chat/tools/search_docs.py

@@ -3,6 +3,7 @@
 import logging
 from typing import Any
 
+from langfuse import observe
 from prisma.enums import ContentType
 
 from backend.api.features.chat.model import ChatSession
@@ -87,6 +88,7 @@ class SearchDocsTool(BaseTool):
         url_path = path.rsplit(".", 1)[0] if "." in path else path
         return f"{DOCS_BASE_URL}/{url_path}"
 
+    @observe(as_type="tool", name="search_docs")
     async def _execute(
         self,
         user_id: str | None,

autogpt_platform/backend/backend/api/features/chat/tools/utils.py

@@ -8,7 +8,7 @@ from backend.api.features.library import model as library_model
 from backend.api.features.store import db as store_db
 from backend.data import graph as graph_db
 from backend.data.graph import GraphModel
-from backend.data.model import CredentialsMetaInput
+from backend.data.model import CredentialsFieldInfo, CredentialsMetaInput
 from backend.integrations.creds_manager import IntegrationCredentialsManager
 from backend.util.exceptions import NotFoundError
 
@@ -89,6 +89,59 @@ def extract_credentials_from_schema(
     return credentials
 
 
+def _serialize_missing_credential(
+    field_key: str, field_info: CredentialsFieldInfo
+) -> dict[str, Any]:
+    """
+    Convert credential field info into a serializable dict that preserves all supported
+    credential types (e.g., api_key + oauth2) so the UI can offer multiple options.
+    """
+    supported_types = sorted(field_info.supported_types)
+    provider = next(iter(field_info.provider), "unknown")
+    scopes = sorted(field_info.required_scopes or [])
+
+    return {
+        "id": field_key,
+        "title": field_key.replace("_", " ").title(),
+        "provider": provider,
+        "provider_name": provider.replace("_", " ").title(),
+        "type": supported_types[0] if supported_types else "api_key",
+        "types": supported_types,
+        "scopes": scopes,
+    }
+
+
+def build_missing_credentials_from_graph(
+    graph: GraphModel, matched_credentials: dict[str, CredentialsMetaInput] | None
+) -> dict[str, Any]:
+    """
+    Build a missing_credentials mapping from a graph's aggregated credentials inputs,
+    preserving all supported credential types for each field.
+    """
+    matched_keys = set(matched_credentials.keys()) if matched_credentials else set()
+    aggregated_fields = graph.aggregate_credentials_inputs()
+
+    return {
+        field_key: _serialize_missing_credential(field_key, field_info)
+        for field_key, (field_info, _node_fields) in aggregated_fields.items()
+        if field_key not in matched_keys
+    }
+
+
+def build_missing_credentials_from_field_info(
+    credential_fields: dict[str, CredentialsFieldInfo],
+    matched_keys: set[str],
+) -> dict[str, Any]:
+    """
+    Build missing_credentials mapping from a simple credentials field info dictionary.
+    """
+    return {
+        field_key: _serialize_missing_credential(field_key, field_info)
+        for field_key, field_info in credential_fields.items()
+        if field_key not in matched_keys
+    }
+
+
 def extract_credentials_as_dict(
     credentials_input_schema: dict[str, Any] | None,
 ) -> dict[str, CredentialsMetaInput]:

autogpt_platform/backend/backend/data/understanding.py

@@ -328,6 +328,8 @@ async def clear_business_understanding(user_id: str) -> bool:
 
 def format_understanding_for_prompt(understanding: BusinessUnderstanding) -> str:
     """Format business understanding as text for system prompt injection."""
+    if not understanding:
+        return ""
     sections = []
 
     # User info section

autogpt_platform/backend/scripts/generate_block_docs.py

@@ -366,12 +366,12 @@ def generate_block_markdown(
     lines.append("")
 
     # What it is (full description)
-    lines.append(f"### What it is")
+    lines.append("### What it is")
     lines.append(block.description or "No description available.")
     lines.append("")
 
     # How it works (manual section)
-    lines.append(f"### How it works")
+    lines.append("### How it works")
     how_it_works = manual_content.get(
         "how_it_works", "_Add technical explanation here._"
     )
@@ -383,7 +383,7 @@ def generate_block_markdown(
     # Inputs table (auto-generated)
     visible_inputs = [f for f in block.inputs if not f.hidden]
     if visible_inputs:
-        lines.append(f"### Inputs")
+        lines.append("### Inputs")
         lines.append("")
         lines.append("| Input | Description | Type | Required |")
         lines.append("|-------|-------------|------|----------|")
@@ -400,7 +400,7 @@ def generate_block_markdown(
     # Outputs table (auto-generated)
     visible_outputs = [f for f in block.outputs if not f.hidden]
     if visible_outputs:
-        lines.append(f"### Outputs")
+        lines.append("### Outputs")
         lines.append("")
         lines.append("| Output | Description | Type |")
         lines.append("|--------|-------------|------|")
@@ -414,7 +414,7 @@ def generate_block_markdown(
         lines.append("")
 
     # Possible use case (manual section)
-    lines.append(f"### Possible use case")
+    lines.append("### Possible use case")
     use_case = manual_content.get("use_case", "_Add practical use case examples here._")
     lines.append("<!-- MANUAL: use_case -->")
     lines.append(use_case)

autogpt_platform/frontend/CONTRIBUTING.md

@@ -175,6 +175,8 @@ While server components and actions are cool and cutting-edge, they introduce a
 
 - Prefer [React Query](https://tanstack.com/query/latest/docs/framework/react/overview) for server state, colocated near consumers (see [state colocation](https://kentcdodds.com/blog/state-colocation-will-make-your-react-app-faster))
 - Co-locate UI state inside components/hooks; keep global state minimal
+- Avoid `useMemo` and `useCallback` unless you have a measured performance issue
+- Do not abuse `useEffect`; prefer state colocation and derive values directly when possible
 
 ### Styling and components
 
@@ -549,9 +551,48 @@ Files:
 Types:
 
 - Prefer `interface` for object shapes
-- Component props should be `interface Props { ... }`
+- Component props should be `interface Props { ... }` (not exported)
+- Only use specific exported names (e.g., `export interface MyComponentProps`) when the interface needs to be used outside the component
+- Keep type definitions inline with the component - do not create separate `types.ts` files unless types are shared across multiple files
 - Use precise types; avoid `any` and unsafe casts
 
+**Props naming examples:**
+
+```tsx
+// ✅ Good - internal props, not exported
+interface Props {
+  title: string;
+  onClose: () => void;
+}
+
+export function Modal({ title, onClose }: Props) {
+  // ...
+}
+
+// ✅ Good - exported when needed externally
+export interface ModalProps {
+  title: string;
+  onClose: () => void;
+}
+
+export function Modal({ title, onClose }: ModalProps) {
+  // ...
+}
+
+// ❌ Bad - unnecessarily specific name for internal use
+interface ModalComponentProps {
+  title: string;
+  onClose: () => void;
+}
+
+// ❌ Bad - separate types.ts file for single component
+// types.ts
+export interface ModalProps { ... }
+
+// Modal.tsx
+import type { ModalProps } from './types';
+```
+
 Parameters:
 
 - If more than one parameter is needed, pass a single `Args` object for clarity

autogpt_platform/frontend/src/app/(no-navbar)/logout/page.tsx

@@ -0,0 +1,45 @@
+"use client";
+
+import { LoadingSpinner } from "@/components/atoms/LoadingSpinner/LoadingSpinner";
+import { Text } from "@/components/atoms/Text/Text";
+import { useSupabase } from "@/lib/supabase/hooks/useSupabase";
+import { useRouter } from "next/navigation";
+import { useEffect, useRef } from "react";
+
+const LOGOUT_REDIRECT_DELAY_MS = 400;
+
+function wait(ms: number): Promise<void> {
+  return new Promise(function resolveAfterDelay(resolve) {
+    setTimeout(resolve, ms);
+  });
+}
+
+export default function LogoutPage() {
+  const { logOut } = useSupabase();
+  const router = useRouter();
+  const hasStartedRef = useRef(false);
+
+  useEffect(function handleLogoutEffect() {
+    if (hasStartedRef.current) return;
+    hasStartedRef.current = true;
+
+    async function runLogout() {
+      await logOut();
+      await wait(LOGOUT_REDIRECT_DELAY_MS);
+      router.replace("/login");
+    }
+
+    void runLogout();
+  }, []);
+
+  return (
+    <div className="flex min-h-screen items-center justify-center px-4">
+      <div className="flex flex-col items-center justify-center gap-4 py-8">
+        <LoadingSpinner size="large" />
+        <Text variant="body" className="text-center">
+          Logging you out...
+        </Text>
+      </div>
+    </div>
+  );
+}

autogpt_platform/frontend/src/app/(platform)/auth/callback/route.ts

@@ -9,7 +9,7 @@ export async function GET(request: Request) {
   const { searchParams, origin } = new URL(request.url);
   const code = searchParams.get("code");
 
-  let next = "/marketplace";
+  let next = "/";
 
   if (code) {
     const supabase = await getServerSupabase();

autogpt_platform/frontend/src/app/(platform)/build/components/BuilderActions/components/RunGraph/RunGraph.tsx

@@ -5,10 +5,11 @@ import {
   TooltipContent,
   TooltipTrigger,
 } from "@/components/atoms/Tooltip/BaseTooltip";
-import { PlayIcon, StopIcon } from "@phosphor-icons/react";
+import { CircleNotchIcon, PlayIcon, StopIcon } from "@phosphor-icons/react";
 import { useShallow } from "zustand/react/shallow";
 import { RunInputDialog } from "../RunInputDialog/RunInputDialog";
 import { useRunGraph } from "./useRunGraph";
+import { cn } from "@/lib/utils";
 
 export const RunGraph = ({ flowID }: { flowID: string | null }) => {
   const {
@@ -24,6 +25,31 @@ export const RunGraph = ({ flowID }: { flowID: string | null }) => {
     useShallow((state) => state.isGraphRunning),
   );
 
+  const isLoading = isExecutingGraph || isTerminatingGraph || isSaving;
+
+  // Determine which icon to show with proper animation
+  const renderIcon = () => {
+    const iconClass = cn(
+      "size-4 transition-transform duration-200 ease-out",
+      !isLoading && "group-hover:scale-110",
+    );
+
+    if (isLoading) {
+      return (
+        <CircleNotchIcon
+          className={cn(iconClass, "animate-spin")}
+          weight="bold"
+        />
+      );
+    }
+
+    if (isGraphRunning) {
+      return <StopIcon className={iconClass} weight="fill" />;
+    }
+
+    return <PlayIcon className={iconClass} weight="fill" />;
+  };
+
   return (
     <>
       <Tooltip>
@@ -33,18 +59,18 @@ export const RunGraph = ({ flowID }: { flowID: string | null }) => {
             variant={isGraphRunning ? "destructive" : "primary"}
             data-id={isGraphRunning ? "stop-graph-button" : "run-graph-button"}
             onClick={isGraphRunning ? handleStopGraph : handleRunGraph}
-            disabled={!flowID || isExecutingGraph || isTerminatingGraph}
-            loading={isExecutingGraph || isTerminatingGraph || isSaving}
+            disabled={!flowID || isLoading}
+            className="group"
           >
-            {!isGraphRunning ? (
-              <PlayIcon className="size-4" />
-            ) : (
-              <StopIcon className="size-4" />
-            )}
+            {renderIcon()}
           </Button>
         </TooltipTrigger>
         <TooltipContent>
-          {isGraphRunning ? "Stop agent" : "Run agent"}
+          {isLoading
+            ? "Processing..."
+            : isGraphRunning
+              ? "Stop agent"
+              : "Run agent"}
         </TooltipContent>
       </Tooltip>
       <RunInputDialog

autogpt_platform/frontend/src/app/(platform)/build/components/BuilderActions/components/RunInputDialog/RunInputDialog.tsx

@@ -10,6 +10,7 @@ import { useRunInputDialog } from "./useRunInputDialog";
 import { CronSchedulerDialog } from "../CronSchedulerDialog/CronSchedulerDialog";
 import { useTutorialStore } from "@/app/(platform)/build/stores/tutorialStore";
 import { useEffect } from "react";
+import { CredentialsGroupedView } from "@/components/contextual/CredentialsInput/components/CredentialsGroupedView/CredentialsGroupedView";
 
 export const RunInputDialog = ({
   isOpen,
@@ -23,19 +24,17 @@ export const RunInputDialog = ({
   const hasInputs = useGraphStore((state) => state.hasInputs);
   const hasCredentials = useGraphStore((state) => state.hasCredentials);
   const inputSchema = useGraphStore((state) => state.inputSchema);
-  const credentialsSchema = useGraphStore(
-    (state) => state.credentialsInputSchema,
-  );
 
   const {
-    credentialsUiSchema,
+    credentialFields,
+    requiredCredentials,
     handleManualRun,
     handleInputChange,
     openCronSchedulerDialog,
     setOpenCronSchedulerDialog,
     inputValues,
     credentialValues,
-    handleCredentialChange,
+    handleCredentialFieldChange,
     isExecutingGraph,
   } = useRunInputDialog({ setIsOpen });
 
@@ -62,67 +61,67 @@ export const RunInputDialog = ({
           isOpen,
           set: setIsOpen,
         }}
-        styling={{ maxWidth: "600px", minWidth: "600px" }}
+        styling={{ maxWidth: "700px", minWidth: "700px" }}
       >
         <Dialog.Content>
-          <div className="space-y-6 p-1" data-id="run-input-dialog-content">
-            {/* Credentials Section */}
-            {hasCredentials() && (
-              <div data-id="run-input-credentials-section">
-                <div className="mb-4">
-                  <Text variant="h4" className="text-gray-900">
-                    Credentials
-                  </Text>
+          <div
+            className="grid grid-cols-[1fr_auto] gap-10 p-1"
+            data-id="run-input-dialog-content"
+          >
+            <div className="space-y-6">
+              {/* Credentials Section */}
+              {hasCredentials() && credentialFields.length > 0 && (
+                <div data-id="run-input-credentials-section">
+                  <div className="mb-4">
+                    <Text variant="h4" className="text-gray-900">
+                      Credentials
+                    </Text>
+                  </div>
+                  <div className="px-2" data-id="run-input-credentials-form">
+                    <CredentialsGroupedView
+                      credentialFields={credentialFields}
+                      requiredCredentials={requiredCredentials}
+                      inputCredentials={credentialValues}
+                      inputValues={inputValues}
+                      onCredentialChange={handleCredentialFieldChange}
+                    />
+                  </div>
                 </div>
-                <div className="px-2" data-id="run-input-credentials-form">
-                  <FormRenderer
-                    jsonSchema={credentialsSchema as RJSFSchema}
-                    handleChange={(v) => handleCredentialChange(v.formData)}
-                    uiSchema={credentialsUiSchema}
-                    initialValues={{}}
-                    formContext={{
-                      showHandles: false,
-                      size: "large",
-                      showOptionalToggle: false,
-                    }}
-                  />
-                </div>
-              </div>
-            )}
+              )}
 
-            {/* Inputs Section */}
-            {hasInputs() && (
-              <div data-id="run-input-inputs-section">
-                <div className="mb-4">
-                  <Text variant="h4" className="text-gray-900">
-                    Inputs
-                  </Text>
+              {/* Inputs Section */}
+              {hasInputs() && (
+                <div data-id="run-input-inputs-section">
+                  <div className="mb-4">
+                    <Text variant="h4" className="text-gray-900">
+                      Inputs
+                    </Text>
+                  </div>
+                  <div data-id="run-input-inputs-form">
+                    <FormRenderer
+                      jsonSchema={inputSchema as RJSFSchema}
+                      handleChange={(v) => handleInputChange(v.formData)}
+                      uiSchema={uiSchema}
+                      initialValues={{}}
+                      formContext={{
+                        showHandles: false,
+                        size: "large",
+                      }}
+                    />
+                  </div>
                 </div>
-                <div data-id="run-input-inputs-form">
-                  <FormRenderer
-                    jsonSchema={inputSchema as RJSFSchema}
-                    handleChange={(v) => handleInputChange(v.formData)}
-                    uiSchema={uiSchema}
-                    initialValues={{}}
-                    formContext={{
-                      showHandles: false,
-                      size: "large",
-                    }}
-                  />
-                </div>
-              </div>
-            )}
+              )}
+            </div>
 
-            {/* Action Button */}
             <div
-              className="flex justify-end pt-2"
+              className="flex flex-col items-end justify-start"
               data-id="run-input-actions-section"
             >
               {purpose === "run" && (
                 <Button
                   variant="primary"
                   size="large"
-                  className="group h-fit min-w-0 gap-2"
+                  className="group h-fit min-w-0 gap-2 px-10"
                   onClick={handleManualRun}
                   loading={isExecutingGraph}
                   data-id="run-input-manual-run-button"
@@ -137,7 +136,7 @@ export const RunInputDialog = ({
                 <Button
                   variant="primary"
                   size="large"
-                  className="group h-fit min-w-0 gap-2"
+                  className="group h-fit min-w-0 gap-2 px-10"
                   onClick={() => setOpenCronSchedulerDialog(true)}
                   data-id="run-input-schedule-button"
                 >

autogpt_platform/frontend/src/app/(platform)/build/components/BuilderActions/components/RunInputDialog/useRunInputDialog.ts

@@ -7,12 +7,11 @@ import {
   GraphExecutionMeta,
 } from "@/lib/autogpt-server-api";
 import { parseAsInteger, parseAsString, useQueryStates } from "nuqs";
-import { useMemo, useState } from "react";
-import { uiSchema } from "../../../FlowEditor/nodes/uiSchema";
-import { isCredentialFieldSchema } from "@/components/renderers/InputRenderer/custom/CredentialField/helpers";
+import { useCallback, useMemo, useState } from "react";
 import { useNodeStore } from "@/app/(platform)/build/stores/nodeStore";
 import { useToast } from "@/components/molecules/Toast/use-toast";
 import { useReactFlow } from "@xyflow/react";
+import type { CredentialField } from "@/components/contextual/CredentialsInput/components/CredentialsGroupedView/helpers";
 
 export const useRunInputDialog = ({
   setIsOpen,
@@ -120,27 +119,32 @@ export const useRunInputDialog = ({
       },
     });
 
-  // We are rendering the credentials field differently compared to other fields.
-  // In the node, we have the field name as "credential" - so our library catches it and renders it differently.
-  // But here we have a different name, something like `Firecrawl credentials`, so here we are telling the library that this field is a credential field type.
+  // Convert credentials schema to credential fields array for CredentialsGroupedView
+  const credentialFields: CredentialField[] = useMemo(() => {
+    if (!credentialsSchema?.properties) return [];
+    return Object.entries(credentialsSchema.properties);
+  }, [credentialsSchema]);
 
-  const credentialsUiSchema = useMemo(() => {
-    const dynamicUiSchema: any = { ...uiSchema };
+  // Get required credentials as a Set
+  const requiredCredentials = useMemo(() => {
+    return new Set<string>(credentialsSchema?.required || []);
+  }, [credentialsSchema]);
 
-    if (credentialsSchema?.properties) {
-      Object.keys(credentialsSchema.properties).forEach((fieldName) => {
-        const fieldSchema = credentialsSchema.properties[fieldName];
-        if (isCredentialFieldSchema(fieldSchema)) {
-          dynamicUiSchema[fieldName] = {
-            ...dynamicUiSchema[fieldName],
-            "ui:field": "custom/credential_field",
-          };
+  // Handler for individual credential changes
+  const handleCredentialFieldChange = useCallback(
+    (key: string, value?: CredentialsMetaInput) => {
+      setCredentialValues((prev) => {
+        if (value) {
+          return { ...prev, [key]: value };
+        } else {
+          const next = { ...prev };
+          delete next[key];
+          return next;
         }
       });
-    }
-
-    return dynamicUiSchema;
-  }, [credentialsSchema]);
+    },
+    [],
+  );
 
   const handleManualRun = async () => {
     // Filter out incomplete credentials (those without a valid id)
@@ -173,12 +177,14 @@ export const useRunInputDialog = ({
   };
 
   return {
-    credentialsUiSchema,
+    credentialFields,
+    requiredCredentials,
     inputValues,
     credentialValues,
     isExecutingGraph,
     handleInputChange,
     handleCredentialChange,
+    handleCredentialFieldChange,
     handleManualRun,
     openCronSchedulerDialog,
     setOpenCronSchedulerDialog,

autogpt_platform/frontend/src/app/(platform)/build/components/FlowEditor/Flow/components/CustomControl.tsx

