fix(frontend): Prevent node drag when selecting text in object editor key input

Add nodrag class to the key name input wrapper in WrapIfAdditionalTemplate
to allow text selection without triggering node drag behavior. This matches
the pattern used by other input components like TextWidget.

https://claude.ai/code/session_012KzXYWLoXF8P8L5a5L19Pi

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

@@ -17,13 +17,6 @@ from .model import ChatSession, create_chat_session, get_chat_session, get_user_
 
 config = ChatConfig()
 
-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__)
 
@@ -39,48 +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."""
-    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"],
 )
@@ -270,17 +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
+        },
     )
 
 
@@ -312,16 +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

@@ -1,81 +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)
-    """
-    # Safety check: original code returned [] if input_schema wasn't a dict
-    if not isinstance(input_schema, dict):
-        return []
-
-    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

@@ -24,7 +24,6 @@ from backend.util.timezone_utils import (
 )
 
 from .base import BaseTool
-from .helpers import get_inputs_from_schema
 from .models import (
     AgentDetails,
     AgentDetailsResponse,
@@ -372,7 +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_block.py

@@ -10,13 +10,12 @@ 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,
@@ -25,10 +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__)
 
@@ -77,22 +73,41 @@ class RunBlockTool(BaseTool):
     def requires_auth(self) -> bool:
         return True
 
-    def _resolve_discriminated_credentials(
+    async def _check_block_credentials(
         self,
+        user_id: str,
         block: Any,
-        input_data: dict[str, Any],
-    ) -> dict[str, CredentialsFieldInfo]:
-        """Resolve credential requirements, applying discriminator logic where needed."""
-        credentials_fields_info = block.input_schema.get_credentials_fields_info()
-        if not credentials_fields_info:
-            return {}
+        input_data: dict[str, Any] | None = None,
+    ) -> tuple[dict[str, CredentialsMetaInput], list[CredentialsMetaInput]]:
+        """
+        Check if user has required credentials for a block.
 
-        resolved: dict[str, CredentialsFieldInfo] = {}
+        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]
+        """
+        matched_credentials: dict[str, CredentialsMetaInput] = {}
+        missing_credentials: list[CredentialsMetaInput] = []
+        input_data = input_data or {}
+
+        # Get credential field info from block's input schema
+        credentials_fields_info = block.input_schema.get_credentials_fields_info()
+
+        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(
@@ -111,34 +126,37 @@ class RunBlockTool(BaseTool):
                         f"{discriminator_value} -> {effective_field_info.provider}"
                     )
 
-            resolved[field_name] = effective_field_info
+            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,
+            )
 
-        return resolved
+            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(),
+                    )
+                )
 
-    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]
-        """
-        input_data = input_data or {}
-        requirements = self._resolve_discriminated_credentials(block, input_data)
-
-        if not requirements:
-            return {}, []
-
-        return await match_credentials_to_requirements(user_id, requirements)
+        return matched_credentials, missing_credentials
 
     async def _execute(
         self,
@@ -329,6 +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

@@ -225,103 +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."""
-    creds_manager = IntegrationCredentialsManager()
-    return await creds_manager.store.get_all_creds(user_id)
-
-
-def find_matching_credential(
-    available_creds: list,
-    field_info: CredentialsFieldInfo,
-    check_scopes: bool = True,
-):
-    """Find a credential that matches the required provider, type, and optionally scopes."""
-    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 check_scopes and 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."""
-    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],
-    check_scopes: bool = True,
-) -> 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: User ID to fetch credentials for
-        requirements: Dict mapping field names to CredentialsFieldInfo
-        check_scopes: Whether to verify OAuth2 scopes match requirements (default True).
-            Set to False to preserve original run_block behavior which didn't check scopes.
-    """
-    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, check_scopes=check_scopes
-        )
-
-        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,

autogpt_platform/backend/backend/util/validation.py

@@ -1,16 +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:
-    return bool(_UUID_V4_PATTERN.fullmatch(text.strip()))
-
-
-def extract_uuids(text: str) -> list[str]:
-    return sorted({m.lower() for m in _UUID_V4_PATTERN.findall(text)})

autogpt_platform/frontend/src/components/renderers/InputRenderer/base/object/WrapIfAdditionalTemplate.tsx

@@ -80,7 +80,7 @@ export default function WrapIfAdditionalTemplate(
           uiSchema={uiSchema}
         />
         {!isHandleConnected && (
-          <div className="flex flex-1 items-center gap-2">
+          <div className="nodrag flex flex-1 items-center gap-2">
             <Input
               label={""}
               hideLabel={true}