refactor: simplify ExecutionQueue docstrings and move test file

- Trim verbose BUG FIX docstring to concise 3-line note - Remove redundant method docstrings (add, get, empty) - Move test file to backend/data/ with proper pytest conventions - Add note about ProcessPoolExecutor migration for future devs Co-authored-by: Zamil Majdy <majdyz@users.noreply.github.com>
fix(backend): format test_execution_queue.py and remove unused variable
2026-02-09 14:25:25 -05:00 · 2026-02-08 16:11:35 +00:00 · 2025-12-14 19:37:29 +05:45 · 2025-12-14 19:05:14 +05:45 · 2025-12-14 19:04:14 +05:45
29 changed files with 522 additions and 9766 deletions
--- a/autogpt_platform/backend/autogpt_platform/backend/poetry.lock
+++ b/autogpt_platform/backend/autogpt_platform/backend/poetry.lock
--- a/autogpt_platform/backend/backend/blocks/smart_agent.py
+++ b/autogpt_platform/backend/backend/blocks/smart_agent.py
@@ -1,858 +0,0 @@
 import logging
 import os
 import re
 from enum import Enum
 from typing import TYPE_CHECKING, Any, Literal, NamedTuple
 from claude_agent_sdk import query
 from claude_agent_sdk.types import (
    AssistantMessage,
    ClaudeAgentOptions,
    TextBlock,
    ToolUseBlock,
 )
 from pydantic import BaseModel, SecretStr
 # Avoid circular imports by importing only essential types
 # ExecutionParams, ToolInfo, and other classes will be imported dynamically when needed
 from backend.data.block import (
    Block,
    BlockCategory,
    BlockOutput,
    BlockSchemaInput,
    BlockSchemaOutput,
    BlockType,
 )
 from backend.data.dynamic_fields import is_tool_pin
 from backend.data.execution import ExecutionContext
 from backend.data.model import (
    APIKeyCredentials,
    CredentialsField,
    CredentialsMetaInput,
    SchemaField,
 )
 from backend.integrations.providers import ProviderName
 from backend.util import json
 from backend.util.clients import get_database_manager_async_client
 if TYPE_CHECKING:
    from backend.data.graph import Link, Node
    from backend.executor.manager import ExecutionProcessor
 logger = logging.getLogger(__name__)
 class ToolInfo(BaseModel):
    """Processed tool call information."""
    tool_call: Any  # The original tool call object from LLM response
    tool_name: str  # The function name
    tool_def: dict[str, Any]  # The tool definition from tool_functions
    input_data: dict[str, Any]  # Processed input data ready for tool execution
    field_mapping: dict[str, str]  # Field name mapping for the tool
 class ExecutionParams(BaseModel):
    """Tool execution parameters."""
    user_id: str
    graph_id: str
    node_id: str
    graph_version: int
    graph_exec_id: str
    node_exec_id: str
    execution_context: "ExecutionContext"
 def _create_tool_response(call_id: str, content: str) -> dict[str, Any]:
    """Create a tool response in the correct format."""
    # Anthropics format: tool IDs typically start with "toolu_"
    if call_id.startswith("toolu_"):
        return {
            "role": "user",
            "type": "message",
            "content": [
                {"tool_use_id": call_id, "type": "tool_result", "content": content}
            ],
        }
    # OpenAI format: tool IDs typically start with "call_".
    # Or default fallback (if the tool_id doesn't match any known prefix)
    return {"role": "tool", "tool_call_id": call_id, "content": content}
 class ModelMetadata(NamedTuple):
    provider: str
    context_window: int
    max_output_tokens: int | None
 class AgentModel(str, Enum):
    """Available models for the Smart Agent."""
    # Claude 4.x models (latest)
    CLAUDE_4_1_OPUS = "claude-opus-4-1-20250805"
    CLAUDE_4_OPUS = "claude-opus-4-20250514"
    CLAUDE_4_SONNET = "claude-sonnet-4-20250514"
    CLAUDE_4_5_OPUS = "claude-opus-4-5-20251101"
    CLAUDE_4_5_SONNET = "claude-sonnet-4-5-20250929"
    CLAUDE_4_5_HAIKU = "claude-haiku-4-5-20251001"
    # Claude 3.x models (stable)
    CLAUDE_3_7_SONNET = "claude-3-7-sonnet-20250219"
    CLAUDE_3_HAIKU = "claude-3-haiku-20240307"
    @property
    def metadata(self) -> ModelMetadata:
        return AGENT_MODEL_METADATA[self]
    @property
    def provider(self) -> str:
        return self.metadata.provider
 # Agent model metadata mapping
 AGENT_MODEL_METADATA = {
    # Claude 4.x models
    AgentModel.CLAUDE_4_1_OPUS: ModelMetadata(ProviderName.ANTHROPIC, 500000, 4096),
    AgentModel.CLAUDE_4_OPUS: ModelMetadata(ProviderName.ANTHROPIC, 500000, 4096),
    AgentModel.CLAUDE_4_SONNET: ModelMetadata(ProviderName.ANTHROPIC, 500000, 4096),
    AgentModel.CLAUDE_4_5_OPUS: ModelMetadata(ProviderName.ANTHROPIC, 500000, 8192),
    AgentModel.CLAUDE_4_5_SONNET: ModelMetadata(ProviderName.ANTHROPIC, 500000, 8192),
    AgentModel.CLAUDE_4_5_HAIKU: ModelMetadata(ProviderName.ANTHROPIC, 200000, 4096),
    # Claude 3.x models
    AgentModel.CLAUDE_3_7_SONNET: ModelMetadata(ProviderName.ANTHROPIC, 200000, 4096),
    AgentModel.CLAUDE_3_HAIKU: ModelMetadata(ProviderName.ANTHROPIC, 200000, 4096),
 }
 # Anthropic-only credentials for Claude models
 ClaudeCredentials = CredentialsMetaInput[
    Literal[ProviderName.ANTHROPIC], Literal["api_key"]
 ]
 def ClaudeCredentialsField() -> ClaudeCredentials:
    return CredentialsField(
        description="Anthropic API key for Claude Agent SDK access.",
        discriminator="model",
        discriminator_mapping={
            model.value: model.metadata.provider for model in AgentModel
        },
    )
 # Test credentials for Claude models
 TEST_CLAUDE_CREDENTIALS = APIKeyCredentials(
    id="test-claude-creds",
    provider=ProviderName.ANTHROPIC,
    api_key=SecretStr("mock-anthropic-api-key"),
    title="Mock Anthropic API key",
    expires_at=None,
 )
 TEST_CLAUDE_CREDENTIALS_INPUT = {
    "provider": TEST_CLAUDE_CREDENTIALS.provider,
    "id": TEST_CLAUDE_CREDENTIALS.id,
    "type": TEST_CLAUDE_CREDENTIALS.type,
    "title": TEST_CLAUDE_CREDENTIALS.title,
 }
 class SmartAgentBlock(Block):
    """
    A smart agent block that uses Claude Agent SDK for native agent capabilities
    while executing AutoGPT tool nodes.
    This block combines Claude's native agent functionality with AutoGPT's tool ecosystem:
    - Uses Claude Agent SDK for core agent intelligence
    - Discovers connected AutoGPT tool nodes like SmartDecisionMaker
    - When Claude calls tools, executes the actual AutoGPT tool nodes
    - Provides Claude with the tool execution results
    """
    class Input(BlockSchemaInput):
        task: str = SchemaField(
            description="The task for the agent to complete. Be specific about your requirements.",
            placeholder="Analyze the data file and create a summary report with key insights...",
        )
        model: AgentModel = SchemaField(
            title="Model",
            default=AgentModel.CLAUDE_4_5_SONNET,
            description="The model to use for the agent.",
            advanced=False,
        )
        credentials: ClaudeCredentials = ClaudeCredentialsField()
        max_iterations: int = SchemaField(
            default=15,
            description="Maximum number of agent iterations. Use -1 for unlimited (use carefully!).",
            advanced=False,
        )
        system_prompt: str = SchemaField(
            title="System Prompt",
            default="You are a helpful AI assistant with access to tools. Think step by step about which tools to use to complete the task efficiently. When you have completed the objective, provide a clear summary of the results.",
            description="System prompt to guide the agent's behavior.",
            advanced=True,
        )
        working_directory: str = SchemaField(
            default="/tmp/smart_agent",
            description="Working directory for the agent.",
            advanced=True,
        )
    class Output(BlockSchemaOutput):
        result: str = SchemaField(
            description="The final result or answer from the agent."
        )
        iterations_used: int = SchemaField(
            description="Number of iterations used to complete the task."
        )
        tools_used: list[str] = SchemaField(
            description="List of AutoGPT tools used during execution.",
            default_factory=list,
        )
        success: bool = SchemaField(
            description="Whether the task was completed successfully."
        )
        error: str = SchemaField(
            default="", description="Error message if the task failed."
        )
        # Tool output pins for connecting to other blocks (like SmartDecisionMakerBlock)
        tools: Any = SchemaField(
            description="Tool calls output for connecting to other AutoGPT blocks."
        )
        conversations: list[Any] = SchemaField(
            description="Conversation history with Claude Agent SDK.",
            default_factory=list,
        )
    def __init__(self):
        super().__init__(
            id="c1a2u3d4-e5a6-g7e8-n9t0-b1l2o3c4k5d6",
            description=(
                "An AI agent powered by Claude Agent SDK that executes connected AutoGPT tool nodes. "
                "Combines Claude's native agent capabilities with AutoGPT's tool ecosystem."
            ),
            categories={BlockCategory.AI},
            block_type=BlockType.AI,
            input_schema=SmartAgentBlock.Input,
            output_schema=SmartAgentBlock.Output,
            test_input={
                "task": "What tools are available?",
                "credentials": TEST_CLAUDE_CREDENTIALS_INPUT,
                "model": AgentModel.CLAUDE_4_5_SONNET,
            },
            test_output=[],
            test_credentials=TEST_CLAUDE_CREDENTIALS,
        )
    @staticmethod
    def cleanup(s: str):
        """Clean up block names for use as tool function names."""
        return re.sub(r"[^a-zA-Z0-9_-]", "_", s).lower()
    async def _create_tool_node_signatures(
        self,
        node_id: str,
    ) -> list[dict[str, Any]]:
        """
        Creates function signatures for connected tools.
        Args:
            node_id: The node_id for which to create function signatures.
        Returns:
            List of function signatures for tools
        """
        from backend.blocks.agent import AgentExecutorBlock
        db_client = get_database_manager_async_client()
        tools = [
            (link, node)
            for link, node in await db_client.get_connected_output_nodes(node_id)
            if is_tool_pin(link.source_name) and link.source_id == node_id
        ]
        if not tools:
            raise ValueError("There is no next node to execute.")
        return_tool_functions: list[dict[str, Any]] = []
        grouped_tool_links: dict[str, tuple["Node", list["Link"]]] = {}
        for link, node in tools:
            if link.sink_id not in grouped_tool_links:
                grouped_tool_links[link.sink_id] = (node, [link])
            else:
                grouped_tool_links[link.sink_id][1].append(link)
        for sink_node, links in grouped_tool_links.values():
            if not sink_node:
                raise ValueError(f"Sink node not found: {links[0].sink_id}")
            if sink_node.block_id == AgentExecutorBlock().id:
                # Dynamic import to avoid circular dependency
                from backend.blocks.smart_decision_maker import SmartDecisionMakerBlock
                tool_func = (
                    await SmartDecisionMakerBlock._create_agent_function_signature(
                        sink_node, links
                    )
                )
                return_tool_functions.append(tool_func)
            else:
                # Dynamic import to avoid circular dependency
                from backend.blocks.smart_decision_maker import SmartDecisionMakerBlock
                tool_func = (
                    await SmartDecisionMakerBlock._create_block_function_signature(
                        sink_node, links
                    )
                )
                return_tool_functions.append(tool_func)
        return return_tool_functions
    async def _execute_single_tool_with_manager(
        self,
        tool_info: ToolInfo,
        execution_params: ExecutionParams,
        execution_processor: "ExecutionProcessor",
    ) -> dict:
        """Execute a single tool using the execution manager for proper integration."""