@@ -53,14 +53,14 @@ export const CustomControls = memo(
     const controls = [
       {
         id: "zoom-in-button",
-        icon: <PlusIcon className="size-4" />,
+        icon: <PlusIcon className="size-3.5 text-zinc-600" />,
         label: "Zoom In",
         onClick: () => zoomIn(),
         className: "h-10 w-10 border-none",
       },
       {
         id: "zoom-out-button",
-        icon: <MinusIcon className="size-4" />,
+        icon: <MinusIcon className="size-3.5 text-zinc-600" />,
         label: "Zoom Out",
         onClick: () => zoomOut(),
         className: "h-10 w-10 border-none",
@@ -68,9 +68,9 @@ export const CustomControls = memo(
       {
         id: "tutorial-button",
         icon: isTutorialLoading ? (
-          <CircleNotchIcon className="size-4 animate-spin" />
+          <CircleNotchIcon className="size-3.5 animate-spin text-zinc-600" />
         ) : (
-          <ChalkboardIcon className="size-4" />
+          <ChalkboardIcon className="size-3.5 text-zinc-600" />
         ),
         label: isTutorialLoading ? "Loading Tutorial..." : "Start Tutorial",
         onClick: handleTutorialClick,
@@ -79,7 +79,7 @@ export const CustomControls = memo(
       },
       {
         id: "fit-view-button",
-        icon: <FrameCornersIcon className="size-4" />,
+        icon: <FrameCornersIcon className="size-3.5 text-zinc-600" />,
         label: "Fit View",
         onClick: () => fitView({ padding: 0.2, duration: 800, maxZoom: 1 }),
         className: "h-10 w-10 border-none",
@@ -87,9 +87,9 @@ export const CustomControls = memo(
       {
         id: "lock-button",
         icon: !isLocked ? (
-          <LockOpenIcon className="size-4" />
+          <LockOpenIcon className="size-3.5 text-zinc-600" />
         ) : (
-          <LockIcon className="size-4" />
+          <LockIcon className="size-3.5 text-zinc-600" />
         ),
         label: "Toggle Lock",
         onClick: () => setIsLocked(!isLocked),

autogpt_platform/frontend/src/app/(platform)/build/components/FlowEditor/Flow/useFlow.ts

@@ -139,14 +139,6 @@ export const useFlow = () => {
       useNodeStore.getState().setNodes([]);
       useNodeStore.getState().clearResolutionState();
       addNodes(customNodes);
-
-      // Sync hardcoded values with handle IDs.
-      // If a key–value field has a key without a value, the backend omits it from hardcoded values.
-      // But if a handleId exists for that key, it causes inconsistency.
-      // This ensures hardcoded values stay in sync with handle IDs.
-      customNodes.forEach((node) => {
-        useNodeStore.getState().syncHardcodedValuesWithHandleIds(node.id);
-      });
     }
   }, [customNodes, addNodes]);
 
@@ -158,6 +150,14 @@ export const useFlow = () => {
     }
   }, [graph?.links, addLinks]);
 
+  useEffect(() => {
+    if (customNodes.length > 0 && graph?.links) {
+      customNodes.forEach((node) => {
+        useNodeStore.getState().syncHardcodedValuesWithHandleIds(node.id);
+      });
+    }
+  }, [customNodes, graph?.links]);
+
   // update node execution status in nodes
   useEffect(() => {
     if (

autogpt_platform/frontend/src/app/(platform)/build/components/FlowEditor/edges/CustomEdge.tsx

@@ -19,6 +19,8 @@ export type CustomEdgeData = {
   beadUp?: number;
   beadDown?: number;
   beadData?: Map<string, NodeExecutionResult["status"]>;
+  edgeColorClass?: string;
+  edgeHexColor?: string;
 };
 
 export type CustomEdge = XYEdge<CustomEdgeData, "custom">;
@@ -36,7 +38,6 @@ const CustomEdge = ({
   selected,
 }: EdgeProps<CustomEdge>) => {
   const removeConnection = useEdgeStore((state) => state.removeEdge);
-  // Subscribe to the brokenEdgeIDs map and check if this edge is broken across any node
   const isBroken = useNodeStore((state) => state.isEdgeBroken(id));
   const [isHovered, setIsHovered] = useState(false);
 
@@ -52,6 +53,7 @@ const CustomEdge = ({
   const isStatic = data?.isStatic ?? false;
   const beadUp = data?.beadUp ?? 0;
   const beadDown = data?.beadDown ?? 0;
+  const edgeColorClass = data?.edgeColorClass;
 
   const handleRemoveEdge = () => {
     removeConnection(id);
@@ -70,7 +72,9 @@ const CustomEdge = ({
             ? "!stroke-red-500 !stroke-[2px] [stroke-dasharray:4]"
             : selected
               ? "stroke-zinc-800"
-              : "stroke-zinc-500/50 hover:stroke-zinc-500",
+              : edgeColorClass
+                ? cn(edgeColorClass, "opacity-70 hover:opacity-100")
+                : "stroke-zinc-500/50 hover:stroke-zinc-500",
         )}
       />
       <JSBeads

autogpt_platform/frontend/src/app/(platform)/build/components/FlowEditor/edges/useCustomEdge.ts

@@ -8,6 +8,7 @@ import { useCallback } from "react";
 import { useNodeStore } from "../../../stores/nodeStore";
 import { useHistoryStore } from "../../../stores/historyStore";
 import { CustomEdge } from "./CustomEdge";
+import { getEdgeColorFromOutputType } from "../nodes/helpers";
 
 export const useCustomEdge = () => {
   const edges = useEdgeStore((s) => s.edges);
@@ -34,8 +35,13 @@ export const useCustomEdge = () => {
       if (exists) return;
 
       const nodes = useNodeStore.getState().nodes;
-      const isStatic = nodes.find((n) => n.id === conn.source)?.data
-        ?.staticOutput;
+      const sourceNode = nodes.find((n) => n.id === conn.source);
+      const isStatic = sourceNode?.data?.staticOutput;
+
+      const { colorClass, hexColor } = getEdgeColorFromOutputType(
+        sourceNode?.data?.outputSchema,
+        conn.sourceHandle,
+      );
 
       addEdge({
         source: conn.source,
@@ -44,6 +50,8 @@ export const useCustomEdge = () => {
         targetHandle: conn.targetHandle,
         data: {
           isStatic,
+          edgeColorClass: colorClass,
+          edgeHexColor: hexColor,
         },
       });
     },

autogpt_platform/frontend/src/app/(platform)/build/components/FlowEditor/nodes/CustomNode/components/NodeOutput/NodeOutput.tsx

@@ -1,22 +1,21 @@
 import { Button } from "@/components/atoms/Button/Button";
 import { Text } from "@/components/atoms/Text/Text";
+import {
+  Accordion,
+  AccordionContent,
+  AccordionItem,
+  AccordionTrigger,
+} from "@/components/molecules/Accordion/Accordion";
 import { beautifyString, cn } from "@/lib/utils";
-import { CaretDownIcon, CopyIcon, CheckIcon } from "@phosphor-icons/react";
+import { CopyIcon, CheckIcon } from "@phosphor-icons/react";
 import { NodeDataViewer } from "./components/NodeDataViewer/NodeDataViewer";
 import { ContentRenderer } from "./components/ContentRenderer";
 import { useNodeOutput } from "./useNodeOutput";
 import { ViewMoreData } from "./components/ViewMoreData";
 
 export const NodeDataRenderer = ({ nodeId }: { nodeId: string }) => {
-  const {
-    outputData,
-    isExpanded,
-    setIsExpanded,
-    copiedKey,
-    handleCopy,
-    executionResultId,
-    inputData,
-  } = useNodeOutput(nodeId);
+  const { outputData, copiedKey, handleCopy, executionResultId, inputData } =
+    useNodeOutput(nodeId);
 
   if (Object.keys(outputData).length === 0) {
     return null;
@@ -25,122 +24,117 @@ export const NodeDataRenderer = ({ nodeId }: { nodeId: string }) => {
   return (
     <div
       data-tutorial-id={`node-output`}
-      className="flex flex-col gap-3 rounded-b-xl border-t border-zinc-200 px-4 py-4"
+      className="rounded-b-xl border-t border-zinc-200 px-4 py-2"
     >
-      <div className="flex items-center justify-between">
-        <Text variant="body-medium" className="!font-semibold text-slate-700">
-          Node Output
-        </Text>
-        <Button
-          variant="ghost"
-          size="small"
-          onClick={() => setIsExpanded(!isExpanded)}
-          className="h-fit min-w-0 p-1 text-slate-600 hover:text-slate-900"
-        >
-          <CaretDownIcon
-            size={16}
-            weight="bold"
-            className={`transition-transform ${isExpanded ? "rotate-180" : ""}`}
-          />
-        </Button>
-      </div>
+      <Accordion type="single" collapsible defaultValue="node-output">
+        <AccordionItem value="node-output" className="border-none">
+          <AccordionTrigger className="py-2 hover:no-underline">
+            <Text
+              variant="body-medium"
+              className="!font-semibold text-slate-700"
+            >
+              Node Output
+            </Text>
+          </AccordionTrigger>
+          <AccordionContent className="pt-2">
+            <div className="flex max-w-[350px] flex-col gap-4">
+              <div className="space-y-2">
+                <Text variant="small-medium">Input</Text>
 
-      {isExpanded && (
-        <>
-          <div className="flex max-w-[350px] flex-col gap-4">
-            <div className="space-y-2">
-              <Text variant="small-medium">Input</Text>
+                <ContentRenderer value={inputData} shortContent={false} />
 
-              <ContentRenderer value={inputData} shortContent={false} />
-
-              <div className="mt-1 flex justify-end gap-1">
-                <NodeDataViewer
-                  data={inputData}
-                  pinName="Input"
-                  execId={executionResultId}
-                />
-                <Button
-                  variant="secondary"
-                  size="small"
-                  onClick={() => handleCopy("input", inputData)}
-                  className={cn(
-                    "h-fit min-w-0 gap-1.5 border border-zinc-200 p-2 text-black hover:text-slate-900",
-                    copiedKey === "input" &&
-                      "border-green-400 bg-green-100 hover:border-green-400 hover:bg-green-200",
-                  )}
-                >
-                  {copiedKey === "input" ? (
-                    <CheckIcon size={12} className="text-green-600" />
-                  ) : (
-                    <CopyIcon size={12} />
-                  )}
-                </Button>
+                <div className="mt-1 flex justify-end gap-1">
+                  <NodeDataViewer
+                    data={inputData}
+                    pinName="Input"
+                    execId={executionResultId}
+                  />
+                  <Button
+                    variant="secondary"
+                    size="small"
+                    onClick={() => handleCopy("input", inputData)}
+                    className={cn(
+                      "h-fit min-w-0 gap-1.5 border border-zinc-200 p-2 text-black hover:text-slate-900",
+                      copiedKey === "input" &&
+                        "border-green-400 bg-green-100 hover:border-green-400 hover:bg-green-200",
+                    )}
+                  >
+                    {copiedKey === "input" ? (
+                      <CheckIcon size={12} className="text-green-600" />
+                    ) : (
+                      <CopyIcon size={12} />
+                    )}
+                  </Button>
+                </div>
               </div>
-            </div>
 
-            {Object.entries(outputData)
-              .slice(0, 2)
-              .map(([key, value]) => (
-                <div key={key} className="flex flex-col gap-2">
-                  <div className="flex items-center gap-2">
-                    <Text
-                      variant="small-medium"
-                      className="!font-semibold text-slate-600"
-                    >
-                      Pin:
-                    </Text>
-                    <Text variant="small" className="text-slate-700">
-                      {beautifyString(key)}
-                    </Text>
-                  </div>
-                  <div className="w-full space-y-2">
-                    <Text
-                      variant="small"
-                      className="!font-semibold text-slate-600"
-                    >
-                      Data:
-                    </Text>
-                    <div className="relative space-y-2">
-                      {value.map((item, index) => (
-                        <div key={index}>
-                          <ContentRenderer value={item} shortContent={true} />
+              {Object.entries(outputData)
+                .slice(0, 2)
+                .map(([key, value]) => (
+                  <div key={key} className="flex flex-col gap-2">
+                    <div className="flex items-center gap-2">
+                      <Text
+                        variant="small-medium"
+                        className="!font-semibold text-slate-600"
+                      >
+                        Pin:
+                      </Text>
+                      <Text variant="small" className="text-slate-700">
+                        {beautifyString(key)}
+                      </Text>
+                    </div>
+                    <div className="w-full space-y-2">
+                      <Text
+                        variant="small"
+                        className="!font-semibold text-slate-600"
+                      >
+                        Data:
+                      </Text>
+                      <div className="relative space-y-2">
+                        {value.map((item, index) => (
+                          <div key={index}>
+                            <ContentRenderer value={item} shortContent={true} />
+                          </div>
+                        ))}
+
+                        <div className="mt-1 flex justify-end gap-1">
+                          <NodeDataViewer
+                            data={value}
+                            pinName={key}
+                            execId={executionResultId}
+                          />
+                          <Button
+                            variant="secondary"
+                            size="small"
+                            onClick={() => handleCopy(key, value)}
+                            className={cn(
+                              "h-fit min-w-0 gap-1.5 border border-zinc-200 p-2 text-black hover:text-slate-900",
+                              copiedKey === key &&
+                                "border-green-400 bg-green-100 hover:border-green-400 hover:bg-green-200",
+                            )}
+                          >
+                            {copiedKey === key ? (
+                              <CheckIcon size={12} className="text-green-600" />
+                            ) : (
+                              <CopyIcon size={12} />
+                            )}
+                          </Button>
                         </div>
-                      ))}
-
-                      <div className="mt-1 flex justify-end gap-1">
-                        <NodeDataViewer
-                          data={value}
-                          pinName={key}
-                          execId={executionResultId}
-                        />
-                        <Button
-                          variant="secondary"
-                          size="small"
-                          onClick={() => handleCopy(key, value)}
-                          className={cn(
-                            "h-fit min-w-0 gap-1.5 border border-zinc-200 p-2 text-black hover:text-slate-900",
-                            copiedKey === key &&
-                              "border-green-400 bg-green-100 hover:border-green-400 hover:bg-green-200",
-                          )}
-                        >
-                          {copiedKey === key ? (
-                            <CheckIcon size={12} className="text-green-600" />
-                          ) : (
-                            <CopyIcon size={12} />
-                          )}
-                        </Button>
                       </div>
                     </div>
                   </div>
-                </div>
-              ))}
-          </div>
+                ))}
+            </div>
 
-          {Object.keys(outputData).length > 2 && (
-            <ViewMoreData outputData={outputData} execId={executionResultId} />
-          )}
-        </>
-      )}
+            {Object.keys(outputData).length > 2 && (
+              <ViewMoreData
+                outputData={outputData}
+                execId={executionResultId}
+              />
+            )}
+          </AccordionContent>
+        </AccordionItem>
+      </Accordion>
     </div>
   );
 };

autogpt_platform/frontend/src/app/(platform)/build/components/FlowEditor/nodes/CustomNode/components/NodeOutput/useNodeOutput.tsx

@@ -4,7 +4,6 @@ import { useShallow } from "zustand/react/shallow";
 import { useState } from "react";
 
 export const useNodeOutput = (nodeId: string) => {
-  const [isExpanded, setIsExpanded] = useState(true);
   const [copiedKey, setCopiedKey] = useState<string | null>(null);
   const { toast } = useToast();
 
@@ -37,13 +36,10 @@ export const useNodeOutput = (nodeId: string) => {
     }
   };
   return {
-    outputData: outputData,
-    inputData: inputData,
-    isExpanded: isExpanded,
-    setIsExpanded: setIsExpanded,
-    copiedKey: copiedKey,
-    setCopiedKey: setCopiedKey,
-    handleCopy: handleCopy,
+    outputData,
+    inputData,
+    copiedKey,
+    handleCopy,
     executionResultId: nodeExecutionResult?.node_exec_id,
   };
 };

autogpt_platform/frontend/src/app/(platform)/build/components/FlowEditor/nodes/helpers.ts

@@ -187,3 +187,38 @@ export const getTypeDisplayInfo = (schema: any) => {
     hexColor,
   };
 };
+
+export function getEdgeColorFromOutputType(
+  outputSchema: RJSFSchema | undefined,
+  sourceHandle: string,
+): { colorClass: string; hexColor: string } {
+  const defaultColor = {
+    colorClass: "stroke-zinc-500/50",
+    hexColor: "#6b7280",
+  };
+
+  if (!outputSchema?.properties) return defaultColor;
+
+  const properties = outputSchema.properties as Record<string, unknown>;
+  const handleParts = sourceHandle.split("_#_");
+  let currentSchema: Record<string, unknown> = properties;
+
+  for (let i = 0; i < handleParts.length; i++) {
+    const part = handleParts[i];
+    const fieldSchema = currentSchema[part] as Record<string, unknown>;
+    if (!fieldSchema) return defaultColor;
+
+    if (i === handleParts.length - 1) {
+      const { hexColor, colorClass } = getTypeDisplayInfo(fieldSchema);
+      return { colorClass: colorClass.replace("!text-", "stroke-"), hexColor };
+    }
+
+    if (fieldSchema.properties) {
+      currentSchema = fieldSchema.properties as Record<string, unknown>;
+    } else {
+      return defaultColor;
+    }
+  }
+
+  return defaultColor;
+}

autogpt_platform/frontend/src/app/(platform)/build/components/FlowEditor/tutorial/icons.ts

@@ -1,7 +1,32 @@
-// These are SVG Phosphor icons
+type IconOptions = {
+  size?: number;
+  color?: string;
+};
+
+const DEFAULT_SIZE = 16;
+const DEFAULT_COLOR = "#52525b"; // zinc-600
+
+const iconPaths = {
+  ClickIcon: `M88,24V16a8,8,0,0,1,16,0v8a8,8,0,0,1-16,0ZM16,104h8a8,8,0,0,0,0-16H16a8,8,0,0,0,0,16ZM124.42,39.16a8,8,0,0,0,10.74-3.58l8-16a8,8,0,0,0-14.31-7.16l-8,16A8,8,0,0,0,124.42,39.16Zm-96,81.69-16,8a8,8,0,0,0,7.16,14.31l16-8a8,8,0,1,0-7.16-14.31ZM219.31,184a16,16,0,0,1,0,22.63l-12.68,12.68a16,16,0,0,1-22.63,0L132.7,168,115,214.09c0,.1-.08.21-.13.32a15.83,15.83,0,0,1-14.6,9.59l-.79,0a15.83,15.83,0,0,1-14.41-11L32.8,52.92A16,16,0,0,1,52.92,32.8L213,85.07a16,16,0,0,1,1.41,29.8l-.32.13L168,132.69ZM208,195.31,156.69,144h0a16,16,0,0,1,4.93-26l.32-.14,45.95-17.64L48,48l52.2,159.86,17.65-46c0-.11.08-.22.13-.33a16,16,0,0,1,11.69-9.34,16.72,16.72,0,0,1,3-.28,16,16,0,0,1,11.3,4.69L195.31,208Z`,
+  Keyboard: `M224,48H32A16,16,0,0,0,16,64V192a16,16,0,0,0,16,16H224a16,16,0,0,0,16-16V64A16,16,0,0,0,224,48Zm0,144H32V64H224V192Zm-16-64a8,8,0,0,1-8,8H56a8,8,0,0,1,0-16H200A8,8,0,0,1,208,128Zm0-32a8,8,0,0,1-8,8H56a8,8,0,0,1,0-16H200A8,8,0,0,1,208,96ZM72,160a8,8,0,0,1-8,8H56a8,8,0,0,1,0-16h8A8,8,0,0,1,72,160Zm96,0a8,8,0,0,1-8,8H96a8,8,0,0,1,0-16h64A8,8,0,0,1,168,160Zm40,0a8,8,0,0,1-8,8h-8a8,8,0,0,1,0-16h8A8,8,0,0,1,208,160Z`,
+  Drag: `M188,80a27.79,27.79,0,0,0-13.36,3.4,28,28,0,0,0-46.64-11A28,28,0,0,0,80,92v20H68a28,28,0,0,0-28,28v12a88,88,0,0,0,176,0V108A28,28,0,0,0,188,80Zm12,72a72,72,0,0,1-144,0V140a12,12,0,0,1,12-12H80v24a8,8,0,0,0,16,0V92a12,12,0,0,1,24,0v28a8,8,0,0,0,16,0V92a12,12,0,0,1,24,0v28a8,8,0,0,0,16,0V108a12,12,0,0,1,24,0Z`,
+};
+
+function createIcon(path: string, options: IconOptions = {}): string {
+  const size = options.size ?? DEFAULT_SIZE;
+  const color = options.color ?? DEFAULT_COLOR;
+  return `<svg xmlns="http://www.w3.org/2000/svg" width="${size}" height="${size}" fill="${color}" viewBox="0 0 256 256"><path d="${path}"></path></svg>`;
+}
 
