Update frontend build based on commit 4878665c66

## Summary

Fixes a bug where the fallback path in context compaction passes
`recent_messages` (already sliced) instead of `messages_dict` (full
conversation) to `_ensure_tool_pairs_intact`.

This caused the function to fail to find assistant messages that exist
in the original conversation but were outside the sliced window,
resulting in orphan tool_results being sent to Anthropic and rejected
with:

```
messages.66.content.0: unexpected tool_use_id found in tool_result blocks: toolu_vrtx_019bi1PDvEn7o5ByAxcS3VdA
```

## Changes

- Pass `messages_dict` and `slice_start` (relative to full conversation)
instead of `recent_messages` and `reduced_slice_start` (relative to
already-sliced list)

## Testing

This is a targeted fix for the fallback path. The bug only manifests
when:
1. Token count > 120k (triggers compaction)
2. Initial compaction + summary still exceeds limit (triggers fallback)
3. A tool_result's corresponding assistant is in `messages_dict` but not
in `recent_messages`

## Related

- Fixes SECRT-1861
- Related: SECRT-1839 (original fix that missed this code path)

.gitignore

@@ -180,3 +180,4 @@ autogpt_platform/backend/settings.py
 .claude/settings.local.json
 CLAUDE.local.md
 /autogpt_platform/backend/logs
+.next

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

@@ -17,14 +17,6 @@ from .model import ChatSession, create_chat_session, get_chat_session, get_user_
 
 config = ChatConfig()
 
-# SSE response headers for streaming
-SSE_RESPONSE_HEADERS = {
-    "Cache-Control": "no-cache",
-    "Connection": "keep-alive",
-    "X-Accel-Buffering": "no",
-    "x-vercel-ai-ui-message-stream": "v1",
-}
-
 
 logger = logging.getLogger(__name__)
 
@@ -40,60 +32,6 @@ async def _validate_and_get_session(
     return session
 
 
-async def _create_stream_generator(
-    session_id: str,
-    message: str,
-    user_id: str | None,
-    session: ChatSession,
-    is_user_message: bool = True,
-    context: dict[str, str] | None = None,
-) -> AsyncGenerator[str, None]:
-    """Create SSE event generator for chat streaming.
-
-    Args:
-        session_id: Chat session ID
-        message: User message to process
-        user_id: Optional authenticated user ID
-        session: Pre-fetched chat session
-        is_user_message: Whether the message is from a user
-        context: Optional context dict with url and content
-
-    Yields:
-        SSE-formatted chunks from the chat completion stream
-    """
-    chunk_count = 0
-    first_chunk_type: str | None = None
-    async for chunk in chat_service.stream_chat_completion(
-        session_id,
-        message,
-        is_user_message=is_user_message,
-        user_id=user_id,
-        session=session,
-        context=context,
-    ):
-        if chunk_count < 3:
-            logger.info(
-                "Chat stream chunk",
-                extra={
-                    "session_id": session_id,
-                    "chunk_type": str(chunk.type),
-                },
-            )
-        if not first_chunk_type:
-            first_chunk_type = str(chunk.type)
-        chunk_count += 1
-        yield chunk.to_sse()
-    logger.info(
-        "Chat stream completed",
-        extra={
-            "session_id": session_id,
-            "chunk_count": chunk_count,
-            "first_chunk_type": first_chunk_type,
-        },
-    )
-    yield "data: [DONE]\n\n"
-
-
 router = APIRouter(
     tags=["chat"],
 )
@@ -283,17 +221,49 @@ async def stream_chat_post(
     """
     session = await _validate_and_get_session(session_id, user_id)
 
-    return StreamingResponse(
-        _create_stream_generator(
-            session_id=session_id,
-            message=request.message,
-            user_id=user_id,
-            session=session,
+    async def event_generator() -> AsyncGenerator[str, None]:
+        chunk_count = 0
+        first_chunk_type: str | None = None
+        async for chunk in chat_service.stream_chat_completion(
+            session_id,
+            request.message,
             is_user_message=request.is_user_message,
+            user_id=user_id,
+            session=session,  # Pass pre-fetched session to avoid double-fetch
             context=request.context,
-        ),
+        ):
+            if chunk_count < 3:
+                logger.info(
+                    "Chat stream chunk",
+                    extra={
+                        "session_id": session_id,
+                        "chunk_type": str(chunk.type),
+                    },
+                )
+            if not first_chunk_type:
+                first_chunk_type = str(chunk.type)
+            chunk_count += 1
+            yield chunk.to_sse()
+        logger.info(
+            "Chat stream completed",
+            extra={
+                "session_id": session_id,
+                "chunk_count": chunk_count,
+                "first_chunk_type": first_chunk_type,
+            },
+        )
+        # AI SDK protocol termination
+        yield "data: [DONE]\n\n"
+
+    return StreamingResponse(
+        event_generator(),
         media_type="text/event-stream",
-        headers=SSE_RESPONSE_HEADERS,
+        headers={
+            "Cache-Control": "no-cache",
+            "Connection": "keep-alive",
+            "X-Accel-Buffering": "no",  # Disable nginx buffering
+            "x-vercel-ai-ui-message-stream": "v1",  # AI SDK protocol header
+        },
     )
 
 
@@ -325,16 +295,48 @@ async def stream_chat_get(
     """
     session = await _validate_and_get_session(session_id, user_id)
 
-    return StreamingResponse(
-        _create_stream_generator(
-            session_id=session_id,
-            message=message,
-            user_id=user_id,
-            session=session,
+    async def event_generator() -> AsyncGenerator[str, None]:
+        chunk_count = 0
+        first_chunk_type: str | None = None
+        async for chunk in chat_service.stream_chat_completion(
+            session_id,
+            message,
             is_user_message=is_user_message,
-        ),
+            user_id=user_id,
+            session=session,  # Pass pre-fetched session to avoid double-fetch
+        ):
+            if chunk_count < 3:
+                logger.info(
+                    "Chat stream chunk",
+                    extra={
+                        "session_id": session_id,
+                        "chunk_type": str(chunk.type),
+                    },
+                )
+            if not first_chunk_type:
+                first_chunk_type = str(chunk.type)
+            chunk_count += 1
+            yield chunk.to_sse()
+        logger.info(
+            "Chat stream completed",
+            extra={
+                "session_id": session_id,
+                "chunk_count": chunk_count,
+                "first_chunk_type": first_chunk_type,
+            },
+        )
+        # AI SDK protocol termination
+        yield "data: [DONE]\n\n"
+
+    return StreamingResponse(
+        event_generator(),
         media_type="text/event-stream",
-        headers=SSE_RESPONSE_HEADERS,
+        headers={
+            "Cache-Control": "no-cache",
+            "Connection": "keep-alive",
+            "X-Accel-Buffering": "no",  # Disable nginx buffering
+            "x-vercel-ai-ui-message-stream": "v1",  # AI SDK protocol header
+        },
     )
 
 