        # Lazy imports to avoid circular dependencies
        from concurrent.futures import Future
        from backend.data.execution import NodeExecutionEntry
        tool_call = tool_info.tool_call
        tool_def = tool_info.tool_def
        raw_input_data = tool_info.input_data
        # Get sink node and field mapping
        sink_node_id = tool_def["function"]["_sink_node_id"]
        # Use proper database operations for tool execution
        db_client = get_database_manager_async_client()
        # Get target node
        target_node = await db_client.get_node(sink_node_id)
        if not target_node:
            raise ValueError(f"Target node {sink_node_id} not found")
        # Create proper node execution using upsert_execution_input
        node_exec_result = None
        final_input_data = None
        # Add all inputs to the execution
        if not raw_input_data:
            raise ValueError(f"Tool call has no input data: {tool_call}")
        for input_name, input_value in raw_input_data.items():
            node_exec_result, final_input_data = await db_client.upsert_execution_input(
                node_id=sink_node_id,
                graph_exec_id=execution_params.graph_exec_id,
                input_name=input_name,
                input_data=input_value,
            )
        assert node_exec_result is not None, "node_exec_result should not be None"
        # Create NodeExecutionEntry for execution manager
        node_exec_entry = NodeExecutionEntry(
            user_id=execution_params.user_id,
            graph_exec_id=execution_params.graph_exec_id,
            graph_id=execution_params.graph_id,
            graph_version=execution_params.graph_version,
            node_exec_id=node_exec_result.node_exec_id,
            node_id=sink_node_id,
            block_id=target_node.block_id,
            inputs=final_input_data or {},
            execution_context=execution_params.execution_context,
        )
        # Use the execution manager to execute the tool node
        try:
            # Get NodeExecutionProgress from the execution manager's running nodes
            node_exec_progress = execution_processor.running_node_execution[
                sink_node_id
            ]
            # Use the execution manager's own graph stats
            graph_stats_pair = (
                execution_processor.execution_stats,
                execution_processor.execution_stats_lock,
            )
            # Create a completed future for the task tracking system
            node_exec_future = Future()
            node_exec_progress.add_task(
                node_exec_id=node_exec_result.node_exec_id,
                task=node_exec_future,
            )
            # Execute the node directly since we're in the SmartAgent context
            node_exec_future.set_result(
                await execution_processor.on_node_execution(
                    node_exec=node_exec_entry,
                    node_exec_progress=node_exec_progress,
                    nodes_input_masks=None,
                    graph_stats_pair=graph_stats_pair,
                )
            )
            # Get outputs from database after execution completes using database manager client
            node_outputs = await db_client.get_execution_outputs_by_node_exec_id(
                node_exec_result.node_exec_id
            )
            # Create tool response
            tool_response_content = (
                json.dumps(node_outputs)
                if node_outputs
                else "Tool executed successfully"
            )
            return _create_tool_response(tool_call.id, tool_response_content)
        except Exception as e:
            logger.error(f"Tool execution with manager failed: {e}")
            # Return error response
            return _create_tool_response(
                tool_call.id, f"Tool execution failed: {str(e)}"
            )
    def _setup_environment(
        self, credentials: APIKeyCredentials, working_dir: str
    ) -> dict[str, str]:
        """Setup environment for Claude Agent SDK."""
        os.makedirs(working_dir, exist_ok=True)
        env = os.environ.copy()
        env["ANTHROPIC_API_KEY"] = credentials.api_key.get_secret_value()
        return env
    def _build_tool_descriptions_for_claude(
        self, tool_functions: list[dict[str, Any]]
    ) -> str:
        """Build description of available AutoGPT tools for Claude."""
        if not tool_functions:
            return "No tools are currently connected to this agent."
        tool_descriptions = ["Available AutoGPT tools:"]
        for tool_def in tool_functions:
            func_def = tool_def.get("function", {})
            name = func_def.get("name", "unknown")
            description = func_def.get("description", "No description")
            tool_descriptions.append(f"- {name}: {description}")
        tool_descriptions.append(
            "\nWhen you need to use a tool, call it with function calling syntax."
        )
        return "\n".join(tool_descriptions)
    def _extract_tool_calls_from_claude_message(
        self, message: AssistantMessage
    ) -> list[dict[str, Any]]:
        """Extract tool calls from Claude Agent SDK message."""
        tool_calls = []
        for content_block in message.content:
            if isinstance(content_block, ToolUseBlock):
                tool_calls.append(
                    {
                        "id": content_block.id,
                        "function": {
                            "name": content_block.name,
                            "arguments": content_block.input,
                        },
                    }
                )
        return tool_calls
    def _extract_text_content_from_claude_message(
        self, message: AssistantMessage
    ) -> str:
        """Extract text content from Claude Agent SDK message."""
        text_parts = []
        for content_block in message.content:
            if isinstance(content_block, TextBlock):
                text_parts.append(content_block.text)
        return "".join(text_parts)
    def _format_conversation_for_claude(self, conversation: list[dict]) -> str:
        """Format conversation history for Claude Agent SDK."""
        formatted = []
        for msg in conversation:
            role = msg.get("role", "user")
            content = msg.get("content", "")
            if role == "tool":
                # Format tool response
                tool_id = msg.get("tool_call_id", "unknown")
                formatted.append(f"Tool result ({tool_id}): {content}")
            else:
                # Simple format for user/assistant messages
                formatted.append(f"{role.title()}: {content}")
        return "\n\n".join(formatted)
    def _normalize_tool_args(self, tool_args: Any) -> dict:
        """Normalize tool arguments to dict format."""
        if isinstance(tool_args, str):
            return json.loads(tool_args)
        elif isinstance(tool_args, dict):
            return tool_args
        else:
            return dict(tool_args) if tool_args else {}
    def _create_tool_info_from_claude_call(
        self, tool_call: dict[str, Any], tool_functions: list[dict[str, Any]]
    ) -> ToolInfo:
        """Convert Claude tool call to AutoGPT ToolInfo format."""
        tool_name = tool_call["function"]["name"]
        tool_args = self._normalize_tool_args(tool_call["function"]["arguments"])
        tool_id = tool_call["id"]
        # Find the AutoGPT tool definition
        tool_def = next(
            (
                tf
                for tf in tool_functions
                if tf.get("function", {}).get("name") == tool_name
            ),
            None,
        )
        if not tool_def:
            raise ValueError(f"AutoGPT tool '{tool_name}' not found")
        # Create mock tool call object for AutoGPT compatibility
        class MockToolCall:
            def __init__(self, tool_id: str, name: str, args: dict):
                self.id = tool_id
                self.function = type(
                    "Function", (), {"name": name, "arguments": json.dumps(args)}
                )()
        # Build input data from arguments
        field_mapping = tool_def["function"].get("_field_mapping", {})
        expected_args = tool_def["function"]["parameters"].get("properties", {})
        input_data = {
            field_mapping.get(clean_arg_name, clean_arg_name): tool_args.get(
                clean_arg_name
            )
            for clean_arg_name in expected_args
        }
        return ToolInfo(
            tool_call=MockToolCall(tool_id, tool_name, tool_args),
            tool_name=tool_name,
            tool_def=tool_def,
            input_data=input_data,
            field_mapping=field_mapping,
        )
    async def _attempt_claude_call_with_validation(
        self,
        prompt: str,
        options: ClaudeAgentOptions,
    ) -> AssistantMessage:
        """Claude SDK call - let generator cleanup happen naturally to avoid cancel scope issues."""
        try:
            # Simple approach: don't try to manually manage the generator lifecycle
            async for message in query(prompt=prompt, options=options):
                if isinstance(message, AssistantMessage):
                    return message
            raise ValueError("No AssistantMessage received from Claude SDK")
        except Exception as e:
            logger.error(f"Claude SDK call failed: {e}")
            raise
        # Note: No finally block - let the generator be cleaned up naturally by garbage collection
    async def _execute_tools_agent_mode(
        self,
        input_data: Input,
        credentials,
        tool_functions: list[dict[str, Any]],
        graph_exec_id: str,
        node_id: str,
        node_exec_id: str,
        user_id: str,
        graph_id: str,
        graph_version: int,
        execution_context: ExecutionContext,
        execution_processor: "ExecutionProcessor",
    ):
        """Execute tools in agent mode with a loop until finished, following SmartDecisionMakerBlock pattern."""
        max_iterations = input_data.max_iterations
        iteration = 0
        # Execution parameters for tool execution
        execution_params = ExecutionParams(
            user_id=user_id,
            graph_id=graph_id,
            node_id=node_id,
            graph_version=graph_version,
            graph_exec_id=graph_exec_id,
            node_exec_id=node_exec_id,
            execution_context=execution_context,
        )
        # Build enhanced task prompt with tool descriptions
        tool_descriptions = self._build_tool_descriptions_for_claude(tool_functions)
        enhanced_task = f"""{input_data.task}
 {tool_descriptions}
 Complete the task step by step using the available tools as needed."""