 export const ICONS = {
-  ClickIcon: `<svg xmlns="http://www.w3.org/2000/svg" width="20" height="20" fill="#000000" viewBox="0 0 256 256"><path d="M88,24V16a8,8,0,0,1,16,0v8a8,8,0,0,1-16,0ZM16,104h8a8,8,0,0,0,0-16H16a8,8,0,0,0,0,16ZM124.42,39.16a8,8,0,0,0,10.74-3.58l8-16a8,8,0,0,0-14.31-7.16l-8,16A8,8,0,0,0,124.42,39.16Zm-96,81.69-16,8a8,8,0,0,0,7.16,14.31l16-8a8,8,0,1,0-7.16-14.31ZM219.31,184a16,16,0,0,1,0,22.63l-12.68,12.68a16,16,0,0,1-22.63,0L132.7,168,115,214.09c0,.1-.08.21-.13.32a15.83,15.83,0,0,1-14.6,9.59l-.79,0a15.83,15.83,0,0,1-14.41-11L32.8,52.92A16,16,0,0,1,52.92,32.8L213,85.07a16,16,0,0,1,1.41,29.8l-.32.13L168,132.69ZM208,195.31,156.69,144h0a16,16,0,0,1,4.93-26l.32-.14,45.95-17.64L48,48l52.2,159.86,17.65-46c0-.11.08-.22.13-.33a16,16,0,0,1,11.69-9.34,16.72,16.72,0,0,1,3-.28,16,16,0,0,1,11.3,4.69L195.31,208Z"></path></svg>`,
-  Keyboard: `<svg xmlns="http://www.w3.org/2000/svg" width="20" height="20" fill="#000000" viewBox="0 0 256 256"><path d="M224,48H32A16,16,0,0,0,16,64V192a16,16,0,0,0,16,16H224a16,16,0,0,0,16-16V64A16,16,0,0,0,224,48Zm0,144H32V64H224V192Zm-16-64a8,8,0,0,1-8,8H56a8,8,0,0,1,0-16H200A8,8,0,0,1,208,128Zm0-32a8,8,0,0,1-8,8H56a8,8,0,0,1,0-16H200A8,8,0,0,1,208,96ZM72,160a8,8,0,0,1-8,8H56a8,8,0,0,1,0-16h8A8,8,0,0,1,72,160Zm96,0a8,8,0,0,1-8,8H96a8,8,0,0,1,0-16h64A8,8,0,0,1,168,160Zm40,0a8,8,0,0,1-8,8h-8a8,8,0,0,1,0-16h8A8,8,0,0,1,208,160Z"></path></svg>`,
-  Drag: `<svg xmlns="http://www.w3.org/2000/svg" width="20" height="20" fill="#000000" viewBox="0 0 256 256"><path d="M188,80a27.79,27.79,0,0,0-13.36,3.4,28,28,0,0,0-46.64-11A28,28,0,0,0,80,92v20H68a28,28,0,0,0-28,28v12a88,88,0,0,0,176,0V108A28,28,0,0,0,188,80Zm12,72a72,72,0,0,1-144,0V140a12,12,0,0,1,12-12H80v24a8,8,0,0,0,16,0V92a12,12,0,0,1,24,0v28a8,8,0,0,0,16,0V92a12,12,0,0,1,24,0v28a8,8,0,0,0,16,0V108a12,12,0,0,1,24,0Z"></path></svg>`,
+  ClickIcon: createIcon(iconPaths.ClickIcon),
+  Keyboard: createIcon(iconPaths.Keyboard),
+  Drag: createIcon(iconPaths.Drag),
 };
+
+export function getIcon(
+  name: keyof typeof iconPaths,
+  options?: IconOptions,
+): string {
+  return createIcon(iconPaths[name], options);
+}

autogpt_platform/frontend/src/app/(platform)/build/components/FlowEditor/tutorial/index.ts

@@ -11,6 +11,7 @@ import {
 } from "./helpers";
 import { useNodeStore } from "../../../stores/nodeStore";
 import { useEdgeStore } from "../../../stores/edgeStore";
+import { useTutorialStore } from "../../../stores/tutorialStore";
 
 let isTutorialLoading = false;
 let tutorialLoadingCallback: ((loading: boolean) => void) | null = null;
@@ -60,12 +61,14 @@ export const startTutorial = async () => {
     handleTutorialComplete();
     removeTutorialStyles();
     clearPrefetchedBlocks();
+    useTutorialStore.getState().setIsTutorialRunning(false);
   });
 
   tour.on("cancel", () => {
     handleTutorialCancel(tour);
     removeTutorialStyles();
     clearPrefetchedBlocks();
+    useTutorialStore.getState().setIsTutorialRunning(false);
   });
 
   for (const step of tour.steps) {

autogpt_platform/frontend/src/app/(platform)/build/components/helper.ts

@@ -61,12 +61,18 @@ export const convertNodesPlusBlockInfoIntoCustomNodes = (
   return customNode;
 };
 
+const isToolSourceName = (sourceName: string): boolean =>
+  sourceName.startsWith("tools_^_");
+
+const cleanupSourceName = (sourceName: string): string =>
+  isToolSourceName(sourceName) ? "tools" : sourceName;
+
 export const linkToCustomEdge = (link: Link): CustomEdge => ({
   id: link.id ?? "",
   type: "custom" as const,
   source: link.source_id,
   target: link.sink_id,
-  sourceHandle: link.source_name,
+  sourceHandle: cleanupSourceName(link.source_name),
   targetHandle: link.sink_name,
   data: {
     isStatic: link.is_static,

autogpt_platform/frontend/src/app/(platform)/chat/components/Chat/Chat.tsx

@@ -1,134 +0,0 @@
-"use client";
-
-import { Button } from "@/components/atoms/Button/Button";
-import { Text } from "@/components/atoms/Text/Text";
-import { cn } from "@/lib/utils";
-import { List } from "@phosphor-icons/react";
-import React, { useState } from "react";
-import { ChatContainer } from "./components/ChatContainer/ChatContainer";
-import { ChatErrorState } from "./components/ChatErrorState/ChatErrorState";
-import { ChatLoadingState } from "./components/ChatLoadingState/ChatLoadingState";
-import { SessionsDrawer } from "./components/SessionsDrawer/SessionsDrawer";
-import { useChat } from "./useChat";
-
-export interface ChatProps {
-  className?: string;
-  headerTitle?: React.ReactNode;
-  showHeader?: boolean;
-  showSessionInfo?: boolean;
-  showNewChatButton?: boolean;
-  onNewChat?: () => void;
-  headerActions?: React.ReactNode;
-}
-
-export function Chat({
-  className,
-  headerTitle = "AutoGPT Copilot",
-  showHeader = true,
-  showSessionInfo = true,
-  showNewChatButton = true,
-  onNewChat,
-  headerActions,
-}: ChatProps) {
-  const {
-    messages,
-    isLoading,
-    isCreating,
-    error,
-    sessionId,
-    createSession,
-    clearSession,
-    loadSession,
-  } = useChat();
-
-  const [isSessionsDrawerOpen, setIsSessionsDrawerOpen] = useState(false);
-
-  const handleNewChat = () => {
-    clearSession();
-    onNewChat?.();
-  };
-
-  const handleSelectSession = async (sessionId: string) => {
-    try {
-      await loadSession(sessionId);
-    } catch (err) {
-      console.error("Failed to load session:", err);
-    }
-  };
-
-  return (
-    <div className={cn("flex h-full flex-col", className)}>
-      {/* Header */}
-      {showHeader && (
-        <header className="shrink-0 border-t border-zinc-200 bg-white p-3">
-          <div className="flex items-center justify-between">
-            <div className="flex items-center gap-3">
-              <button
-                aria-label="View sessions"
-                onClick={() => setIsSessionsDrawerOpen(true)}
-                className="flex size-8 items-center justify-center rounded hover:bg-zinc-100"
-              >
-                <List width="1.25rem" height="1.25rem" />
-              </button>
-              {typeof headerTitle === "string" ? (
-                <Text variant="h2" className="text-lg font-semibold">
-                  {headerTitle}
-                </Text>
-              ) : (
-                headerTitle
-              )}
-            </div>
-            <div className="flex items-center gap-3">
-              {showSessionInfo && sessionId && (
-                <>
-                  {showNewChatButton && (
-                    <Button
-                      variant="outline"
-                      size="small"
-                      onClick={handleNewChat}
-                    >
-                      New Chat
-                    </Button>
-                  )}
-                </>
-              )}
-              {headerActions}
-            </div>
-          </div>
-        </header>
-      )}
-
-      {/* Main Content */}
-      <main className="flex min-h-0 flex-1 flex-col overflow-hidden">
-        {/* Loading State - show when explicitly loading/creating OR when we don't have a session yet and no error */}
-        {(isLoading || isCreating || (!sessionId && !error)) && (
-          <ChatLoadingState
-            message={isCreating ? "Creating session..." : "Loading..."}
-          />
-        )}
-
-        {/* Error State */}
-        {error && !isLoading && (
-          <ChatErrorState error={error} onRetry={createSession} />
-        )}
-
-        {/* Session Content */}
-        {sessionId && !isLoading && !error && (
-          <ChatContainer
-            sessionId={sessionId}
-            initialMessages={messages}
-            className="flex-1"
-          />
-        )}
-      </main>
-
-      {/* Sessions Drawer */}
-      <SessionsDrawer
-        isOpen={isSessionsDrawerOpen}
-        onClose={() => setIsSessionsDrawerOpen(false)}
-        onSelectSession={handleSelectSession}
-        currentSessionId={sessionId}
-      />
-    </div>
-  );
-}

autogpt_platform/frontend/src/app/(platform)/chat/components/Chat/components/ChatInput/ChatInput.tsx

@@ -1,64 +0,0 @@
-import { Input } from "@/components/atoms/Input/Input";
-import { cn } from "@/lib/utils";
-import { ArrowUpIcon } from "@phosphor-icons/react";
-import { useChatInput } from "./useChatInput";
-
-export interface ChatInputProps {
-  onSend: (message: string) => void;
-  disabled?: boolean;
-  placeholder?: string;
-  className?: string;
-}
-
-export function ChatInput({
-  onSend,
-  disabled = false,
-  placeholder = "Type your message...",
-  className,
-}: ChatInputProps) {
-  const inputId = "chat-input";
-  const { value, setValue, handleKeyDown, handleSend } = useChatInput({
-    onSend,
-    disabled,
-    maxRows: 5,
-    inputId,
-  });
-
-  return (
-    <div className={cn("relative flex-1", className)}>
-      <Input
-        id={inputId}
-        label="Chat message input"
-        hideLabel
-        type="textarea"
-        value={value}
-        onChange={(e) => setValue(e.target.value)}
-        onKeyDown={handleKeyDown}
-        placeholder={placeholder}
-        disabled={disabled}
-        rows={1}
-        wrapperClassName="mb-0 relative"
-        className="pr-12"
-      />
-      <span id="chat-input-hint" className="sr-only">
-        Press Enter to send, Shift+Enter for new line
-      </span>
-
-      <button
-        onClick={handleSend}
-        disabled={disabled || !value.trim()}
-        className={cn(
-          "absolute right-3 top-1/2 flex h-8 w-8 -translate-y-1/2 items-center justify-center rounded-full",
-          "border border-zinc-800 bg-zinc-800 text-white",
-          "hover:border-zinc-900 hover:bg-zinc-900",
-          "disabled:border-zinc-200 disabled:bg-zinc-200 disabled:text-white disabled:opacity-50",
-          "transition-colors focus-visible:outline-none focus-visible:ring-1 focus-visible:ring-neutral-950",
-          "disabled:pointer-events-none",
-        )}
-        aria-label="Send message"
-      >
-        <ArrowUpIcon className="h-3 w-3" weight="bold" />
-      </button>
-    </div>
-  );
-}

autogpt_platform/frontend/src/app/(platform)/chat/components/Chat/components/ChatInput/useChatInput.ts

@@ -1,60 +0,0 @@
-import { KeyboardEvent, useCallback, useEffect, useState } from "react";
-
-interface UseChatInputArgs {
-  onSend: (message: string) => void;
-  disabled?: boolean;
-  maxRows?: number;
-  inputId?: string;
-}
-
-export function useChatInput({
-  onSend,
-  disabled = false,
-  maxRows = 5,
-  inputId = "chat-input",
-}: UseChatInputArgs) {
-  const [value, setValue] = useState("");
-
-  useEffect(() => {
-    const textarea = document.getElementById(inputId) as HTMLTextAreaElement;
-    if (!textarea) return;
-    textarea.style.height = "auto";
-    const lineHeight = parseInt(
-      window.getComputedStyle(textarea).lineHeight,
-      10,
-    );
-    const maxHeight = lineHeight * maxRows;
-    const newHeight = Math.min(textarea.scrollHeight, maxHeight);
-    textarea.style.height = `${newHeight}px`;
-    textarea.style.overflowY =
-      textarea.scrollHeight > maxHeight ? "auto" : "hidden";
-  }, [value, maxRows, inputId]);
-
-  const handleSend = useCallback(() => {
-    if (disabled || !value.trim()) return;
-    onSend(value.trim());
-    setValue("");
-    const textarea = document.getElementById(inputId) as HTMLTextAreaElement;
-    if (textarea) {
-      textarea.style.height = "auto";
-    }
-  }, [value, onSend, disabled, inputId]);
-
-  const handleKeyDown = useCallback(
-    (event: KeyboardEvent<HTMLInputElement | HTMLTextAreaElement>) => {
-      if (event.key === "Enter" && !event.shiftKey) {
-        event.preventDefault();
-        handleSend();
-      }
-      // Shift+Enter allows default behavior (new line) - no need to handle explicitly
-    },
-    [handleSend],
-  );
-
-  return {
-    value,
-    setValue,
-    handleKeyDown,
-    handleSend,
-  };
-}

autogpt_platform/frontend/src/app/(platform)/chat/components/Chat/components/MessageList/MessageList.tsx

@@ -1,121 +0,0 @@
-"use client";
-
-import { cn } from "@/lib/utils";
-import { ChatMessage } from "../ChatMessage/ChatMessage";
-import type { ChatMessageData } from "../ChatMessage/useChatMessage";
-import { StreamingMessage } from "../StreamingMessage/StreamingMessage";
-import { ThinkingMessage } from "../ThinkingMessage/ThinkingMessage";
-import { useMessageList } from "./useMessageList";
-
-export interface MessageListProps {
-  messages: ChatMessageData[];
-  streamingChunks?: string[];
-  isStreaming?: boolean;
-  className?: string;
-  onStreamComplete?: () => void;
-  onSendMessage?: (content: string) => void;
-}
-
-export function MessageList({
-  messages,
-  streamingChunks = [],
-  isStreaming = false,
-  className,
-  onStreamComplete,
-  onSendMessage,
-}: MessageListProps) {
-  const { messagesEndRef, messagesContainerRef } = useMessageList({
-    messageCount: messages.length,
-    isStreaming,
-  });
-
-  return (
-    <div
-      ref={messagesContainerRef}
-      className={cn(
-        "flex-1 overflow-y-auto",
-        "scrollbar-thin scrollbar-track-transparent scrollbar-thumb-zinc-300",
-        className,
-      )}
-    >
-      <div className="mx-auto flex max-w-3xl flex-col py-4">
-        {/* Render all persisted messages */}
-        {messages.map((message, index) => {
-          // Check if current message is an agent_output tool_response
-          // and if previous message is an assistant message
-          let agentOutput: ChatMessageData | undefined;
-
-          if (message.type === "tool_response" && message.result) {
-            let parsedResult: Record<string, unknown> | null = null;
-            try {
-              parsedResult =
-                typeof message.result === "string"
-                  ? JSON.parse(message.result)
-                  : (message.result as Record<string, unknown>);
-            } catch {
-              parsedResult = null;
-            }
-            if (parsedResult?.type === "agent_output") {
-              const prevMessage = messages[index - 1];
-              if (
-                prevMessage &&
-                prevMessage.type === "message" &&
-                prevMessage.role === "assistant"
-              ) {
-                // This agent output will be rendered inside the previous assistant message
-                // Skip rendering this message separately
-                return null;
-              }
-            }
-          }
-
-          // Check if next message is an agent_output tool_response to include in current assistant message
-          if (message.type === "message" && message.role === "assistant") {
-            const nextMessage = messages[index + 1];
-            if (
-              nextMessage &&
-              nextMessage.type === "tool_response" &&
-              nextMessage.result
-            ) {
-              let parsedResult: Record<string, unknown> | null = null;
-              try {
-                parsedResult =
-                  typeof nextMessage.result === "string"
-                    ? JSON.parse(nextMessage.result)
-                    : (nextMessage.result as Record<string, unknown>);
-              } catch {
-                parsedResult = null;
-              }
-              if (parsedResult?.type === "agent_output") {
-                agentOutput = nextMessage;
-              }
-            }
-          }
-
-          return (
-            <ChatMessage
-              key={index}
-              message={message}
-              onSendMessage={onSendMessage}
-              agentOutput={agentOutput}
-            />
-          );
-        })}
-
-        {/* Render thinking message when streaming but no chunks yet */}
-        {isStreaming && streamingChunks.length === 0 && <ThinkingMessage />}
-
-        {/* Render streaming message if active */}
-        {isStreaming && streamingChunks.length > 0 && (
-          <StreamingMessage
-            chunks={streamingChunks}
-            onComplete={onStreamComplete}
-          />
-        )}
-
-        {/* Invisible div to scroll to */}
-        <div ref={messagesEndRef} />
-      </div>
-    </div>
-  );
-}

autogpt_platform/frontend/src/app/(platform)/chat/components/Chat/components/ToolCallMessage/ToolCallMessage.tsx

@@ -1,24 +0,0 @@
-import { Text } from "@/components/atoms/Text/Text";
-import { cn } from "@/lib/utils";
-import { WrenchIcon } from "@phosphor-icons/react";
-import { getToolActionPhrase } from "../../helpers";
-
-export interface ToolCallMessageProps {
-  toolName: string;
-  className?: string;
-}
-
-export function ToolCallMessage({ toolName, className }: ToolCallMessageProps) {
-  return (
-    <div className={cn("flex items-center justify-center gap-2", className)}>
-      <WrenchIcon
-        size={14}
-        weight="bold"
-        className="flex-shrink-0 text-neutral-500"
-      />
-      <Text variant="small" className="text-neutral-500">
-        {getToolActionPhrase(toolName)}...
-      </Text>
-    </div>
-  );
-}

autogpt_platform/frontend/src/app/(platform)/chat/components/Chat/components/ToolResponseMessage/ToolResponseMessage.tsx

