fix: address CodeRabbit review bugs

- customize_agent.py: Strip whitespace from split parts of agent_id
- edit_agent.py: Use model_config instead of deprecated class Config
- edit_agent.py: Fix undefined agent_id/changes → params.agent_id/params.changes
- find_library_agent.py: Remove docstrings per coding guidelines
- get_doc_page.py: Fix undefined path → params.path
- run_block.py: Fix undefined block_id → params.block_id
- workspace_files.py: Fix undefined include_all_sessions → params.include_all_sessions

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

@@ -1,12 +1,15 @@
 import asyncio
 import logging
 import time
+import uuid as uuid_module
 from asyncio import CancelledError
 from collections.abc import AsyncGenerator
 from typing import TYPE_CHECKING, Any, cast
 
 import openai
 
+from backend.util.prompt import compress_context
+
 if TYPE_CHECKING:
     from backend.util.prompt import CompressResult
 
@@ -467,8 +470,6 @@ async def stream_chat_completion(
     should_retry = False
 
     # Generate unique IDs for AI SDK protocol
-    import uuid as uuid_module
-
     message_id = str(uuid_module.uuid4())
     text_block_id = str(uuid_module.uuid4())
 
@@ -826,10 +827,6 @@ async def _manage_context_window(
     Returns:
         CompressResult with compacted messages and metadata
     """
-    import openai
-
-    from backend.util.prompt import compress_context
-
     # Convert messages to dict format
     messages_dict = []
     for msg in messages:
@@ -1140,8 +1137,6 @@ async def _yield_tool_call(
         KeyError: If expected tool call fields are missing
         TypeError: If tool call structure is invalid
     """
-    import uuid as uuid_module
-
     tool_name = tool_calls[yield_idx]["function"]["name"]
     tool_call_id = tool_calls[yield_idx]["id"]
 
@@ -1762,8 +1757,6 @@ async def _generate_llm_continuation_with_streaming(
     after a tool result is saved. Chunks are published to the stream registry
     so reconnecting clients can receive them.
     """
-    import uuid as uuid_module
-
     try:
         # Load fresh session from DB (bypass cache to get the updated tool result)
         await invalidate_session_cache(session_id)
@@ -1799,10 +1792,6 @@ async def _generate_llm_continuation_with_streaming(
             extra_body["session_id"] = session_id[:128]
 
         # Make streaming LLM call (no tools - just text response)
-        from typing import cast
-
-        from openai.types.chat import ChatCompletionMessageParam
-
         # Generate unique IDs for AI SDK protocol
         message_id = str(uuid_module.uuid4())
         text_block_id = str(uuid_module.uuid4())

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

@@ -3,6 +3,8 @@
 import logging
 from typing import Any
 
+from pydantic import BaseModel, field_validator
+
 from backend.api.features.chat.model import ChatSession
 
 from .agent_generator import (
@@ -28,6 +30,26 @@ from .models import (
 logger = logging.getLogger(__name__)
 
 
+class CreateAgentInput(BaseModel):
+    """Input parameters for the create_agent tool."""
+
+    description: str = ""
+    context: str = ""
+    save: bool = True
+    # Internal async processing params (passed by long-running tool handler)
+    _operation_id: str | None = None
+    _task_id: str | None = None
+
+    @field_validator("description", "context", mode="before")
+    @classmethod
+    def strip_strings(cls, v: Any) -> str:
+        """Strip whitespace from string fields."""
+        return v.strip() if isinstance(v, str) else (v if v is not None else "")
+
+    class Config:
+        extra = "allow"  # Allow _operation_id, _task_id from kwargs
+
+
 class CreateAgentTool(BaseTool):
     """Tool for creating agents from natural language descriptions."""
 
@@ -85,7 +107,7 @@ class CreateAgentTool(BaseTool):
         self,
         user_id: str | None,
         session: ChatSession,
-        **kwargs,
+        **kwargs: Any,
     ) -> ToolResponseBase:
         """Execute the create_agent tool.
 
@@ -94,16 +116,14 @@ class CreateAgentTool(BaseTool):
         2. Generate agent JSON (external service handles fixing and validation)
         3. Preview or save based on the save parameter
         """
-        description = kwargs.get("description", "").strip()
-        context = kwargs.get("context", "")
-        save = kwargs.get("save", True)
+        params = CreateAgentInput(**kwargs)
         session_id = session.session_id if session else None
 
-        # Extract async processing params (passed by long-running tool handler)
+        # Extract async processing params
         operation_id = kwargs.get("_operation_id")
         task_id = kwargs.get("_task_id")
 
-        if not description:
+        if not params.description:
             return ErrorResponse(
                 message="Please provide a description of what the agent should do.",
                 error="Missing description parameter",
@@ -115,7 +135,7 @@ class CreateAgentTool(BaseTool):
             try:
                 library_agents = await get_all_relevant_agents_for_generation(
                     user_id=user_id,
-                    search_query=description,
+                    search_query=params.description,
                     include_marketplace=True,
                 )
                 logger.debug(
@@ -126,7 +146,7 @@ class CreateAgentTool(BaseTool):
 
         try:
             decomposition_result = await decompose_goal(
-                description, context, library_agents
+                params.description, params.context, library_agents
             )
         except AgentGeneratorNotConfiguredError:
             return ErrorResponse(
@@ -142,7 +162,7 @@ class CreateAgentTool(BaseTool):
             return ErrorResponse(
                 message="Failed to analyze the goal. The agent generation service may be unavailable. Please try again.",
                 error="decomposition_failed",
-                details={"description": description[:100]},
+                details={"description": params.description[:100]},
                 session_id=session_id,
             )
 
@@ -158,7 +178,7 @@ class CreateAgentTool(BaseTool):
                 message=user_message,
                 error=f"decomposition_failed:{error_type}",
                 details={
-                    "description": description[:100],
+                    "description": params.description[:100],
                     "service_error": error_msg,
                     "error_type": error_type,
                 },
@@ -244,7 +264,7 @@ class CreateAgentTool(BaseTool):
             return ErrorResponse(
                 message="Failed to generate the agent. The agent generation service may be unavailable. Please try again.",
                 error="generation_failed",
-                details={"description": description[:100]},
+                details={"description": params.description[:100]},
                 session_id=session_id,
             )
 