        # Start conversation with enhanced task
        current_conversation = [{"role": "user", "content": enhanced_task}]
        while max_iterations < 0 or iteration < max_iterations:
            iteration += 1
            logger.debug(f"Claude agent mode iteration {iteration}")
            # Prepare conversation for this iteration
            iteration_conversation = list(current_conversation)
            # On the last iteration, add encouragement to finish
            if max_iterations > 0 and iteration == max_iterations:
                last_iteration_message = {
                    "role": "system",
                    "content": f"This is your last iteration ({iteration}/{max_iterations}). "
                    "Try to complete the task with the information you have. "
                    "Prefer finishing with a clear response rather than making additional tool calls.",
                }
                iteration_conversation.append(last_iteration_message)
            # Format conversation for Claude SDK
            conversation_text = self._format_conversation_for_claude(
                iteration_conversation
            )
            # Setup Claude options for this iteration
            claude_options = ClaudeAgentOptions(
                system_prompt=input_data.system_prompt,
                model=input_data.model.value,
                max_turns=1,  # Single turn per iteration
                cwd=input_data.working_directory,
                env=self._setup_environment(credentials, input_data.working_directory),
                permission_mode="bypassPermissions",
            )
            # Get Claude response
            logger.debug(f"Claude agent iteration {iteration}: Making Claude SDK call")
            try:
                claude_response = await self._attempt_claude_call_with_validation(
                    conversation_text, claude_options
                )
                logger.debug(f"Claude agent iteration {iteration}: Received response")
            except Exception as e:
                logger.error(
                    f"Claude agent iteration {iteration}: Call failed with {type(e).__name__}: {str(e)}"
                )
                yield (
                    "error",
                    f"Claude call failed in agent mode iteration {iteration}: {str(e)}",
                )
                return
            # Process tool calls
            tool_calls = self._extract_tool_calls_from_claude_message(claude_response)
            text_content = self._extract_text_content_from_claude_message(
                claude_response
            )
            # Add Claude's response to conversation
            assistant_message = {
                "role": "assistant",
                "content": text_content,
                "tool_calls": tool_calls if tool_calls else [],
            }
            current_conversation.append(assistant_message)
            # If no tool calls, we're done
            if not tool_calls:
                yield "finished", text_content
                yield "conversations", current_conversation
                return
            # Execute tools and collect responses
            tool_outputs = []
            for tool_call in tool_calls:
                # Convert tool call to ToolInfo format for AutoGPT execution
                tool_info = self._create_tool_info_from_claude_call(
                    tool_call, tool_functions
                )
                try:
                    # Execute via AutoGPT's execution manager
                    tool_response = await self._execute_single_tool_with_manager(
                        tool_info, execution_params, execution_processor
                    )
                    tool_outputs.append(tool_response)
                except Exception as e:
                    logger.error(f"Tool execution failed: {e}")
                    error_response = _create_tool_response(
                        tool_call["id"], f"Error: {str(e)}"
                    )
                    tool_outputs.append(error_response)
            # Add tool results to conversation
            current_conversation.extend(tool_outputs)
            # Yield intermediate conversation state
            yield "conversations", current_conversation
        # If we reach max iterations, yield the current state
        if max_iterations < 0:
            yield "finished", f"Agent mode completed after {iteration} iterations"
        else:
            yield (
                "finished",
                f"Agent mode completed after {max_iterations} iterations (limit reached)",
            )
        yield "conversations", current_conversation
    async def _execute_single_call_mode(
        self,
        input_data: Input,  # Used for configuration and consistency with agent mode
        tool_functions: list[dict[str, Any]],
        enhanced_task: str,
        claude_options: ClaudeAgentOptions | None,
    ):
        """Execute single call mode and yield tool outputs for external execution."""
        # Create Claude options for single call if not provided
        if claude_options is None:
            claude_options = ClaudeAgentOptions(
                system_prompt=input_data.system_prompt,
                model=input_data.model.value,
                max_turns=1,  # Single call mode
                cwd=input_data.working_directory,
                permission_mode="bypassPermissions",
            )
        else:
            # Override max_turns to 1 for single call
            claude_options.max_turns = 1
        try:
            claude_response = await self._attempt_claude_call_with_validation(
                enhanced_task, claude_options
            )
        except Exception as e:
            yield "error", f"Claude SDK error: {str(e)}"
            yield "success", False
            return
        if claude_response:
            text_content = self._extract_text_content_from_claude_message(
                claude_response
            )
            tool_calls = self._extract_tool_calls_from_claude_message(claude_response)
            if not tool_calls:
                # No tool calls - just return the result
                yield "result", text_content
                yield "success", True
                yield "tools", []  # No tools used
                return
            # Process and yield tool calls for external execution
            for tool_call in tool_calls:
                tool_name = tool_call["function"]["name"]
                tool_args = self._normalize_tool_args(
                    tool_call["function"]["arguments"]
                )
                # Find the tool definition (fallback to first if only one available)
                tool_def = next(
                    (
                        tool
                        for tool in tool_functions
                        if tool["function"]["name"] == tool_name
                    ),
                    tool_functions[0] if len(tool_functions) == 1 else None,
                )
                if not tool_def:
                    continue
                # Get field mapping and sink node ID
                field_mapping = tool_def["function"].get("_field_mapping", {})
                sink_node_id = tool_def["function"]["_sink_node_id"]
                expected_args = tool_def["function"]["parameters"].get(
                    "properties", tool_args.keys()
                )
                # Yield tool outputs like SmartDecisionMakerBlock
                for clean_arg_name in expected_args:
                    original_field_name = field_mapping.get(
                        clean_arg_name, clean_arg_name
                    )
                    arg_value = tool_args.get(clean_arg_name)
                    # Create the same emit key format as SmartDecisionMakerBlock
                    sanitized_arg_name = self.cleanup(original_field_name)
                    emit_key = f"tools_^_{sink_node_id}_~_{sanitized_arg_name}"
                    logger.debug(f"Yielding tool output: {emit_key}")
                    yield emit_key, arg_value
            # Yield conversation and tool results
            yield (
                "conversations",
                [
                    {
                        "role": "assistant",
                        "content": text_content,
                        "tool_calls": tool_calls,
                    }
                ],
            )
            yield "tools", tool_calls
            yield "success", True
            return
        # If no messages received
        yield "error", "No response from Claude Agent SDK"
        yield "success", False
    async def run(
        self,
        input_data: Input,
        *,
        credentials: APIKeyCredentials,
        graph_id: str,
        node_id: str,
        graph_exec_id: str,
        node_exec_id: str,
        user_id: str,
        graph_version: int,
        execution_context: ExecutionContext,
        execution_processor: "ExecutionProcessor",
        **kwargs,  # Additional execution context parameters
    ) -> BlockOutput:
        _ = kwargs  # Suppress unused parameter warning
        # Validate credentials
        if credentials.provider != ProviderName.ANTHROPIC:
            error_msg = f"SmartAgentBlock requires Anthropic/Claude credentials, but received {credentials.provider} credentials. Please configure Anthropic API key credentials."
            logger.error(error_msg)
            yield "error", error_msg
            yield "success", False
            return
        # Discover connected AutoGPT tool nodes
        try:
            tool_functions = await self._create_tool_node_signatures(node_id)
        except ValueError as e:
            if "no next node" in str(e).lower():
                # Agent can work without tools - just provide Claude with reasoning capability
                tool_functions = []
                logger.info("No tools connected - running as pure Claude Agent")
            else:
                raise
        yield "tool_functions", json.dumps(tool_functions)
        # Always run Claude Agent SDK in agent mode (iterative execution)
        async for result in self._execute_tools_agent_mode(
            input_data=input_data,
            credentials=credentials,
            tool_functions=tool_functions,
            graph_exec_id=graph_exec_id,
            node_id=node_id,
            node_exec_id=node_exec_id,
            user_id=user_id,
            graph_id=graph_id,
            graph_version=graph_version,
            execution_context=execution_context,
            execution_processor=execution_processor,
        ):
            yield result
--- a/autogpt_platform/backend/backend/data/execution.py
+++ b/autogpt_platform/backend/backend/data/execution.py
@@ -1,9 +1,8 @@
 import logging
 import queue
 from collections import defaultdict
 from datetime import datetime, timedelta, timezone
 from enum import Enum
 from multiprocessing import Manager
 from queue import Empty
 from typing import (
    TYPE_CHECKING,
    Annotated,
@@ -1164,12 +1163,16 @@ class NodeExecutionEntry(BaseModel):
 class ExecutionQueue(Generic[T]):
    """
-    Queue for managing the execution of agents.
+    Thread-safe queue for managing node execution within a single graph execution.
-    This will be shared between different processes
+
    Note: Uses queue.Queue (not multiprocessing.Queue) since all access is from
    threads within the same process. If migrating back to ProcessPoolExecutor,
    replace with multiprocessing.Manager().Queue() for cross-process safety.
    """
    def __init__(self):
-        self.queue = Manager().Queue()
+        # Thread-safe queue (not multiprocessing) — see class docstring
        self.queue: queue.Queue[T] = queue.Queue()
    def add(self, execution: T) -> T:
        self.queue.put(execution)
@@ -1184,7 +1187,7 @@ class ExecutionQueue(Generic[T]):
    def get_or_none(self) -> T | None:
        try:
            return self.queue.get_nowait()
-        except Empty:
+        except queue.Empty:
            return None
--- a/autogpt_platform/backend/backend/data/execution_queue_test.py
+++ b/autogpt_platform/backend/backend/data/execution_queue_test.py
@@ -0,0 +1,60 @@
 """Tests for ExecutionQueue thread-safety."""
 import queue
 import threading
 import pytest
 from backend.data.execution import ExecutionQueue
 def test_execution_queue_uses_stdlib_queue():
    """Verify ExecutionQueue uses queue.Queue (not multiprocessing)."""
    q = ExecutionQueue()
    assert isinstance(q.queue, queue.Queue)
 def test_basic_operations():
    """Test add, get, empty, and get_or_none."""
    q = ExecutionQueue()
    assert q.empty() is True
    assert q.get_or_none() is None
    result = q.add("item1")
    assert result == "item1"
    assert q.empty() is False
    item = q.get()
    assert item == "item1"
    assert q.empty() is True
 def test_thread_safety():
    """Test concurrent access from multiple threads."""
    q = ExecutionQueue()
    results = []
    num_items = 100
    def producer():
        for i in range(num_items):
            q.add(f"item_{i}")
    def consumer():
        count = 0
        while count < num_items:
            item = q.get_or_none()
            if item is not None:
                results.append(item)
                count += 1
    producer_thread = threading.Thread(target=producer)
    consumer_thread = threading.Thread(target=consumer)
    producer_thread.start()
    consumer_thread.start()
    producer_thread.join(timeout=5)
    consumer_thread.join(timeout=5)
    assert len(results) == num_items
--- a/autogpt_platform/backend/poetry.lock
+++ b/autogpt_platform/backend/poetry.lock
@@ -825,29 +825,6 @@ files = [
    {file = "charset_normalizer-3.4.2.tar.gz", hash = "sha256:5baececa9ecba31eff645232d59845c07aa030f0c81ee70184a90d35099a0e63"},
 ]
 [[package]]
 name = "claude-agent-sdk"
 version = "0.1.17"
 description = "Python SDK for Claude Code"
 optional = false
 python-versions = ">=3.10"
 groups = ["main"]
 files = [
    {file = "claude_agent_sdk-0.1.17-py3-none-macosx_11_0_arm64.whl", hash = "sha256:46fd904ce90a183414f979d359519cff347f52c1906d50f1e247551c786a3613"},
    {file = "claude_agent_sdk-0.1.17-py3-none-manylinux_2_17_aarch64.whl", hash = "sha256:08c41656da3ec7930cb966b35df23da6f68fa0fc0a32c61e73d6450c40c0e17e"},
    {file = "claude_agent_sdk-0.1.17-py3-none-manylinux_2_17_x86_64.whl", hash = "sha256:be5fe696e50829348b031106dc926bb459c94804a13584a52a483a35ebd1c388"},
    {file = "claude_agent_sdk-0.1.17-py3-none-win_amd64.whl", hash = "sha256:f2f4e05785a42525cf8026f0bba69bce359b83a57856f0b7349cd311a0d644be"},
    {file = "claude_agent_sdk-0.1.17.tar.gz", hash = "sha256:85d0818b7259b65ea0ee3103ae736f2b359243de81540ab1eee771d8cae0d8ac"},
 ]
 [package.dependencies]
 anyio = ">=4.0.0"
 mcp = ">=0.1.0"
 typing-extensions = {version = ">=4.0.0", markers = "python_version < \"3.11\""}
 [package.extras]
 dev = ["anyio[trio] (>=4.0.0)", "mypy (>=1.0.0)", "pytest (>=7.0.0)", "pytest-asyncio (>=0.20.0)", "pytest-cov (>=4.0.0)", "ruff (>=0.1.0)"]
 [[package]]
 name = "cleo"
 version = "2.1.0"
@@ -2327,18 +2304,6 @@ http2 = ["h2 (>=3,<5)"]
 socks = ["socksio (==1.*)"]
 zstd = ["zstandard (>=0.18.0)"]
 [[package]]
 name = "httpx-sse"
 version = "0.4.3"
 description = "Consume Server-Sent Event (SSE) messages with HTTPX."