@@ -1,260 +0,0 @@
-import { Text } from "@/components/atoms/Text/Text";
-import "@/components/contextual/OutputRenderers";
-import {
-  globalRegistry,
-  OutputItem,
-} from "@/components/contextual/OutputRenderers";
-import { cn } from "@/lib/utils";
-import type { ToolResult } from "@/types/chat";
-import { WrenchIcon } from "@phosphor-icons/react";
-import { getToolActionPhrase } from "../../helpers";
-
-export interface ToolResponseMessageProps {
-  toolName: string;
-  result?: ToolResult;
-  success?: boolean;
-  className?: string;
-}
-
-export function ToolResponseMessage({
-  toolName,
-  result,
-  success: _success = true,
-  className,
-}: ToolResponseMessageProps) {
-  if (!result) {
-    return (
-      <div className={cn("flex items-center justify-center gap-2", className)}>
-        <WrenchIcon
-          size={14}
-          weight="bold"
-          className="flex-shrink-0 text-neutral-500"
-        />
-        <Text variant="small" className="text-neutral-500">
-          {getToolActionPhrase(toolName)}...
-        </Text>
-      </div>
-    );
-  }
-
-  let parsedResult: Record<string, unknown> | null = null;
-  try {
-    parsedResult =
-      typeof result === "string"
-        ? JSON.parse(result)
-        : (result as Record<string, unknown>);
-  } catch {
-    parsedResult = null;
-  }
-
-  if (parsedResult && typeof parsedResult === "object") {
-    const responseType = parsedResult.type as string | undefined;
-
-    if (responseType === "agent_output") {
-      const execution = parsedResult.execution as
-        | {
-            outputs?: Record<string, unknown[]>;
-          }
-        | null
-        | undefined;
-      const outputs = execution?.outputs || {};
-      const message = parsedResult.message as string | undefined;
-
-      return (
-        <div className={cn("space-y-4 px-4 py-2", className)}>
-          <div className="flex items-center gap-2">
-            <WrenchIcon
-              size={14}
-              weight="bold"
-              className="flex-shrink-0 text-neutral-500"
-            />
-            <Text variant="small" className="text-neutral-500">
-              {getToolActionPhrase(toolName)}
-            </Text>
-          </div>
-          {message && (
-            <div className="rounded border p-4">
-              <Text variant="small" className="text-neutral-600">
-                {message}
-              </Text>
-            </div>
-          )}
-          {Object.keys(outputs).length > 0 && (
-            <div className="space-y-4">
-              {Object.entries(outputs).map(([outputName, values]) =>
-                values.map((value, index) => {
-                  const renderer = globalRegistry.getRenderer(value);
-                  if (renderer) {
-                    return (
-                      <OutputItem
-                        key={`${outputName}-${index}`}
-                        value={value}
-                        renderer={renderer}
-                        label={outputName}
-                      />
-                    );
-                  }
-                  return (
-                    <div
-                      key={`${outputName}-${index}`}
-                      className="rounded border p-4"
-                    >
-                      <Text variant="large-medium" className="mb-2 capitalize">
-                        {outputName}
-                      </Text>
-                      <pre className="overflow-auto text-sm">
-                        {JSON.stringify(value, null, 2)}
-                      </pre>
-                    </div>
-                  );
-                }),
-              )}
-            </div>
-          )}
-        </div>
-      );
-    }
-
-    if (responseType === "block_output" && parsedResult.outputs) {
-      const outputs = parsedResult.outputs as Record<string, unknown[]>;
-
-      return (
-        <div className={cn("space-y-4 px-4 py-2", className)}>
-          <div className="flex items-center gap-2">
-            <WrenchIcon
-              size={14}
-              weight="bold"
-              className="flex-shrink-0 text-neutral-500"
-            />
-            <Text variant="small" className="text-neutral-500">
-              {getToolActionPhrase(toolName)}
-            </Text>
-          </div>
-          <div className="space-y-4">
-            {Object.entries(outputs).map(([outputName, values]) =>
-              values.map((value, index) => {
-                const renderer = globalRegistry.getRenderer(value);
-                if (renderer) {
-                  return (
-                    <OutputItem
-                      key={`${outputName}-${index}`}
-                      value={value}
-                      renderer={renderer}
-                      label={outputName}
-                    />
-                  );
-                }
-                return (
-                  <div
-                    key={`${outputName}-${index}`}
-                    className="rounded border p-4"
-                  >
-                    <Text variant="large-medium" className="mb-2 capitalize">
-                      {outputName}
-                    </Text>
-                    <pre className="overflow-auto text-sm">
-                      {JSON.stringify(value, null, 2)}
-                    </pre>
-                  </div>
-                );
-              }),
-            )}
-          </div>
-        </div>
-      );
-    }
-
-    // Handle other response types with a message field (e.g., understanding_updated)
-    if (parsedResult.message && typeof parsedResult.message === "string") {
-      // Format tool name from snake_case to Title Case
-      const formattedToolName = toolName
-        .split("_")
-        .map((word) => word.charAt(0).toUpperCase() + word.slice(1))
-        .join(" ");
-
-      // Clean up message - remove incomplete user_name references
-      let cleanedMessage = parsedResult.message;
-      // Remove "Updated understanding with: user_name" pattern if user_name is just a placeholder
-      cleanedMessage = cleanedMessage.replace(
-        /Updated understanding with:\s*user_name\.?\s*/gi,
-        "",
-      );
-      // Remove standalone user_name references
-      cleanedMessage = cleanedMessage.replace(/\buser_name\b\.?\s*/gi, "");
-      cleanedMessage = cleanedMessage.trim();
-
-      // Only show message if it has content after cleaning
-      if (!cleanedMessage) {
-        return (
-          <div
-            className={cn(
-              "flex items-center justify-center gap-2 px-4 py-2",
-              className,
-            )}
-          >
-            <WrenchIcon
-              size={14}
-              weight="bold"
-              className="flex-shrink-0 text-neutral-500"
-            />
-            <Text variant="small" className="text-neutral-500">
-              {formattedToolName}
-            </Text>
-          </div>
-        );
-      }
-
-      return (
-        <div className={cn("space-y-2 px-4 py-2", className)}>
-          <div className="flex items-center justify-center gap-2">
-            <WrenchIcon
-              size={14}
-              weight="bold"
-              className="flex-shrink-0 text-neutral-500"
-            />
-            <Text variant="small" className="text-neutral-500">
-              {formattedToolName}
-            </Text>
-          </div>
-          <div className="rounded border p-4">
-            <Text variant="small" className="text-neutral-600">
-              {cleanedMessage}
-            </Text>
-          </div>
-        </div>
-      );
-    }
-  }
-
-  const renderer = globalRegistry.getRenderer(result);
-  if (renderer) {
-    return (
-      <div className={cn("px-4 py-2", className)}>
-        <div className="mb-2 flex items-center gap-2">
-          <WrenchIcon
-            size={14}
-            weight="bold"
-            className="flex-shrink-0 text-neutral-500"
-          />
-          <Text variant="small" className="text-neutral-500">
-            {getToolActionPhrase(toolName)}
-          </Text>
-        </div>
-        <OutputItem value={result} renderer={renderer} />
-      </div>
-    );
-  }
-
-  return (
-    <div className={cn("flex items-center justify-center gap-2", className)}>
-      <WrenchIcon
-        size={14}
-        weight="bold"
-        className="flex-shrink-0 text-neutral-500"
-      />
-      <Text variant="small" className="text-neutral-500">
-        {getToolActionPhrase(toolName)}...
-      </Text>
-    </div>
-  );
-}

autogpt_platform/frontend/src/app/(platform)/chat/components/Chat/helpers.ts

@@ -1,66 +0,0 @@
-/**
- * Maps internal tool names to user-friendly display names with emojis.
- * @deprecated Use getToolActionPhrase or getToolCompletionPhrase for status messages
- *
- * @param toolName - The internal tool name from the backend
- * @returns A user-friendly display name with an emoji prefix
- */
-export function getToolDisplayName(toolName: string): string {
-  const toolDisplayNames: Record<string, string> = {
-    find_agent: "🔍 Search Marketplace",
-    get_agent_details: "📋 Get Agent Details",
-    check_credentials: "🔑 Check Credentials",
-    setup_agent: "⚙️ Setup Agent",
-    run_agent: "▶️ Run Agent",
-    get_required_setup_info: "📝 Get Setup Requirements",
-  };
-  return toolDisplayNames[toolName] || toolName;
-}
-
-/**
- * Maps internal tool names to human-friendly action phrases (present continuous).
- * Used for tool call messages to indicate what action is currently happening.
- *
- * @param toolName - The internal tool name from the backend
- * @returns A human-friendly action phrase in present continuous tense
- */
-export function getToolActionPhrase(toolName: string): string {
-  const toolActionPhrases: Record<string, string> = {
-    find_agent: "Looking for agents in the marketplace",
-    agent_carousel: "Looking for agents in the marketplace",
-    get_agent_details: "Learning about the agent",
-    check_credentials: "Checking your credentials",
-    setup_agent: "Setting up the agent",
-    execution_started: "Running the agent",
-    run_agent: "Running the agent",
-    get_required_setup_info: "Getting setup requirements",
-    schedule_agent: "Scheduling the agent to run",
-  };
-
-  // Return mapped phrase or generate human-friendly fallback
-  return toolActionPhrases[toolName] || toolName;
-}
-
-/**
- * Maps internal tool names to human-friendly completion phrases (past tense).
- * Used for tool response messages to indicate what action was completed.
- *
- * @param toolName - The internal tool name from the backend
- * @returns A human-friendly completion phrase in past tense
- */
-export function getToolCompletionPhrase(toolName: string): string {
-  const toolCompletionPhrases: Record<string, string> = {
-    find_agent: "Finished searching the marketplace",
-    get_agent_details: "Got agent details",
-    check_credentials: "Checked credentials",
-    setup_agent: "Agent setup complete",
-    run_agent: "Agent execution started",
-    get_required_setup_info: "Got setup requirements",
-  };
-
-  // Return mapped phrase or generate human-friendly fallback
-  return (
-    toolCompletionPhrases[toolName] ||
-    `Finished ${toolName.replace(/_/g, " ").replace("...", "")}`
-  );
-}

autogpt_platform/frontend/src/app/(platform)/chat/components/Chat/useChatSession.ts

@@ -1,271 +0,0 @@
-import {
-  getGetV2GetSessionQueryKey,
-  getGetV2GetSessionQueryOptions,
-  postV2CreateSession,
-  useGetV2GetSession,
-  usePatchV2SessionAssignUser,
-  usePostV2CreateSession,
-} from "@/app/api/__generated__/endpoints/chat/chat";
-import type { SessionDetailResponse } from "@/app/api/__generated__/models/sessionDetailResponse";
-import { okData } from "@/app/api/helpers";
-import { isValidUUID } from "@/lib/utils";
-import { Key, storage } from "@/services/storage/local-storage";
-import { useQueryClient } from "@tanstack/react-query";
-import { useCallback, useEffect, useMemo, useRef, useState } from "react";
-import { toast } from "sonner";
-
-interface UseChatSessionArgs {
-  urlSessionId?: string | null;
-  autoCreate?: boolean;
-}
-
-export function useChatSession({
-  urlSessionId,
-  autoCreate = false,
-}: UseChatSessionArgs = {}) {
-  const queryClient = useQueryClient();
-  const [sessionId, setSessionId] = useState<string | null>(null);
-  const [error, setError] = useState<Error | null>(null);
-  const justCreatedSessionIdRef = useRef<string | null>(null);
-
-  useEffect(() => {
-    if (urlSessionId) {
-      if (!isValidUUID(urlSessionId)) {
-        console.error("Invalid session ID format:", urlSessionId);
-        toast.error("Invalid session ID", {
-          description:
-            "The session ID in the URL is not valid. Starting a new session...",
-        });
-        setSessionId(null);
-        storage.clean(Key.CHAT_SESSION_ID);
-        return;
-      }
-      setSessionId(urlSessionId);
-      storage.set(Key.CHAT_SESSION_ID, urlSessionId);
-    } else {
-      const storedSessionId = storage.get(Key.CHAT_SESSION_ID);
-      if (storedSessionId) {
-        if (!isValidUUID(storedSessionId)) {
-          console.error("Invalid stored session ID:", storedSessionId);
-          storage.clean(Key.CHAT_SESSION_ID);
-          setSessionId(null);
-        } else {
-          setSessionId(storedSessionId);
-        }
-      } else if (autoCreate) {
-        setSessionId(null);
-      }
-    }
-  }, [urlSessionId, autoCreate]);
-
-  const {
-    mutateAsync: createSessionMutation,
-    isPending: isCreating,
-    error: createError,
-  } = usePostV2CreateSession();
-
-  const {
-    data: sessionData,
-    isLoading: isLoadingSession,
-    error: loadError,
-    refetch,
-  } = useGetV2GetSession(sessionId || "", {
-    query: {
-      enabled: !!sessionId,
-      select: okData,
-      staleTime: Infinity, // Never mark as stale
-      refetchOnMount: false, // Don't refetch on component mount
-      refetchOnWindowFocus: false, // Don't refetch when window regains focus
-      refetchOnReconnect: false, // Don't refetch when network reconnects
-      retry: 1,
-    },
-  });
-
-  const { mutateAsync: claimSessionMutation } = usePatchV2SessionAssignUser();
-
-  const session = useMemo(() => {
-    if (sessionData) return sessionData;
-
-    if (sessionId && justCreatedSessionIdRef.current === sessionId) {
-      return {
-        id: sessionId,
-        user_id: null,
-        messages: [],
-        created_at: new Date().toISOString(),
-        updated_at: new Date().toISOString(),
-      } as SessionDetailResponse;
-    }
-    return null;
-  }, [sessionData, sessionId]);
-
-  const messages = session?.messages || [];
-  const isLoading = isCreating || isLoadingSession;
-
-  useEffect(() => {
-    if (createError) {
-      setError(
-        createError instanceof Error
-          ? createError
-          : new Error("Failed to create session"),
-      );
-    } else if (loadError) {
-      setError(
-        loadError instanceof Error
-          ? loadError
-          : new Error("Failed to load session"),
-      );
-    } else {
-      setError(null);
-    }
-  }, [createError, loadError]);
-
-  const createSession = useCallback(
-    async function createSession() {
-      try {
-        setError(null);
-        const response = await postV2CreateSession({
-          body: JSON.stringify({}),
-        });
-        if (response.status !== 200) {
-          throw new Error("Failed to create session");
-        }
-        const newSessionId = response.data.id;
-        setSessionId(newSessionId);
-        storage.set(Key.CHAT_SESSION_ID, newSessionId);
-        justCreatedSessionIdRef.current = newSessionId;
-        setTimeout(() => {
-          if (justCreatedSessionIdRef.current === newSessionId) {
-            justCreatedSessionIdRef.current = null;
-          }
-        }, 10000);
-        return newSessionId;
-      } catch (err) {
-        const error =
-          err instanceof Error ? err : new Error("Failed to create session");
-        setError(error);
-        toast.error("Failed to create chat session", {
-          description: error.message,
-        });
-        throw error;
-      }
-    },
-    [createSessionMutation],
-  );
-
-  const loadSession = useCallback(
-    async function loadSession(id: string) {
-      try {
-        setError(null);
-        // Invalidate the query cache for this session to force a fresh fetch
-        await queryClient.invalidateQueries({
-          queryKey: getGetV2GetSessionQueryKey(id),
-        });
-        // Set sessionId after invalidation to ensure the hook refetches
-        setSessionId(id);
-        storage.set(Key.CHAT_SESSION_ID, id);
-        // Force fetch with fresh data (bypass cache)
-        const queryOptions = getGetV2GetSessionQueryOptions(id, {
-          query: {
-            staleTime: 0, // Force fresh fetch
-            retry: 1,
-          },
-        });
-        const result = await queryClient.fetchQuery(queryOptions);
-        if (!result || ("status" in result && result.status !== 200)) {
-          console.warn("Session not found on server, clearing local state");
-          storage.clean(Key.CHAT_SESSION_ID);
-          setSessionId(null);
-          throw new Error("Session not found");
-        }
-      } catch (err) {
-        const error =
-          err instanceof Error ? err : new Error("Failed to load session");
-        setError(error);
-        throw error;
-      }
-    },
-    [queryClient],
-  );
-
-  const refreshSession = useCallback(
-    async function refreshSession() {
-      if (!sessionId) {
-        console.log("[refreshSession] Skipping - no session ID");
-        return;
-      }
-      try {
-        setError(null);
-        await refetch();
-      } catch (err) {
-        const error =
-          err instanceof Error ? err : new Error("Failed to refresh session");
-        setError(error);
-        throw error;
-      }
-    },
-    [sessionId, refetch],
-  );
-
-  const claimSession = useCallback(
-    async function claimSession(id: string) {
-      try {
-        setError(null);
-        await claimSessionMutation({ sessionId: id });
-        if (justCreatedSessionIdRef.current === id) {
-          justCreatedSessionIdRef.current = null;
-        }
-        await queryClient.invalidateQueries({
-          queryKey: getGetV2GetSessionQueryKey(id),
-        });
-        await refetch();
-        toast.success("Session claimed successfully", {
-          description: "Your chat history has been saved to your account",
-        });
-      } catch (err: unknown) {
-        const error =
-          err instanceof Error ? err : new Error("Failed to claim session");
-        const is404 =
-          (typeof err === "object" &&
-            err !== null &&
-            "status" in err &&
-            err.status === 404) ||
-          (typeof err === "object" &&
-            err !== null &&
-            "response" in err &&
-            typeof err.response === "object" &&
-            err.response !== null &&
-            "status" in err.response &&
-            err.response.status === 404);
-        if (!is404) {
-          setError(error);
-          toast.error("Failed to claim session", {
-            description: error.message || "Unable to claim session",
-          });
-        }
-        throw error;
-      }
-    },
-    [claimSessionMutation, queryClient, refetch],
-  );
-
-  const clearSession = useCallback(function clearSession() {
-    setSessionId(null);
-    setError(null);
-    storage.clean(Key.CHAT_SESSION_ID);
-    justCreatedSessionIdRef.current = null;
-  }, []);
-
-  return {
-    session,
-    sessionId,
-    messages,
-    isLoading,
-    isCreating,
-    error,
-    createSession,
-    loadSession,
-    refreshSession,
-    claimSession,
-    clearSession,
-  };
-}

autogpt_platform/frontend/src/app/(platform)/chat/page.tsx

@@ -1,27 +0,0 @@
-"use client";
-
-import { Flag, useGetFlag } from "@/services/feature-flags/use-get-flag";
-import { useRouter } from "next/navigation";
-import { useEffect } from "react";
-import { Chat } from "./components/Chat/Chat";
-
-export default function ChatPage() {
-  const isChatEnabled = useGetFlag(Flag.CHAT);
-  const router = useRouter();
-
-  useEffect(() => {
-    if (isChatEnabled === false) {
-      router.push("/marketplace");
-    }
-  }, [isChatEnabled, router]);
-
-  if (isChatEnabled === null || isChatEnabled === false) {
-    return null;
-  }
-
-  return (
-    <div className="flex h-full flex-col">
-      <Chat className="flex-1" />
-    </div>
-  );
-}

autogpt_platform/frontend/src/app/(platform)/copilot/components/CopilotShell/CopilotShell.tsx

@@ -0,0 +1,88 @@
+"use client";
+
+import { LoadingSpinner } from "@/components/atoms/LoadingSpinner/LoadingSpinner";
+import { NAVBAR_HEIGHT_PX } from "@/lib/constants";
+import type { ReactNode } from "react";
+import { DesktopSidebar } from "./components/DesktopSidebar/DesktopSidebar";
+import { LoadingState } from "./components/LoadingState/LoadingState";
+import { MobileDrawer } from "./components/MobileDrawer/MobileDrawer";
+import { MobileHeader } from "./components/MobileHeader/MobileHeader";
+import { useCopilotShell } from "./useCopilotShell";
+
+interface Props {
+  children: ReactNode;
+}
+
+export function CopilotShell({ children }: Props) {
+  const {
+    isMobile,
+    isDrawerOpen,
+    isLoading,
+    isLoggedIn,
+    hasActiveSession,
+    sessions,
+    currentSessionId,
+    handleSelectSession,
+    handleOpenDrawer,
+    handleCloseDrawer,
+    handleDrawerOpenChange,
+    handleNewChat,
+    hasNextPage,
+    isFetchingNextPage,
+    fetchNextPage,
+    isReadyToShowContent,
+  } = useCopilotShell();
+
+  if (!isLoggedIn) {
+    return (
+      <div className="flex h-full items-center justify-center">
+        <LoadingSpinner size="large" />
+      </div>
+    );
+  }
+
+  return (
+    <div
+      className="flex overflow-hidden bg-[#EFEFF0]"
+      style={{ height: `calc(100vh - ${NAVBAR_HEIGHT_PX}px)` }}
+    >
+      {!isMobile && (
+        <DesktopSidebar
+          sessions={sessions}
+          currentSessionId={currentSessionId}
+          isLoading={isLoading}
+          hasNextPage={hasNextPage}
+          isFetchingNextPage={isFetchingNextPage}
+          onSelectSession={handleSelectSession}
+          onFetchNextPage={fetchNextPage}
+          onNewChat={handleNewChat}
+          hasActiveSession={Boolean(hasActiveSession)}
+        />
+      )}
+
+      <div className="relative flex min-h-0 flex-1 flex-col">
+        {isMobile && <MobileHeader onOpenDrawer={handleOpenDrawer} />}
+        <div className="flex min-h-0 flex-1 flex-col">
+          {isReadyToShowContent ? children : <LoadingState />}
+        </div>
+      </div>
+
+      {isMobile && (
+        <MobileDrawer
+          isOpen={isDrawerOpen}
+          sessions={sessions}
+          currentSessionId={currentSessionId}
+          isLoading={isLoading}
+          hasNextPage={hasNextPage}
+          isFetchingNextPage={isFetchingNextPage}
+          onSelectSession={handleSelectSession}
+          onFetchNextPage={fetchNextPage}
+          onNewChat={handleNewChat}
+          onClose={handleCloseDrawer}
+          onOpenChange={handleDrawerOpenChange}
+          hasActiveSession={Boolean(hasActiveSession)}
+        />
+      )}
+    </div>
+  );
+}

autogpt_platform/frontend/src/app/(platform)/copilot/components/CopilotShell/components/DesktopSidebar/DesktopSidebar.tsx