@@ -266,7 +286,7 @@ class CreateAgentTool(BaseTool):
                 message=user_message,
                 error=f"generation_failed:{error_type}",
                 details={
-                    "description": description[:100],
+                    "description": params.description[:100],
                     "service_error": error_msg,
                     "error_type": error_type,
                 },
@@ -291,7 +311,7 @@ class CreateAgentTool(BaseTool):
         node_count = len(agent_json.get("nodes", []))
         link_count = len(agent_json.get("links", []))
 
-        if not save:
+        if not params.save:
             return AgentPreviewResponse(
                 message=(
                     f"I've generated an agent called '{agent_name}' with {node_count} blocks. "

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

@@ -3,6 +3,8 @@
 import logging
 from typing import Any
 
+from pydantic import BaseModel, field_validator
+
 from backend.api.features.chat.model import ChatSession
 from backend.api.features.store import db as store_db
 from backend.api.features.store.exceptions import AgentNotFoundError
@@ -27,6 +29,23 @@ from .models import (
 logger = logging.getLogger(__name__)
 
 
+class CustomizeAgentInput(BaseModel):
+    """Input parameters for the customize_agent tool."""
+
+    agent_id: str = ""
+    modifications: str = ""
+    context: str = ""
+    save: bool = True
+
+    @field_validator("agent_id", "modifications", "context", mode="before")
+    @classmethod
+    def strip_strings(cls, v: Any) -> str:
+        """Strip whitespace from string fields."""
+        if isinstance(v, str):
+            return v.strip()
+        return v if v is not None else ""
+
+
 class CustomizeAgentTool(BaseTool):
     """Tool for customizing marketplace/template agents using natural language."""
 
@@ -92,7 +111,7 @@ class CustomizeAgentTool(BaseTool):
         self,
         user_id: str | None,
         session: ChatSession,
-        **kwargs,
+        **kwargs: Any,
     ) -> ToolResponseBase:
         """Execute the customize_agent tool.
 
@@ -102,20 +121,17 @@ class CustomizeAgentTool(BaseTool):
         3. Call customize_template with the modification request
         4. Preview or save based on the save parameter
         """
-        agent_id = kwargs.get("agent_id", "").strip()
-        modifications = kwargs.get("modifications", "").strip()
-        context = kwargs.get("context", "")
-        save = kwargs.get("save", True)
+        params = CustomizeAgentInput(**kwargs)
         session_id = session.session_id if session else None
 
-        if not agent_id:
+        if not params.agent_id:
             return ErrorResponse(
                 message="Please provide the marketplace agent ID (e.g., 'creator/agent-name').",
                 error="missing_agent_id",
                 session_id=session_id,
             )
 
-        if not modifications:
+        if not params.modifications:
             return ErrorResponse(
                 message="Please describe how you want to customize this agent.",
                 error="missing_modifications",
@@ -123,11 +139,11 @@ class CustomizeAgentTool(BaseTool):
             )
 
         # Parse agent_id in format "creator/slug"
-        parts = [p.strip() for p in agent_id.split("/")]
+        parts = [p.strip() for p in params.agent_id.split("/")]
         if len(parts) != 2 or not parts[0] or not parts[1]:
             return ErrorResponse(
                 message=(
-                    f"Invalid agent ID format: '{agent_id}'. "
+                    f"Invalid agent ID format: '{params.agent_id}'. "
                     "Expected format is 'creator/agent-name' "
                     "(e.g., 'autogpt/newsletter-writer')."
                 ),
@@ -145,14 +161,14 @@ class CustomizeAgentTool(BaseTool):
         except AgentNotFoundError:
             return ErrorResponse(
                 message=(
-                    f"Could not find marketplace agent '{agent_id}'. "
+                    f"Could not find marketplace agent '{params.agent_id}'. "
                     "Please check the agent ID and try again."
                 ),
                 error="agent_not_found",
                 session_id=session_id,
             )
         except Exception as e:
-            logger.error(f"Error fetching marketplace agent {agent_id}: {e}")
+            logger.error(f"Error fetching marketplace agent {params.agent_id}: {e}")
             return ErrorResponse(
                 message="Failed to fetch the marketplace agent. Please try again.",
                 error="fetch_error",
@@ -162,7 +178,7 @@ class CustomizeAgentTool(BaseTool):
         if not agent_details.store_listing_version_id:
             return ErrorResponse(
                 message=(
-                    f"The agent '{agent_id}' does not have an available version. "
+                    f"The agent '{params.agent_id}' does not have an available version. "
                     "Please try a different agent."
                 ),
                 error="no_version_available",
@@ -174,7 +190,7 @@ class CustomizeAgentTool(BaseTool):
             graph = await store_db.get_agent(agent_details.store_listing_version_id)
             template_agent = graph_to_json(graph)
         except Exception as e:
-            logger.error(f"Error fetching agent graph for {agent_id}: {e}")
+            logger.error(f"Error fetching agent graph for {params.agent_id}: {e}")
             return ErrorResponse(
                 message="Failed to fetch the agent configuration. Please try again.",
                 error="graph_fetch_error",
@@ -185,8 +201,8 @@ class CustomizeAgentTool(BaseTool):
         try:
             result = await customize_template(
                 template_agent=template_agent,
-                modification_request=modifications,
-                context=context,
+                modification_request=params.modifications,
+                context=params.context,
             )
         except AgentGeneratorNotConfiguredError:
             return ErrorResponse(
@@ -198,7 +214,7 @@ class CustomizeAgentTool(BaseTool):
                 session_id=session_id,
             )
         except Exception as e:
-            logger.error(f"Error calling customize_template for {agent_id}: {e}")
+            logger.error(f"Error calling customize_template for {params.agent_id}: {e}")
             return ErrorResponse(
                 message=(
                     "Failed to customize the agent due to a service error. "
@@ -219,55 +235,25 @@ class CustomizeAgentTool(BaseTool):
                 session_id=session_id,
             )
 