 optional = false
 python-versions = ">=3.9"
 groups = ["main"]
 files = [
    {file = "httpx_sse-0.4.3-py3-none-any.whl", hash = "sha256:0ac1c9fe3c0afad2e0ebb25a934a59f4c7823b60792691f779fad2c5568830fc"},
    {file = "httpx_sse-0.4.3.tar.gz", hash = "sha256:9b1ed0127459a66014aec3c56bebd93da3c1bc8bb6618c8082039a44889a755d"},
 ]
 [[package]]
 name = "huggingface-hub"
 version = "0.34.4"
@@ -2976,39 +2941,6 @@ files = [
    {file = "mccabe-0.7.0.tar.gz", hash = "sha256:348e0240c33b60bbdf4e523192ef919f28cb2c3d7d5c7794f74009290f236325"},
 ]
 [[package]]
 name = "mcp"
 version = "1.24.0"
 description = "Model Context Protocol SDK"
 optional = false
 python-versions = ">=3.10"
 groups = ["main"]
 files = [
    {file = "mcp-1.24.0-py3-none-any.whl", hash = "sha256:db130e103cc50ddc3dffc928382f33ba3eaef0b711f7a87c05e7ded65b1ca062"},
    {file = "mcp-1.24.0.tar.gz", hash = "sha256:aeaad134664ce56f2721d1abf300666a1e8348563f4d3baff361c3b652448efc"},
 ]
 [package.dependencies]
 anyio = ">=4.5"
 httpx = ">=0.27.1"
 httpx-sse = ">=0.4"
 jsonschema = ">=4.20.0"
 pydantic = ">=2.11.0,<3.0.0"
 pydantic-settings = ">=2.5.2"
 pyjwt = {version = ">=2.10.1", extras = ["crypto"]}
 python-multipart = ">=0.0.9"
 pywin32 = {version = ">=310", markers = "sys_platform == \"win32\""}
 sse-starlette = ">=1.6.1"
 starlette = ">=0.27"
 typing-extensions = ">=4.9.0"
 typing-inspection = ">=0.4.1"
 uvicorn = {version = ">=0.31.1", markers = "sys_platform != \"emscripten\""}
 [package.extras]
 cli = ["python-dotenv (>=1.0.0)", "typer (>=0.16.0)"]
 rich = ["rich (>=13.9.4)"]
 ws = ["websockets (>=15.0.1)"]
 [[package]]
 name = "mdurl"
 version = "0.1.2"
@@ -4549,6 +4481,7 @@ files = [
    {file = "psycopg2_binary-2.9.10-cp313-cp313-musllinux_1_2_i686.whl", hash = "sha256:bb89f0a835bcfc1d42ccd5f41f04870c1b936d8507c6df12b7737febc40f0909"},
    {file = "psycopg2_binary-2.9.10-cp313-cp313-musllinux_1_2_ppc64le.whl", hash = "sha256:f0c2d907a1e102526dd2986df638343388b94c33860ff3bbe1384130828714b1"},
    {file = "psycopg2_binary-2.9.10-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:f8157bed2f51db683f31306aa497311b560f2265998122abe1dce6428bd86567"},
    {file = "psycopg2_binary-2.9.10-cp313-cp313-win_amd64.whl", hash = "sha256:27422aa5f11fbcd9b18da48373eb67081243662f9b46e6fd07c3eb46e4535142"},
    {file = "psycopg2_binary-2.9.10-cp38-cp38-macosx_12_0_x86_64.whl", hash = "sha256:eb09aa7f9cecb45027683bb55aebaaf45a0df8bf6de68801a6afdc7947bb09d4"},
    {file = "psycopg2_binary-2.9.10-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:b73d6d7f0ccdad7bc43e6d34273f70d587ef62f824d7261c4ae9b8b1b6af90e8"},
    {file = "psycopg2_binary-2.9.10-cp38-cp38-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:ce5ab4bf46a211a8e924d307c1b1fcda82368586a19d0a24f8ae166f5c784864"},
@@ -5153,7 +5086,7 @@ description = "Python for Window Extensions"
 optional = false
 python-versions = "*"
 groups = ["main"]
-markers = "platform_system == \"Windows\" or sys_platform == \"win32\""
+markers = "platform_system == \"Windows\""
 files = [
    {file = "pywin32-311-cp310-cp310-win32.whl", hash = "sha256:d03ff496d2a0cd4a5893504789d4a15399133fe82517455e78bad62efbb7f0a3"},
    {file = "pywin32-311-cp310-cp310-win_amd64.whl", hash = "sha256:797c2772017851984b97180b0bebe4b620bb86328e8a884bb626156295a63b3b"},
@@ -6120,27 +6053,6 @@ postgresql-psycopgbinary = ["psycopg[binary] (>=3.0.7)"]
 pymysql = ["pymysql"]
 sqlcipher = ["sqlcipher3_binary"]
 [[package]]
 name = "sse-starlette"
 version = "3.0.3"
 description = "SSE plugin for Starlette"
 optional = false
 python-versions = ">=3.9"
 groups = ["main"]
 files = [
    {file = "sse_starlette-3.0.3-py3-none-any.whl", hash = "sha256:af5bf5a6f3933df1d9c7f8539633dc8444ca6a97ab2e2a7cd3b6e431ac03a431"},
    {file = "sse_starlette-3.0.3.tar.gz", hash = "sha256:88cfb08747e16200ea990c8ca876b03910a23b547ab3bd764c0d8eb81019b971"},
 ]
 [package.dependencies]
 anyio = ">=4.7.0"
 [package.extras]
 daphne = ["daphne (>=4.2.0)"]
 examples = ["aiosqlite (>=0.21.0)", "fastapi (>=0.115.12)", "sqlalchemy[asyncio] (>=2.0.41)", "starlette (>=0.49.1)", "uvicorn (>=0.34.0)"]
 granian = ["granian (>=2.3.1)"]
 uvicorn = ["uvicorn (>=0.34.0)"]
 [[package]]
 name = "stagehand"
 version = "0.5.1"
@@ -7367,4 +7279,4 @@ cffi = ["cffi (>=1.11)"]
 [metadata]
 lock-version = "2.1"
 python-versions = ">=3.10,<3.14"
-content-hash = "4594d56a0d808095e20861774ddfe8f87bc461f4f88ca7b748ff066225fa2684"
+content-hash = "13b191b2a1989d3321ff713c66ff6f5f4f3b82d15df4d407e0e5dbf87d7522c4"
--- a/autogpt_platform/backend/pyproject.toml
+++ b/autogpt_platform/backend/pyproject.toml
@@ -82,7 +82,6 @@ firecrawl-py = "^4.3.6"
 exa-py = "^1.14.20"
 croniter = "^6.0.0"
 stagehand = "^0.5.1"
 claude-agent-sdk = "^0.1.17"
 [tool.poetry.group.dev.dependencies]
 aiohappyeyeballs = "^2.6.1"
--- a/autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/NewAgentLibraryView/components/modals/AgentInputsReadOnly/AgentInputsReadOnly.tsx
+++ b/autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/NewAgentLibraryView/components/modals/AgentInputsReadOnly/AgentInputsReadOnly.tsx
@@ -1,11 +1,16 @@
 "use client";
 import type { LibraryAgent } from "@/app/api/__generated__/models/libraryAgent";
-import { Text } from "@/components/atoms/Text/Text";
+import type {
-import type { CredentialsMetaInput } from "@/lib/autogpt-server-api/types";
+  BlockIOSubSchema,
  CredentialsMetaInput,
 } from "@/lib/autogpt-server-api/types";
 import { CredentialsInput } from "../CredentialsInputs/CredentialsInputs";
-import { RunAgentInputs } from "../RunAgentInputs/RunAgentInputs";
+import {
-import { getAgentCredentialsFields, getAgentInputFields } from "./helpers";
+  getAgentCredentialsFields,
  getAgentInputFields,
  renderValue,
 } from "./helpers";
 type Props = {
  agent: LibraryAgent;
@@ -23,23 +28,19 @@ export function AgentInputsReadOnly({
    getAgentCredentialsFields(agent),
  );
  // Take actual input entries as leading; augment with schema from input fields.
  // TODO: ensure consistent ordering.
  const inputEntries =
    inputs &&
-    Object.entries(inputs).map(([key, value]) => ({
+    Object.entries(inputs).map<[string, [BlockIOSubSchema | undefined, any]]>(
-      key,
+      ([k, v]) => [k, [inputFields[k], v]],
-      schema: inputFields[key],
+    );
      value,
    }));
  const hasInputs = inputEntries && inputEntries.length > 0;
  const hasCredentials = credentialInputs && credentialFieldEntries.length > 0;
  if (!hasInputs && !hasCredentials) {
-    return (
+    return <div className="text-neutral-600">No input for this run.</div>;
      <Text variant="body" className="text-zinc-700">
        No input for this run.