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

@@ -1,77 +0,0 @@
-"""Shared helpers for chat tools."""
-
-from typing import Any
-
-from .models import ErrorResponse
-
-
-def error_response(
-    message: str, session_id: str | None, **kwargs: Any
-) -> ErrorResponse:
-    """Create standardized error response.
-
-    Args:
-        message: Error message to display
-        session_id: Current session ID
-        **kwargs: Additional fields to pass to ErrorResponse
-
-    Returns:
-        ErrorResponse with the given message and session_id
-    """
-    return ErrorResponse(message=message, session_id=session_id, **kwargs)
-
-
-def get_inputs_from_schema(
-    input_schema: dict[str, Any],
-    exclude_fields: set[str] | None = None,
-) -> list[dict[str, Any]]:
-    """Extract input field info from JSON schema.
-
-    Args:
-        input_schema: JSON schema dict with 'properties' and 'required'
-        exclude_fields: Set of field names to exclude (e.g., credential fields)
-
-    Returns:
-        List of dicts with field info (name, title, type, description, required, default)
-    """
-    exclude = exclude_fields or set()
-    properties = input_schema.get("properties", {})
-    required = set(input_schema.get("required", []))
-
-    return [
-        {
-            "name": name,
-            "title": schema.get("title", name),
-            "type": schema.get("type", "string"),
-            "description": schema.get("description", ""),
-            "required": name in required,
-            "default": schema.get("default"),
-        }
-        for name, schema in properties.items()
-        if name not in exclude
-    ]
-
-
-def format_inputs_as_markdown(inputs: list[dict[str, Any]]) -> str:
-    """Format input fields as a readable markdown list.
-
-    Args:
-        inputs: List of input dicts from get_inputs_from_schema
-
-    Returns:
-        Markdown-formatted string listing the inputs
-    """
-    if not inputs:
-        return "No inputs required."
-
-    lines = []
-    for inp in inputs:
-        required_marker = " (required)" if inp.get("required") else ""
-        default = inp.get("default")
-        default_info = f" [default: {default}]" if default is not None else ""
-        description = inp.get("description", "")
-        desc_info = f" - {description}" if description else ""
-
-        lines.append(f"- **{inp['name']}**{required_marker}{default_info}{desc_info}")
-
-    return "\n".join(lines)

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

@@ -38,6 +38,8 @@ class ResponseType(str, Enum):
     OPERATION_STARTED = "operation_started"
     OPERATION_PENDING = "operation_pending"
     OPERATION_IN_PROGRESS = "operation_in_progress"
+    # Input validation
+    INPUT_VALIDATION_ERROR = "input_validation_error"
 
 
 # Base response model
@@ -68,6 +70,10 @@ class AgentInfo(BaseModel):
     has_external_trigger: bool | None = None
     new_output: bool | None = None
     graph_id: str | None = None
+    inputs: dict[str, Any] | None = Field(
+        default=None,
+        description="Input schema for the agent, including field names, types, and defaults",
+    )
 
 
 class AgentsFoundResponse(ToolResponseBase):
@@ -194,6 +200,20 @@ class ErrorResponse(ToolResponseBase):
     details: dict[str, Any] | None = None
 
 
+class InputValidationErrorResponse(ToolResponseBase):
+    """Response when run_agent receives unknown input fields."""
+
+    type: ResponseType = ResponseType.INPUT_VALIDATION_ERROR
+    unrecognized_fields: list[str] = Field(
+        description="List of input field names that were not recognized"
+    )
+    inputs: dict[str, Any] = Field(
+        description="The agent's valid input schema for reference"
+    )
+    graph_id: str | None = None
+    graph_version: int | None = None
+
+
 # Agent output models
 class ExecutionOutputInfo(BaseModel):
     """Summary of a single execution's outputs."""

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

@@ -24,13 +24,13 @@ from backend.util.timezone_utils import (
 )
 
 from .base import BaseTool
-from .helpers import get_inputs_from_schema
 from .models import (
     AgentDetails,
     AgentDetailsResponse,
     ErrorResponse,
     ExecutionOptions,
     ExecutionStartedResponse,
+    InputValidationErrorResponse,
     SetupInfo,
     SetupRequirementsResponse,
     ToolResponseBase,
@@ -274,6 +274,22 @@ class RunAgentTool(BaseTool):
             input_properties = graph.input_schema.get("properties", {})
             required_fields = set(graph.input_schema.get("required", []))
             provided_inputs = set(params.inputs.keys())
+            valid_fields = set(input_properties.keys())
+
+            # Check for unknown input fields
+            unrecognized_fields = provided_inputs - valid_fields
+            if unrecognized_fields:
+                return InputValidationErrorResponse(
+                    message=(
+                        f"Unknown input field(s) provided: {', '.join(sorted(unrecognized_fields))}. "
+                        f"Agent was not executed. Please use the correct field names from the schema."
+                    ),
+                    session_id=session_id,
+                    unrecognized_fields=sorted(unrecognized_fields),
+                    inputs=graph.input_schema,
+                    graph_id=graph.id,
+                    graph_version=graph.version,
+                )
 
             # If agent has inputs but none were provided AND use_defaults is not set,
             # always show what's available first so user can decide
@@ -355,7 +371,19 @@ class RunAgentTool(BaseTool):
 
     def _get_inputs_list(self, input_schema: dict[str, Any]) -> list[dict[str, Any]]:
         """Extract inputs list from schema."""
-        return get_inputs_from_schema(input_schema)
+        inputs_list = []
+        if isinstance(input_schema, dict) and "properties" in input_schema:
+            for field_name, field_schema in input_schema["properties"].items():
+                inputs_list.append(
+                    {
+                        "name": field_name,
+                        "title": field_schema.get("title", field_name),
+                        "type": field_schema.get("type", "string"),
+                        "description": field_schema.get("description", ""),
+                        "required": field_name in input_schema.get("required", []),
+                    }
+                )
+        return inputs_list
 
     def _get_execution_modes(self, graph: GraphModel) -> list[str]:
         """Get available execution modes for the graph."""

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

@@ -402,3 +402,42 @@ async def test_run_agent_schedule_without_name(setup_test_data):
     # Should return error about missing schedule_name
     assert result_data.get("type") == "error"
     assert "schedule_name" in result_data["message"].lower()
+
+
+@pytest.mark.asyncio(loop_scope="session")
+async def test_run_agent_rejects_unknown_input_fields(setup_test_data):
+    """Test that run_agent returns input_validation_error for unknown input fields."""
+    user = setup_test_data["user"]
+    store_submission = setup_test_data["store_submission"]
+
+    tool = RunAgentTool()
+    agent_marketplace_id = f"{user.email.split('@')[0]}/{store_submission.slug}"
+    session = make_session(user_id=user.id)
+
+    # Execute with unknown input field names
+    response = await tool.execute(
+        user_id=user.id,
+        session_id=str(uuid.uuid4()),
+        tool_call_id=str(uuid.uuid4()),
+        username_agent_slug=agent_marketplace_id,
+        inputs={
+            "unknown_field": "some value",
+            "another_unknown": "another value",
+        },
+        session=session,
+    )
+
+    assert response is not None
+    assert hasattr(response, "output")
+    assert isinstance(response.output, str)
+    result_data = orjson.loads(response.output)
+
+    # Should return input_validation_error type with unrecognized fields
+    assert result_data.get("type") == "input_validation_error"
+    assert "unrecognized_fields" in result_data
+    assert set(result_data["unrecognized_fields"]) == {
+        "another_unknown",
+        "unknown_field",
+    }
+    assert "inputs" in result_data  # Contains the valid schema
+    assert "Agent was not executed" in result_data["message"]

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

@@ -5,16 +5,17 @@ import uuid
 from collections import defaultdict
 from typing import Any
 
+from pydantic_core import PydanticUndefined
+
 from backend.api.features.chat.model import ChatSession
 from backend.data.block import get_block
 from backend.data.execution import ExecutionContext
-from backend.data.model import CredentialsFieldInfo, CredentialsMetaInput
+from backend.data.model import CredentialsMetaInput
 from backend.data.workspace import get_or_create_workspace
 from backend.integrations.creds_manager import IntegrationCredentialsManager
 from backend.util.exceptions import BlockError
 
 from .base import BaseTool
-from .helpers import get_inputs_from_schema
 from .models import (
     BlockOutputResponse,
     ErrorResponse,
@@ -23,10 +24,7 @@ from .models import (
     ToolResponseBase,
     UserReadiness,
 )
-from .utils import (
-    build_missing_credentials_from_field_info,
-    match_credentials_to_requirements,
-)
+from .utils import build_missing_credentials_from_field_info
 
 logger = logging.getLogger(__name__)
 
@@ -75,39 +73,90 @@ class RunBlockTool(BaseTool):
     def requires_auth(self) -> bool:
         return True
 
-    def _get_credentials_requirements(
-        self,
-        block: Any,
-    ) -> dict[str, CredentialsFieldInfo]:
-        """
-        Get credential requirements from block's input schema.
-
-        Args:
-            block: Block to get credentials for
-
-        Returns:
-            Dict mapping field names to CredentialsFieldInfo
-        """
-        credentials_fields_info = block.input_schema.get_credentials_fields_info()
-        return credentials_fields_info if credentials_fields_info else {}
-
     async def _check_block_credentials(
         self,
         user_id: str,
         block: Any,
+        input_data: dict[str, Any] | None = None,
     ) -> tuple[dict[str, CredentialsMetaInput], list[CredentialsMetaInput]]:
         """
         Check if user has required credentials for a block.
 