-        # Handle error response
-        if isinstance(result, dict) and result.get("type") == "error":
-            error_msg = result.get("error", "Unknown error")
-            error_type = result.get("error_type", "unknown")
-            user_message = get_user_message_for_error(
-                error_type,
-                operation="customize the agent",
-                llm_parse_message=(
-                    "The AI had trouble customizing the agent. "
-                    "Please try again or simplify your request."
-                ),
-                validation_message=(
-                    "The customized agent failed validation. "
-                    "Please try rephrasing your request."
-                ),
-                error_details=error_msg,
-            )
-            return ErrorResponse(
-                message=user_message,
-                error=f"customization_failed:{error_type}",
-                session_id=session_id,
-            )
+        # Handle response using match/case for cleaner pattern matching
+        return await self._handle_customization_result(
+            result=result,
+            params=params,
+            agent_details=agent_details,
+            user_id=user_id,
+            session_id=session_id,
+        )
 
-        # Handle clarifying questions
-        if isinstance(result, dict) and result.get("type") == "clarifying_questions":
-            questions = result.get("questions") or []
-            if not isinstance(questions, list):
-                logger.error(
-                    f"Unexpected clarifying questions format: {type(questions)}"
-                )
-                questions = []
-            return ClarificationNeededResponse(
-                message=(
-                    "I need some more information to customize this agent. "
-                    "Please answer the following questions:"
-                ),
-                questions=[
-                    ClarifyingQuestion(
-                        question=q.get("question", ""),
-                        keyword=q.get("keyword", ""),
-                        example=q.get("example"),
-                    )
-                    for q in questions
-                    if isinstance(q, dict)
-                ],
-                session_id=session_id,
-            )
-
-        # Result should be the customized agent JSON
+    async def _handle_customization_result(
+        self,
+        result: dict[str, Any],
+        params: CustomizeAgentInput,
+        agent_details: Any,
+        user_id: str | None,
+        session_id: str | None,
+    ) -> ToolResponseBase:
+        """Handle the result from customize_template using pattern matching."""
+        # Ensure result is a dict
         if not isinstance(result, dict):
             logger.error(f"Unexpected customize_template response type: {type(result)}")
             return ErrorResponse(
@@ -276,8 +262,77 @@ class CustomizeAgentTool(BaseTool):
                 session_id=session_id,
             )
 
-        customized_agent = result
+        result_type = result.get("type")
 
+        match result_type:
+            case "error":
+                error_msg = result.get("error", "Unknown error")
+                error_type = result.get("error_type", "unknown")
+                user_message = get_user_message_for_error(
+                    error_type,
+                    operation="customize the agent",
+                    llm_parse_message=(
+                        "The AI had trouble customizing the agent. "
+                        "Please try again or simplify your request."
+                    ),
+                    validation_message=(
+                        "The customized agent failed validation. "
+                        "Please try rephrasing your request."
+                    ),
+                    error_details=error_msg,
+                )
+                return ErrorResponse(
+                    message=user_message,
+                    error=f"customization_failed:{error_type}",
+                    session_id=session_id,
+                )
+
+            case "clarifying_questions":
+                questions_data = result.get("questions") or []
+                if not isinstance(questions_data, list):
+                    logger.error(
+                        f"Unexpected clarifying questions format: {type(questions_data)}"
+                    )
+                    questions_data = []
+
+                questions = [
+                    ClarifyingQuestion(
+                        question=q.get("question", "") if isinstance(q, dict) else "",
+                        keyword=q.get("keyword", "") if isinstance(q, dict) else "",
+                        example=q.get("example") if isinstance(q, dict) else None,
+                    )
+                    for q in questions_data
+                    if isinstance(q, dict)
+                ]
+
+                return ClarificationNeededResponse(
+                    message=(
+                        "I need some more information to customize this agent. "
+                        "Please answer the following questions:"
+                    ),
+                    questions=questions,
+                    session_id=session_id,
+                )
+
+            case _:
+                # Default case: result is the customized agent JSON
+                return await self._save_or_preview_agent(
+                    customized_agent=result,
+                    params=params,
+                    agent_details=agent_details,
+                    user_id=user_id,
+                    session_id=session_id,
+                )
+
+    async def _save_or_preview_agent(
+        self,
+        customized_agent: dict[str, Any],
+        params: CustomizeAgentInput,
+        agent_details: Any,
+        user_id: str | None,
+        session_id: str | None,
+    ) -> ToolResponseBase:
+        """Save or preview the customized agent based on params.save."""
         agent_name = customized_agent.get(
             "name", f"Customized {agent_details.agent_name}"
         )
@@ -287,7 +342,7 @@ class CustomizeAgentTool(BaseTool):
         node_count = len(nodes) if isinstance(nodes, list) else 0
         link_count = len(links) if isinstance(links, list) else 0
 
-        if not save:
+        if not params.save:
             return AgentPreviewResponse(
                 message=(
                     f"I've customized the agent '{agent_details.agent_name}'. "

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

@@ -3,6 +3,8 @@
 import logging
 from typing import Any
 
+from pydantic import BaseModel, ConfigDict, field_validator
+
 from backend.api.features.chat.model import ChatSession
 
 from .agent_generator import (
@@ -27,6 +29,20 @@ from .models import (
 logger = logging.getLogger(__name__)
 
 
+class EditAgentInput(BaseModel):
+    model_config = ConfigDict(extra="allow")
+
+    agent_id: str = ""
+    changes: str = ""
+    context: str = ""
+    save: bool = True
+
+    @field_validator("agent_id", "changes", "context", mode="before")
+    @classmethod
+    def strip_strings(cls, v: Any) -> str:
+        return v.strip() if isinstance(v, str) else (v if v is not None else "")
+
+
 class EditAgentTool(BaseTool):
     """Tool for editing existing agents using natural language."""
 
@@ -90,7 +106,7 @@ class EditAgentTool(BaseTool):
         self,
         user_id: str | None,
         session: ChatSession,
-        **kwargs,
+        **kwargs: Any,
     ) -> ToolResponseBase:
         """Execute the edit_agent tool.
 