      </Text>
    );
  }
  return (
@@ -47,20 +48,16 @@ export function AgentInputsReadOnly({
      {/* Regular inputs */}
      {hasInputs && (
        <div className="flex flex-col gap-4">
-          {inputEntries.map(({ key, schema, value }) => {
+          {inputEntries.map(([key, [schema, value]]) => (
-            if (!schema) return null;
+            <div key={key} className="flex flex-col gap-1.5">
-
+              <label className="text-sm font-medium">
-            return (
+                {schema?.title || key}
-              <RunAgentInputs
+              </label>
-                key={key}
+              <p className="whitespace-pre-wrap break-words text-sm text-neutral-700">
-                schema={schema}
+                {renderValue(value)}
-                value={value}
+              </p>
-                placeholder={schema.description}
+            </div>
-                onChange={() => {}}
+          ))}
                readOnly={true}
              />
            );
          })}
        </div>
      )}
--- a/autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/NewAgentLibraryView/components/modals/RunAgentInputs/RunAgentInputs.tsx
+++ b/autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/NewAgentLibraryView/components/modals/RunAgentInputs/RunAgentInputs.tsx
@@ -9,7 +9,6 @@ import { Button } from "@/components/atoms/Button/Button";
 import { FileInput } from "@/components/atoms/FileInput/FileInput";
 import { Switch } from "@/components/atoms/Switch/Switch";
 import { GoogleDrivePickerInput } from "@/components/contextual/GoogleDrivePicker/GoogleDrivePickerInput";
 import { InformationTooltip } from "@/components/molecules/InformationTooltip/InformationTooltip";
 import { TimePicker } from "@/components/molecules/TimePicker/TimePicker";
 import {
  BlockIOObjectSubSchema,
@@ -33,7 +32,6 @@ interface Props {
  value?: any;
  placeholder?: string;
  onChange: (value: any) => void;
  readOnly?: boolean;
 }
 /**
@@ -46,7 +44,6 @@ export function RunAgentInputs({
  value,
  placeholder,
  onChange,
  readOnly = false,
  ...props
 }: Props & React.HTMLAttributes<HTMLElement>) {
  const { handleUploadFile, uploadProgress } = useRunAgentInputs();
@@ -65,6 +62,7 @@ export function RunAgentInputs({
          id={`${baseId}-number`}
          label={schema.title ?? placeholder ?? "Number"}
          hideLabel
          size="small"
          type="number"
          value={value ?? ""}
          placeholder={placeholder || "Enter number"}
@@ -82,6 +80,7 @@ export function RunAgentInputs({
          id={`${baseId}-textarea`}
          label={schema.title ?? placeholder ?? "Text"}
          hideLabel
          size="small"
          type="textarea"
          rows={3}
          value={value ?? ""}
@@ -131,6 +130,7 @@ export function RunAgentInputs({
          id={`${baseId}-date`}
          label={schema.title ?? placeholder ?? "Date"}
          hideLabel
          size="small"
          type="date"
          value={value ? format(value as Date, "yyyy-MM-dd") : ""}
          onChange={(e) => {
@@ -159,6 +159,7 @@ export function RunAgentInputs({
          id={`${baseId}-datetime`}
          label={schema.title ?? placeholder ?? "Date time"}
          hideLabel
          size="small"
          type="datetime-local"
          value={value ?? ""}
          onChange={(e) => onChange((e.target as HTMLInputElement).value)}
@@ -193,6 +194,7 @@ export function RunAgentInputs({
            label={schema.title ?? placeholder ?? "Select"}
            hideLabel
            value={value ?? ""}
            size="small"
            onValueChange={(val: string) => onChange(val)}
            placeholder={placeholder || "Select an option"}
            options={schema.enum
@@ -215,6 +217,7 @@ export function RunAgentInputs({
          items={allKeys.map((key) => ({
            value: key,
            label: _schema.properties[key]?.title ?? key,
            size: "small",
          }))}
          selectedValues={selectedValues}
          onChange={(values: string[]) =>
@@ -333,6 +336,7 @@ export function RunAgentInputs({
          id={`${baseId}-text`}
          label={schema.title ?? placeholder ?? "Text"}
          hideLabel
          size="small"
          type="text"
          value={value ?? ""}
          onChange={(e) => onChange((e.target as HTMLInputElement).value)}
@@ -343,17 +347,6 @@ export function RunAgentInputs({
  }
  return (
-    <div className="flex w-full flex-col gap-0 space-y-2">
+    <div className="no-drag relative flex w-full">{innerInputElement}</div>
      <label className="large-medium flex items-center gap-1 font-medium">
        {schema.title || placeholder}
        <InformationTooltip description={schema.description} />
      </label>
      <div
        className="no-drag relative flex w-full"
        style={readOnly ? { pointerEvents: "none", opacity: 0.7 } : undefined}
      >
        {innerInputElement}
      </div>
    </div>
  );
 }
--- a/autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/NewAgentLibraryView/components/modals/RunAgentModal/components/ModalRunSection/ModalRunSection.tsx
+++ b/autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/NewAgentLibraryView/components/modals/RunAgentModal/components/ModalRunSection/ModalRunSection.tsx
@@ -73,15 +73,22 @@ export function ModalRunSection() {
          title="Task Inputs"
          subtitle="Enter the information you want to provide to the agent for this task"
        >
          {/* Regular inputs */}
          {inputFields.map(([key, inputSubSchema]) => (
-            <RunAgentInputs
+            <div key={key} className="flex w-full flex-col gap-0 space-y-2">
-              key={key}
+              <label className="flex items-center gap-1 text-sm font-medium">
-              schema={inputSubSchema}
+                {inputSubSchema.title || key}
-              value={inputValues[key] ?? inputSubSchema.default}
+                <InformationTooltip description={inputSubSchema.description} />
-              placeholder={inputSubSchema.description}
+              </label>
-              onChange={(value) => setInputValue(key, value)}
+
-              data-testid={`agent-input-${key}`}
+              <RunAgentInputs
-            />
+                schema={inputSubSchema}
                value={inputValues[key] ?? inputSubSchema.default}
                placeholder={inputSubSchema.description}
                onChange={(value) => setInputValue(key, value)}
                data-testid={`agent-input-${key}`}
              />
            </div>
          ))}
        </ModalSection>
      ) : null}
--- a/autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/NewAgentLibraryView/components/selected-views/SelectedRunView/SelectedRunView.tsx
+++ b/autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/NewAgentLibraryView/components/selected-views/SelectedRunView/SelectedRunView.tsx
@@ -4,19 +4,20 @@ import { AgentExecutionStatus } from "@/app/api/__generated__/models/agentExecut
 import type { LibraryAgent } from "@/app/api/__generated__/models/libraryAgent";
 import { LoadingSpinner } from "@/components/atoms/LoadingSpinner/LoadingSpinner";
 import { Text } from "@/components/atoms/Text/Text";
 import { ErrorCard } from "@/components/molecules/ErrorCard/ErrorCard";
 import { InformationTooltip } from "@/components/molecules/InformationTooltip/InformationTooltip";
 import {
-  ScrollableTabs,
+  Tooltip,
-  ScrollableTabsContent,
+  TooltipContent,
-  ScrollableTabsList,
+  TooltipProvider,
-  ScrollableTabsTrigger,
+  TooltipTrigger,
-} from "@/components/molecules/ScrollableTabs/ScrollableTabs";
+} from "@/components/atoms/Tooltip/BaseTooltip";
 import { ErrorCard } from "@/components/molecules/ErrorCard/ErrorCard";
 import { PendingReviewsList } from "@/components/organisms/PendingReviewsList/PendingReviewsList";
 import { usePendingReviewsForExecution } from "@/hooks/usePendingReviews";
 import { isLargeScreen, useBreakpoint } from "@/lib/hooks/useBreakpoint";
 import { InfoIcon } from "@phosphor-icons/react";
 import { useEffect } from "react";
 import { AgentInputsReadOnly } from "../../modals/AgentInputsReadOnly/AgentInputsReadOnly";
 import { AnchorLinksWrap } from "../AnchorLinksWrap";
 import { LoadingSelectedContent } from "../LoadingSelectedContent";
 import { RunDetailCard } from "../RunDetailCard/RunDetailCard";
 import { RunDetailHeader } from "../RunDetailHeader/RunDetailHeader";
@@ -27,6 +28,9 @@ import { SelectedRunActions } from "./components/SelectedRunActions/SelectedRunA
 import { WebhookTriggerSection } from "./components/WebhookTriggerSection";
 import { useSelectedRunView } from "./useSelectedRunView";
 const anchorStyles =
  "border-b-2 border-transparent pb-1 text-sm font-medium text-slate-600 transition-colors hover:text-slate-900 hover:border-slate-900";
 interface Props {
  agent: LibraryAgent;
  runId: string;
@@ -61,6 +65,13 @@ export function SelectedRunView({
  const withSummary = run?.stats?.activity_status;
  const withReviews = run?.status === AgentExecutionStatus.REVIEW;
  function scrollToSection(id: string) {
    const element = document.getElementById(id);
    if (element) {
      element.scrollIntoView({ behavior: "smooth", block: "start" });
    }
  }
  if (responseError || httpError) {
    return (
      <ErrorCard
@@ -101,116 +112,118 @@ export function SelectedRunView({
                />
              )}
-            <ScrollableTabs
+            {/* Navigation Links */}
-              defaultValue="output"
+            <AnchorLinksWrap>
-              className="-mt-2 flex flex-col"
+              {withSummary && (
-            >
+                <button
-              <ScrollableTabsList className="px-4">
+                  onClick={() => scrollToSection("summary")}
-                {withSummary && (
+                  className={anchorStyles}
-                  <ScrollableTabsTrigger value="summary">
+                >
-                    Summary
+                  Summary
-                  </ScrollableTabsTrigger>
+                </button>
-                )}
+              )}
-                <ScrollableTabsTrigger value="output">
+              <button
-                  Output
+                onClick={() => scrollToSection("output")}
-                </ScrollableTabsTrigger>
+                className={anchorStyles}
-                <ScrollableTabsTrigger value="input">
+              >
-                  Your input
+                Output
-                </ScrollableTabsTrigger>
+              </button>
-                {withReviews && (
+              <button
-                  <ScrollableTabsTrigger value="reviews">
+                onClick={() => scrollToSection("input")}
-                    Reviews ({pendingReviews.length})
+                className={anchorStyles}
-                  </ScrollableTabsTrigger>
+              >
-                )}
+                Your input
-              </ScrollableTabsList>
+              </button>
-              <div className="my-6 flex flex-col gap-6">
+              {withReviews && (
-                {/* Summary Section */}
+                <button
-                {withSummary && (
+                  onClick={() => scrollToSection("reviews")}
-                  <ScrollableTabsContent value="summary">
+                  className={anchorStyles}
-                    <div className="scroll-mt-4">
+                >
-                      <RunDetailCard
+                  Reviews ({pendingReviews.length})
-                        title={
+                </button>
-                          <div className="flex items-center gap-1">
+              )}
-                            <Text variant="lead-semibold">Summary</Text>
+            </AnchorLinksWrap>
-                            <InformationTooltip
+
-                              iconSize={20}
+            {/* Summary Section */}
-                              description="This AI-generated summary describes how the agent handled your task. It's an experimental feature and may occasionally be inaccurate."
+            {withSummary && (
              <div id="summary" className="scroll-mt-4">
                <RunDetailCard
                  title={
                    <div className="flex items-center gap-2">
                      <Text variant="lead-semibold">Summary</Text>
                      <TooltipProvider>
                        <Tooltip>
                          <TooltipTrigger asChild>
                            <InfoIcon
                              size={16}
                              className="cursor-help text-neutral-500 hover:text-neutral-700"
                            />
-                          </div>
+                          </TooltipTrigger>
-                        }
+                          <TooltipContent>
-                      >
+                            <p className="max-w-xs">
-                        <RunSummary run={run} />
+                              This AI-generated summary describes how the agent
-                      </RunDetailCard>
+                              handled your task. It&apos;s an experimental
                              feature and may occasionally be inaccurate.
                            </p>
                          </TooltipContent>
                        </Tooltip>
                      </TooltipProvider>
                    </div>
-                  </ScrollableTabsContent>
+                  }
-                )}
+                >
-
+                  <RunSummary run={run} />
-                {/* Output Section */}
+                </RunDetailCard>
                <ScrollableTabsContent value="output">
                  <div className="scroll-mt-4">
                    <RunDetailCard title="Output">
                      {isLoading ? (
                        <div className="text-neutral-500">
                          <LoadingSpinner />
                        </div>
                      ) : run && "outputs" in run ? (
                        <RunOutputs outputs={run.outputs as any} />
                      ) : (
                        <Text variant="body" className="text-neutral-600">
                          No output from this run.
                        </Text>
                      )}
                    </RunDetailCard>
                  </div>
                </ScrollableTabsContent>
                {/* Input Section */}
                <ScrollableTabsContent value="input">
                  <div id="input" className="scroll-mt-4">
                    <RunDetailCard
                      title={
                        <div className="flex items-center gap-1">
                          <Text variant="lead-semibold">Your input</Text>
                          <InformationTooltip
                            iconSize={20}
                            description="This is the input that was provided to the agent for running this task."
