fix: address PR review feedback

- Remove inline comments per code style guidelines
- Add scope checking to credential matching (was missing after refactor)
- Update find_matching_credential to take CredentialsFieldInfo and check scopes
- Remove redundant comments in routes.py, run_block.py, utils.py, validation.py

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

@@ -17,6 +17,14 @@ 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__)
 
@@ -32,6 +40,60 @@ 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"],
 )
@@ -221,49 +283,17 @@ async def stream_chat_post(
     """
     session = await _validate_and_get_session(session_id, user_id)
 
-    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(),
+        _create_stream_generator(
+            session_id=session_id,
+            message=request.message,
+            user_id=user_id,
+            session=session,
+            is_user_message=request.is_user_message,
+            context=request.context,
+        ),
         media_type="text/event-stream",
-        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
-        },
+        headers=SSE_RESPONSE_HEADERS,
     )
 
 
@@ -295,48 +325,16 @@ async def stream_chat_get(
     """
     session = await _validate_and_get_session(session_id, user_id)
 
-    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(),
+        _create_stream_generator(
+            session_id=session_id,
+            message=message,
+            user_id=user_id,
+            session=session,
+            is_user_message=is_user_message,
+        ),
         media_type="text/event-stream",
-        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
-        },
+        headers=SSE_RESPONSE_HEADERS,
     )
 
 

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

@@ -0,0 +1,77 @@
+"""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/run_agent.py

@@ -24,6 +24,7 @@ from backend.util.timezone_utils import (
 )
 
 from .base import BaseTool
+from .helpers import get_inputs_from_schema
 from .models import (
     AgentDetails,
     AgentDetailsResponse,
@@ -354,19 +355,7 @@ class RunAgentTool(BaseTool):
 
     def _get_inputs_list(self, input_schema: dict[str, Any]) -> list[dict[str, Any]]:
         """Extract inputs list from 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
+        return get_inputs_from_schema(input_schema)
 
     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_block.py

@@ -8,12 +8,13 @@ from typing import Any
 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 CredentialsMetaInput
+from backend.data.model import CredentialsFieldInfo, 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,
@@ -22,7 +23,10 @@ from .models import (
     ToolResponseBase,
     UserReadiness,
 )
-from .utils import build_missing_credentials_from_field_info
+from .utils import (
+    build_missing_credentials_from_field_info,
+    match_credentials_to_requirements,
+)
 
 logger = logging.getLogger(__name__)
 
@@ -71,6 +75,22 @@ 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,
@@ -82,53 +102,12 @@ class RunBlockTool(BaseTool):
         Returns:
             tuple[matched_credentials, missing_credentials]
         """
-        matched_credentials: dict[str, CredentialsMetaInput] = {}
-        missing_credentials: list[CredentialsMetaInput] = []
+        requirements = self._get_credentials_requirements(block)
 
-        # Get credential field info from block's input schema
-        credentials_fields_info = block.input_schema.get_credentials_fields_info()
+        if not requirements:
+            return {}, []
 
-        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():
-            # field_info.provider is a frozenset of acceptable providers
-            # field_info.supported_types is a frozenset of acceptable types
-            matching_cred = next(
-                (
-                    cred
-                    for cred in available_creds
-                    if cred.provider in field_info.provider
-                    and cred.type in 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(field_info.provider), "unknown")
-                cred_type = next(iter(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
+        return await match_credentials_to_requirements(user_id, requirements)
 
     async def _execute(
         self,
@@ -320,27 +299,7 @@ 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())
-
-        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
+        return get_inputs_from_schema(schema, exclude_fields=credentials_fields)

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

@@ -225,6 +225,127 @@ 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,
@@ -242,9 +363,6 @@ 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(
@@ -252,69 +370,30 @@ async def match_user_credentials_to_graph(
     )
 
     if not aggregated_creds:
-        return graph_credentials_inputs, missing_creds
+        return {}, []
 
-    # Get all available credentials for the user
-    creds_manager = IntegrationCredentialsManager()
-    available_creds = await creds_manager.store.get_all_creds(user_id)
+    # Convert aggregated format to simple requirements dict
+    requirements = {
+        field_name: field_info
+        for field_name, (field_info, _node_fields) in aggregated_creds.items()
+    }
 
-    # 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,
-        )
-
-        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(graph_credentials_inputs)}/{len(aggregated_creds)} matched"
+    # Use shared matching logic
+    matched, missing_list = await match_credentials_to_requirements(
+        user_id, requirements
     )
 
-    return graph_credentials_inputs, missing_creds
+    # 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
+    ]
+
+    logger.info(
+        f"Credential matching complete: {len(matched)}/{len(aggregated_creds)} matched"
+    )
+
+    return matched, missing_descriptions
 
 
 def _credential_has_required_scopes(

autogpt_platform/backend/backend/util/validation.py

@@ -0,0 +1,32 @@
+"""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)})