@@ -99,35 +115,32 @@ class EditAgentTool(BaseTool):
         2. Generate updated agent (external service handles fixing and validation)
         3. Preview or save based on the save parameter
         """
-        agent_id = kwargs.get("agent_id", "").strip()
-        changes = kwargs.get("changes", "").strip()
-        context = kwargs.get("context", "")
-        save = kwargs.get("save", True)
+        params = EditAgentInput(**kwargs)
         session_id = session.session_id if session else None
 
         # Extract async processing params (passed by long-running tool handler)
         operation_id = kwargs.get("_operation_id")
         task_id = kwargs.get("_task_id")
 
-        if not agent_id:
+        if not params.agent_id:
             return ErrorResponse(
                 message="Please provide the agent ID to edit.",
                 error="Missing agent_id parameter",
                 session_id=session_id,
             )
 
-        if not changes:
+        if not params.changes:
             return ErrorResponse(
                 message="Please describe what changes you want to make.",
                 error="Missing changes parameter",
                 session_id=session_id,
             )
 
-        current_agent = await get_agent_as_json(agent_id, user_id)
+        current_agent = await get_agent_as_json(params.agent_id, user_id)
 
         if current_agent is None:
             return ErrorResponse(
-                message=f"Could not find agent with ID '{agent_id}' in your library.",
+                message=f"Could not find agent '{params.agent_id}' in your library.",
                 error="agent_not_found",
                 session_id=session_id,
             )
@@ -138,7 +151,7 @@ class EditAgentTool(BaseTool):
                 graph_id = current_agent.get("id")
                 library_agents = await get_all_relevant_agents_for_generation(
                     user_id=user_id,
-                    search_query=changes,
+                    search_query=params.changes,
                     exclude_graph_id=graph_id,
                     include_marketplace=True,
                 )
@@ -148,9 +161,11 @@ class EditAgentTool(BaseTool):
             except Exception as e:
                 logger.warning(f"Failed to fetch library agents: {e}")
 
-        update_request = changes
-        if context:
-            update_request = f"{changes}\n\nAdditional context:\n{context}"
+        update_request = params.changes
+        if params.context:
+            update_request = (
+                f"{params.changes}\n\nAdditional context:\n{params.context}"
+            )
 
         try:
             result = await generate_agent_patch(
@@ -174,7 +189,7 @@ class EditAgentTool(BaseTool):
             return ErrorResponse(
                 message="Failed to generate changes. The agent generation service may be unavailable or timed out. Please try again.",
                 error="update_generation_failed",
-                details={"agent_id": agent_id, "changes": changes[:100]},
+                details={"agent_id": params.agent_id, "changes": params.changes[:100]},
                 session_id=session_id,
             )
 
@@ -206,8 +221,8 @@ class EditAgentTool(BaseTool):
                 message=user_message,
                 error=f"update_generation_failed:{error_type}",
                 details={
-                    "agent_id": agent_id,
-                    "changes": changes[:100],
+                    "agent_id": params.agent_id,
+                    "changes": params.changes[:100],
                     "service_error": error_msg,
                     "error_type": error_type,
                 },
@@ -239,7 +254,7 @@ class EditAgentTool(BaseTool):
         node_count = len(updated_agent.get("nodes", []))
         link_count = len(updated_agent.get("links", []))
 
-        if not save:
+        if not params.save:
             return AgentPreviewResponse(
                 message=(
                     f"I've updated the agent. "

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

@@ -2,6 +2,8 @@
 
 from typing import Any
 
+from pydantic import BaseModel, field_validator
+
 from backend.api.features.chat.model import ChatSession
 
 from .agent_search import search_agents
@@ -9,6 +11,18 @@ from .base import BaseTool
 from .models import ToolResponseBase
 
 
+class FindAgentInput(BaseModel):
+    """Input parameters for the find_agent tool."""
+
+    query: str = ""
+
+    @field_validator("query", mode="before")
+    @classmethod
+    def strip_string(cls, v: Any) -> str:
+        """Strip whitespace from query."""
+        return v.strip() if isinstance(v, str) else (v if v is not None else "")
+
+
 class FindAgentTool(BaseTool):
     """Tool for discovering agents from the marketplace."""
 
@@ -36,10 +50,11 @@ class FindAgentTool(BaseTool):
         }
 
     async def _execute(
-        self, user_id: str | None, session: ChatSession, **kwargs
+        self, user_id: str | None, session: ChatSession, **kwargs: Any
     ) -> ToolResponseBase:
+        params = FindAgentInput(**kwargs)
         return await search_agents(
-            query=kwargs.get("query", "").strip(),
+            query=params.query,
             source="marketplace",
             session_id=session.session_id,
             user_id=user_id,

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

@@ -2,6 +2,7 @@ import logging
 from typing import Any
 
 from prisma.enums import ContentType
+from pydantic import BaseModel, field_validator
 
 from backend.api.features.chat.model import ChatSession
 from backend.api.features.chat.tools.base import BaseTool, ToolResponseBase
@@ -18,6 +19,18 @@ from backend.data.block import get_block
 logger = logging.getLogger(__name__)
 
 
+class FindBlockInput(BaseModel):
+    """Input parameters for the find_block tool."""
+
+    query: str = ""
+
+    @field_validator("query", mode="before")
+    @classmethod
+    def strip_string(cls, v: Any) -> str:
+        """Strip whitespace from query."""
+        return v.strip() if isinstance(v, str) else (v if v is not None else "")
+
+
 class FindBlockTool(BaseTool):
     """Tool for searching available blocks."""
 
@@ -59,24 +72,24 @@ class FindBlockTool(BaseTool):
         self,
         user_id: str | None,
         session: ChatSession,
-        **kwargs,
+        **kwargs: Any,
     ) -> ToolResponseBase:
         """Search for blocks matching the query.
 