                          />
                        </div>
                      }
                    >
                      <AgentInputsReadOnly
                        agent={agent}
                        inputs={run?.inputs}
                        credentialInputs={run?.credential_inputs}
                      />
                    </RunDetailCard>
                  </div>
                </ScrollableTabsContent>
                {/* Reviews Section */}
                {withReviews && (
                  <ScrollableTabsContent value="reviews">
                    <div className="scroll-mt-4">
                      <RunDetailCard>
                        {reviewsLoading ? (
                          <LoadingSpinner size="small" />
                        ) : pendingReviews.length > 0 ? (
                          <PendingReviewsList
                            reviews={pendingReviews}
                            onReviewComplete={refetchReviews}
                            emptyMessage="No pending reviews for this execution"
                          />
                        ) : (
                          <Text variant="body" className="text-zinc-700">
                            No pending reviews for this execution
                          </Text>
                        )}
                      </RunDetailCard>
                    </div>
                  </ScrollableTabsContent>
                )}
              </div>
-            </ScrollableTabs>
+            )}
            {/* Output Section */}
            <div id="output" className="scroll-mt-4">
              <RunDetailCard title="Output">
                {isLoading ? (
                  <div className="text-neutral-500">
                    <LoadingSpinner />
                  </div>
                ) : run && "outputs" in run ? (
                  <RunOutputs outputs={run.outputs as any} />
                ) : (
                  <Text variant="body" className="text-neutral-600">
                    No output from this run.
                  </Text>
                )}
              </RunDetailCard>
            </div>
            {/* Input Section */}
            <div id="input" className="scroll-mt-4">
              <RunDetailCard title="Your input">
                <AgentInputsReadOnly
                  agent={agent}
                  inputs={run?.inputs}
                  credentialInputs={run?.credential_inputs}
                />
              </RunDetailCard>
            </div>
            {/* Reviews Section */}
            {withReviews && (
              <div id="reviews" className="scroll-mt-4">
                <RunDetailCard>
                  {reviewsLoading ? (
                    <div className="text-neutral-500">Loading reviews…</div>
                  ) : pendingReviews.length > 0 ? (
                    <PendingReviewsList
                      reviews={pendingReviews}
                      onReviewComplete={refetchReviews}
                      emptyMessage="No pending reviews for this execution"
                    />
                  ) : (
                    <div className="text-neutral-600">
                      No pending reviews for this execution
                    </div>
                  )}
                </RunDetailCard>
              </div>
            )}
          </div>
        </SelectedViewLayout>
      </div>
--- a/autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/NewAgentLibraryView/components/selected-views/SelectedScheduleView/SelectedScheduleView.tsx
+++ b/autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/NewAgentLibraryView/components/selected-views/SelectedScheduleView/SelectedScheduleView.tsx
@@ -9,6 +9,7 @@ import { humanizeCronExpression } from "@/lib/cron-expression-utils";
 import { isLargeScreen, useBreakpoint } from "@/lib/hooks/useBreakpoint";
 import { formatInTimezone, getTimezoneDisplayName } from "@/lib/timezone-utils";
 import { AgentInputsReadOnly } from "../../modals/AgentInputsReadOnly/AgentInputsReadOnly";
 import { AnchorLinksWrap } from "../AnchorLinksWrap";
 import { LoadingSelectedContent } from "../LoadingSelectedContent";
 import { RunDetailCard } from "../RunDetailCard/RunDetailCard";
 import { RunDetailHeader } from "../RunDetailHeader/RunDetailHeader";
@@ -16,6 +17,9 @@ import { SelectedViewLayout } from "../SelectedViewLayout";
 import { SelectedScheduleActions } from "./components/SelectedScheduleActions";
 import { useSelectedScheduleView } from "./useSelectedScheduleView";
 const anchorStyles =
  "border-b-2 border-transparent pb-1 text-sm font-medium text-slate-600 transition-colors hover:text-slate-900 hover:border-slate-900";
 interface Props {
  agent: LibraryAgent;
  scheduleId: string;
@@ -41,6 +45,13 @@ export function SelectedScheduleView({
  const breakpoint = useBreakpoint();
  const isLgScreenUp = isLargeScreen(breakpoint);
  function scrollToSection(id: string) {
    const element = document.getElementById(id);
    if (element) {
      element.scrollIntoView({ behavior: "smooth", block: "start" });
    }
  }
  if (error) {
    return (
      <ErrorCard
@@ -97,6 +108,22 @@ export function SelectedScheduleView({
              ) : null}
            </div>
            {/* Navigation Links */}
            <AnchorLinksWrap>
              <button
                onClick={() => scrollToSection("schedule")}
                className={anchorStyles}
              >
                Schedule
              </button>
              <button
                onClick={() => scrollToSection("input")}
                className={anchorStyles}
              >
                Your input
              </button>
            </AnchorLinksWrap>
            {/* Schedule Section */}
            <div id="schedule" className="scroll-mt-4">
              <RunDetailCard title="Schedule">
--- a/autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/NewAgentLibraryView/components/selected-views/SelectedScheduleView/components/EditInputsModal/EditInputsModal.tsx
+++ b/autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/NewAgentLibraryView/components/selected-views/SelectedScheduleView/components/EditInputsModal/EditInputsModal.tsx
@@ -0,0 +1,84 @@
 "use client";
 import type { GraphExecutionJobInfo } from "@/app/api/__generated__/models/graphExecutionJobInfo";
 import type { LibraryAgent } from "@/app/api/__generated__/models/libraryAgent";
 import { Button } from "@/components/atoms/Button/Button";
 import { Text } from "@/components/atoms/Text/Text";
 import { Dialog } from "@/components/molecules/Dialog/Dialog";
 import { PencilSimpleIcon } from "@phosphor-icons/react";
 import { RunAgentInputs } from "../../../../modals/RunAgentInputs/RunAgentInputs";
 import { useEditInputsModal } from "./useEditInputsModal";
 type Props = {
  agent: LibraryAgent;
  schedule: GraphExecutionJobInfo;
 };
 export function EditInputsModal({ agent, schedule }: Props) {
  const {
    isOpen,
    setIsOpen,
    inputFields,
    values,
    setValues,
    handleSave,
    isSaving,
  } = useEditInputsModal(agent, schedule);
  return (
    <Dialog
      controlled={{ isOpen, set: setIsOpen }}
      styling={{ maxWidth: "32rem" }}
    >
      <Dialog.Trigger>
        <Button
          variant="ghost"
          size="small"
          className="absolute -right-2 -top-2"
        >
          <PencilSimpleIcon className="size-4" /> Edit inputs
        </Button>
      </Dialog.Trigger>
      <Dialog.Content>
        <div className="flex flex-col gap-4">
          <Text variant="h3">Edit inputs</Text>
          <div className="flex flex-col gap-4">
            {Object.entries(inputFields).map(([key, fieldSchema]) => (
              <div key={key} className="flex flex-col gap-1.5">
                <label className="text-sm font-medium">
                  {fieldSchema?.title || key}
                </label>
                <RunAgentInputs
                  schema={fieldSchema as any}
                  value={values[key]}
                  onChange={(v) => setValues((prev) => ({ ...prev, [key]: v }))}
                />
              </div>
            ))}
          </div>
        </div>
        <Dialog.Footer>
          <div className="flex w-full justify-end gap-2">
            <Button
              variant="secondary"
              size="small"
              onClick={() => setIsOpen(false)}
              className="min-w-32"
            >
              Cancel
            </Button>
            <Button
              variant="primary"
              size="small"
              onClick={handleSave}
              loading={isSaving}
              className="min-w-32"
            >
              {isSaving ? "Saving…" : "Save"}
            </Button>
          </div>
        </Dialog.Footer>
      </Dialog.Content>
    </Dialog>
  );
 }
--- a/autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/NewAgentLibraryView/components/selected-views/SelectedScheduleView/components/EditInputsModal/useEditInputsModal.ts
+++ b/autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/NewAgentLibraryView/components/selected-views/SelectedScheduleView/components/EditInputsModal/useEditInputsModal.ts
@@ -0,0 +1,78 @@
 "use client";
 import { useMemo, useState } from "react";
 import { useQueryClient } from "@tanstack/react-query";
 import { getGetV1ListExecutionSchedulesForAGraphQueryKey } from "@/app/api/__generated__/endpoints/schedules/schedules";
 import type { LibraryAgent } from "@/app/api/__generated__/models/libraryAgent";
 import type { GraphExecutionJobInfo } from "@/app/api/__generated__/models/graphExecutionJobInfo";
 import { useToast } from "@/components/molecules/Toast/use-toast";
 function getAgentInputFields(agent: LibraryAgent): Record<string, any> {
  const schema = agent.input_schema as unknown as {
    properties?: Record<string, any>;
  } | null;
  if (!schema || !schema.properties) return {};
  const properties = schema.properties as Record<string, any>;
  const visibleEntries = Object.entries(properties).filter(
    ([, sub]) => !sub?.hidden,
  );
  return Object.fromEntries(visibleEntries);
 }
 export function useEditInputsModal(
  agent: LibraryAgent,
  schedule: GraphExecutionJobInfo,
 ) {
  const queryClient = useQueryClient();
  const { toast } = useToast();
  const [isOpen, setIsOpen] = useState(false);
  const [isSaving, setIsSaving] = useState(false);
  const inputFields = useMemo(() => getAgentInputFields(agent), [agent]);
  const [values, setValues] = useState<Record<string, any>>({
    ...(schedule.input_data as Record<string, any>),
  });
  async function handleSave() {
    setIsSaving(true);
    try {
      const res = await fetch(`/api/schedules/${schedule.id}`, {
        method: "PATCH",
        headers: { "Content-Type": "application/json" },
        body: JSON.stringify({ inputs: values }),
      });
      if (!res.ok) {
        let message = "Failed to update schedule inputs";
        const data = await res.json();
        message = data?.message || data?.detail || message;
        throw new Error(message);
      }
      await queryClient.invalidateQueries({
        queryKey: getGetV1ListExecutionSchedulesForAGraphQueryKey(
          schedule.graph_id,
        ),
      });
      toast({
        title: "Schedule inputs updated",
      });
      setIsOpen(false);
    } catch (error: any) {
      toast({
        title: "Failed to update schedule inputs",
        description: error?.message || "An unexpected error occurred.",
        variant: "destructive",
      });
    }
    setIsSaving(false);
  }
  return {
    isOpen,
    setIsOpen,
    inputFields,
    values,
    setValues,
    handleSave,
    isSaving,
  } as const;
 }
--- a/autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/NewAgentLibraryView/components/selected-views/SelectedScheduleView/components/SelectedScheduleActions.tsx
+++ b/autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/NewAgentLibraryView/components/selected-views/SelectedScheduleView/components/SelectedScheduleActions.tsx
@@ -25,10 +25,9 @@ export function SelectedScheduleActions({ agent, scheduleId }: Props) {
          <Button
            variant="icon"
            size="icon"
            aria-label="Open in builder"
            as="NextLink"
            href={openInBuilderHref}