@@ -0,0 +1,70 @@
+import type { SessionSummaryResponse } from "@/app/api/__generated__/models/sessionSummaryResponse";
+import { Button } from "@/components/atoms/Button/Button";
+import { Text } from "@/components/atoms/Text/Text";
+import { scrollbarStyles } from "@/components/styles/scrollbars";
+import { cn } from "@/lib/utils";
+import { Plus } from "@phosphor-icons/react";
+import { SessionsList } from "../SessionsList/SessionsList";
+
+interface Props {
+  sessions: SessionSummaryResponse[];
+  currentSessionId: string | null;
+  isLoading: boolean;
+  hasNextPage: boolean;
+  isFetchingNextPage: boolean;
+  onSelectSession: (sessionId: string) => void;
+  onFetchNextPage: () => void;
+  onNewChat: () => void;
+  hasActiveSession: boolean;
+}
+
+export function DesktopSidebar({
+  sessions,
+  currentSessionId,
+  isLoading,
+  hasNextPage,
+  isFetchingNextPage,
+  onSelectSession,
+  onFetchNextPage,
+  onNewChat,
+  hasActiveSession,
+}: Props) {
+  return (
+    <aside className="flex h-full w-80 flex-col border-r border-zinc-100 bg-zinc-50">
+      <div className="shrink-0 px-6 py-4">
+        <Text variant="h3" size="body-medium">
+          Your chats
+        </Text>
+      </div>
+      <div
+        className={cn(
+          "flex min-h-0 flex-1 flex-col overflow-y-auto px-3 py-3",
+          scrollbarStyles,
+        )}
+      >
+        <SessionsList
+          sessions={sessions}
+          currentSessionId={currentSessionId}
+          isLoading={isLoading}
+          hasNextPage={hasNextPage}
+          isFetchingNextPage={isFetchingNextPage}
+          onSelectSession={onSelectSession}
+          onFetchNextPage={onFetchNextPage}
+        />
+      </div>
+      {hasActiveSession && (
+        <div className="shrink-0 bg-zinc-50 p-3 shadow-[0_-4px_6px_-1px_rgba(0,0,0,0.05)]">
+          <Button
+            variant="primary"
+            size="small"
+            onClick={onNewChat}
+            className="w-full"
+            leftIcon={<Plus width="1rem" height="1rem" />}
+          >
+            New Chat
+          </Button>
+        </div>
+      )}
+    </aside>
+  );
+}

autogpt_platform/frontend/src/app/(platform)/copilot/components/CopilotShell/components/LoadingState/LoadingState.tsx

@@ -0,0 +1,15 @@
+import { Text } from "@/components/atoms/Text/Text";
+import { ChatLoader } from "@/components/contextual/Chat/components/ChatLoader/ChatLoader";
+
+export function LoadingState() {
+  return (
+    <div className="flex flex-1 items-center justify-center">
+      <div className="flex flex-col items-center gap-4">
+        <ChatLoader />
+        <Text variant="body" className="text-zinc-500">
+          Loading your chats...
+        </Text>
+      </div>
+    </div>
+  );
+}

autogpt_platform/frontend/src/app/(platform)/copilot/components/CopilotShell/components/MobileDrawer/MobileDrawer.tsx

@@ -0,0 +1,91 @@
+import type { SessionSummaryResponse } from "@/app/api/__generated__/models/sessionSummaryResponse";
+import { Button } from "@/components/atoms/Button/Button";
+import { scrollbarStyles } from "@/components/styles/scrollbars";
+import { cn } from "@/lib/utils";
+import { PlusIcon, X } from "@phosphor-icons/react";
+import { Drawer } from "vaul";
+import { SessionsList } from "../SessionsList/SessionsList";
+
+interface Props {
+  isOpen: boolean;
+  sessions: SessionSummaryResponse[];
+  currentSessionId: string | null;
+  isLoading: boolean;
+  hasNextPage: boolean;
+  isFetchingNextPage: boolean;
+  onSelectSession: (sessionId: string) => void;
+  onFetchNextPage: () => void;
+  onNewChat: () => void;
+  onClose: () => void;
+  onOpenChange: (open: boolean) => void;
+  hasActiveSession: boolean;
+}
+
+export function MobileDrawer({
+  isOpen,
+  sessions,
+  currentSessionId,
+  isLoading,
+  hasNextPage,
+  isFetchingNextPage,
+  onSelectSession,
+  onFetchNextPage,
+  onNewChat,
+  onClose,
+  onOpenChange,
+  hasActiveSession,
+}: Props) {
+  return (
+    <Drawer.Root open={isOpen} onOpenChange={onOpenChange} direction="left">
+      <Drawer.Portal>
+        <Drawer.Overlay className="fixed inset-0 z-[60] bg-black/10 backdrop-blur-sm" />
+        <Drawer.Content className="fixed left-0 top-0 z-[70] flex h-full w-80 flex-col border-r border-zinc-200 bg-zinc-50">
+          <div className="shrink-0 border-b border-zinc-200 p-4">
+            <div className="flex items-center justify-between">
+              <Drawer.Title className="text-lg font-semibold text-zinc-800">
+                Your tasks
+              </Drawer.Title>
+              <Button
+                variant="icon"
+                size="icon"
+                aria-label="Close sessions"
+                onClick={onClose}
+              >
+                <X width="1.25rem" height="1.25rem" />
+              </Button>
+            </div>
+          </div>
+          <div
+            className={cn(
+              "flex min-h-0 flex-1 flex-col overflow-y-auto px-3 py-3",
+              scrollbarStyles,
+            )}
+          >
+            <SessionsList
+              sessions={sessions}
+              currentSessionId={currentSessionId}
+              isLoading={isLoading}
+              hasNextPage={hasNextPage}
+              isFetchingNextPage={isFetchingNextPage}
+              onSelectSession={onSelectSession}
+              onFetchNextPage={onFetchNextPage}
+            />
+          </div>
+          {hasActiveSession && (
+            <div className="shrink-0 bg-white p-3 shadow-[0_-4px_6px_-1px_rgba(0,0,0,0.05)]">
+              <Button
+                variant="primary"
+                size="small"
+                onClick={onNewChat}
+                className="w-full"
+                leftIcon={<PlusIcon width="1rem" height="1rem" />}
+              >
+                New Chat
+              </Button>
+            </div>
+          )}
+        </Drawer.Content>
+      </Drawer.Portal>
+    </Drawer.Root>
+  );
+}

autogpt_platform/frontend/src/app/(platform)/copilot/components/CopilotShell/components/MobileDrawer/useMobileDrawer.ts

@@ -0,0 +1,24 @@
+import { useState } from "react";
+
+export function useMobileDrawer() {
+  const [isDrawerOpen, setIsDrawerOpen] = useState(false);
+
+  function handleOpenDrawer() {
+    setIsDrawerOpen(true);
+  }
+
+  function handleCloseDrawer() {
+    setIsDrawerOpen(false);
+  }
+
+  function handleDrawerOpenChange(open: boolean) {
+    setIsDrawerOpen(open);
+  }
+
+  return {
+    isDrawerOpen,
+    handleOpenDrawer,
+    handleCloseDrawer,
+    handleDrawerOpenChange,
+  };
+}

autogpt_platform/frontend/src/app/(platform)/copilot/components/CopilotShell/components/MobileHeader/MobileHeader.tsx

@@ -0,0 +1,22 @@
+import { Button } from "@/components/atoms/Button/Button";
+import { NAVBAR_HEIGHT_PX } from "@/lib/constants";
+import { ListIcon } from "@phosphor-icons/react";
+
+interface Props {
+  onOpenDrawer: () => void;
+}
+
+export function MobileHeader({ onOpenDrawer }: Props) {
+  return (
+    <Button
+      variant="icon"
+      size="icon"
+      aria-label="Open sessions"
+      onClick={onOpenDrawer}
+      className="fixed z-50 bg-white shadow-md"
+      style={{ left: "1rem", top: `${NAVBAR_HEIGHT_PX + 20}px` }}
+    >
+      <ListIcon width="1.25rem" height="1.25rem" />
+    </Button>
+  );
+}

autogpt_platform/frontend/src/app/(platform)/copilot/components/CopilotShell/components/SessionsList/SessionsList.tsx

@@ -0,0 +1,80 @@
+import type { SessionSummaryResponse } from "@/app/api/__generated__/models/sessionSummaryResponse";
+import { Skeleton } from "@/components/__legacy__/ui/skeleton";
+import { Text } from "@/components/atoms/Text/Text";
+import { InfiniteList } from "@/components/molecules/InfiniteList/InfiniteList";
+import { cn } from "@/lib/utils";
+import { getSessionTitle } from "../../helpers";
+
+interface Props {
+  sessions: SessionSummaryResponse[];
+  currentSessionId: string | null;
+  isLoading: boolean;
+  hasNextPage: boolean;
+  isFetchingNextPage: boolean;
+  onSelectSession: (sessionId: string) => void;
+  onFetchNextPage: () => void;
+}
+
+export function SessionsList({
+  sessions,
+  currentSessionId,
+  isLoading,
+  hasNextPage,
+  isFetchingNextPage,
+  onSelectSession,
+  onFetchNextPage,
+}: Props) {
+  if (isLoading) {
+    return (
+      <div className="space-y-1">
+        {Array.from({ length: 5 }).map((_, i) => (
+          <div key={i} className="rounded-lg px-3 py-2.5">
+            <Skeleton className="h-5 w-full" />
+          </div>
+        ))}
+      </div>
+    );
+  }
+
+  if (sessions.length === 0) {
+    return (
+      <div className="flex h-full items-center justify-center">
+        <Text variant="body" className="text-zinc-500">
+          You don&apos;t have previous chats
+        </Text>
+      </div>
+    );
+  }
+
+  return (
+    <InfiniteList
+      items={sessions}
+      hasMore={hasNextPage}
+      isFetchingMore={isFetchingNextPage}
+      onEndReached={onFetchNextPage}
+      className="space-y-1"
+      renderItem={(session) => {
+        const isActive = session.id === currentSessionId;
+        return (
+          <button
+            onClick={() => onSelectSession(session.id)}
+            className={cn(
+              "w-full rounded-lg px-3 py-2.5 text-left transition-colors",
+              isActive ? "bg-zinc-100" : "hover:bg-zinc-50",
+            )}
+          >
+            <Text
+              variant="body"
+              className={cn(
+                "font-normal",
+                isActive ? "text-zinc-600" : "text-zinc-800",
+              )}
+            >
+              {getSessionTitle(session)}
+            </Text>
+          </button>
+        );
+      }}
+    />
+  );
+}

autogpt_platform/frontend/src/app/(platform)/copilot/components/CopilotShell/components/SessionsList/useSessionsPagination.ts

@@ -0,0 +1,92 @@
+import { useGetV2ListSessions } from "@/app/api/__generated__/endpoints/chat/chat";
+import type { SessionSummaryResponse } from "@/app/api/__generated__/models/sessionSummaryResponse";
+import { okData } from "@/app/api/helpers";
+import { useEffect, useMemo, useState } from "react";
+
+const PAGE_SIZE = 50;
+
+export interface UseSessionsPaginationArgs {
+  enabled: boolean;
+}
+
+export function useSessionsPagination({ enabled }: UseSessionsPaginationArgs) {
+  const [offset, setOffset] = useState(0);
+  const [accumulatedSessions, setAccumulatedSessions] = useState<
+    SessionSummaryResponse[]
+  >([]);
+  const [totalCount, setTotalCount] = useState<number | null>(null);
+
+  const { data, isLoading, isFetching, isError } = useGetV2ListSessions(
+    { limit: PAGE_SIZE, offset },
+    {
+      query: {
+        enabled: enabled && offset >= 0,
+      },
+    },
+  );
+
+  useEffect(() => {
+    const responseData = okData(data);
+    if (responseData) {
+      const newSessions = responseData.sessions;
+      const total = responseData.total;
+      setTotalCount(total);
+
+      if (offset === 0) {
+        setAccumulatedSessions(newSessions);
+      } else {
+        setAccumulatedSessions((prev) => [...prev, ...newSessions]);
+      }
+    } else if (!enabled) {
+      setAccumulatedSessions([]);
+      setTotalCount(null);
+    }
+  }, [data, offset, enabled]);
+
+  const hasNextPage = useMemo(() => {
+    if (totalCount === null) return false;
+    return accumulatedSessions.length < totalCount;
+  }, [accumulatedSessions.length, totalCount]);
+
+  const areAllSessionsLoaded = useMemo(() => {
+    if (totalCount === null) return false;
+    return (
+      accumulatedSessions.length >= totalCount && !isFetching && !isLoading
+    );
+  }, [accumulatedSessions.length, totalCount, isFetching, isLoading]);
+
+  useEffect(() => {
+    if (
+      hasNextPage &&
+      !isFetching &&
+      !isLoading &&
+      !isError &&
+      totalCount !== null
+    ) {
+      setOffset((prev) => prev + PAGE_SIZE);
+    }
+  }, [hasNextPage, isFetching, isLoading, isError, totalCount]);
+
+  function fetchNextPage() {
+    if (hasNextPage && !isFetching) {
+      setOffset((prev) => prev + PAGE_SIZE);
+    }
+  }
+
+  function reset() {
+    setOffset(0);
+    setAccumulatedSessions([]);
+    setTotalCount(null);
+  }
+
+  return {
+    sessions: accumulatedSessions,
+    isLoading,
+    isFetching,
+    hasNextPage,
+    areAllSessionsLoaded,
+    totalCount,
+    fetchNextPage,
+    reset,
+  };
+}

autogpt_platform/frontend/src/app/(platform)/copilot/components/CopilotShell/helpers.ts

@@ -0,0 +1,165 @@
+import type { SessionDetailResponse } from "@/app/api/__generated__/models/sessionDetailResponse";
+import type { SessionSummaryResponse } from "@/app/api/__generated__/models/sessionSummaryResponse";
+import { format, formatDistanceToNow, isToday } from "date-fns";
+
+export function convertSessionDetailToSummary(
+  session: SessionDetailResponse,
+): SessionSummaryResponse {
+  return {
+    id: session.id,
+    created_at: session.created_at,
+    updated_at: session.updated_at,
+    title: undefined,
+  };
+}
+
+export function filterVisibleSessions(
+  sessions: SessionSummaryResponse[],
+): SessionSummaryResponse[] {
+  return sessions.filter(
+    (session) => session.updated_at !== session.created_at,
+  );
+}
+
+export function getSessionTitle(session: SessionSummaryResponse): string {
+  if (session.title) return session.title;
+  const isNewSession = session.updated_at === session.created_at;
+  if (isNewSession) {
+    const createdDate = new Date(session.created_at);
+    if (isToday(createdDate)) {
+      return "Today";
+    }
+    return format(createdDate, "MMM d, yyyy");
+  }
+  return "Untitled Chat";
+}
+
+export function getSessionUpdatedLabel(
+  session: SessionSummaryResponse,
+): string {
+  if (!session.updated_at) return "";
+  return formatDistanceToNow(new Date(session.updated_at), { addSuffix: true });
+}
+
+export function mergeCurrentSessionIntoList(
+  accumulatedSessions: SessionSummaryResponse[],
+  currentSessionId: string | null,
+  currentSessionData: SessionDetailResponse | null | undefined,
+): SessionSummaryResponse[] {
+  const filteredSessions: SessionSummaryResponse[] = [];
+
+  if (accumulatedSessions.length > 0) {
+    const visibleSessions = filterVisibleSessions(accumulatedSessions);
+
+    if (currentSessionId) {
+      const currentInAll = accumulatedSessions.find(
+        (s) => s.id === currentSessionId,
+      );
+      if (currentInAll) {
+        const isInVisible = visibleSessions.some(
+          (s) => s.id === currentSessionId,
+        );
+        if (!isInVisible) {
+          filteredSessions.push(currentInAll);
+        }
+      }
+    }
+
+    filteredSessions.push(...visibleSessions);
+  }
+
+  if (currentSessionId && currentSessionData) {
+    const isCurrentInList = filteredSessions.some(
+      (s) => s.id === currentSessionId,
+    );
+    if (!isCurrentInList) {
+      const summarySession = convertSessionDetailToSummary(currentSessionData);
+      filteredSessions.unshift(summarySession);
+    }
+  }
+
+  return filteredSessions;
+}
+
+export function getCurrentSessionId(
+  searchParams: URLSearchParams,
+): string | null {
+  return searchParams.get("sessionId");
+}
+
+export function shouldAutoSelectSession(
+  areAllSessionsLoaded: boolean,
+  hasAutoSelectedSession: boolean,
+  paramSessionId: string | null,
+  visibleSessions: SessionSummaryResponse[],
+  accumulatedSessions: SessionSummaryResponse[],
+  isLoading: boolean,
+  totalCount: number | null,
+): {
+  shouldSelect: boolean;
+  sessionIdToSelect: string | null;
+  shouldCreate: boolean;
+} {
+  if (!areAllSessionsLoaded || hasAutoSelectedSession) {
+    return {
+      shouldSelect: false,
+      sessionIdToSelect: null,
+      shouldCreate: false,
+    };
+  }
+
+  if (paramSessionId) {
+    return {
+      shouldSelect: false,
+      sessionIdToSelect: null,
+      shouldCreate: false,
+    };
+  }
+
+  if (visibleSessions.length > 0) {
+    return {
+      shouldSelect: true,
+      sessionIdToSelect: visibleSessions[0].id,
+      shouldCreate: false,
+    };
+  }
+
+  if (accumulatedSessions.length === 0 && !isLoading && totalCount === 0) {
+    return { shouldSelect: false, sessionIdToSelect: null, shouldCreate: true };
+  }
+
+  if (totalCount === 0) {
+    return {
+      shouldSelect: false,
+      sessionIdToSelect: null,
+      shouldCreate: false,
+    };
+  }
+
+  return { shouldSelect: false, sessionIdToSelect: null, shouldCreate: false };
+}
+
+export function checkReadyToShowContent(
+  areAllSessionsLoaded: boolean,
+  paramSessionId: string | null,
+  accumulatedSessions: SessionSummaryResponse[],
+  isCurrentSessionLoading: boolean,
+  currentSessionData: SessionDetailResponse | null | undefined,
+  hasAutoSelectedSession: boolean,
+): boolean {
+  if (!areAllSessionsLoaded) return false;
+
+  if (paramSessionId) {
+    const sessionFound = accumulatedSessions.some(
+      (s) => s.id === paramSessionId,
+    );
+    return (
+      sessionFound ||
+      (!isCurrentSessionLoading &&
+        currentSessionData !== undefined &&
+        currentSessionData !== null)
+    );
+  }
+
+  return hasAutoSelectedSession;
+}

autogpt_platform/frontend/src/app/(platform)/copilot/components/CopilotShell/useCopilotShell.ts