         Args:
             user_id: User ID (required)
             session: Chat session
-            query: Search query
+            **kwargs: Tool parameters
 
         Returns:
             BlockListResponse: List of matching blocks
             NoResultsResponse: No blocks found
             ErrorResponse: Error message
         """
-        query = kwargs.get("query", "").strip()
+        params = FindBlockInput(**kwargs)
         session_id = session.session_id
 
-        if not query:
+        if not params.query:
             return ErrorResponse(
                 message="Please provide a search query",
                 session_id=session_id,
@@ -85,7 +98,7 @@ class FindBlockTool(BaseTool):
         try:
             # Search for blocks using hybrid search
             results, total = await unified_hybrid_search(
-                query=query,
+                query=params.query,
                 content_types=[ContentType.BLOCK],
                 page=1,
                 page_size=10,
@@ -93,7 +106,7 @@ class FindBlockTool(BaseTool):
 
             if not results:
                 return NoResultsResponse(
-                    message=f"No blocks found for '{query}'",
+                    message=f"No blocks found for '{params.query}'",
                     suggestions=[
                         "Try broader keywords like 'email', 'http', 'text', 'ai'",
                         "Check spelling of technical terms",
@@ -165,7 +178,7 @@ class FindBlockTool(BaseTool):
 
             if not blocks:
                 return NoResultsResponse(
-                    message=f"No blocks found for '{query}'",
+                    message=f"No blocks found for '{params.query}'",
                     suggestions=[
                         "Try broader keywords like 'email', 'http', 'text', 'ai'",
                     ],
@@ -174,13 +187,13 @@ class FindBlockTool(BaseTool):
 
             return BlockListResponse(
                 message=(
-                    f"Found {len(blocks)} block(s) matching '{query}'. "
+                    f"Found {len(blocks)} block(s) matching '{params.query}'. "
                     "To execute a block, use run_block with the block's 'id' field "
                     "and provide 'input_data' matching the block's input_schema."
                 ),
                 blocks=blocks,
                 count=len(blocks),
-                query=query,
+                query=params.query,
                 session_id=session_id,
             )
 

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

@@ -2,6 +2,8 @@
 
 from typing import Any
 
+from pydantic import BaseModel, field_validator
+
 from backend.api.features.chat.model import ChatSession
 
 from .agent_search import search_agents
@@ -9,6 +11,15 @@ from .base import BaseTool
 from .models import ToolResponseBase
 
 
+class FindLibraryAgentInput(BaseModel):
+    query: str = ""
+
+    @field_validator("query", mode="before")
+    @classmethod
+    def strip_string(cls, v: Any) -> str:
+        return v.strip() if isinstance(v, str) else (v if v is not None else "")
+
+
 class FindLibraryAgentTool(BaseTool):
     """Tool for searching agents in the user's library."""
 
@@ -42,10 +53,11 @@ class FindLibraryAgentTool(BaseTool):
         return True
 
     async def _execute(
-        self, user_id: str | None, session: ChatSession, **kwargs
+        self, user_id: str | None, session: ChatSession, **kwargs: Any
     ) -> ToolResponseBase:
+        params = FindLibraryAgentInput(**kwargs)
         return await search_agents(
-            query=kwargs.get("query", "").strip(),
+            query=params.query,
             source="library",
             session_id=session.session_id,
             user_id=user_id,

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

@@ -4,6 +4,8 @@ import logging
 from pathlib import Path
 from typing import Any
 
+from pydantic import BaseModel, field_validator
+
 from backend.api.features.chat.model import ChatSession
 from backend.api.features.chat.tools.base import BaseTool
 from backend.api.features.chat.tools.models import (
@@ -18,6 +20,18 @@ logger = logging.getLogger(__name__)
 DOCS_BASE_URL = "https://docs.agpt.co"
 
 
+class GetDocPageInput(BaseModel):
+    """Input parameters for the get_doc_page tool."""
+
+    path: str = ""
+
+    @field_validator("path", mode="before")
+    @classmethod
+    def strip_string(cls, v: Any) -> str:
+        """Strip whitespace from path."""
+        return v.strip() if isinstance(v, str) else (v if v is not None else "")
+
+
 class GetDocPageTool(BaseTool):
     """Tool for fetching full content of a documentation page."""
 
@@ -75,23 +89,23 @@ class GetDocPageTool(BaseTool):
         self,
         user_id: str | None,
         session: ChatSession,
-        **kwargs,
+        **kwargs: Any,
     ) -> ToolResponseBase:
         """Fetch full content of a documentation page.
 
         Args:
             user_id: User ID (not required for docs)
             session: Chat session
-            path: Path to the documentation file
+            **kwargs: Tool parameters
 
         Returns:
             DocPageResponse: Full document content
             ErrorResponse: Error message
         """
-        path = kwargs.get("path", "").strip()
+        params = GetDocPageInput(**kwargs)
         session_id = session.session_id if session else None
 
-        if not path:
+        if not params.path:
             return ErrorResponse(
                 message="Please provide a documentation path.",
                 error="Missing path parameter",
@@ -99,7 +113,7 @@ class GetDocPageTool(BaseTool):
             )
 
         # Sanitize path to prevent directory traversal
-        if ".." in path or path.startswith("/"):
+        if ".." in params.path or params.path.startswith("/"):
             return ErrorResponse(
                 message="Invalid documentation path.",
                 error="invalid_path",
@@ -107,11 +121,11 @@ class GetDocPageTool(BaseTool):
             )
 
         docs_root = self._get_docs_root()
-        full_path = docs_root / path
+        full_path = docs_root / params.path
 
         if not full_path.exists():
             return ErrorResponse(
-                message=f"Documentation page not found: {path}",
+                message=f"Documentation page not found: {params.path}",
                 error="not_found",
                 session_id=session_id,
             )
@@ -128,19 +142,19 @@ class GetDocPageTool(BaseTool):
 
         try:
             content = full_path.read_text(encoding="utf-8")
-            title = self._extract_title(content, path)
+            title = self._extract_title(content, params.path)
 
             return DocPageResponse(
                 message=f"Retrieved documentation page: {title}",
                 title=title,
-                path=path,
+                path=params.path,
                 content=content,
-                doc_url=self._make_doc_url(path),
+                doc_url=self._make_doc_url(params.path),
                 session_id=session_id,
             )
 
         except Exception as e:
-            logger.error(f"Failed to read documentation page {path}: {e}")
+            logger.error(f"Failed to read documentation page {params.path}: {e}")
             return ErrorResponse(
                 message=f"Failed to read documentation page: {str(e)}",
                 error="read_failed",

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

@@ -5,6 +5,7 @@ import uuid
 from collections import defaultdict
 from typing import Any
 