            target="_blank"
            aria-label="View scheduled task details"
          >
            <EyeIcon weight="bold" size={18} className="text-zinc-700" />
          </Button>
--- a/autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/NewAgentLibraryView/components/selected-views/SelectedTemplateView/SelectedTemplateView.tsx
+++ b/autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/NewAgentLibraryView/components/selected-views/SelectedTemplateView/SelectedTemplateView.tsx
@@ -4,6 +4,7 @@ import type { GraphExecutionMeta } from "@/app/api/__generated__/models/graphExe
 import type { LibraryAgent } from "@/app/api/__generated__/models/libraryAgent";
 import { Input } from "@/components/atoms/Input/Input";
 import { ErrorCard } from "@/components/molecules/ErrorCard/ErrorCard";
 import { InformationTooltip } from "@/components/molecules/InformationTooltip/InformationTooltip";
 import {
  getAgentCredentialsFields,
  getAgentInputFields,
@@ -137,13 +138,25 @@ export function SelectedTemplateView({
              <RunDetailCard title="Your Input">
                <div className="flex flex-col gap-4">
                  {inputFields.map(([key, inputSubSchema]) => (
-                    <RunAgentInputs
+                    <div
                      key={key}
-                      schema={inputSubSchema}
+                      className="flex w-full flex-col gap-0 space-y-2"
-                      value={inputs[key] ?? inputSubSchema.default}
+                    >
-                      placeholder={inputSubSchema.description}
+                      <label className="flex items-center gap-1 text-sm font-medium">
-                      onChange={(value) => setInputValue(key, value)}
+                        {inputSubSchema.title || key}
-                    />
+                        {inputSubSchema.description && (
                          <InformationTooltip
                            description={inputSubSchema.description}
                          />
                        )}
                      </label>
                      <RunAgentInputs
                        schema={inputSubSchema}
                        value={inputs[key] ?? inputSubSchema.default}
                        placeholder={inputSubSchema.description}
                        onChange={(value) => setInputValue(key, value)}
                      />
                    </div>
                  ))}
                </div>
              </RunDetailCard>
--- a/autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/NewAgentLibraryView/components/selected-views/SelectedTriggerView/SelectedTriggerView.tsx
+++ b/autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/NewAgentLibraryView/components/selected-views/SelectedTriggerView/SelectedTriggerView.tsx
@@ -3,6 +3,7 @@
 import type { LibraryAgent } from "@/app/api/__generated__/models/libraryAgent";
 import { Input } from "@/components/atoms/Input/Input";
 import { ErrorCard } from "@/components/molecules/ErrorCard/ErrorCard";
 import { InformationTooltip } from "@/components/molecules/InformationTooltip/InformationTooltip";
 import {
  getAgentCredentialsFields,
  getAgentInputFields,
@@ -130,13 +131,25 @@ export function SelectedTriggerView({
              <RunDetailCard title="Your Input">
                <div className="flex flex-col gap-4">
                  {inputFields.map(([key, inputSubSchema]) => (
-                    <RunAgentInputs
+                    <div
                      key={key}
-                      schema={inputSubSchema}
+                      className="flex w-full flex-col gap-0 space-y-2"
-                      value={inputs[key] ?? inputSubSchema.default}
+                    >
-                      placeholder={inputSubSchema.description}
+                      <label className="flex items-center gap-1 text-sm font-medium">
-                      onChange={(value) => setInputValue(key, value)}
+                        {inputSubSchema.title || key}
-                    />
+                        {inputSubSchema.description && (
                          <InformationTooltip
                            description={inputSubSchema.description}
                          />
                        )}
                      </label>
                      <RunAgentInputs
                        schema={inputSubSchema}
                        value={inputs[key] ?? inputSubSchema.default}
                        placeholder={inputSubSchema.description}
                        onChange={(value) => setInputValue(key, value)}
                      />
                    </div>
                  ))}
                </div>
              </RunDetailCard>
--- a/autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/OldAgentLibraryView/components/agent-run-draft-view.tsx
+++ b/autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/OldAgentLibraryView/components/agent-run-draft-view.tsx
@@ -680,20 +680,28 @@ export function AgentRunDraftView({
            {/* Regular inputs */}
            {Object.entries(agentInputFields).map(([key, inputSubSchema]) => (
-              <RunAgentInputs
+              <div key={key} className="flex flex-col space-y-2">
-                key={key}
+                <label className="flex items-center gap-1 text-sm font-medium">
-                schema={inputSubSchema}
+                  {inputSubSchema.title || key}
-                value={inputValues[key] ?? inputSubSchema.default}
+                  <InformationTooltip
-                placeholder={inputSubSchema.description}
+                    description={inputSubSchema.description}
-                onChange={(value) => {
+                  />
-                  setInputValues((obj) => ({
+                </label>
-                    ...obj,
+
-                    [key]: value,
+                <RunAgentInputs
-                  }));
+                  schema={inputSubSchema}
-                  setChangedPresetAttributes((prev) => prev.add("inputs"));
+                  value={inputValues[key] ?? inputSubSchema.default}
-                }}
+                  placeholder={inputSubSchema.description}
-                data-testid={`agent-input-${key}`}
+                  onChange={(value) => {
-              />
+                    setInputValues((obj) => ({
                      ...obj,
                      [key]: value,
                    }));
                    setChangedPresetAttributes((prev) => prev.add("inputs"));
                  }}
                  data-testid={`agent-input-${key}`}
                />
              </div>
            ))}
          </CardContent>
        </Card>
--- a/autogpt_platform/frontend/src/app/providers.tsx
+++ b/autogpt_platform/frontend/src/app/providers.tsx
@@ -1,33 +1,36 @@
 "use client";
-import { TooltipProvider } from "@/components/atoms/Tooltip/BaseTooltip";
+import { LaunchDarklyProvider } from "@/services/feature-flags/feature-flag-provider";
-import { SentryUserTracker } from "@/components/monitor/SentryUserTracker";
+import OnboardingProvider from "@/providers/onboarding/onboarding-provider";
 import { BackendAPIProvider } from "@/lib/autogpt-server-api/context";
 import { getQueryClient } from "@/lib/react-query/queryClient";
 import CredentialsProvider from "@/providers/agent-credentials/credentials-provider";
 import OnboardingProvider from "@/providers/onboarding/onboarding-provider";
 import { LaunchDarklyProvider } from "@/services/feature-flags/feature-flag-provider";
 import { QueryClientProvider } from "@tanstack/react-query";
-import { ThemeProvider, ThemeProviderProps } from "next-themes";
+import {
  ThemeProvider as NextThemesProvider,
  ThemeProviderProps,
 } from "next-themes";
 import { NuqsAdapter } from "nuqs/adapters/next/app";
 import { TooltipProvider } from "@/components/atoms/Tooltip/BaseTooltip";
 import CredentialsProvider from "@/providers/agent-credentials/credentials-provider";
 import { SentryUserTracker } from "@/components/monitor/SentryUserTracker";
 export function Providers({ children, ...props }: ThemeProviderProps) {
  const queryClient = getQueryClient();
  return (
    <QueryClientProvider client={queryClient}>
      <NuqsAdapter>
-        <BackendAPIProvider>
+        <NextThemesProvider {...props}>
-          <SentryUserTracker />
+          <BackendAPIProvider>
-          <CredentialsProvider>
+            <SentryUserTracker />
-            <LaunchDarklyProvider>
+            <CredentialsProvider>
-              <OnboardingProvider>
+              <LaunchDarklyProvider>
-                <ThemeProvider forcedTheme="light" {...props}>
+                <OnboardingProvider>
                  <TooltipProvider>{children}</TooltipProvider>
-                </ThemeProvider>
+                </OnboardingProvider>
-              </OnboardingProvider>
+              </LaunchDarklyProvider>
-            </LaunchDarklyProvider>
+            </CredentialsProvider>
-          </CredentialsProvider>
+          </BackendAPIProvider>
-        </BackendAPIProvider>
+        </NextThemesProvider>
      </NuqsAdapter>
    </QueryClientProvider>
  );
--- a/autogpt_platform/frontend/src/components/molecules/InformationTooltip/InformationTooltip.tsx
+++ b/autogpt_platform/frontend/src/components/molecules/InformationTooltip/InformationTooltip.tsx
@@ -9,20 +9,16 @@ import ReactMarkdown from "react-markdown";
 type Props = {
  description?: string;
  iconSize?: number;
 };
-export function InformationTooltip({ description, iconSize = 24 }: Props) {
+export function InformationTooltip({ description }: Props) {
  if (!description) return null;
  return (
    <TooltipProvider delayDuration={400}>
      <Tooltip>
        <TooltipTrigger asChild>
-          <Info
+          <Info className="rounded-full p-1 hover:bg-slate-50" size={24} />
            className="rounded-full p-1 hover:bg-slate-50"
            size={iconSize}
          />
        </TooltipTrigger>
        <TooltipContent>
          <ReactMarkdown
--- a/autogpt_platform/frontend/src/components/molecules/ScrollableTabs/ScrollableTabs.stories.tsx
+++ b/autogpt_platform/frontend/src/components/molecules/ScrollableTabs/ScrollableTabs.stories.tsx
@@ -1,437 +0,0 @@
 import type { Meta, StoryObj } from "@storybook/nextjs";
 import {
  ScrollableTabs,
  ScrollableTabsContent,
  ScrollableTabsList,
  ScrollableTabsTrigger,
 } from "./ScrollableTabs";
 const meta = {
  title: "Molecules/ScrollableTabs",
  component: ScrollableTabs,
  parameters: {
    layout: "fullscreen",
  },
  tags: ["autodocs"],
  argTypes: {},
 } satisfies Meta<typeof ScrollableTabs>;
 export default meta;
 type Story = StoryObj<typeof meta>;
 function ScrollableTabsDemo() {
  return (
    <div className="flex flex-col gap-8 p-8">
      <h2 className="text-2xl font-bold">ScrollableTabs Examples</h2>
      <div className="space-y-6">
        <div>
          <h3 className="mb-4 text-lg font-semibold">
            Short Content (Tabs Hidden)
          </h3>
          <div className="h-[300px] overflow-y-auto border border-zinc-200">
            <ScrollableTabs defaultValue="tab1" className="h-full">
              <ScrollableTabsList>
                <ScrollableTabsTrigger value="tab1">
                  Account
                </ScrollableTabsTrigger>
                <ScrollableTabsTrigger value="tab2">
                  Password
                </ScrollableTabsTrigger>
                <ScrollableTabsTrigger value="tab3">
                  Settings
                </ScrollableTabsTrigger>
              </ScrollableTabsList>
              <ScrollableTabsContent value="tab1">
                <div className="p-4 text-sm">
                  Make changes to your account here. Click save when you&apos;re
                  done.
                </div>
              </ScrollableTabsContent>
              <ScrollableTabsContent value="tab2">
                <div className="p-4 text-sm">
                  Change your password here. After saving, you&apos;ll be logged
                  out.
                </div>
              </ScrollableTabsContent>
              <ScrollableTabsContent value="tab3">
                <div className="p-4 text-sm">
                  Update your preferences and settings here.