+        Args:
+            user_id: User ID
+            block: Block to check credentials for
+            input_data: Input data for the block (used to determine provider via discriminator)
+
         Returns:
             tuple[matched_credentials, missing_credentials]
         """
-        requirements = self._get_credentials_requirements(block)
+        matched_credentials: dict[str, CredentialsMetaInput] = {}
+        missing_credentials: list[CredentialsMetaInput] = []
+        input_data = input_data or {}
 
-        if not requirements:
-            return {}, []
+        # Get credential field info from block's input schema
+        credentials_fields_info = block.input_schema.get_credentials_fields_info()
 
-        return await match_credentials_to_requirements(user_id, requirements)
+        if not credentials_fields_info:
+            return matched_credentials, missing_credentials
+
+        # Get user's available credentials
+        creds_manager = IntegrationCredentialsManager()
+        available_creds = await creds_manager.store.get_all_creds(user_id)
+
+        for field_name, field_info in credentials_fields_info.items():
+            effective_field_info = field_info
+            if field_info.discriminator and field_info.discriminator_mapping:
+                # Get discriminator from input, falling back to schema default
+                discriminator_value = input_data.get(field_info.discriminator)
+                if discriminator_value is None:
+                    field = block.input_schema.model_fields.get(
+                        field_info.discriminator
+                    )
+                    if field and field.default is not PydanticUndefined:
+                        discriminator_value = field.default
+
+                if (
+                    discriminator_value
+                    and discriminator_value in field_info.discriminator_mapping
+                ):
+                    effective_field_info = field_info.discriminate(discriminator_value)
+                    logger.debug(
+                        f"Discriminated provider for {field_name}: "
+                        f"{discriminator_value} -> {effective_field_info.provider}"
+                    )
+
+            matching_cred = next(
+                (
+                    cred
+                    for cred in available_creds
+                    if cred.provider in effective_field_info.provider
+                    and cred.type in effective_field_info.supported_types
+                ),
+                None,
+            )
+
+            if matching_cred:
+                matched_credentials[field_name] = CredentialsMetaInput(
+                    id=matching_cred.id,
+                    provider=matching_cred.provider,  # type: ignore
+                    type=matching_cred.type,
+                    title=matching_cred.title,
+                )
+            else:
+                # Create a placeholder for the missing credential
+                provider = next(iter(effective_field_info.provider), "unknown")
+                cred_type = next(iter(effective_field_info.supported_types), "api_key")
+                missing_credentials.append(
+                    CredentialsMetaInput(
+                        id=field_name,
+                        provider=provider,  # type: ignore
+                        type=cred_type,  # type: ignore
+                        title=field_name.replace("_", " ").title(),
+                    )
+                )
+
+        return matched_credentials, missing_credentials
 
     async def _execute(
         self,
@@ -165,10 +214,9 @@ class RunBlockTool(BaseTool):
 
         logger.info(f"Executing block {block.name} ({block_id}) for user {user_id}")
 
-        # Check credentials
         creds_manager = IntegrationCredentialsManager()
         matched_credentials, missing_credentials = await self._check_block_credentials(
-            user_id, block
+            user_id, block, input_data
         )
 
         if missing_credentials:
@@ -299,7 +347,27 @@ class RunBlockTool(BaseTool):
 
     def _get_inputs_list(self, block: Any) -> list[dict[str, Any]]:
         """Extract non-credential inputs from block schema."""
+        inputs_list = []
         schema = block.input_schema.jsonschema()
+        properties = schema.get("properties", {})
+        required_fields = set(schema.get("required", []))
+
         # Get credential field names to exclude
         credentials_fields = set(block.input_schema.get_credentials_fields().keys())
-        return get_inputs_from_schema(schema, exclude_fields=credentials_fields)
+
+        for field_name, field_schema in properties.items():
+            # Skip credential fields
+            if field_name in credentials_fields:
+                continue
+
+            inputs_list.append(
+                {
+                    "name": field_name,
+                    "title": field_schema.get("title", field_name),
+                    "type": field_schema.get("type", "string"),
+                    "description": field_schema.get("description", ""),
+                    "required": field_name in required_fields,
+                }
+            )
+
+        return inputs_list

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

@@ -225,127 +225,6 @@ async def get_or_create_library_agent(
     return library_agents[0]
 
 
-async def get_user_credentials(user_id: str) -> list:
-    """
-    Get all available credentials for a user.
-
-    Args:
-        user_id: The user's ID
-
-    Returns:
-        List of user's credentials
-    """
-    creds_manager = IntegrationCredentialsManager()
-    return await creds_manager.store.get_all_creds(user_id)
-
-
-def find_matching_credential(
-    available_creds: list,
-    field_info: CredentialsFieldInfo,
-):
-    """
-    Find a credential that matches the required provider, type, and scopes.
-
-    Args:
-        available_creds: List of user's available credentials
-        field_info: CredentialsFieldInfo with provider, type, and scope requirements
-
-    Returns:
-        Matching credential or None
-    """
-    for cred in available_creds:
-        if cred.provider not in field_info.provider:
-            continue
-        if cred.type not in field_info.supported_types:
-            continue
-        if not _credential_has_required_scopes(cred, field_info):
-            continue
-        return cred
-    return None
-
-
-def create_credential_meta_from_match(
-    matching_cred,
-) -> CredentialsMetaInput:
-    """
-    Create a CredentialsMetaInput from a matched credential.
-
-    Args:
-        matching_cred: The matched credential object
-
-    Returns:
-        CredentialsMetaInput instance
-    """
-    return CredentialsMetaInput(
-        id=matching_cred.id,
-        provider=matching_cred.provider,  # type: ignore
-        type=matching_cred.type,
-        title=matching_cred.title,
-    )
-
-
-async def match_credentials_to_requirements(
-    user_id: str,
-    requirements: dict[str, CredentialsFieldInfo],
-) -> tuple[dict[str, CredentialsMetaInput], list[CredentialsMetaInput]]:
-    """
-    Match user's credentials against a dictionary of credential requirements.
-
-    This is the core matching logic shared by both graph and block credential matching.
-
-    Args:
-        user_id: The user's ID
-        requirements: Dict mapping field names to CredentialsFieldInfo
-
-    Returns:
-        tuple[matched_credentials dict, missing_credentials list]
-    """
-    matched: dict[str, CredentialsMetaInput] = {}
-    missing: list[CredentialsMetaInput] = []
-
-    if not requirements:
-        return matched, missing
-
-    available_creds = await get_user_credentials(user_id)
-
-    for field_name, field_info in requirements.items():
-        matching_cred = find_matching_credential(available_creds, field_info)
-
-        if matching_cred:
-            try:
-                matched[field_name] = create_credential_meta_from_match(matching_cred)
-            except Exception as e:
-                logger.error(
-                    f"Failed to create CredentialsMetaInput for field '{field_name}': "
-                    f"provider={matching_cred.provider}, type={matching_cred.type}, "
-                    f"credential_id={matching_cred.id}",
-                    exc_info=True,
-                )
-                provider = next(iter(field_info.provider), "unknown")
-                cred_type = next(iter(field_info.supported_types), "api_key")
-                missing.append(
-                    CredentialsMetaInput(
-                        id=field_name,
-                        provider=provider,  # type: ignore
-                        type=cred_type,  # type: ignore
-                        title=f"{field_name} (validation failed: {e})",
-                    )
-                )
-        else:
-            provider = next(iter(field_info.provider), "unknown")
-            cred_type = next(iter(field_info.supported_types), "api_key")
-            missing.append(
-                CredentialsMetaInput(
-                    id=field_name,
-                    provider=provider,  # type: ignore
-                    type=cred_type,  # type: ignore
-                    title=field_name.replace("_", " ").title(),
-                )
-            )
-
-    return matched, missing
-
-
 async def match_user_credentials_to_graph(
     user_id: str,
     graph: GraphModel,
@@ -363,6 +242,9 @@ async def match_user_credentials_to_graph(
     Returns:
         tuple[matched_credentials dict, missing_credential_descriptions list]
     """
+    graph_credentials_inputs: dict[str, CredentialsMetaInput] = {}
+    missing_creds: list[str] = []
+
     # Get aggregated credentials requirements from the graph
     aggregated_creds = graph.aggregate_credentials_inputs()
     logger.debug(
@@ -370,30 +252,69 @@ async def match_user_credentials_to_graph(
     )
 
     if not aggregated_creds:
-        return {}, []
+        return graph_credentials_inputs, missing_creds
 