+from pydantic import BaseModel, field_validator
 from pydantic_core import PydanticUndefined
 
 from backend.api.features.chat.model import ChatSession
@@ -29,6 +30,25 @@ from .utils import build_missing_credentials_from_field_info
 logger = logging.getLogger(__name__)
 
 
+class RunBlockInput(BaseModel):
+    """Input parameters for the run_block tool."""
+
+    block_id: str = ""
+    input_data: dict[str, Any] = {}
+
+    @field_validator("block_id", mode="before")
+    @classmethod
+    def strip_block_id(cls, v: Any) -> str:
+        """Strip whitespace from block_id."""
+        return v.strip() if isinstance(v, str) else (v if v is not None else "")
+
+    @field_validator("input_data", mode="before")
+    @classmethod
+    def ensure_dict(cls, v: Any) -> dict[str, Any]:
+        """Ensure input_data is a dict."""
+        return v if isinstance(v, dict) else {}
+
+
 class RunBlockTool(BaseTool):
     """Tool for executing a block and returning its outputs."""
 
@@ -162,37 +182,29 @@ class RunBlockTool(BaseTool):
         self,
         user_id: str | None,
         session: ChatSession,
-        **kwargs,
+        **kwargs: Any,
     ) -> ToolResponseBase:
         """Execute a block with the given input data.
 
         Args:
             user_id: User ID (required)
             session: Chat session
-            block_id: Block UUID to execute
-            input_data: Input values for the block
+            **kwargs: Tool parameters
 
         Returns:
             BlockOutputResponse: Block execution outputs
             SetupRequirementsResponse: Missing credentials
             ErrorResponse: Error message
         """
-        block_id = kwargs.get("block_id", "").strip()
-        input_data = kwargs.get("input_data", {})
+        params = RunBlockInput(**kwargs)
         session_id = session.session_id
 
-        if not block_id:
+        if not params.block_id:
             return ErrorResponse(
                 message="Please provide a block_id",
                 session_id=session_id,
             )
 
-        if not isinstance(input_data, dict):
-            return ErrorResponse(
-                message="input_data must be an object",
-                session_id=session_id,
-            )
-
         if not user_id:
             return ErrorResponse(
                 message="Authentication required",
@@ -200,23 +212,25 @@ class RunBlockTool(BaseTool):
             )
 
         # Get the block
-        block = get_block(block_id)
+        block = get_block(params.block_id)
         if not block:
             return ErrorResponse(
-                message=f"Block '{block_id}' not found",
+                message=f"Block '{params.block_id}' not found",
                 session_id=session_id,
             )
         if block.disabled:
             return ErrorResponse(
-                message=f"Block '{block_id}' is disabled",
+                message=f"Block '{params.block_id}' is disabled",
                 session_id=session_id,
             )
 
-        logger.info(f"Executing block {block.name} ({block_id}) for user {user_id}")
+        logger.info(
+            f"Executing block {block.name} ({params.block_id}) for user {user_id}"
+        )
 
         creds_manager = IntegrationCredentialsManager()
         matched_credentials, missing_credentials = await self._check_block_credentials(
-            user_id, block, input_data
+            user_id, block, params.input_data
         )
 
         if missing_credentials:
@@ -234,7 +248,7 @@ class RunBlockTool(BaseTool):
                 ),
                 session_id=session_id,
                 setup_info=SetupInfo(
-                    agent_id=block_id,
+                    agent_id=params.block_id,
                     agent_name=block.name,
                     user_readiness=UserReadiness(
                         has_all_credentials=False,
@@ -263,7 +277,7 @@ class RunBlockTool(BaseTool):
             # - node_exec_id = unique per block execution
             synthetic_graph_id = f"copilot-session-{session.session_id}"
             synthetic_graph_exec_id = f"copilot-session-{session.session_id}"
-            synthetic_node_id = f"copilot-node-{block_id}"
+            synthetic_node_id = f"copilot-node-{params.block_id}"
             synthetic_node_exec_id = (
                 f"copilot-{session.session_id}-{uuid.uuid4().hex[:8]}"
             )
@@ -298,8 +312,8 @@ class RunBlockTool(BaseTool):
 
             for field_name, cred_meta in matched_credentials.items():
                 # Inject metadata into input_data (for validation)
-                if field_name not in input_data:
-                    input_data[field_name] = cred_meta.model_dump()
+                if field_name not in params.input_data:
+                    params.input_data[field_name] = cred_meta.model_dump()
 
                 # Fetch actual credentials and pass as kwargs (for execution)
                 actual_credentials = await creds_manager.get(
@@ -316,14 +330,14 @@ class RunBlockTool(BaseTool):
             # Execute the block and collect outputs
             outputs: dict[str, list[Any]] = defaultdict(list)
             async for output_name, output_data in block.execute(
-                input_data,
+                params.input_data,
                 **exec_kwargs,
             ):
                 outputs[output_name].append(output_data)
 
             return BlockOutputResponse(
                 message=f"Block '{block.name}' executed successfully",
-                block_id=block_id,
+                block_id=params.block_id,
                 block_name=block.name,
                 outputs=dict(outputs),
                 success=True,

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

@@ -4,6 +4,7 @@ import logging
 from typing import Any
 
 from prisma.enums import ContentType
+from pydantic import BaseModel, field_validator
 
 from backend.api.features.chat.model import ChatSession
 from backend.api.features.chat.tools.base import BaseTool
@@ -28,6 +29,18 @@ MAX_RESULTS = 5
 SNIPPET_LENGTH = 200
 
 
+class SearchDocsInput(BaseModel):
+    """Input parameters for the search_docs tool."""
+
+    query: str = ""
+
+    @field_validator("query", mode="before")
+    @classmethod
+    def strip_string(cls, v: Any) -> str:
+        """Strip whitespace from query."""
+        return v.strip() if isinstance(v, str) else (v if v is not None else "")
+
+
 class SearchDocsTool(BaseTool):
     """Tool for searching AutoGPT platform documentation."""
 
@@ -91,24 +104,24 @@ class SearchDocsTool(BaseTool):
         self,
         user_id: str | None,
         session: ChatSession,
-        **kwargs,
+        **kwargs: Any,
     ) -> ToolResponseBase:
         """Search documentation and return relevant sections.
 