@@ -0,0 +1,170 @@
+"use client";
+
+import {
+  getGetV2ListSessionsQueryKey,
+  useGetV2GetSession,
+} from "@/app/api/__generated__/endpoints/chat/chat";
+import { okData } from "@/app/api/helpers";
+import { useBreakpoint } from "@/lib/hooks/useBreakpoint";
+import { useSupabase } from "@/lib/supabase/hooks/useSupabase";
+import { useQueryClient } from "@tanstack/react-query";
+import { usePathname, useRouter, useSearchParams } from "next/navigation";
+import { useEffect, useRef, useState } from "react";
+import { useMobileDrawer } from "./components/MobileDrawer/useMobileDrawer";
+import { useSessionsPagination } from "./components/SessionsList/useSessionsPagination";
+import {
+  checkReadyToShowContent,
+  filterVisibleSessions,
+  getCurrentSessionId,
+  mergeCurrentSessionIntoList,
+} from "./helpers";
+
+export function useCopilotShell() {
+  const router = useRouter();
+  const pathname = usePathname();
+  const searchParams = useSearchParams();
+  const queryClient = useQueryClient();
+  const breakpoint = useBreakpoint();
+  const { isLoggedIn } = useSupabase();
+  const isMobile =
+    breakpoint === "base" || breakpoint === "sm" || breakpoint === "md";
+
+  const isOnHomepage = pathname === "/copilot";
+  const paramSessionId = searchParams.get("sessionId");
+
+  const {
+    isDrawerOpen,
+    handleOpenDrawer,
+    handleCloseDrawer,
+    handleDrawerOpenChange,
+  } = useMobileDrawer();
+
+  const paginationEnabled = !isMobile || isDrawerOpen || !!paramSessionId;
+
+  const {
+    sessions: accumulatedSessions,
+    isLoading: isSessionsLoading,
+    isFetching: isSessionsFetching,
+    hasNextPage,
+    areAllSessionsLoaded,
+    fetchNextPage,
+    reset: resetPagination,
+  } = useSessionsPagination({
+    enabled: paginationEnabled,
+  });
+
+  const currentSessionId = getCurrentSessionId(searchParams);
+
+  const { data: currentSessionData, isLoading: isCurrentSessionLoading } =
+    useGetV2GetSession(currentSessionId || "", {
+      query: {
+        enabled: !!currentSessionId,
+        select: okData,
+      },
+    });
+
+  const [hasAutoSelectedSession, setHasAutoSelectedSession] = useState(false);
+  const hasAutoSelectedRef = useRef(false);
+
+  // Mark as auto-selected when sessionId is in URL
+  useEffect(() => {
+    if (paramSessionId && !hasAutoSelectedRef.current) {
+      hasAutoSelectedRef.current = true;
+      setHasAutoSelectedSession(true);
+    }
+  }, [paramSessionId]);
+
+  // On homepage without sessionId, mark as ready immediately
+  useEffect(() => {
+    if (isOnHomepage && !paramSessionId && !hasAutoSelectedRef.current) {
+      hasAutoSelectedRef.current = true;
+      setHasAutoSelectedSession(true);
+    }
+  }, [isOnHomepage, paramSessionId]);
+
+  // Invalidate sessions list when navigating to homepage (to show newly created sessions)
+  useEffect(() => {
+    if (isOnHomepage && !paramSessionId) {
+      queryClient.invalidateQueries({
+        queryKey: getGetV2ListSessionsQueryKey(),
+      });
+    }
+  }, [isOnHomepage, paramSessionId, queryClient]);
+
+  // Reset pagination when query becomes disabled
+  const prevPaginationEnabledRef = useRef(paginationEnabled);
+  useEffect(() => {
+    if (prevPaginationEnabledRef.current && !paginationEnabled) {
+      resetPagination();
+      resetAutoSelect();
+    }
+    prevPaginationEnabledRef.current = paginationEnabled;
+  }, [paginationEnabled, resetPagination]);
+
+  const sessions = mergeCurrentSessionIntoList(
+    accumulatedSessions,
+    currentSessionId,
+    currentSessionData,
+  );
+
+  const visibleSessions = filterVisibleSessions(sessions);
+
+  const sidebarSelectedSessionId =
+    isOnHomepage && !paramSessionId ? null : currentSessionId;
+
+  const isReadyToShowContent = isOnHomepage
+    ? true
+    : checkReadyToShowContent(
+        areAllSessionsLoaded,
+        paramSessionId,
+        accumulatedSessions,
+        isCurrentSessionLoading,
+        currentSessionData,
+        hasAutoSelectedSession,
+      );
+
+  function handleSelectSession(sessionId: string) {
+    // Navigate using replaceState to avoid full page reload
+    window.history.replaceState(null, "", `/copilot?sessionId=${sessionId}`);
+    // Force a re-render by updating the URL through router
+    router.replace(`/copilot?sessionId=${sessionId}`);
+    if (isMobile) handleCloseDrawer();
+  }
+
+  function handleNewChat() {
+    resetAutoSelect();
+    resetPagination();
+    // Invalidate and refetch sessions list to ensure newly created sessions appear
+    queryClient.invalidateQueries({
+      queryKey: getGetV2ListSessionsQueryKey(),
+    });
+    window.history.replaceState(null, "", "/copilot");
+    router.replace("/copilot");
+    if (isMobile) handleCloseDrawer();
+  }
+
+  function resetAutoSelect() {
+    hasAutoSelectedRef.current = false;
+    setHasAutoSelectedSession(false);
+  }
+
+  return {
+    isMobile,
+    isDrawerOpen,
+    isLoggedIn,
+    hasActiveSession:
+      Boolean(currentSessionId) && (!isOnHomepage || Boolean(paramSessionId)),
+    isLoading: isSessionsLoading || !areAllSessionsLoaded,
+    sessions: visibleSessions,
+    currentSessionId: sidebarSelectedSessionId,
+    handleSelectSession,
+    handleOpenDrawer,
+    handleCloseDrawer,
+    handleDrawerOpenChange,
+    handleNewChat,
+    hasNextPage,
+    isFetchingNextPage: isSessionsFetching,
+    fetchNextPage,
+    isReadyToShowContent,
+  };
+}

autogpt_platform/frontend/src/app/(platform)/copilot/helpers.ts

@@ -0,0 +1,33 @@
+import type { User } from "@supabase/supabase-js";
+
+export function getGreetingName(user?: User | null): string {
+  if (!user) return "there";
+  const metadata = user.user_metadata as Record<string, unknown> | undefined;
+  const fullName = metadata?.full_name;
+  const name = metadata?.name;
+  if (typeof fullName === "string" && fullName.trim()) {
+    return fullName.split(" ")[0];
+  }
+  if (typeof name === "string" && name.trim()) {
+    return name.split(" ")[0];
+  }
+  if (user.email) {
+    return user.email.split("@")[0];
+  }
+  return "there";
+}
+
+export function buildCopilotChatUrl(prompt: string): string {
+  const trimmed = prompt.trim();
+  if (!trimmed) return "/copilot/chat";
+  const encoded = encodeURIComponent(trimmed);
+  return `/copilot/chat?prompt=${encoded}`;
+}
+
+export function getQuickActions(): string[] {
+  return [
+    "Show me what I can automate",
+    "Design a custom workflow",
+    "Help me with content creation",
+  ];
+}

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

@@ -0,0 +1,6 @@
+import type { ReactNode } from "react";
+import { CopilotShell } from "./components/CopilotShell/CopilotShell";
+
+export default function CopilotLayout({ children }: { children: ReactNode }) {
+  return <CopilotShell>{children}</CopilotShell>;
+}

autogpt_platform/frontend/src/app/(platform)/copilot/page.tsx

@@ -0,0 +1,223 @@
+"use client";
+
+import { postV2CreateSession } from "@/app/api/__generated__/endpoints/chat/chat";
+import { Skeleton } from "@/components/__legacy__/ui/skeleton";
+import { Button } from "@/components/atoms/Button/Button";
+import { LoadingSpinner } from "@/components/atoms/LoadingSpinner/LoadingSpinner";
+import { Text } from "@/components/atoms/Text/Text";
+import { Chat } from "@/components/contextual/Chat/Chat";
+import { ChatInput } from "@/components/contextual/Chat/components/ChatInput/ChatInput";
+import { getHomepageRoute } from "@/lib/constants";
+import { useSupabase } from "@/lib/supabase/hooks/useSupabase";
+import {
+  Flag,
+  type FlagValues,
+  useGetFlag,
+} from "@/services/feature-flags/use-get-flag";
+import { useFlags } from "launchdarkly-react-client-sdk";
+import { useRouter, useSearchParams } from "next/navigation";
+import { useEffect, useMemo, useRef, useState } from "react";
+import { getGreetingName, getQuickActions } from "./helpers";
+
+type PageState =
+  | { type: "welcome" }
+  | { type: "creating"; prompt: string }
+  | { type: "chat"; sessionId: string; initialPrompt?: string };
+
+export default function CopilotPage() {
+  const router = useRouter();
+  const searchParams = useSearchParams();
+  const { user, isLoggedIn, isUserLoading } = useSupabase();
+
+  const isChatEnabled = useGetFlag(Flag.CHAT);
+  const flags = useFlags<FlagValues>();
+  const homepageRoute = getHomepageRoute(isChatEnabled);
+  const envEnabled = process.env.NEXT_PUBLIC_LAUNCHDARKLY_ENABLED === "true";
+  const clientId = process.env.NEXT_PUBLIC_LAUNCHDARKLY_CLIENT_ID;
+  const isLaunchDarklyConfigured = envEnabled && Boolean(clientId);
+  const isFlagReady =
+    !isLaunchDarklyConfigured || flags[Flag.CHAT] !== undefined;
+
+  const [pageState, setPageState] = useState<PageState>({ type: "welcome" });
+  const initialPromptRef = useRef<Map<string, string>>(new Map());
+
+  const urlSessionId = searchParams.get("sessionId");
+
+  // Sync with URL sessionId (preserve initialPrompt from ref)
+  useEffect(
+    function syncSessionFromUrl() {
+      if (urlSessionId) {
+        // If we're already in chat state with this sessionId, don't overwrite
+        if (pageState.type === "chat" && pageState.sessionId === urlSessionId) {
+          return;
+        }
+        // Get initialPrompt from ref or current state
+        const storedInitialPrompt = initialPromptRef.current.get(urlSessionId);
+        const currentInitialPrompt =
+          storedInitialPrompt ||
+          (pageState.type === "creating"
+            ? pageState.prompt
+            : pageState.type === "chat"
+              ? pageState.initialPrompt
+              : undefined);
+        if (currentInitialPrompt) {
+          initialPromptRef.current.set(urlSessionId, currentInitialPrompt);
+        }
+        setPageState({
+          type: "chat",
+          sessionId: urlSessionId,
+          initialPrompt: currentInitialPrompt,
+        });
+      } else if (pageState.type === "chat") {
+        setPageState({ type: "welcome" });
+      }
+    },
+    [urlSessionId],
+  );
+
+  useEffect(
+    function ensureAccess() {
+      if (!isFlagReady) return;
+      if (isChatEnabled === false) {
+        router.replace(homepageRoute);
+      }
+    },
+    [homepageRoute, isChatEnabled, isFlagReady, router],
+  );
+
+  const greetingName = useMemo(
+    function getName() {
+      return getGreetingName(user);
+    },
+    [user],
+  );
+
+  const quickActions = useMemo(function getActions() {
+    return getQuickActions();
+  }, []);
+
+  async function startChatWithPrompt(prompt: string) {
+    if (!prompt?.trim()) return;
+    if (pageState.type === "creating") return;
+
+    const trimmedPrompt = prompt.trim();
+    setPageState({ type: "creating", prompt: trimmedPrompt });
+
+    try {
+      // Create session
+      const sessionResponse = await postV2CreateSession({
+        body: JSON.stringify({}),
+      });
+
+      if (sessionResponse.status !== 200 || !sessionResponse.data?.id) {
+        throw new Error("Failed to create session");
+      }
+
+      const sessionId = sessionResponse.data.id;
+
+      // Store initialPrompt in ref so it persists across re-renders
+      initialPromptRef.current.set(sessionId, trimmedPrompt);
+
+      // Update URL and show Chat with initial prompt
+      // Chat will handle sending the message and streaming
+      window.history.replaceState(null, "", `/copilot?sessionId=${sessionId}`);
+      setPageState({ type: "chat", sessionId, initialPrompt: trimmedPrompt });
+    } catch (error) {
+      console.error("[CopilotPage] Failed to start chat:", error);
+      setPageState({ type: "welcome" });
+    }
+  }
+
+  function handleQuickAction(action: string) {
+    startChatWithPrompt(action);
+  }
+
+  if (!isFlagReady || isChatEnabled === false || !isLoggedIn) {
+    return null;
+  }
+
+  // Show Chat when we have an active session
+  if (pageState.type === "chat") {
+    return (
+      <div className="flex h-full flex-col">
+        <Chat
+          key={pageState.sessionId ?? "welcome"}
+          className="flex-1"
+          urlSessionId={pageState.sessionId}
+          initialPrompt={pageState.initialPrompt}
+        />
+      </div>
+    );
+  }
+
+  // Show loading state while creating session and sending first message
+  if (pageState.type === "creating") {
+    return (
+      <div className="flex h-full flex-1 flex-col items-center justify-center bg-[#f8f8f9] px-6 py-10">
+        <LoadingSpinner size="large" />
+        <Text variant="body" className="mt-4 text-zinc-500">
+          Starting your chat...
+        </Text>
+      </div>
+    );
+  }
+
+  // Show Welcome screen
+  const isLoading = isUserLoading;
+
+  return (
+    <div className="flex h-full flex-1 items-center justify-center overflow-y-auto bg-[#f8f8f9] px-6 py-10">
+      <div className="w-full text-center">
+        {isLoading ? (
+          <div className="mx-auto max-w-2xl">
+            <Skeleton className="mx-auto mb-3 h-8 w-64" />
+            <Skeleton className="mx-auto mb-8 h-6 w-80" />
+            <div className="mb-8">
+              <Skeleton className="mx-auto h-14 w-full rounded-lg" />
+            </div>
+            <div className="flex flex-wrap items-center justify-center gap-3">
+              {Array.from({ length: 4 }).map((_, i) => (
+                <Skeleton key={i} className="h-9 w-48 rounded-md" />
+              ))}
+            </div>
+          </div>
+        ) : (
+          <>
+            <div className="mx-auto max-w-2xl">
+              <Text
+                variant="h3"
+                className="mb-3 !text-[1.375rem] text-zinc-700"
+              >
+                Hey, <span className="text-violet-600">{greetingName}</span>
+              </Text>
+              <Text variant="h3" className="mb-8 !font-normal">
+                What do you want to automate?
+              </Text>
+
+              <div className="mb-6">
+                <ChatInput
+                  onSend={startChatWithPrompt}
+                  placeholder='You can search or just ask - e.g. "create a blog post outline"'
+                />
+              </div>
+            </div>
+            <div className="flex flex-nowrap items-center justify-center gap-3 overflow-x-auto [-ms-overflow-style:none] [scrollbar-width:none] [&::-webkit-scrollbar]:hidden">
+              {quickActions.map((action) => (
+                <Button
+                  key={action}
+                  type="button"
+                  variant="outline"
+                  size="small"
+                  onClick={() => handleQuickAction(action)}
+                  className="h-auto shrink-0 border-zinc-600 !px-4 !py-2 text-[1rem] text-zinc-600"
+                >
+                  {action}
+                </Button>
+              ))}
+            </div>
+          </>
+        )}
+      </div>
+    </div>
+  );
+}

autogpt_platform/frontend/src/app/(platform)/error/page.tsx

@@ -1,6 +1,8 @@
 "use client";
 
 import { ErrorCard } from "@/components/molecules/ErrorCard/ErrorCard";
+import { getHomepageRoute } from "@/lib/constants";
+import { Flag, useGetFlag } from "@/services/feature-flags/use-get-flag";
 import { useSearchParams } from "next/navigation";
 import { Suspense } from "react";
 import { getErrorDetails } from "./helpers";
@@ -9,6 +11,8 @@ function ErrorPageContent() {
   const searchParams = useSearchParams();
   const errorMessage = searchParams.get("message");
   const errorDetails = getErrorDetails(errorMessage);
+  const isChatEnabled = useGetFlag(Flag.CHAT);
+  const homepageRoute = getHomepageRoute(isChatEnabled);
 
   function handleRetry() {
     // Auth-related errors should redirect to login
@@ -25,8 +29,8 @@ function ErrorPageContent() {
         window.location.reload();
       }, 2000);
     } else {
-      // For server/network errors, go to marketplace
-      window.location.href = "/marketplace";
+      // For server/network errors, go to home
+      window.location.href = homepageRoute;
     }
   }
 

autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/NewAgentLibraryView/components/modals/RunAgentModal/RunAgentModal.tsx

@@ -180,7 +180,7 @@ export function RunAgentModal({
 
               {/* Content */}
               {hasAnySetupFields ? (
-                <div className="mt-10 pb-32">
+                <div className="mt-4 pb-10">
                   <RunAgentModalContextProvider
                     value={{
                       agent,

autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/NewAgentLibraryView/components/modals/RunAgentModal/components/ModalHeader/ModalHeader.tsx

@@ -29,7 +29,7 @@ export function ModalHeader({ agent }: ModalHeaderProps) {
           <ShowMoreText
             previewLimit={400}
             variant="small"
-            className="mt-4 !text-zinc-700"
+            className="mb-2 mt-4 !text-zinc-700"
           >
             {agent.description}
           </ShowMoreText>
@@ -40,6 +40,8 @@ export function ModalHeader({ agent }: ModalHeaderProps) {
             <Text variant="lead-semibold" className="text-blue-600">
               Tip
             </Text>
+            <div className="h-px w-full bg-blue-100" />
+
             <Text variant="body">
               For best results, run this agent{" "}
               {humanizeCronExpression(
@@ -50,7 +52,7 @@ export function ModalHeader({ agent }: ModalHeaderProps) {
         ) : null}
 
         {agent.instructions ? (
-          <div className="flex flex-col gap-4 rounded-medium border border-purple-100 bg-[#F1EBFE/5] p-4">
+          <div className="mt-4 flex flex-col gap-4 rounded-medium border border-purple-100 bg-[#f1ebfe80] p-4">
             <Text variant="lead-semibold" className="text-purple-600">
               Instructions
             </Text>

autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/NewAgentLibraryView/components/modals/RunAgentModal/components/ModalRunSection/ModalRunSection.tsx

@@ -1,9 +1,9 @@
 import { Input } from "@/components/atoms/Input/Input";
+import { CredentialsGroupedView } from "@/components/contextual/CredentialsInput/components/CredentialsGroupedView/CredentialsGroupedView";
 import { InformationTooltip } from "@/components/molecules/InformationTooltip/InformationTooltip";
 import { useMemo } from "react";
 import { RunAgentInputs } from "../../../RunAgentInputs/RunAgentInputs";
 import { useRunAgentModalContext } from "../../context";
-import { CredentialsGroupedView } from "../CredentialsGroupedView/CredentialsGroupedView";
 import { ModalSection } from "../ModalSection/ModalSection";
 import { WebhookTriggerBanner } from "../WebhookTriggerBanner/WebhookTriggerBanner";
 
@@ -19,6 +19,8 @@ export function ModalRunSection() {
     setInputValue,
     agentInputFields,
     agentCredentialsInputFields,
+    inputCredentials,
+    setInputCredentialsValue,
   } = useRunAgentModalContext();
 
   const inputFields = Object.entries(agentInputFields || {});
@@ -102,6 +104,9 @@ export function ModalRunSection() {
           <CredentialsGroupedView
             credentialFields={credentialFields}
             requiredCredentials={requiredCredentials}
+            inputCredentials={inputCredentials}
+            inputValues={inputValues}
+            onCredentialChange={setInputCredentialsValue}
           />
         </ModalSection>
       ) : null}

autogpt_platform/frontend/src/app/(platform)/library/components/LibraryAgentCard/useLibraryAgentCard.ts

@@ -8,6 +8,8 @@ import { useGetV2GetUserProfile } from "@/app/api/__generated__/endpoints/store/
 import { LibraryAgent } from "@/app/api/__generated__/models/libraryAgent";
 import { okData } from "@/app/api/helpers";
 import { useToast } from "@/components/molecules/Toast/use-toast";
+import { isLogoutInProgress } from "@/lib/autogpt-server-api/helpers";
+import { useSupabase } from "@/lib/supabase/hooks/useSupabase";
 import { updateFavoriteInQueries } from "./helpers";
 
 interface Props {
@@ -23,10 +25,14 @@ export function useLibraryAgentCard({ agent }: Props) {
   const { toast } = useToast();
   const queryClient = getQueryClient();
   const { mutateAsync: updateLibraryAgent } = usePatchV2UpdateLibraryAgent();
+  const { user, isLoggedIn } = useSupabase();
+  const logoutInProgress = isLogoutInProgress();
 
   const { data: profile } = useGetV2GetUserProfile({
     query: {
       select: okData,
+      enabled: isLoggedIn && !!user && !logoutInProgress,
+      queryKey: ["/api/store/profile", user?.id],
     },
   });
 

autogpt_platform/frontend/src/app/(platform)/library/components/LibraryUploadAgentDialog/LibraryUploadAgentDialog.tsx

@@ -2,6 +2,7 @@
 import { Button } from "@/components/atoms/Button/Button";
 import { FileInput } from "@/components/atoms/FileInput/FileInput";
 import { Input } from "@/components/atoms/Input/Input";
+import { LoadingSpinner } from "@/components/atoms/LoadingSpinner/LoadingSpinner";
 import { Dialog } from "@/components/molecules/Dialog/Dialog";
 import {
   Form,
@@ -120,7 +121,7 @@ export default function LibraryUploadAgentDialog() {
           >
             {isUploading ? (
               <div className="flex items-center gap-2">
-                <div className="h-4 w-4 animate-spin rounded-full border-b-2 border-t-2 border-white"></div>
+                <LoadingSpinner size="small" className="text-white" />
                 <span>Uploading...</span>
               </div>
             ) : (

autogpt_platform/frontend/src/app/(platform)/login/useLoginPage.ts

@@ -1,6 +1,8 @@
 import { useToast } from "@/components/molecules/Toast/use-toast";
+import { getHomepageRoute } from "@/lib/constants";
 import { useSupabase } from "@/lib/supabase/hooks/useSupabase";
 import { environment } from "@/services/environment";
+import { Flag, useGetFlag } from "@/services/feature-flags/use-get-flag";
 import { loginFormSchema, LoginProvider } from "@/types/auth";
 import { zodResolver } from "@hookform/resolvers/zod";
 import { useRouter, useSearchParams } from "next/navigation";
@@ -20,15 +22,17 @@ export function useLoginPage() {
   const [isGoogleLoading, setIsGoogleLoading] = useState(false);
   const [showNotAllowedModal, setShowNotAllowedModal] = useState(false);
   const isCloudEnv = environment.isCloud();
+  const isChatEnabled = useGetFlag(Flag.CHAT);
+  const homepageRoute = getHomepageRoute(isChatEnabled);
 