-    # Convert aggregated format to simple requirements dict
-    requirements = {
-        field_name: field_info
-        for field_name, (field_info, _node_fields) in aggregated_creds.items()
-    }
+    # Get all available credentials for the user
+    creds_manager = IntegrationCredentialsManager()
+    available_creds = await creds_manager.store.get_all_creds(user_id)
 
-    # Use shared matching logic
-    matched, missing_list = await match_credentials_to_requirements(
-        user_id, requirements
-    )
+    # For each required credential field, find a matching user credential
+    # field_info.provider is a frozenset because aggregate_credentials_inputs()
+    # combines requirements from multiple nodes. A credential matches if its
+    # provider is in the set of acceptable providers.
+    for credential_field_name, (
+        credential_requirements,
+        _node_fields,
+    ) in aggregated_creds.items():
+        # Find first matching credential by provider, type, and scopes
+        matching_cred = next(
+            (
+                cred
+                for cred in available_creds
+                if cred.provider in credential_requirements.provider
+                and cred.type in credential_requirements.supported_types
+                and _credential_has_required_scopes(cred, credential_requirements)
+            ),
+            None,
+        )
 
-    # Convert missing list to string descriptions for backward compatibility
-    missing_descriptions = [
-        f"{cred.id} (requires provider={cred.provider}, type={cred.type})"
-        for cred in missing_list
-    ]
+        if matching_cred:
+            try:
+                graph_credentials_inputs[credential_field_name] = CredentialsMetaInput(
+                    id=matching_cred.id,
+                    provider=matching_cred.provider,  # type: ignore
+                    type=matching_cred.type,
+                    title=matching_cred.title,
+                )
+            except Exception as e:
+                logger.error(
+                    f"Failed to create CredentialsMetaInput for field '{credential_field_name}': "
+                    f"provider={matching_cred.provider}, type={matching_cred.type}, "
+                    f"credential_id={matching_cred.id}",
+                    exc_info=True,
+                )
+                missing_creds.append(
+                    f"{credential_field_name} (validation failed: {e})"
+                )
+        else:
+            # Build a helpful error message including scope requirements
+            error_parts = [
+                f"provider in {list(credential_requirements.provider)}",
+                f"type in {list(credential_requirements.supported_types)}",
+            ]
+            if credential_requirements.required_scopes:
+                error_parts.append(
+                    f"scopes including {list(credential_requirements.required_scopes)}"
+                )
+            missing_creds.append(
+                f"{credential_field_name} (requires {', '.join(error_parts)})"
+            )
 
     logger.info(
-        f"Credential matching complete: {len(matched)}/{len(aggregated_creds)} matched"
+        f"Credential matching complete: {len(graph_credentials_inputs)}/{len(aggregated_creds)} matched"
     )
 
-    return matched, missing_descriptions
+    return graph_credentials_inputs, missing_creds
 
 
 def _credential_has_required_scopes(

autogpt_platform/backend/backend/util/validation.py

@@ -1,32 +0,0 @@
-"""Validation utilities."""
-
-import re
-
-_UUID_V4_PATTERN = re.compile(
-    r"[a-f0-9]{8}-[a-f0-9]{4}-4[a-f0-9]{3}-[89ab][a-f0-9]{3}-[a-f0-9]{12}",
-    re.IGNORECASE,
-)
-
-
-def is_uuid_v4(text: str) -> bool:
-    """Check if text is a valid UUID v4.
-
-    Args:
-        text: String to validate
-
-    Returns:
-        True if the text is a valid UUID v4, False otherwise
-    """
-    return bool(_UUID_V4_PATTERN.fullmatch(text.strip()))
-
-
-def extract_uuids(text: str) -> list[str]:
-    """Extract all UUID v4 strings from text.
-
-    Args:
-        text: String to search for UUIDs
-
-    Returns:
-        List of unique UUIDs found (lowercase)
-    """
-    return list({m.lower() for m in _UUID_V4_PATTERN.findall(text)})

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

@@ -1,10 +1,9 @@
 "use client";
+import { getV1OnboardingState } from "@/app/api/__generated__/endpoints/onboarding/onboarding";
+import { getOnboardingStatus, resolveResponse } from "@/app/api/helpers";
 import { LoadingSpinner } from "@/components/atoms/LoadingSpinner/LoadingSpinner";
 import { useRouter } from "next/navigation";
 import { useEffect } from "react";
-import { resolveResponse, getOnboardingStatus } from "@/app/api/helpers";
-import { getV1OnboardingState } from "@/app/api/__generated__/endpoints/onboarding/onboarding";
-import { getHomepageRoute } from "@/lib/constants";
 
 export default function OnboardingPage() {
   const router = useRouter();
@@ -13,12 +12,10 @@ export default function OnboardingPage() {
     async function redirectToStep() {
       try {
         // Check if onboarding is enabled (also gets chat flag for redirect)
-        const { shouldShowOnboarding, isChatEnabled } =
-          await getOnboardingStatus();
-        const homepageRoute = getHomepageRoute(isChatEnabled);
+        const { shouldShowOnboarding } = await getOnboardingStatus();
 
         if (!shouldShowOnboarding) {
-          router.replace(homepageRoute);
+          router.replace("/");
           return;
         }
 
@@ -26,7 +23,7 @@ export default function OnboardingPage() {
 
         // Handle completed onboarding
         if (onboarding.completedSteps.includes("GET_RESULTS")) {
-          router.replace(homepageRoute);
+          router.replace("/");
           return;
         }
 

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

@@ -1,9 +1,8 @@
-import { getServerSupabase } from "@/lib/supabase/server/getServerSupabase";
-import { getHomepageRoute } from "@/lib/constants";
-import BackendAPI from "@/lib/autogpt-server-api";
-import { NextResponse } from "next/server";
-import { revalidatePath } from "next/cache";
 import { getOnboardingStatus } from "@/app/api/helpers";
+import BackendAPI from "@/lib/autogpt-server-api";
+import { getServerSupabase } from "@/lib/supabase/server/getServerSupabase";
+import { revalidatePath } from "next/cache";
+import { NextResponse } from "next/server";
 
 // Handle the callback to complete the user session login
 export async function GET(request: Request) {
@@ -27,13 +26,12 @@ export async function GET(request: Request) {
         await api.createUser();
 
         // Get onboarding status from backend (includes chat flag evaluated for this user)
-        const { shouldShowOnboarding, isChatEnabled } =
-          await getOnboardingStatus();
+        const { shouldShowOnboarding } = await getOnboardingStatus();
         if (shouldShowOnboarding) {
           next = "/onboarding";
           revalidatePath("/onboarding", "layout");
         } else {
-          next = getHomepageRoute(isChatEnabled);
+          next = "/";
           revalidatePath(next, "layout");
         }
       } catch (createUserError) {