         Args:
             user_id: User ID (not required for docs)
             session: Chat session
-            query: Search query
+            **kwargs: Tool parameters
 
         Returns:
             DocSearchResultsResponse: List of matching documentation sections
             NoResultsResponse: No results found
             ErrorResponse: Error message
         """
-        query = kwargs.get("query", "").strip()
+        params = SearchDocsInput(**kwargs)
         session_id = session.session_id if session else None
 
-        if not query:
+        if not params.query:
             return ErrorResponse(
                 message="Please provide a search query.",
                 error="Missing query parameter",
@@ -118,7 +131,7 @@ class SearchDocsTool(BaseTool):
         try:
             # Search using hybrid search for DOCUMENTATION content type only
             results, total = await unified_hybrid_search(
-                query=query,
+                query=params.query,
                 content_types=[ContentType.DOCUMENTATION],
                 page=1,
                 page_size=MAX_RESULTS * 2,  # Fetch extra for deduplication
@@ -127,7 +140,7 @@ class SearchDocsTool(BaseTool):
 
             if not results:
                 return NoResultsResponse(
-                    message=f"No documentation found for '{query}'.",
+                    message=f"No documentation found for '{params.query}'.",
                     suggestions=[
                         "Try different keywords",
                         "Use more general terms",
@@ -162,7 +175,7 @@ class SearchDocsTool(BaseTool):
 
             if not deduplicated:
                 return NoResultsResponse(
-                    message=f"No documentation found for '{query}'.",
+                    message=f"No documentation found for '{params.query}'.",
                     suggestions=[
                         "Try different keywords",
                         "Use more general terms",
@@ -195,7 +208,7 @@ class SearchDocsTool(BaseTool):
                 message=f"Found {len(doc_results)} relevant documentation sections.",
                 results=doc_results,
                 count=len(doc_results),
-                query=query,
+                query=params.query,
                 session_id=session_id,
             )
 

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

@@ -2,9 +2,9 @@
 
 import base64
 import logging
-from typing import Any, Optional
+from typing import Any
 
-from pydantic import BaseModel
+from pydantic import BaseModel, field_validator
 
 from backend.api.features.chat.model import ChatSession
 from backend.data.workspace import get_or_create_workspace
@@ -78,6 +78,65 @@ class WorkspaceDeleteResponse(ToolResponseBase):
     success: bool
 
 
+# Input models for workspace tools
+class ListWorkspaceFilesInput(BaseModel):
+    """Input parameters for list_workspace_files tool."""
+
+    path_prefix: str | None = None
+    limit: int = 50
+    include_all_sessions: bool = False
+
+    @field_validator("path_prefix", mode="before")
+    @classmethod
+    def strip_path(cls, v: Any) -> str | None:
+        return v.strip() if isinstance(v, str) else None
+
+
+class ReadWorkspaceFileInput(BaseModel):
+    """Input parameters for read_workspace_file tool."""
+
+    file_id: str | None = None
+    path: str | None = None
+    force_download_url: bool = False
+
+    @field_validator("file_id", "path", mode="before")
+    @classmethod
+    def strip_strings(cls, v: Any) -> str | None:
+        return v.strip() if isinstance(v, str) else None
+
+
+class WriteWorkspaceFileInput(BaseModel):
+    """Input parameters for write_workspace_file tool."""
+
+    filename: str = ""
+    content_base64: str = ""
+    path: str | None = None
+    mime_type: str | None = None
+    overwrite: bool = False
+
+    @field_validator("filename", "content_base64", mode="before")
+    @classmethod
+    def strip_required(cls, v: Any) -> str:
+        return v.strip() if isinstance(v, str) else (v if v is not None else "")
+
+    @field_validator("path", "mime_type", mode="before")
+    @classmethod
+    def strip_optional(cls, v: Any) -> str | None:
+        return v.strip() if isinstance(v, str) else None
+
+
+class DeleteWorkspaceFileInput(BaseModel):
+    """Input parameters for delete_workspace_file tool."""
+
+    file_id: str | None = None
+    path: str | None = None
+
+    @field_validator("file_id", "path", mode="before")
+    @classmethod
+    def strip_strings(cls, v: Any) -> str | None:
+        return v.strip() if isinstance(v, str) else None
+
+
 class ListWorkspaceFilesTool(BaseTool):
     """Tool for listing files in user's workspace."""
 
@@ -131,8 +190,9 @@ class ListWorkspaceFilesTool(BaseTool):
         self,
         user_id: str | None,
         session: ChatSession,
-        **kwargs,
+        **kwargs: Any,
     ) -> ToolResponseBase:
+        params = ListWorkspaceFilesInput(**kwargs)
         session_id = session.session_id
 
         if not user_id:
@@ -141,9 +201,7 @@ class ListWorkspaceFilesTool(BaseTool):
                 session_id=session_id,
             )
 
-        path_prefix: Optional[str] = kwargs.get("path_prefix")
-        limit = min(kwargs.get("limit", 50), 100)
-        include_all_sessions: bool = kwargs.get("include_all_sessions", False)
+        limit = min(params.limit, 100)
 
         try:
             workspace = await get_or_create_workspace(user_id)
@@ -151,13 +209,13 @@ class ListWorkspaceFilesTool(BaseTool):
             manager = WorkspaceManager(user_id, workspace.id, session_id)
 
             files = await manager.list_files(
-                path=path_prefix,
+                path=params.path_prefix,
                 limit=limit,
-                include_all_sessions=include_all_sessions,
+                include_all_sessions=params.include_all_sessions,
             )
             total = await manager.get_file_count(
-                path=path_prefix,
-                include_all_sessions=include_all_sessions,
+                path=params.path_prefix,
+                include_all_sessions=params.include_all_sessions,
             )
 
             file_infos = [
@@ -171,7 +229,9 @@ class ListWorkspaceFilesTool(BaseTool):
                 for f in files
             ]
 