   // Get redirect destination from 'next' query parameter
   const nextUrl = searchParams.get("next");
 
   useEffect(() => {
     if (isLoggedIn && !isLoggingIn) {
-      router.push(nextUrl || "/marketplace");
+      router.push(nextUrl || homepageRoute);
     }
-  }, [isLoggedIn, isLoggingIn, nextUrl, router]);
+  }, [homepageRoute, isLoggedIn, isLoggingIn, nextUrl, router]);
 
   const form = useForm<z.infer<typeof loginFormSchema>>({
     resolver: zodResolver(loginFormSchema),
@@ -98,7 +102,7 @@ export function useLoginPage() {
       } else if (result.onboarding) {
         router.replace("/onboarding");
       } else {
-        router.replace("/marketplace");
+        router.replace(homepageRoute);
       }
     } catch (error) {
       toast({

autogpt_platform/frontend/src/app/(platform)/profile/(user)/page.tsx

@@ -3,12 +3,14 @@
 import { useGetV2GetUserProfile } from "@/app/api/__generated__/endpoints/store/store";
 import { ProfileInfoForm } from "@/components/__legacy__/ProfileInfoForm";
 import { ErrorCard } from "@/components/molecules/ErrorCard/ErrorCard";
+import { isLogoutInProgress } from "@/lib/autogpt-server-api/helpers";
 import { ProfileDetails } from "@/lib/autogpt-server-api/types";
 import { useSupabase } from "@/lib/supabase/hooks/useSupabase";
 import { ProfileLoading } from "./ProfileLoading";
 
 export default function UserProfilePage() {
   const { user } = useSupabase();
+  const logoutInProgress = isLogoutInProgress();
 
   const {
     data: profile,
@@ -18,7 +20,7 @@ export default function UserProfilePage() {
     refetch,
   } = useGetV2GetUserProfile<ProfileDetails | null>({
     query: {
-      enabled: !!user,
+      enabled: !!user && !logoutInProgress,
       select: (res) => {
         if (res.status === 200) {
           return {

autogpt_platform/frontend/src/app/(platform)/signup/actions.ts

@@ -1,5 +1,6 @@
 "use server";
 
+import { getHomepageRoute } from "@/lib/constants";
 import { getServerSupabase } from "@/lib/supabase/server/getServerSupabase";
 import { signupFormSchema } from "@/types/auth";
 import * as Sentry from "@sentry/nextjs";
@@ -58,7 +59,7 @@ export async function signup(
     }
 
     const isOnboardingEnabled = await shouldShowOnboarding();
-    const next = isOnboardingEnabled ? "/onboarding" : "/";
+    const next = isOnboardingEnabled ? "/onboarding" : getHomepageRoute();
 
     return { success: true, next };
   } catch (err) {

autogpt_platform/frontend/src/app/(platform)/signup/useSignupPage.ts

@@ -1,6 +1,8 @@
 import { useToast } from "@/components/molecules/Toast/use-toast";
+import { getHomepageRoute } from "@/lib/constants";
 import { useSupabase } from "@/lib/supabase/hooks/useSupabase";
 import { environment } from "@/services/environment";
+import { Flag, useGetFlag } from "@/services/feature-flags/use-get-flag";
 import { LoginProvider, signupFormSchema } from "@/types/auth";
 import { zodResolver } from "@hookform/resolvers/zod";
 import { useRouter, useSearchParams } from "next/navigation";
@@ -20,15 +22,17 @@ export function useSignupPage() {
   const [isGoogleLoading, setIsGoogleLoading] = useState(false);
   const [showNotAllowedModal, setShowNotAllowedModal] = useState(false);
   const isCloudEnv = environment.isCloud();
+  const isChatEnabled = useGetFlag(Flag.CHAT);
+  const homepageRoute = getHomepageRoute(isChatEnabled);
 
   // Get redirect destination from 'next' query parameter
   const nextUrl = searchParams.get("next");
 
   useEffect(() => {
     if (isLoggedIn && !isSigningUp) {
-      router.push(nextUrl || "/marketplace");
+      router.push(nextUrl || homepageRoute);
     }
-  }, [isLoggedIn, isSigningUp, nextUrl, router]);
+  }, [homepageRoute, isLoggedIn, isSigningUp, nextUrl, router]);
 
   const form = useForm<z.infer<typeof signupFormSchema>>({
     resolver: zodResolver(signupFormSchema),
@@ -129,7 +133,7 @@ export function useSignupPage() {
       }
 
       // Prefer the URL's next parameter, then result.next (for onboarding), then default
-      const redirectTo = nextUrl || result.next || "/";
+      const redirectTo = nextUrl || result.next || homepageRoute;
       router.replace(redirectTo);
     } catch (error) {
       setIsLoading(false);

autogpt_platform/frontend/src/app/api/mutators/custom-mutator.ts

@@ -4,12 +4,12 @@ import {
   getServerAuthToken,
 } from "@/lib/autogpt-server-api/helpers";
 
-import { transformDates } from "./date-transformer";
-import { environment } from "@/services/environment";
 import {
   IMPERSONATION_HEADER_NAME,
   IMPERSONATION_STORAGE_KEY,
 } from "@/lib/constants";
+import { environment } from "@/services/environment";
+import { transformDates } from "./date-transformer";
 
 const FRONTEND_BASE_URL =
   process.env.NEXT_PUBLIC_FRONTEND_BASE_URL || "http://localhost:3000";

autogpt_platform/frontend/src/app/api/openapi.json

@@ -1022,7 +1022,7 @@
       "get": {
         "tags": ["v2", "chat", "chat"],
         "summary": "Get Session",
-        "description": "Retrieve the details of a specific chat session.\n\nLooks up a chat session by ID for the given user (if authenticated) and returns all session data including messages.\n\nArgs:\n    session_id: The unique identifier for the desired chat session.\n    user_id: The optional authenticated user ID, or None for anonymous access.\n\nReturns:\n    SessionDetailResponse: Details for the requested session; raises NotFoundError if not found.",
+        "description": "Retrieve the details of a specific chat session.\n\nLooks up a chat session by ID for the given user (if authenticated) and returns all session data including messages.\n\nArgs:\n    session_id: The unique identifier for the desired chat session.\n    user_id: The optional authenticated user ID, or None for anonymous access.\n\nReturns:\n    SessionDetailResponse: Details for the requested session, or None if not found.",
         "operationId": "getV2GetSession",
         "security": [{ "HTTPBearerJWT": [] }],
         "parameters": [
@@ -1039,7 +1039,11 @@
             "content": {
               "application/json": {
                 "schema": {
-                  "$ref": "#/components/schemas/SessionDetailResponse"
+                  "anyOf": [
+                    { "$ref": "#/components/schemas/SessionDetailResponse" },
+                    { "type": "null" }
+                  ],
+                  "title": "Response Getv2Getsession"
                 }
               }
             }

autogpt_platform/frontend/src/app/globals.css

@@ -174,7 +174,7 @@
 .loader {
   width: 80px;
   height: 70px;
-  border: 5px solid rgb(241 245 249);
+  border: 5px solid transparent;
   padding: 0 8px;
   box-sizing: border-box;
   background:

autogpt_platform/frontend/src/app/page.tsx

@@ -1,5 +1,33 @@
-import { redirect } from "next/navigation";
+"use client";
+
+import { getHomepageRoute } from "@/lib/constants";
+import {
+  Flag,
+  type FlagValues,
+  useGetFlag,
+} from "@/services/feature-flags/use-get-flag";
+import { useFlags } from "launchdarkly-react-client-sdk";
+import { useRouter } from "next/navigation";
+import { useEffect } from "react";
 
 export default function Page() {
-  redirect("/marketplace");
+  const isChatEnabled = useGetFlag(Flag.CHAT);
+  const flags = useFlags<FlagValues>();
+  const router = useRouter();
+  const homepageRoute = getHomepageRoute(isChatEnabled);
+  const envEnabled = process.env.NEXT_PUBLIC_LAUNCHDARKLY_ENABLED === "true";
+  const clientId = process.env.NEXT_PUBLIC_LAUNCHDARKLY_CLIENT_ID;
+  const isLaunchDarklyConfigured = envEnabled && Boolean(clientId);
+  const isFlagReady =
+    !isLaunchDarklyConfigured || flags[Flag.CHAT] !== undefined;
+
+  useEffect(
+    function redirectToHomepage() {
+      if (!isFlagReady) return;
+      router.replace(homepageRoute);
+    },
+    [homepageRoute, isFlagReady, router],
+  );
+
+  return null;
 }

autogpt_platform/frontend/src/components/contextual/Chat/Chat.tsx

@@ -0,0 +1,60 @@
+"use client";
+
+import { Text } from "@/components/atoms/Text/Text";
+import { cn } from "@/lib/utils";
+import { ChatContainer } from "./components/ChatContainer/ChatContainer";
+import { ChatErrorState } from "./components/ChatErrorState/ChatErrorState";
+import { ChatLoader } from "./components/ChatLoader/ChatLoader";
+import { useChat } from "./useChat";
+
+export interface ChatProps {
+  className?: string;
+  urlSessionId?: string | null;
+  initialPrompt?: string;
+}
+
+export function Chat({ className, urlSessionId, initialPrompt }: ChatProps) {
+  const {
+    messages,
+    isLoading,
+    isCreating,
+    error,
+    sessionId,
+    createSession,
+    showLoader,
+  } = useChat({ urlSessionId });
+
+  return (
+    <div className={cn("flex h-full flex-col", className)}>
+      {/* Main Content */}
+      <main className="flex min-h-0 w-full flex-1 flex-col overflow-hidden bg-[#f8f8f9]">
+        {/* Loading State */}
+        {showLoader && (isLoading || isCreating) && (
+          <div className="flex flex-1 items-center justify-center">
+            <div className="flex flex-col items-center gap-4">
+              <ChatLoader />
+              <Text variant="body" className="text-zinc-500">
+                Loading your chats...
+              </Text>
+            </div>
+          </div>
+        )}
+
+        {/* Error State */}
+        {error && !isLoading && (
+          <ChatErrorState error={error} onRetry={createSession} />
+        )}
+
+        {/* Session Content */}
+        {sessionId && !isLoading && !error && (
+          <ChatContainer
+            sessionId={sessionId}
+            initialMessages={messages}
+            initialPrompt={initialPrompt}
+            className="flex-1"
+          />
+        )}
+      </main>
+    </div>
+  );
+}

autogpt_platform/frontend/src/components/contextual/Chat/components/AIChatBubble/AIChatBubble.tsx

@@ -0,0 +1,15 @@
+import { cn } from "@/lib/utils";
+import { ReactNode } from "react";
+
+export interface AIChatBubbleProps {
+  children: ReactNode;
+  className?: string;
+}
+
+export function AIChatBubble({ children, className }: AIChatBubbleProps) {
+  return (
+    <div className={cn("text-left text-[1rem] leading-relaxed", className)}>
+      {children}
+    </div>
+  );
+}

autogpt_platform/frontend/src/components/contextual/Chat/components/AuthPromptWidget/AuthPromptWidget.tsx

@@ -21,7 +21,7 @@ export function AuthPromptWidget({
   message,
   sessionId,
   agentInfo,
-  returnUrl = "/chat",
+  returnUrl = "/copilot/chat",
   className,
 }: AuthPromptWidgetProps) {
   const router = useRouter();

autogpt_platform/frontend/src/components/contextual/Chat/components/ChatContainer/ChatContainer.tsx

@@ -1,31 +1,37 @@
 import type { SessionDetailResponse } from "@/app/api/__generated__/models/sessionDetailResponse";
+import { useBreakpoint } from "@/lib/hooks/useBreakpoint";
 import { cn } from "@/lib/utils";
 import { useCallback } from "react";
 import { usePageContext } from "../../usePageContext";
 import { ChatInput } from "../ChatInput/ChatInput";
 import { MessageList } from "../MessageList/MessageList";
-import { QuickActionsWelcome } from "../QuickActionsWelcome/QuickActionsWelcome";
 import { useChatContainer } from "./useChatContainer";
 
 export interface ChatContainerProps {
   sessionId: string | null;
   initialMessages: SessionDetailResponse["messages"];
+  initialPrompt?: string;
   className?: string;
 }
 
 export function ChatContainer({
   sessionId,
   initialMessages,
+  initialPrompt,
   className,
 }: ChatContainerProps) {
-  const { messages, streamingChunks, isStreaming, sendMessage } =
+  const { messages, streamingChunks, isStreaming, sendMessage, stopStreaming } =
     useChatContainer({
       sessionId,
       initialMessages,
+      initialPrompt,
     });
-  const { capturePageContext } = usePageContext();
 
-  // Wrap sendMessage to automatically capture page context
+  const { capturePageContext } = usePageContext();
+  const breakpoint = useBreakpoint();
+  const isMobile =
+    breakpoint === "base" || breakpoint === "sm" || breakpoint === "md";
+
   const sendMessageWithContext = useCallback(
     async (content: string, isUserMessage: boolean = true) => {
       const context = capturePageContext();
@@ -34,35 +40,16 @@ export function ChatContainer({
     [sendMessage, capturePageContext],
   );
 
-  const quickActions = [
-    "Find agents for social media management",
-    "Show me agents for content creation",
-    "Help me automate my business",
-    "What can you help me with?",
-  ];
-
   return (
     <div
-      className={cn("flex h-full min-h-0 flex-col", className)}
-      style={{
-        backgroundColor: "#ffffff",
-        backgroundImage:
-          "radial-gradient(#e5e5e5 0.5px, transparent 0.5px), radial-gradient(#e5e5e5 0.5px, #ffffff 0.5px)",
-        backgroundSize: "20px 20px",
-        backgroundPosition: "0 0, 10px 10px",
-      }}
+      className={cn(
+        "mx-auto flex h-full min-h-0 w-full max-w-3xl flex-col bg-[#f8f8f9]",
+        className,
+      )}
     >
-      {/* Messages or Welcome Screen */}
-      <div className="flex min-h-0 flex-1 flex-col overflow-hidden pb-24">
-        {messages.length === 0 ? (
-          <QuickActionsWelcome
-            title="Welcome to AutoGPT Copilot"
-            description="Start a conversation to discover and run AI agents."
-            actions={quickActions}
-            onActionClick={sendMessageWithContext}
-            disabled={isStreaming || !sessionId}
-          />
-        ) : (
+      {/* Messages - Scrollable */}
+      <div className="relative flex min-h-0 flex-1 flex-col">
+        <div className="flex min-h-full flex-col justify-end">
           <MessageList
             messages={messages}
             streamingChunks={streamingChunks}
@@ -70,16 +57,21 @@ export function ChatContainer({
             onSendMessage={sendMessageWithContext}
             className="flex-1"
           />
-        )}
+        </div>
       </div>
 
-      {/* Input - Always visible */}
-      <div className="fixed bottom-0 left-0 right-0 z-50 border-t border-zinc-200 bg-white p-4">
+      {/* Input - Fixed at bottom */}
+      <div className="relative px-3 pb-6 pt-2">
+        <div className="pointer-events-none absolute top-[-18px] z-10 h-6 w-full bg-gradient-to-b from-transparent to-[#f8f8f9]" />
         <ChatInput
           onSend={sendMessageWithContext}
           disabled={isStreaming || !sessionId}
+          isStreaming={isStreaming}
+          onStop={stopStreaming}
           placeholder={
-            sessionId ? "Type your message..." : "Creating session..."
+            isMobile
+              ? "You can search or just ask"
+              : 'You can search or just ask — e.g. "create a blog post outline"'
           }
         />
       </div>

autogpt_platform/frontend/src/components/contextual/Chat/components/ChatContainer/helpers.ts

@@ -1,6 +1,33 @@
+import { SessionKey, sessionStorage } from "@/services/storage/session-storage";
 import type { ToolResult } from "@/types/chat";
 import type { ChatMessageData } from "../ChatMessage/useChatMessage";
 
+export function hasSentInitialPrompt(sessionId: string): boolean {
+  try {
+    const sent = JSON.parse(
+      sessionStorage.get(SessionKey.CHAT_SENT_INITIAL_PROMPTS) || "{}",
+    );
+    return sent[sessionId] === true;
+  } catch {
+    return false;
+  }
+}
+
+export function markInitialPromptSent(sessionId: string): void {
+  try {
+    const sent = JSON.parse(
+      sessionStorage.get(SessionKey.CHAT_SENT_INITIAL_PROMPTS) || "{}",
+    );
+    sent[sessionId] = true;
+    sessionStorage.set(
+      SessionKey.CHAT_SENT_INITIAL_PROMPTS,
+      JSON.stringify(sent),
+    );
+  } catch {
+    // Ignore storage errors
+  }
+}
+
 export function removePageContext(content: string): string {
   // Remove "Page URL: ..." pattern at start of line (case insensitive, handles various formats)
   let cleaned = content.replace(/^\s*Page URL:\s*[^\n\r]*/gim, "");
@@ -207,12 +234,22 @@ export function parseToolResponse(
     if (responseType === "setup_requirements") {
       return null;
     }
+    if (responseType === "understanding_updated") {
+      return {
+        type: "tool_response",
+        toolId,
+        toolName,
+        result: (parsedResult || result) as ToolResult,
+        success: true,
+        timestamp: timestamp || new Date(),
+      };
+    }
   }
   return {
     type: "tool_response",
     toolId,
     toolName,
-    result,
+    result: parsedResult ? (parsedResult as ToolResult) : result,
     success: true,
     timestamp: timestamp || new Date(),
   };
@@ -267,23 +304,34 @@ export function extractCredentialsNeeded(
       | undefined;
     if (missingCreds && Object.keys(missingCreds).length > 0) {
       const agentName = (setupInfo?.agent_name as string) || "this block";
-      const credentials = Object.values(missingCreds).map((credInfo) => ({
-        provider: (credInfo.provider as string) || "unknown",
-        providerName:
-          (credInfo.provider_name as string) ||
-          (credInfo.provider as string) ||
-          "Unknown Provider",
-        credentialType:
+      const credentials = Object.values(missingCreds).map((credInfo) => {
+        // Normalize to array at boundary - prefer 'types' array, fall back to single 'type'
+        const typesArray = credInfo.types as
+          | Array<"api_key" | "oauth2" | "user_password" | "host_scoped">
+          | undefined;
+        const singleType =
           (credInfo.type as
             | "api_key"
             | "oauth2"
             | "user_password"
-            | "host_scoped") || "api_key",
-        title:
-          (credInfo.title as string) ||
-          `${(credInfo.provider_name as string) || (credInfo.provider as string)} credentials`,
-        scopes: credInfo.scopes as string[] | undefined,
-      }));
+            | "host_scoped"
+            | undefined) || "api_key";
+        const credentialTypes =
+          typesArray && typesArray.length > 0 ? typesArray : [singleType];
+
+        return {
+          provider: (credInfo.provider as string) || "unknown",
+          providerName:
+            (credInfo.provider_name as string) ||
+            (credInfo.provider as string) ||
+            "Unknown Provider",
+          credentialTypes,
+          title:
+            (credInfo.title as string) ||
+            `${(credInfo.provider_name as string) || (credInfo.provider as string)} credentials`,
+          scopes: credInfo.scopes as string[] | undefined,
+        };
+      });
       return {
         type: "credentials_needed",
         toolName,
@@ -358,11 +406,14 @@ export function extractInputsNeeded(
       credentials.forEach((cred) => {
         const id = cred.id as string;
         if (id) {
+          const credentialTypes = Array.isArray(cred.types)
+            ? cred.types
+            : [(cred.type as string) || "api_key"];
           credentialsSchema[id] = {
             type: "object",
             properties: {},
             credentials_provider: [cred.provider as string],
-            credentials_types: [(cred.type as string) || "api_key"],
+            credentials_types: credentialTypes,
             credentials_scopes: cred.scopes as string[] | undefined,
           };
         }

autogpt_platform/frontend/src/components/contextual/Chat/components/ChatContainer/useChatContainer.handlers.ts