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

@@ -1,6 +1,13 @@
-import type { ReactNode } from "react";
+"use client";
+import { FeatureFlagPage } from "@/services/feature-flags/FeatureFlagPage";
+import { Flag } from "@/services/feature-flags/use-get-flag";
+import { type ReactNode } from "react";
 import { CopilotShell } from "./components/CopilotShell/CopilotShell";
 
 export default function CopilotLayout({ children }: { children: ReactNode }) {
-  return <CopilotShell>{children}</CopilotShell>;
+  return (
+    <FeatureFlagPage flag={Flag.CHAT} whenDisabled="/library">
+      <CopilotShell>{children}</CopilotShell>
+    </FeatureFlagPage>
+  );
 }

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

@@ -14,14 +14,8 @@ export default function CopilotPage() {
   const isInterruptModalOpen = useCopilotStore((s) => s.isInterruptModalOpen);
   const confirmInterrupt = useCopilotStore((s) => s.confirmInterrupt);
   const cancelInterrupt = useCopilotStore((s) => s.cancelInterrupt);
-  const {
-    greetingName,
-    quickActions,
-    isLoading,
-    hasSession,
-    initialPrompt,
-    isReady,
-  } = state;
+  const { greetingName, quickActions, isLoading, hasSession, initialPrompt } =
+    state;
   const {
     handleQuickAction,
     startChatWithPrompt,
@@ -29,8 +23,6 @@ export default function CopilotPage() {
     handleStreamingChange,
   } = handlers;
 
-  if (!isReady) return null;
-
   if (hasSession) {
     return (
       <div className="flex h-full flex-col">

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

@@ -3,18 +3,11 @@ import {
   postV2CreateSession,
 } from "@/app/api/__generated__/endpoints/chat/chat";
 import { useToast } from "@/components/molecules/Toast/use-toast";
-import { getHomepageRoute } from "@/lib/constants";
 import { useSupabase } from "@/lib/supabase/hooks/useSupabase";
 import { useOnboarding } from "@/providers/onboarding/onboarding-provider";
-import {
-  Flag,
-  type FlagValues,
-  useGetFlag,
-} from "@/services/feature-flags/use-get-flag";
 import { SessionKey, sessionStorage } from "@/services/storage/session-storage";
 import * as Sentry from "@sentry/nextjs";
 import { useQueryClient } from "@tanstack/react-query";
-import { useFlags } from "launchdarkly-react-client-sdk";
 import { useRouter } from "next/navigation";
 import { useEffect } from "react";
 import { useCopilotStore } from "./copilot-page-store";
@@ -33,22 +26,6 @@ export function useCopilotPage() {
   const isCreating = useCopilotStore((s) => s.isCreatingSession);
   const setIsCreating = useCopilotStore((s) => s.setIsCreatingSession);
 
-  // Complete VISIT_COPILOT onboarding step to grant $5 welcome bonus
-  useEffect(() => {
-    if (isLoggedIn) {
-      completeStep("VISIT_COPILOT");
-    }
-  }, [completeStep, isLoggedIn]);
-
-  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 greetingName = getGreetingName(user);
   const quickActions = getQuickActions();
 
@@ -58,11 +35,8 @@ export function useCopilotPage() {
     : undefined;
 
   useEffect(() => {
-    if (!isFlagReady) return;
-    if (isChatEnabled === false) {
-      router.replace(homepageRoute);
-    }
-  }, [homepageRoute, isChatEnabled, isFlagReady, router]);
+    if (isLoggedIn) completeStep("VISIT_COPILOT");
+  }, [completeStep, isLoggedIn]);
 
   async function startChatWithPrompt(prompt: string) {
     if (!prompt?.trim()) return;
@@ -116,7 +90,6 @@ export function useCopilotPage() {
       isLoading: isUserLoading,
       hasSession,
       initialPrompt,
-      isReady: isFlagReady && isChatEnabled !== false && isLoggedIn,
     },
     handlers: {
       handleQuickAction,

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

@@ -1,8 +1,6 @@
 "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";
@@ -11,8 +9,6 @@ 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
@@ -30,7 +26,7 @@ function ErrorPageContent() {
       }, 2000);
     } else {
       // For server/network errors, go to home
-      window.location.href = homepageRoute;
+      window.location.href = "/";
     }
   }
 

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

@@ -1,6 +1,5 @@
 "use server";
 
-import { getHomepageRoute } from "@/lib/constants";
 import BackendAPI from "@/lib/autogpt-server-api";
 import { getServerSupabase } from "@/lib/supabase/server/getServerSupabase";
 import { loginFormSchema } from "@/types/auth";
@@ -38,10 +37,8 @@ export async function login(email: string, password: string) {
     await api.createUser();
 
     // Get onboarding status from backend (includes chat flag evaluated for this user)
-    const { shouldShowOnboarding, isChatEnabled } = await getOnboardingStatus();
-    const next = shouldShowOnboarding
-      ? "/onboarding"
-      : getHomepageRoute(isChatEnabled);
+    const { shouldShowOnboarding } = await getOnboardingStatus();
+    const next = shouldShowOnboarding ? "/onboarding" : "/";
 
     return {
       success: true,

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

@@ -1,8 +1,6 @@
 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";
@@ -22,17 +20,15 @@ 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 || homepageRoute);
+      router.push(nextUrl || "/");
     }
-  }, [homepageRoute, isLoggedIn, isLoggingIn, nextUrl, router]);
+  }, [isLoggedIn, isLoggingIn, nextUrl, router]);
 
   const form = useForm<z.infer<typeof loginFormSchema>>({
     resolver: zodResolver(loginFormSchema),
@@ -98,7 +94,7 @@ export function useLoginPage() {
       }
 
       // Prefer URL's next parameter, then use backend-determined route
-      router.replace(nextUrl || result.next || homepageRoute);
+      router.replace(nextUrl || result.next || "/");
     } catch (error) {
       toast({
         title:

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

@@ -1,6 +1,5 @@
 "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";
@@ -59,10 +58,8 @@ export async function signup(
     }
 
     // Get onboarding status from backend (includes chat flag evaluated for this user)
-    const { shouldShowOnboarding, isChatEnabled } = await getOnboardingStatus();
-    const next = shouldShowOnboarding
-      ? "/onboarding"
-      : getHomepageRoute(isChatEnabled);
+    const { shouldShowOnboarding } = await getOnboardingStatus();
+    const next = shouldShowOnboarding ? "/onboarding" : "/";
 
     return { success: true, next };
   } catch (err) {

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

@@ -1,8 +1,6 @@
 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";
@@ -22,17 +20,15 @@ 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 || homepageRoute);
+      router.push(nextUrl || "/");
     }
-  }, [homepageRoute, isLoggedIn, isSigningUp, nextUrl, router]);
+  }, [isLoggedIn, isSigningUp, nextUrl, router]);
 
   const form = useForm<z.infer<typeof signupFormSchema>>({
     resolver: zodResolver(signupFormSchema),
@@ -133,7 +129,7 @@ export function useSignupPage() {
       }
 
       // Prefer the URL's next parameter, then result.next (for onboarding), then default
-      const redirectTo = nextUrl || result.next || homepageRoute;
+      const redirectTo = nextUrl || result.next || "/";
       router.replace(redirectTo);
     } catch (error) {
       setIsLoading(false);

autogpt_platform/frontend/src/app/api/helpers.ts

@@ -181,6 +181,5 @@ export async function getOnboardingStatus() {
   const isCompleted = onboarding.completedSteps.includes("CONGRATS");
   return {
     shouldShowOnboarding: status.is_onboarding_enabled && !isCompleted,
-    isChatEnabled: status.is_chat_enabled,
   };
 }

autogpt_platform/frontend/src/app/page.tsx

@@ -1,27 +1,15 @@
 "use client";
 