-            scope_msg = "all sessions" if include_all_sessions else "current session"
+            scope_msg = (
+                "all sessions" if params.include_all_sessions else "current session"
+            )
             return WorkspaceFileListResponse(
                 files=file_infos,
                 total_count=total,
@@ -259,8 +319,9 @@ class ReadWorkspaceFileTool(BaseTool):
         self,
         user_id: str | None,
         session: ChatSession,
-        **kwargs,
+        **kwargs: Any,
     ) -> ToolResponseBase:
+        params = ReadWorkspaceFileInput(**kwargs)
         session_id = session.session_id
 
         if not user_id:
@@ -269,11 +330,7 @@ class ReadWorkspaceFileTool(BaseTool):
                 session_id=session_id,
             )
 
-        file_id: Optional[str] = kwargs.get("file_id")
-        path: Optional[str] = kwargs.get("path")
-        force_download_url: bool = kwargs.get("force_download_url", False)
-
-        if not file_id and not path:
+        if not params.file_id and not params.path:
             return ErrorResponse(
                 message="Please provide either file_id or path",
                 session_id=session_id,
@@ -285,21 +342,21 @@ class ReadWorkspaceFileTool(BaseTool):
             manager = WorkspaceManager(user_id, workspace.id, session_id)
 
             # Get file info
-            if file_id:
-                file_info = await manager.get_file_info(file_id)
+            if params.file_id:
+                file_info = await manager.get_file_info(params.file_id)
                 if file_info is None:
                     return ErrorResponse(
-                        message=f"File not found: {file_id}",
+                        message=f"File not found: {params.file_id}",
                         session_id=session_id,
                     )
-                target_file_id = file_id
+                target_file_id = params.file_id
             else:
                 # path is guaranteed to be non-None here due to the check above
-                assert path is not None
-                file_info = await manager.get_file_info_by_path(path)
+                assert params.path is not None
+                file_info = await manager.get_file_info_by_path(params.path)
                 if file_info is None:
                     return ErrorResponse(
-                        message=f"File not found at path: {path}",
+                        message=f"File not found at path: {params.path}",
                         session_id=session_id,
                     )
                 target_file_id = file_info.id
@@ -309,7 +366,7 @@ class ReadWorkspaceFileTool(BaseTool):
             is_text_file = self._is_text_mime_type(file_info.mimeType)
 
             # Return inline content for small text files (unless force_download_url)
-            if is_small_file and is_text_file and not force_download_url:
+            if is_small_file and is_text_file and not params.force_download_url:
                 content = await manager.read_file_by_id(target_file_id)
                 content_b64 = base64.b64encode(content).decode("utf-8")
 
@@ -429,8 +486,9 @@ class WriteWorkspaceFileTool(BaseTool):
         self,
         user_id: str | None,
         session: ChatSession,
-        **kwargs,
+        **kwargs: Any,
     ) -> ToolResponseBase:
+        params = WriteWorkspaceFileInput(**kwargs)
         session_id = session.session_id
 
         if not user_id:
@@ -439,19 +497,13 @@ class WriteWorkspaceFileTool(BaseTool):
                 session_id=session_id,
             )
 
-        filename: str = kwargs.get("filename", "")
-        content_b64: str = kwargs.get("content_base64", "")
-        path: Optional[str] = kwargs.get("path")
-        mime_type: Optional[str] = kwargs.get("mime_type")
-        overwrite: bool = kwargs.get("overwrite", False)
-
-        if not filename:
+        if not params.filename:
             return ErrorResponse(
                 message="Please provide a filename",
                 session_id=session_id,
             )
 
-        if not content_b64:
+        if not params.content_base64:
             return ErrorResponse(
                 message="Please provide content_base64",
                 session_id=session_id,
@@ -459,7 +511,7 @@ class WriteWorkspaceFileTool(BaseTool):
 
         # Decode content
         try:
-            content = base64.b64decode(content_b64)
+            content = base64.b64decode(params.content_base64)
         except Exception:
             return ErrorResponse(
                 message="Invalid base64-encoded content",
@@ -476,7 +528,7 @@ class WriteWorkspaceFileTool(BaseTool):
 
         try:
             # Virus scan
-            await scan_content_safe(content, filename=filename)
+            await scan_content_safe(content, filename=params.filename)
 
             workspace = await get_or_create_workspace(user_id)
             # Pass session_id for session-scoped file access
@@ -484,10 +536,10 @@ class WriteWorkspaceFileTool(BaseTool):
 
             file_record = await manager.write_file(
                 content=content,
-                filename=filename,
-                path=path,
-                mime_type=mime_type,
-                overwrite=overwrite,
+                filename=params.filename,
+                path=params.path,
+                mime_type=params.mime_type,
+                overwrite=params.overwrite,
             )
 
             return WorkspaceWriteResponse(
@@ -557,8 +609,9 @@ class DeleteWorkspaceFileTool(BaseTool):
         self,
         user_id: str | None,
         session: ChatSession,
-        **kwargs,
+        **kwargs: Any,
     ) -> ToolResponseBase:
+        params = DeleteWorkspaceFileInput(**kwargs)
         session_id = session.session_id
 
         if not user_id:
@@ -567,10 +620,7 @@ class DeleteWorkspaceFileTool(BaseTool):
                 session_id=session_id,
             )
 
-        file_id: Optional[str] = kwargs.get("file_id")
-        path: Optional[str] = kwargs.get("path")
-
-        if not file_id and not path:
+        if not params.file_id and not params.path:
             return ErrorResponse(
                 message="Please provide either file_id or path",
                 session_id=session_id,
@@ -583,15 +633,15 @@ class DeleteWorkspaceFileTool(BaseTool):
 
             # Determine the file_id to delete
             target_file_id: str
-            if file_id:
-                target_file_id = file_id
+            if params.file_id:
+                target_file_id = params.file_id
             else:
                 # path is guaranteed to be non-None here due to the check above
-                assert path is not None
-                file_info = await manager.get_file_info_by_path(path)
+                assert params.path is not None
+                file_info = await manager.get_file_info_by_path(params.path)
                 if file_info is None:
                     return ErrorResponse(
-                        message=f"File not found at path: {path}",
+                        message=f"File not found at path: {params.path}",
                         session_id=session_id,
                     )
                 target_file_id = file_info.id