@@ -30,16 +30,17 @@ export function handleTextEnded(
   _chunk: StreamChunk,
   deps: HandlerDependencies,
 ) {
-  console.log("[Text Ended] Saving streamed text as assistant message");
   const completedText = deps.streamingChunksRef.current.join("");
   if (completedText.trim()) {
-    const assistantMessage: ChatMessageData = {
-      type: "message",
-      role: "assistant",
-      content: completedText,
-      timestamp: new Date(),
-    };
-    deps.setMessages((prev) => [...prev, assistantMessage]);
+    deps.setMessages((prev) => {
+      const assistantMessage: ChatMessageData = {
+        type: "message",
+        role: "assistant",
+        content: completedText,
+        timestamp: new Date(),
+      };
+      return [...prev, assistantMessage];
+    });
   }
   deps.setStreamingChunks([]);
   deps.streamingChunksRef.current = [];
@@ -58,22 +59,12 @@ export function handleToolCallStart(
     timestamp: new Date(),
   };
   deps.setMessages((prev) => [...prev, toolCallMessage]);
-  console.log("[Tool Call Start]", {
-    toolId: toolCallMessage.toolId,
-    toolName: toolCallMessage.toolName,
-    timestamp: new Date().toISOString(),
-  });
 }
 
 export function handleToolResponse(
   chunk: StreamChunk,
   deps: HandlerDependencies,
 ) {
-  console.log("[Tool Response] Received:", {
-    toolId: chunk.tool_id,
-    toolName: chunk.tool_name,
-    timestamp: new Date().toISOString(),
-  });
   let toolName = chunk.tool_name || "unknown";
   if (!chunk.tool_name || chunk.tool_name === "unknown") {
     deps.setMessages((prev) => {
@@ -130,19 +121,8 @@ export function handleToolResponse(
     if (toolCallIndex !== -1) {
       const newMessages = [...prev];
       newMessages[toolCallIndex] = responseMessage;
-      console.log(
-        "[Tool Response] Replaced tool_call with matching tool_id:",
-        chunk.tool_id,
-        "at index:",
-        toolCallIndex,
-      );
       return newMessages;
     }
-    console.warn(
-      "[Tool Response] No tool_call found with tool_id:",
-      chunk.tool_id,
-      "appending instead",
-    );
     return [...prev, responseMessage];
   });
 }
@@ -167,50 +147,19 @@ export function handleStreamEnd(
   deps: HandlerDependencies,
 ) {
   const completedContent = deps.streamingChunksRef.current.join("");
-  // Only save message if there are uncommitted chunks
-  // (text_ended already saved if there were tool calls)
   if (completedContent.trim()) {
-    console.log(
-      "[Stream End] Saving remaining streamed text as assistant message",
-    );
     const assistantMessage: ChatMessageData = {
       type: "message",
       role: "assistant",
       content: completedContent,
       timestamp: new Date(),
     };
-    deps.setMessages((prev) => {
-      const updated = [...prev, assistantMessage];
-      console.log("[Stream End] Final state:", {
-        localMessages: updated.map((m) => ({
-          type: m.type,
-          ...(m.type === "message" && {
-            role: m.role,
-            contentLength: m.content.length,
-          }),
-          ...(m.type === "tool_call" && {
-            toolId: m.toolId,
-            toolName: m.toolName,
-          }),
-          ...(m.type === "tool_response" && {
-            toolId: m.toolId,
-            toolName: m.toolName,
-            success: m.success,
-          }),
-        })),
-        streamingChunks: deps.streamingChunksRef.current,
-        timestamp: new Date().toISOString(),
-      });
-      return updated;
-    });
-  } else {
-    console.log("[Stream End] No uncommitted chunks, message already saved");
+    deps.setMessages((prev) => [...prev, assistantMessage]);
   }
   deps.setStreamingChunks([]);
   deps.streamingChunksRef.current = [];
   deps.setHasTextChunks(false);
   deps.setIsStreamingInitiated(false);
-  console.log("[Stream End] Stream complete, messages in local state");
 }
 
 export function handleError(chunk: StreamChunk, deps: HandlerDependencies) {

autogpt_platform/frontend/src/components/contextual/Chat/components/ChatContainer/useChatContainer.ts

@@ -1,14 +1,17 @@
 import type { SessionDetailResponse } from "@/app/api/__generated__/models/sessionDetailResponse";
-import { useCallback, useMemo, useRef, useState } from "react";
+import { useCallback, useEffect, useMemo, useRef, useState } from "react";
 import { toast } from "sonner";
 import { useChatStream } from "../../useChatStream";
+import { usePageContext } from "../../usePageContext";
 import type { ChatMessageData } from "../ChatMessage/useChatMessage";
 import { createStreamEventDispatcher } from "./createStreamEventDispatcher";
 import {
   createUserMessage,
   filterAuthMessages,
+  hasSentInitialPrompt,
   isToolCallArray,
   isValidMessage,
+  markInitialPromptSent,
   parseToolResponse,
   removePageContext,
 } from "./helpers";
@@ -16,20 +19,40 @@ import {
 interface Args {
   sessionId: string | null;
   initialMessages: SessionDetailResponse["messages"];
+  initialPrompt?: string;
 }
 
-export function useChatContainer({ sessionId, initialMessages }: Args) {
+export function useChatContainer({
+  sessionId,
+  initialMessages,
+  initialPrompt,
+}: Args) {
   const [messages, setMessages] = useState<ChatMessageData[]>([]);
   const [streamingChunks, setStreamingChunks] = useState<string[]>([]);
   const [hasTextChunks, setHasTextChunks] = useState(false);
   const [isStreamingInitiated, setIsStreamingInitiated] = useState(false);
   const streamingChunksRef = useRef<string[]>([]);
-  const { error, sendMessage: sendStreamMessage } = useChatStream();
+  const previousSessionIdRef = useRef<string | null>(null);
+  const {
+    error,
+    sendMessage: sendStreamMessage,
+    stopStreaming,
+  } = useChatStream();
   const isStreaming = isStreamingInitiated || hasTextChunks;
 
+  useEffect(() => {
+    if (sessionId !== previousSessionIdRef.current) {
+      previousSessionIdRef.current = sessionId;
+      setMessages([]);
+      setStreamingChunks([]);
+      streamingChunksRef.current = [];
+      setHasTextChunks(false);
+      setIsStreamingInitiated(false);
+    }
+  }, [sessionId]);
+
   const allMessages = useMemo(() => {
     const processedInitialMessages: ChatMessageData[] = [];
-    // Map to track tool calls by their ID so we can look up tool names for tool responses
     const toolCallMap = new Map<string, string>();
 
     for (const msg of initialMessages) {
@@ -45,13 +68,9 @@ export function useChatContainer({ sessionId, initialMessages }: Args) {
         ? new Date(msg.timestamp as string)
         : undefined;
 
-      // Remove page context from user messages when loading existing sessions
       if (role === "user") {
         content = removePageContext(content);
-        // Skip user messages that become empty after removing page context
-        if (!content.trim()) {
-          continue;
-        }
+        if (!content.trim()) continue;
         processedInitialMessages.push({
           type: "message",
           role: "user",
@@ -61,19 +80,15 @@ export function useChatContainer({ sessionId, initialMessages }: Args) {
         continue;
       }
 
-      // Handle assistant messages first (before tool messages) to build tool call map
       if (role === "assistant") {
-        // Strip <thinking> tags from content
         content = content
           .replace(/<thinking>[\s\S]*?<\/thinking>/gi, "")
           .trim();
 
-        // If assistant has tool calls, create tool_call messages for each
         if (toolCalls && isToolCallArray(toolCalls) && toolCalls.length > 0) {
           for (const toolCall of toolCalls) {
             const toolName = toolCall.function.name;
             const toolId = toolCall.id;
-            // Store tool name for later lookup
             toolCallMap.set(toolId, toolName);
 
             try {
@@ -96,7 +111,6 @@ export function useChatContainer({ sessionId, initialMessages }: Args) {
               });
             }
           }
-          // Only add assistant message if there's content after stripping thinking tags
           if (content.trim()) {
             processedInitialMessages.push({
               type: "message",
@@ -106,7 +120,6 @@ export function useChatContainer({ sessionId, initialMessages }: Args) {
             });
           }
         } else if (content.trim()) {
-          // Assistant message without tool calls, but with content
           processedInitialMessages.push({
             type: "message",
             role: "assistant",
@@ -117,7 +130,6 @@ export function useChatContainer({ sessionId, initialMessages }: Args) {
         continue;
       }
 
-      // Handle tool messages - look up tool name from tool call map
       if (role === "tool") {
         const toolCallId = (msg.tool_call_id as string) || "";
         const toolName = toolCallMap.get(toolCallId) || "unknown";
@@ -133,7 +145,6 @@ export function useChatContainer({ sessionId, initialMessages }: Args) {
         continue;
       }
 
-      // Handle other message types (system, etc.)
       if (content.trim()) {
         processedInitialMessages.push({
           type: "message",
@@ -154,7 +165,7 @@ export function useChatContainer({ sessionId, initialMessages }: Args) {
       context?: { url: string; content: string },
     ) {
       if (!sessionId) {
-        console.error("Cannot send message: no session ID");
+        console.error("[useChatContainer] Cannot send message: no session ID");
         return;
       }
       if (isUserMessage) {
@@ -167,6 +178,7 @@ export function useChatContainer({ sessionId, initialMessages }: Args) {
       streamingChunksRef.current = [];
       setHasTextChunks(false);
       setIsStreamingInitiated(true);
+
       const dispatcher = createStreamEventDispatcher({
         setHasTextChunks,
         setStreamingChunks,
@@ -175,6 +187,7 @@ export function useChatContainer({ sessionId, initialMessages }: Args) {
         sessionId,
         setIsStreamingInitiated,
       });
+
       try {
         await sendStreamMessage(
           sessionId,
@@ -184,8 +197,12 @@ export function useChatContainer({ sessionId, initialMessages }: Args) {
           context,
         );
       } catch (err) {
-        console.error("Failed to send message:", err);
+        console.error("[useChatContainer] Failed to send message:", err);
         setIsStreamingInitiated(false);
+
+        // Don't show error toast for AbortError (expected during cleanup)
+        if (err instanceof Error && err.name === "AbortError") return;
+
         const errorMessage =
           err instanceof Error ? err.message : "Failed to send message";
         toast.error("Failed to send message", {
@@ -196,11 +213,42 @@ export function useChatContainer({ sessionId, initialMessages }: Args) {
     [sessionId, sendStreamMessage],
   );
 
+  const handleStopStreaming = useCallback(() => {
+    stopStreaming();
+    setStreamingChunks([]);
+    streamingChunksRef.current = [];
+    setHasTextChunks(false);
+    setIsStreamingInitiated(false);
+  }, [stopStreaming]);
+
+  const { capturePageContext } = usePageContext();
+
+  // Send initial prompt if provided (for new sessions from homepage)
+  useEffect(
+    function handleInitialPrompt() {
+      if (!initialPrompt || !sessionId) return;
+      if (initialMessages.length > 0) return;
+      if (hasSentInitialPrompt(sessionId)) return;
+
+      markInitialPromptSent(sessionId);
+      const context = capturePageContext();
+      sendMessage(initialPrompt, true, context);
+    },
+    [
+      initialPrompt,
+      sessionId,
+      initialMessages.length,
+      sendMessage,
+      capturePageContext,
+    ],
+  );
+
   return {
     messages: allMessages,
     streamingChunks,
     isStreaming,
     error,
     sendMessage,
+    stopStreaming: handleStopStreaming,
   };
 }

autogpt_platform/frontend/src/components/contextual/Chat/components/ChatCredentialsSetup/ChatCredentialsSetup.tsx

@@ -9,7 +9,9 @@ import { useChatCredentialsSetup } from "./useChatCredentialsSetup";
 export interface CredentialInfo {
   provider: string;
   providerName: string;
-  credentialType: "api_key" | "oauth2" | "user_password" | "host_scoped";
+  credentialTypes: Array<
+    "api_key" | "oauth2" | "user_password" | "host_scoped"
+  >;
   title: string;
   scopes?: string[];
 }
@@ -30,7 +32,7 @@ function createSchemaFromCredentialInfo(
     type: "object",
     properties: {},
     credentials_provider: [credential.provider],
-    credentials_types: [credential.credentialType],
+    credentials_types: credential.credentialTypes,
     credentials_scopes: credential.scopes,
     discriminator: undefined,
     discriminator_mapping: undefined,

autogpt_platform/frontend/src/components/contextual/Chat/components/ChatInput/ChatInput.tsx

@@ -0,0 +1,103 @@
+import { Button } from "@/components/atoms/Button/Button";
+import { cn } from "@/lib/utils";
+import { ArrowUpIcon, StopIcon } from "@phosphor-icons/react";
+import { useChatInput } from "./useChatInput";
+
+export interface Props {
+  onSend: (message: string) => void;
+  disabled?: boolean;
+  isStreaming?: boolean;
+  onStop?: () => void;
+  placeholder?: string;
+  className?: string;
+}
+
+export function ChatInput({
+  onSend,
+  disabled = false,
+  isStreaming = false,
+  onStop,
+  placeholder = "Type your message...",
+  className,
+}: Props) {
+  const inputId = "chat-input";
+  const { value, setValue, handleKeyDown, handleSend, hasMultipleLines } =
+    useChatInput({
+      onSend,
+      disabled: disabled || isStreaming,
+      maxRows: 4,
+      inputId,
+    });
+
+  function handleSubmit(e: React.FormEvent<HTMLFormElement>) {
+    e.preventDefault();
+    handleSend();
+  }
+
+  function handleChange(e: React.ChangeEvent<HTMLTextAreaElement>) {
+    setValue(e.target.value);
+  }
+
+  return (
+    <form onSubmit={handleSubmit} className={cn("relative flex-1", className)}>
+      <div className="relative">
+        <div
+          id={`${inputId}-wrapper`}
+          className={cn(
+            "relative overflow-hidden border border-neutral-200 bg-white shadow-sm",
+            "focus-within:border-zinc-400 focus-within:ring-1 focus-within:ring-zinc-400",
+            hasMultipleLines ? "rounded-xlarge" : "rounded-full",
+          )}
+        >
+          <textarea
+            id={inputId}
+            aria-label="Chat message input"
+            value={value}
+            onChange={handleChange}
+            onKeyDown={handleKeyDown}
+            placeholder={placeholder}
+            disabled={disabled || isStreaming}
+            rows={1}
+            className={cn(
+              "w-full resize-none overflow-y-auto border-0 bg-transparent text-[1rem] leading-6 text-black",
+              "placeholder:text-zinc-400",
+              "focus:outline-none focus:ring-0",
+              "disabled:text-zinc-500",
+              hasMultipleLines ? "pb-6 pl-4 pr-4 pt-2" : "pb-4 pl-4 pr-14 pt-4",
+            )}
+          />
+        </div>
+        <span id="chat-input-hint" className="sr-only">
+          Press Enter to send, Shift+Enter for new line
+        </span>
+
+        {isStreaming ? (
+          <Button
+            type="button"
+            variant="icon"
+            size="icon"
+            aria-label="Stop generating"
+            onClick={onStop}
+            className="absolute bottom-[7px] right-2 border-red-600 bg-red-600 text-white hover:border-red-800 hover:bg-red-800"
+          >
+            <StopIcon className="h-4 w-4" weight="bold" />
+          </Button>
+        ) : (
+          <Button
+            type="submit"
+            variant="icon"
+            size="icon"
+            aria-label="Send message"
+            className={cn(
+              "absolute bottom-[7px] right-2 border-zinc-800 bg-zinc-800 text-white hover:border-zinc-900 hover:bg-zinc-900",
+              (disabled || !value.trim()) && "opacity-20",
+            )}
+            disabled={disabled || !value.trim()}
+          >
+            <ArrowUpIcon className="h-4 w-4" weight="bold" />
+          </Button>
+        )}
+      </div>
+    </form>
+  );
+}

autogpt_platform/frontend/src/components/contextual/Chat/components/ChatInput/useChatInput.ts

@@ -0,0 +1,115 @@
+import { KeyboardEvent, useCallback, useEffect, useState } from "react";
+
+interface UseChatInputArgs {
+  onSend: (message: string) => void;
+  disabled?: boolean;
+  maxRows?: number;
+  inputId?: string;
+}
+
+export function useChatInput({
+  onSend,
+  disabled = false,
+  maxRows = 5,
+  inputId = "chat-input",
+}: UseChatInputArgs) {
+  const [value, setValue] = useState("");
+  const [hasMultipleLines, setHasMultipleLines] = useState(false);
+
+  useEffect(() => {
+    const textarea = document.getElementById(inputId) as HTMLTextAreaElement;
+    const wrapper = document.getElementById(
+      `${inputId}-wrapper`,
+    ) as HTMLDivElement;
+    if (!textarea || !wrapper) return;
+
+    const isEmpty = !value.trim();
+    const lines = value.split("\n").length;
+    const hasExplicitNewlines = lines > 1;
+
+    const computedStyle = window.getComputedStyle(textarea);
+    const lineHeight = parseInt(computedStyle.lineHeight, 10);
+    const paddingTop = parseInt(computedStyle.paddingTop, 10);
+    const paddingBottom = parseInt(computedStyle.paddingBottom, 10);
+
+    const singleLinePadding = paddingTop + paddingBottom;
+
+    textarea.style.height = "auto";
+    const scrollHeight = textarea.scrollHeight;
+
+    const singleLineHeight = lineHeight + singleLinePadding;
+    const isMultiLine =
+      hasExplicitNewlines || scrollHeight > singleLineHeight + 2;
+    setHasMultipleLines(isMultiLine);
+
+    if (isEmpty) {
+      wrapper.style.height = `${singleLineHeight}px`;
+      wrapper.style.maxHeight = "";
+      textarea.style.height = `${singleLineHeight}px`;
+      textarea.style.maxHeight = "";
+      textarea.style.overflowY = "hidden";
+      return;
+    }
+
+    if (isMultiLine) {
+      const wrapperMaxHeight = 196;
+      const currentMultilinePadding = paddingTop + paddingBottom;
+      const contentMaxHeight = wrapperMaxHeight - currentMultilinePadding;
+      const minMultiLineHeight = lineHeight * 2 + currentMultilinePadding;
+      const contentHeight = scrollHeight;
+      const targetWrapperHeight = Math.min(
+        Math.max(contentHeight + currentMultilinePadding, minMultiLineHeight),
+        wrapperMaxHeight,
+      );
+
+      wrapper.style.height = `${targetWrapperHeight}px`;
+      wrapper.style.maxHeight = `${wrapperMaxHeight}px`;
+      textarea.style.height = `${contentHeight}px`;
+      textarea.style.maxHeight = `${contentMaxHeight}px`;
+      textarea.style.overflowY =
+        contentHeight > contentMaxHeight ? "auto" : "hidden";
+    } else {
+      wrapper.style.height = `${singleLineHeight}px`;
+      wrapper.style.maxHeight = "";
+      textarea.style.height = `${singleLineHeight}px`;
+      textarea.style.maxHeight = "";
+      textarea.style.overflowY = "hidden";
+    }
+  }, [value, maxRows, inputId]);
+
+  const handleSend = useCallback(() => {
+    if (disabled || !value.trim()) return;
+    onSend(value.trim());
+    setValue("");
+    setHasMultipleLines(false);
+    const textarea = document.getElementById(inputId) as HTMLTextAreaElement;
+    const wrapper = document.getElementById(
+      `${inputId}-wrapper`,
+    ) as HTMLDivElement;
+    if (textarea) {
+      textarea.style.height = "auto";
+    }
+    if (wrapper) {
+      wrapper.style.height = "";
+      wrapper.style.maxHeight = "";
+    }
+  }, [value, onSend, disabled, inputId]);
+
+  const handleKeyDown = useCallback(
+    (event: KeyboardEvent<HTMLTextAreaElement>) => {
+      if (event.key === "Enter" && !event.shiftKey) {
+        event.preventDefault();
+        handleSend();
+      }
+    },
+    [handleSend],
+  );
+
+  return {
+    value,
+    setValue,
+    handleKeyDown,
+    handleSend,
+    hasMultipleLines,
+  };
+}

autogpt_platform/frontend/src/components/contextual/Chat/components/ChatLoader/ChatLoader.module.css

@@ -0,0 +1,13 @@
+.loader {
+  width: 20px;
+  aspect-ratio: 1;
+  border-radius: 50%;
+  background: #000;
+  box-shadow: 0 0 0 0 #0004;
+  animation: l1 1s infinite;
+}
+@keyframes l1 {
+  100% {
+    box-shadow: 0 0 0 30px #0000;
+  }
+}