-import { getHomepageRoute } from "@/lib/constants";
-import { Flag, useGetFlag } from "@/services/feature-flags/use-get-flag";
+import { LoadingSpinner } from "@/components/atoms/LoadingSpinner/LoadingSpinner";
 import { useRouter } from "next/navigation";
 import { useEffect } from "react";
 
 export default function Page() {
-  const isChatEnabled = useGetFlag(Flag.CHAT);
   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 || typeof isChatEnabled === "boolean";
 
-  useEffect(
-    function redirectToHomepage() {
-      if (!isFlagReady) return;
-      router.replace(homepageRoute);
-    },
-    [homepageRoute, isFlagReady, router],
-  );
+  useEffect(() => {
+    router.replace("/copilot");
+  }, [router]);
 
-  return null;
+  return <LoadingSpinner size="large" cover />;
 }

autogpt_platform/frontend/src/components/layout/Navbar/components/NavbarLink.tsx

@@ -1,7 +1,6 @@
 "use client";
 
 import { IconLaptop } from "@/components/__legacy__/ui/icons";
-import { getHomepageRoute } from "@/lib/constants";
 import { cn } from "@/lib/utils";
 import { Flag, useGetFlag } from "@/services/feature-flags/use-get-flag";
 import { ListChecksIcon } from "@phosphor-icons/react/dist/ssr";
@@ -24,11 +23,11 @@ interface Props {
 export function NavbarLink({ name, href }: Props) {
   const pathname = usePathname();
   const isChatEnabled = useGetFlag(Flag.CHAT);
-  const homepageRoute = getHomepageRoute(isChatEnabled);
+  const expectedHomeRoute = isChatEnabled ? "/copilot" : "/library";
 
   const isActive =
-    href === homepageRoute
-      ? pathname === "/" || pathname.startsWith(homepageRoute)
+    href === expectedHomeRoute
+      ? pathname === "/" || pathname.startsWith(expectedHomeRoute)
       : pathname.includes(href);
 
   return (

autogpt_platform/frontend/src/hooks/useAgentGraph.tsx

@@ -66,7 +66,7 @@ export default function useAgentGraph(
   >(null);
   const [xyNodes, setXYNodes] = useState<CustomNode[]>([]);
   const [xyEdges, setXYEdges] = useState<CustomEdge[]>([]);
-  const betaBlocks = useGetFlag(Flag.BETA_BLOCKS);
+  const betaBlocks = useGetFlag(Flag.BETA_BLOCKS) as string[];
 
   // Filter blocks based on beta flags
   const availableBlocks = useMemo(() => {

autogpt_platform/frontend/src/lib/constants.ts

@@ -11,10 +11,3 @@ export const API_KEY_HEADER_NAME = "X-API-Key";
 
 // Layout
 export const NAVBAR_HEIGHT_PX = 60;
-
-// Routes
-export function getHomepageRoute(isChatEnabled?: boolean | null): string {
-  if (isChatEnabled === true) return "/copilot";
-  if (isChatEnabled === false) return "/library";
-  return "/";
-}

autogpt_platform/frontend/src/lib/supabase/helpers.ts

@@ -1,4 +1,3 @@
-import { getHomepageRoute } from "@/lib/constants";
 import { environment } from "@/services/environment";
 import { Key, storage } from "@/services/storage/local-storage";
 import { type CookieOptions } from "@supabase/ssr";
@@ -71,7 +70,7 @@ export function getRedirectPath(
   }
 
   if (isAdminPage(path) && userRole !== "admin") {
-    return getHomepageRoute();
+    return "/";
   }
 
   return null;

autogpt_platform/frontend/src/lib/supabase/middleware.ts

@@ -1,4 +1,3 @@
-import { getHomepageRoute } from "@/lib/constants";
 import { environment } from "@/services/environment";
 import { createServerClient } from "@supabase/ssr";
 import { NextResponse, type NextRequest } from "next/server";
@@ -67,7 +66,7 @@ export async function updateSession(request: NextRequest) {
 
     // 2. Check if user is authenticated but lacks admin role when accessing admin pages
     if (user && userRole !== "admin" && isAdminPage(pathname)) {
-      url.pathname = getHomepageRoute();
+      url.pathname = "/";
       return NextResponse.redirect(url);
     }
 

autogpt_platform/frontend/src/providers/onboarding/onboarding-provider.tsx

@@ -23,9 +23,7 @@ import {
   WebSocketNotification,
 } from "@/lib/autogpt-server-api";
 import { useBackendAPI } from "@/lib/autogpt-server-api/context";
-import { getHomepageRoute } from "@/lib/constants";
 import { useSupabase } from "@/lib/supabase/hooks/useSupabase";
-import { Flag, useGetFlag } from "@/services/feature-flags/use-get-flag";
 import Link from "next/link";
 import { usePathname, useRouter } from "next/navigation";
 import {
@@ -104,8 +102,6 @@ export default function OnboardingProvider({
   const pathname = usePathname();
   const router = useRouter();
   const { isLoggedIn } = useSupabase();
-  const isChatEnabled = useGetFlag(Flag.CHAT);
-  const homepageRoute = getHomepageRoute(isChatEnabled);
 
   useOnboardingTimezoneDetection();
 
@@ -150,7 +146,7 @@ export default function OnboardingProvider({
         if (isOnOnboardingRoute) {
           const enabled = await resolveResponse(getV1IsOnboardingEnabled());
           if (!enabled) {
-            router.push(homepageRoute);
+            router.push("/");
             return;
           }
         }
@@ -162,7 +158,7 @@ export default function OnboardingProvider({
           isOnOnboardingRoute &&
           shouldRedirectFromOnboarding(onboarding.completedSteps, pathname)
         ) {
-          router.push(homepageRoute);
+          router.push("/");
         }
       } catch (error) {
         console.error("Failed to initialize onboarding:", error);
@@ -177,7 +173,7 @@ export default function OnboardingProvider({
     }
 
     initializeOnboarding();
-  }, [api, homepageRoute, isOnOnboardingRoute, router, isLoggedIn, pathname]);
+  }, [api, isOnOnboardingRoute, router, isLoggedIn, pathname]);
 
   const handleOnboardingNotification = useCallback(
     (notification: WebSocketNotification) => {

autogpt_platform/frontend/src/services/environment/index.ts

@@ -83,6 +83,10 @@ function getPostHogCredentials() {
   };
 }
 
+function getLaunchDarklyClientId() {
+  return process.env.NEXT_PUBLIC_LAUNCHDARKLY_CLIENT_ID;
+}
+
 function isProductionBuild() {
   return process.env.NODE_ENV === "production";
 }
@@ -120,7 +124,10 @@ function isVercelPreview() {
 }
 
 function areFeatureFlagsEnabled() {
-  return process.env.NEXT_PUBLIC_LAUNCHDARKLY_ENABLED === "enabled";
+  return (
+    process.env.NEXT_PUBLIC_LAUNCHDARKLY_ENABLED === "true" &&
+    Boolean(process.env.NEXT_PUBLIC_LAUNCHDARKLY_CLIENT_ID)
+  );
 }
 
 function isPostHogEnabled() {
@@ -143,6 +150,7 @@ export const environment = {
   getSupabaseAnonKey,
   getPreviewStealingDev,
   getPostHogCredentials,
+  getLaunchDarklyClientId,
   // Assertions
   isServerSide,
   isClientSide,

autogpt_platform/frontend/src/services/feature-flags/FeatureFlagPage.tsx

@@ -0,0 +1,59 @@
+"use client";
+
+import { LoadingSpinner } from "@/components/atoms/LoadingSpinner/LoadingSpinner";
+import { useLDClient } from "launchdarkly-react-client-sdk";
+import { useRouter } from "next/navigation";
+import { ReactNode, useEffect, useState } from "react";
+import { environment } from "../environment";
+import { Flag, useGetFlag } from "./use-get-flag";
+
+interface FeatureFlagRedirectProps {
+  flag: Flag;
+  whenDisabled: string;
+  children: ReactNode;
+}
+
+export function FeatureFlagPage({
+  flag,
+  whenDisabled,
+  children,
+}: FeatureFlagRedirectProps) {
+  const [isLoading, setIsLoading] = useState(true);
+  const router = useRouter();
+  const flagValue = useGetFlag(flag);
+  const ldClient = useLDClient();
+  const ldEnabled = environment.areFeatureFlagsEnabled();
+  const ldReady = Boolean(ldClient);
+  const flagEnabled = Boolean(flagValue);
+
+  useEffect(() => {
+    const initialize = async () => {
+      if (!ldEnabled) {
+        router.replace(whenDisabled);
+        setIsLoading(false);
+        return;
+      }
+
+      // Wait for LaunchDarkly to initialize when enabled to prevent race conditions
+      if (ldEnabled && !ldReady) return;
+
+      try {
+        await ldClient?.waitForInitialization();
+        if (!flagEnabled) router.replace(whenDisabled);
+      } catch (error) {
+        console.error(error);
+        router.replace(whenDisabled);
+      } finally {
+        setIsLoading(false);
+      }
+    };
+
+    initialize();
+  }, [ldReady, flagEnabled]);
+
+  return isLoading || !flagEnabled ? (
+    <LoadingSpinner size="large" cover />
+  ) : (
+    <>{children}</>
+  );
+}

autogpt_platform/frontend/src/services/feature-flags/FeatureFlagRedirect.tsx

@@ -0,0 +1,51 @@
+"use client";
+
+import { LoadingSpinner } from "@/components/atoms/LoadingSpinner/LoadingSpinner";
+import { useLDClient } from "launchdarkly-react-client-sdk";
+import { useRouter } from "next/navigation";
+import { useEffect } from "react";
+import { environment } from "../environment";
+import { Flag, useGetFlag } from "./use-get-flag";
+
+interface FeatureFlagRedirectProps {
+  flag: Flag;
+  whenEnabled: string;
+  whenDisabled: string;
+}
+
+export function FeatureFlagRedirect({
+  flag,
+  whenEnabled,
+  whenDisabled,
+}: FeatureFlagRedirectProps) {
+  const router = useRouter();
+  const flagValue = useGetFlag(flag);
+  const ldEnabled = environment.areFeatureFlagsEnabled();
+  const ldClient = useLDClient();
+  const ldReady = Boolean(ldClient);
+  const flagEnabled = Boolean(flagValue);
+
+  useEffect(() => {
+    const initialize = async () => {
+      if (!ldEnabled) {
+        router.replace(whenDisabled);
+        return;
+      }
+
+      // Wait for LaunchDarkly to initialize when enabled to prevent race conditions
+      if (ldEnabled && !ldReady) return;
+
+      try {
+        await ldClient?.waitForInitialization();
+        router.replace(flagEnabled ? whenEnabled : whenDisabled);
+      } catch (error) {
+        console.error(error);
+        router.replace(whenDisabled);
+      }
+    };
+
+    initialize();
+  }, [ldReady, flagEnabled]);
+
+  return <LoadingSpinner size="large" cover />;
+}

autogpt_platform/frontend/src/services/feature-flags/feature-flag-provider.tsx

@@ -1,5 +1,6 @@
 "use client";
 
+import { LoadingSpinner } from "@/components/atoms/LoadingSpinner/LoadingSpinner";
 import { useSupabase } from "@/lib/supabase/hooks/useSupabase";
 import * as Sentry from "@sentry/nextjs";
 import { LDProvider } from "launchdarkly-react-client-sdk";
@@ -7,17 +8,17 @@ import type { ReactNode } from "react";
 import { useMemo } from "react";
 import { environment } from "../environment";
 
-const clientId = process.env.NEXT_PUBLIC_LAUNCHDARKLY_CLIENT_ID;
-const envEnabled = process.env.NEXT_PUBLIC_LAUNCHDARKLY_ENABLED === "true";
 const LAUNCHDARKLY_INIT_TIMEOUT_MS = 5000;
 
 export function LaunchDarklyProvider({ children }: { children: ReactNode }) {
   const { user, isUserLoading } = useSupabase();
-  const isCloud = environment.isCloud();
-  const isLaunchDarklyConfigured = isCloud && envEnabled && clientId;
+  const envEnabled = environment.areFeatureFlagsEnabled();
+  const clientId = environment.getLaunchDarklyClientId();
 
   const context = useMemo(() => {
-    if (isUserLoading || !user) {
+    if (isUserLoading) return;
+
+    if (!user) {
       return {
         kind: "user" as const,
         key: "anonymous",
@@ -36,15 +37,17 @@ export function LaunchDarklyProvider({ children }: { children: ReactNode }) {
     };
   }, [user, isUserLoading]);
 
-  if (!isLaunchDarklyConfigured) {
+  if (!envEnabled) {
     return <>{children}</>;
   }
 
+  if (isUserLoading) {
+    return <LoadingSpinner size="large" cover />;
+  }
+
   return (
     <LDProvider
-      // Add this key prop. It will be 'anonymous' when logged out,
-      key={context.key}
-      clientSideID={clientId}
+      clientSideID={clientId ?? ""}
       context={context}
       timeout={LAUNCHDARKLY_INIT_TIMEOUT_MS}
       reactOptions={{ useCamelCaseFlagKeys: false }}

autogpt_platform/frontend/src/services/feature-flags/use-get-flag.ts

@@ -1,6 +1,7 @@
 "use client";
 
 import { DEFAULT_SEARCH_TERMS } from "@/app/(platform)/marketplace/components/HeroSection/helpers";
+import { environment } from "@/services/environment";
 import { useFlags } from "launchdarkly-react-client-sdk";
 
 export enum Flag {
@@ -18,24 +19,9 @@ export enum Flag {
   CHAT = "chat",
 }
 
-export type FlagValues = {
-  [Flag.BETA_BLOCKS]: string[];
-  [Flag.NEW_BLOCK_MENU]: boolean;
-  [Flag.NEW_AGENT_RUNS]: boolean;
-  [Flag.GRAPH_SEARCH]: boolean;
-  [Flag.ENABLE_ENHANCED_OUTPUT_HANDLING]: boolean;
-  [Flag.NEW_FLOW_EDITOR]: boolean;
-  [Flag.BUILDER_VIEW_SWITCH]: boolean;
-  [Flag.SHARE_EXECUTION_RESULTS]: boolean;
-  [Flag.AGENT_FAVORITING]: boolean;
-  [Flag.MARKETPLACE_SEARCH_TERMS]: string[];
-  [Flag.ENABLE_PLATFORM_PAYMENT]: boolean;
-  [Flag.CHAT]: boolean;
-};
-
 const isPwMockEnabled = process.env.NEXT_PUBLIC_PW_TEST === "true";
 
-const mockFlags = {
+const defaultFlags = {
   [Flag.BETA_BLOCKS]: [],
   [Flag.NEW_BLOCK_MENU]: false,
   [Flag.NEW_AGENT_RUNS]: false,
@@ -50,17 +36,16 @@ const mockFlags = {
   [Flag.CHAT]: false,
 };
 
-export function useGetFlag<T extends Flag>(flag: T): FlagValues[T] | null {
+type FlagValues = typeof defaultFlags;
+
+export function useGetFlag<T extends Flag>(flag: T): FlagValues[T] {
   const currentFlags = useFlags<FlagValues>();
   const flagValue = currentFlags[flag];
+  const areFlagsEnabled = environment.areFeatureFlagsEnabled();
 
-  const envEnabled = process.env.NEXT_PUBLIC_LAUNCHDARKLY_ENABLED === "true";
-  const clientId = process.env.NEXT_PUBLIC_LAUNCHDARKLY_CLIENT_ID;
-  const isLaunchDarklyConfigured = envEnabled && Boolean(clientId);
-
-  if (!isLaunchDarklyConfigured || isPwMockEnabled) {
-    return mockFlags[flag];
+  if (!areFlagsEnabled || isPwMockEnabled) {
+    return defaultFlags[flag];
   }
 
-  return flagValue ?? mockFlags[flag];
+  return flagValue ?? defaultFlags[flag];
 }

classic/frontend/.gitignore

@@ -8,6 +8,7 @@
 .buildlog/
 .history
 .svn/
+.next/
 migrate_working_dir/
 
 # IntelliJ related

classic/frontend/build/web/flutter_service_worker.js

@@ -3,45 +3,45 @@ const MANIFEST = 'flutter-app-manifest';
 const TEMP = 'flutter-temp-cache';
 const CACHE_NAME = 'flutter-app-cache';
 
-const RESOURCES = {"canvaskit/skwasm.worker.js": "51253d3321b11ddb8d73fa8aa87d3b15",
-"canvaskit/skwasm.js": "95f16c6690f955a45b2317496983dbe9",
-"canvaskit/canvaskit.wasm": "d9f69e0f428f695dc3d66b3a83a4aa8e",
-"canvaskit/skwasm.wasm": "d1fde2560be92c0b07ad9cf9acb10d05",
-"canvaskit/canvaskit.js": "5caccb235fad20e9b72ea6da5a0094e6",
-"canvaskit/chromium/canvaskit.wasm": "393ec8fb05d94036734f8104fa550a67",
-"canvaskit/chromium/canvaskit.js": "ffb2bb6484d5689d91f393b60664d530",
-"icons/Icon-maskable-192.png": "c457ef57daa1d16f64b27b786ec2ea3c",
-"icons/Icon-maskable-512.png": "301a7604d45b3e739efc881eb04896ea",
+const RESOURCES = {"flutter.js": "6fef97aeca90b426343ba6c5c9dc5d4a",
 "icons/Icon-512.png": "96e752610906ba2a93c65f8abe1645f1",
+"icons/Icon-maskable-512.png": "301a7604d45b3e739efc881eb04896ea",
 "icons/Icon-192.png": "ac9a721a12bbc803b44f645561ecb1e1",
+"icons/Icon-maskable-192.png": "c457ef57daa1d16f64b27b786ec2ea3c",
 "manifest.json": "0fa552613b8ec0fda5cda565914e3b16",
-"favicon.png": "5dcef449791fa27946b3d35ad8803796",
-"version.json": "46a52461e018faa623d9196334aa3f50",
-"index.html": "e6981504a32bf86f892909c1875df208",
-"/": "e6981504a32bf86f892909c1875df208",
-"main.dart.js": "6fcbf8bbcb0a76fae9029f72ac7fbdc3",
-"assets/AssetManifest.json": "1b1e4a4276722b65eb1ef765e2991840",
-"assets/packages/cupertino_icons/assets/CupertinoIcons.ttf": "055d9e87e4a40dbf72b2af1a20865d57",
-"assets/packages/fluttertoast/assets/toastify.js": "56e2c9cedd97f10e7e5f1cebd85d53e3",
-"assets/packages/fluttertoast/assets/toastify.css": "a85675050054f179444bc5ad70ffc635",
+"index.html": "3442c510a9ea217672c82e799ae070f7",
+"/": "3442c510a9ea217672c82e799ae070f7",
 "assets/shaders/ink_sparkle.frag": "f8b80e740d33eb157090be4e995febdf",
-"assets/fonts/MaterialIcons-Regular.otf": "245e0462249d95ad589a087f1c9f58e1",
-"assets/assets/images/twitter_logo.png": "af6c11b96a5e732b8dfda86a2351ecab",
-"assets/assets/images/discord_logo.png": "0e4a4162c5de8665a7d63ae9665405ae",
-"assets/assets/images/google_logo.svg.png": "0e29f8e1acfb8996437dbb2b0f591f19",
-"assets/assets/images/autogpt_logo.png": "6a5362a7d1f2f840e43ee259e733476c",
-"assets/assets/images/github_logo.svg.png": "ba087b073efdc4996b035d3a12bad0e4",
-"assets/assets/scrape_synthesize_tree_structure.json": "a9665c1b465bb0cb939c7210f2bf0b13",
+"assets/assets/tree_structure.json": "cda9b1a239f956c547411efad9f7c794",
 "assets/assets/coding_tree_structure.json": "017a857cf3e274346a0a7eab4ce02eed",
 "assets/assets/general_tree_structure.json": "41dfbcdc2349dcdda2b082e597c6d5ee",
-"assets/assets/google_logo.svg.png": "0e29f8e1acfb8996437dbb2b0f591f19",
-"assets/assets/tree_structure.json": "cda9b1a239f956c547411efad9f7c794",
-"assets/assets/data_tree_structure.json": "5f9627548304155821968182f3883ca7",
 "assets/assets/github_logo.svg.png": "ba087b073efdc4996b035d3a12bad0e4",
+"assets/assets/images/discord_logo.png": "0e4a4162c5de8665a7d63ae9665405ae",
+"assets/assets/images/github_logo.svg.png": "ba087b073efdc4996b035d3a12bad0e4",
+"assets/assets/images/twitter_logo.png": "af6c11b96a5e732b8dfda86a2351ecab",
+"assets/assets/images/google_logo.svg.png": "0e29f8e1acfb8996437dbb2b0f591f19",
+"assets/assets/images/autogpt_logo.png": "6a5362a7d1f2f840e43ee259e733476c",
+"assets/assets/google_logo.svg.png": "0e29f8e1acfb8996437dbb2b0f591f19",
+"assets/assets/scrape_synthesize_tree_structure.json": "a9665c1b465bb0cb939c7210f2bf0b13",
+"assets/assets/data_tree_structure.json": "5f9627548304155821968182f3883ca7",
+"assets/fonts/MaterialIcons-Regular.otf": "245e0462249d95ad589a087f1c9f58e1",
 "assets/NOTICES": "28ba0c63fc6e4d1ef829af7441e27f78",
-"assets/AssetManifest.bin": "791447d17744ac2ade3999c1672fdbe8",
+"assets/packages/fluttertoast/assets/toastify.css": "a85675050054f179444bc5ad70ffc635",
+"assets/packages/fluttertoast/assets/toastify.js": "56e2c9cedd97f10e7e5f1cebd85d53e3",
+"assets/packages/cupertino_icons/assets/CupertinoIcons.ttf": "055d9e87e4a40dbf72b2af1a20865d57",
 "assets/FontManifest.json": "dc3d03800ccca4601324923c0b1d6d57",
-"flutter.js": "6fef97aeca90b426343ba6c5c9dc5d4a"};
+"assets/AssetManifest.bin": "791447d17744ac2ade3999c1672fdbe8",
+"assets/AssetManifest.json": "1b1e4a4276722b65eb1ef765e2991840",
+"canvaskit/chromium/canvaskit.wasm": "393ec8fb05d94036734f8104fa550a67",
+"canvaskit/chromium/canvaskit.js": "ffb2bb6484d5689d91f393b60664d530",
+"canvaskit/skwasm.worker.js": "51253d3321b11ddb8d73fa8aa87d3b15",
+"canvaskit/skwasm.js": "95f16c6690f955a45b2317496983dbe9",
+"canvaskit/canvaskit.wasm": "d9f69e0f428f695dc3d66b3a83a4aa8e",
+"canvaskit/canvaskit.js": "5caccb235fad20e9b72ea6da5a0094e6",
+"canvaskit/skwasm.wasm": "d1fde2560be92c0b07ad9cf9acb10d05",
+"favicon.png": "5dcef449791fa27946b3d35ad8803796",
+"version.json": "46a52461e018faa623d9196334aa3f50",
+"main.dart.js": "6fcbf8bbcb0a76fae9029f72ac7fbdc3"};
 // The application shell files that are downloaded before a service worker can
 // start.
 const CORE = ["main.dart.js",

classic/frontend/build/web/index.html

@@ -35,7 +35,7 @@
 
   <script>
     // The value below is injected by flutter build, do not touch.
-    const serviceWorkerVersion = "726743092";
+    const serviceWorkerVersion = "1550046101";
   </script>
   <!-- This script adds the flutter initialization JS code -->
   <script src="flutter.js" defer></script>