                </div>
              </ScrollableTabsContent>
            </ScrollableTabs>
          </div>
        </div>
        <div>
          <h3 className="mb-4 text-lg font-semibold">
            Long Content (Tabs Visible)
          </h3>
          <div className="h-[400px] overflow-y-auto border border-zinc-200">
            <ScrollableTabs defaultValue="tab1" className="h-full">
              <ScrollableTabsList>
                <ScrollableTabsTrigger value="tab1">
                  Account
                </ScrollableTabsTrigger>
                <ScrollableTabsTrigger value="tab2">
                  Password
                </ScrollableTabsTrigger>
                <ScrollableTabsTrigger value="tab3">
                  Settings
                </ScrollableTabsTrigger>
              </ScrollableTabsList>
              <ScrollableTabsContent value="tab1">
                <div className="p-8 text-sm">
                  <h4 className="mb-4 text-lg font-semibold">
                    Account Settings
                  </h4>
                  <p className="mb-4">
                    Make changes to your account here. Click save when
                    you&apos;re done.
                  </p>
                  <p className="mb-4">
                    Lorem ipsum dolor sit amet, consectetur adipiscing elit. Sed
                    do eiusmod tempor incididunt ut labore et dolore magna
                    aliqua. Ut enim ad minim veniam, quis nostrud exercitation
                    ullamco laboris.
                  </p>
                  <p className="mb-4">
                    Duis aute irure dolor in reprehenderit in voluptate velit
                    esse cillum dolore eu fugiat nulla pariatur. Excepteur sint
                    occaecat cupidatat non proident.
                  </p>
                  <p>
                    Sed ut perspiciatis unde omnis iste natus error sit
                    voluptatem accusantium doloremque laudantium, totam rem
                    aperiam.
                  </p>
                </div>
              </ScrollableTabsContent>
              <ScrollableTabsContent value="tab2">
                <div className="p-8 text-sm">
                  <h4 className="mb-4 text-lg font-semibold">
                    Password Settings
                  </h4>
                  <p className="mb-4">
                    Change your password here. After saving, you&apos;ll be
                    logged out.
                  </p>
                  <p className="mb-4">
                    At vero eos et accusamus et iusto odio dignissimos ducimus
                    qui blanditiis praesentium voluptatum deleniti atque
                    corrupti quos dolores et quas molestias excepturi sint
                    occaecati cupiditate.
                  </p>
                  <p className="mb-4">
                    Et harum quidem rerum facilis est et expedita distinctio.
                    Nam libero tempore, cum soluta nobis est eligendi optio
                    cumque nihil impedit quo minus.
                  </p>
                  <p>
                    Temporibus autem quibusdam et aut officiis debitis aut rerum
                    necessitatibus saepe eveniet ut et voluptates repudiandae
                    sint.
                  </p>
                </div>
              </ScrollableTabsContent>
              <ScrollableTabsContent value="tab3">
                <div className="p-8 text-sm">
                  <h4 className="mb-4 text-lg font-semibold">
                    General Settings
                  </h4>
                  <p className="mb-4">
                    Update your preferences and settings here.
                  </p>
                  <p className="mb-4">
                    Nemo enim ipsam voluptatem quia voluptas sit aspernatur aut
                    odit aut fugit, sed quia consequuntur magni dolores eos qui
                    ratione voluptatem sequi nesciunt.
                  </p>
                  <p className="mb-4">
                    Neque porro quisquam est, qui dolorem ipsum quia dolor sit
                    amet, consectetur, adipisci velit, sed quia non numquam eius
                    modi tempora incidunt ut labore et dolore magnam aliquam
                    quaerat voluptatem.
                  </p>
                  <p>
                    Ut enim ad minima veniam, quis nostrum exercitationem ullam
                    corporis suscipit laboriosam, nisi ut aliquid ex ea commodi
                    consequatur.
                  </p>
                </div>
              </ScrollableTabsContent>
            </ScrollableTabs>
          </div>
        </div>
        <div>
          <h3 className="mb-4 text-lg font-semibold">Many Tabs</h3>
          <div className="h-[500px] overflow-y-auto border border-zinc-200">
            <ScrollableTabs defaultValue="overview" className="h-full">
              <ScrollableTabsList>
                <ScrollableTabsTrigger value="overview">
                  Overview
                </ScrollableTabsTrigger>
                <ScrollableTabsTrigger value="analytics">
                  Analytics
                </ScrollableTabsTrigger>
                <ScrollableTabsTrigger value="reports">
                  Reports
                </ScrollableTabsTrigger>
                <ScrollableTabsTrigger value="notifications">
                  Notifications
                </ScrollableTabsTrigger>
                <ScrollableTabsTrigger value="integrations">
                  Integrations
                </ScrollableTabsTrigger>
                <ScrollableTabsTrigger value="billing">
                  Billing
                </ScrollableTabsTrigger>
              </ScrollableTabsList>
              <ScrollableTabsContent value="overview">
                <div className="p-8 text-sm">
                  <h4 className="mb-4 text-lg font-semibold">
                    Dashboard Overview
                  </h4>
                  <p className="mb-4">
                    Dashboard overview with key metrics and recent activity.
                  </p>
                  <p className="mb-4">
                    Lorem ipsum dolor sit amet, consectetur adipiscing elit. Sed
                    do eiusmod tempor incididunt ut labore et dolore magna
                    aliqua.
                  </p>
                  <p>
                    Ut enim ad minim veniam, quis nostrud exercitation ullamco
                    laboris nisi ut aliquip ex ea commodo consequat.
                  </p>
                </div>
              </ScrollableTabsContent>
              <ScrollableTabsContent value="analytics">
                <div className="p-8 text-sm">
                  <h4 className="mb-4 text-lg font-semibold">Analytics</h4>
                  <p className="mb-4">
                    Detailed analytics and performance metrics.
                  </p>
                  <p className="mb-4">
                    Duis aute irure dolor in reprehenderit in voluptate velit
                    esse cillum dolore eu fugiat nulla pariatur.
                  </p>
                  <p>
                    Excepteur sint occaecat cupidatat non proident, sunt in
                    culpa qui officia deserunt mollit anim id est laborum.
                  </p>
                </div>
              </ScrollableTabsContent>
              <ScrollableTabsContent value="reports">
                <div className="p-8 text-sm">
                  <h4 className="mb-4 text-lg font-semibold">Reports</h4>
                  <p className="mb-4">
                    Generate and view reports for your account.
                  </p>
                  <p className="mb-4">
                    Sed ut perspiciatis unde omnis iste natus error sit
                    voluptatem accusantium doloremque laudantium.
                  </p>
                  <p>
                    Totam rem aperiam, eaque ipsa quae ab illo inventore
                    veritatis et quasi architecto beatae vitae dicta sunt
                    explicabo.
                  </p>
                </div>
              </ScrollableTabsContent>
              <ScrollableTabsContent value="notifications">
                <div className="p-8 text-sm">
                  <h4 className="mb-4 text-lg font-semibold">Notifications</h4>
                  <p className="mb-4">Manage your notification preferences.</p>
                  <p className="mb-4">
                    Nemo enim ipsam voluptatem quia voluptas sit aspernatur aut
                    odit aut fugit.
                  </p>
                  <p>
                    Sed quia consequuntur magni dolores eos qui ratione
                    voluptatem sequi nesciunt.
                  </p>
                </div>
              </ScrollableTabsContent>
              <ScrollableTabsContent value="integrations">
                <div className="p-8 text-sm">
                  <h4 className="mb-4 text-lg font-semibold">Integrations</h4>
                  <p className="mb-4">
                    Connect and manage third-party integrations.
                  </p>
                  <p className="mb-4">
                    Neque porro quisquam est, qui dolorem ipsum quia dolor sit
                    amet.
                  </p>
                  <p>
                    Consectetur, adipisci velit, sed quia non numquam eius modi
                    tempora incidunt.
                  </p>
                </div>
              </ScrollableTabsContent>
              <ScrollableTabsContent value="billing">
                <div className="p-8 text-sm">
                  <h4 className="mb-4 text-lg font-semibold">Billing</h4>
                  <p className="mb-4">
                    View and manage your billing information.
                  </p>
                  <p className="mb-4">
                    Ut enim ad minima veniam, quis nostrum exercitationem ullam
                    corporis suscipit laboriosam.
                  </p>
                  <p>
                    Nisi ut aliquid ex ea commodi consequatur? Quis autem vel
                    eum iure reprehenderit qui in ea voluptate velit esse.
                  </p>
                </div>
              </ScrollableTabsContent>
            </ScrollableTabs>
          </div>
        </div>
      </div>
    </div>
  );
 }
 export const Default = {
  render: () => <ScrollableTabsDemo />,
 } satisfies Story;
 export const ShortContent = {
  render: () => (
    <div className="p-8">
      <div className="h-[200px] overflow-y-auto border border-zinc-200">
        <ScrollableTabs defaultValue="account" className="h-full">
          <ScrollableTabsList>
            <ScrollableTabsTrigger value="account">
              Account
            </ScrollableTabsTrigger>
            <ScrollableTabsTrigger value="password">
              Password
            </ScrollableTabsTrigger>
          </ScrollableTabsList>
          <ScrollableTabsContent value="account">
            <div className="p-4 text-sm">
              Make changes to your account here. Click save when you&apos;re
              done.
            </div>
          </ScrollableTabsContent>
          <ScrollableTabsContent value="password">
            <div className="p-4 text-sm">
              Change your password here. After saving, you&apos;ll be logged
              out.
            </div>
          </ScrollableTabsContent>
        </ScrollableTabs>
      </div>
    </div>
  ),
 } satisfies Story;
 export const LongContent = {
  render: () => (
    <div className="p-8">
      <div className="h-[600px] overflow-y-auto border border-zinc-200">
        <ScrollableTabs defaultValue="tab1" className="h-full">
          <ScrollableTabsList>
            <ScrollableTabsTrigger value="tab1">Account</ScrollableTabsTrigger>
            <ScrollableTabsTrigger value="tab2">Password</ScrollableTabsTrigger>
            <ScrollableTabsTrigger value="tab3">Settings</ScrollableTabsTrigger>
          </ScrollableTabsList>
          <ScrollableTabsContent value="tab1">
            <div className="p-8 text-sm">
              <h4 className="mb-4 text-lg font-semibold">Account Settings</h4>
              <p className="mb-4">
                Make changes to your account here. Click save when you&apos;re
                done.
              </p>
              <p className="mb-4">
                Lorem ipsum dolor sit amet, consectetur adipiscing elit. Sed do
                eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut
                enim ad minim veniam, quis nostrud exercitation ullamco laboris
                nisi ut aliquip ex ea commodo consequat.
              </p>
              <p className="mb-4">
                Duis aute irure dolor in reprehenderit in voluptate velit esse
                cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat
                cupidatat non proident, sunt in culpa qui officia deserunt
                mollit anim id est laborum.
              </p>
              <p className="mb-4">
                Sed ut perspiciatis unde omnis iste natus error sit voluptatem
                accusantium doloremque laudantium, totam rem aperiam, eaque ipsa
                quae ab illo inventore veritatis et quasi architecto beatae
                vitae dicta sunt explicabo.
              </p>
              <p>
                Nemo enim ipsam voluptatem quia voluptas sit aspernatur aut odit
                aut fugit, sed quia consequuntur magni dolores eos qui ratione
                voluptatem sequi nesciunt.
              </p>
            </div>
          </ScrollableTabsContent>
          <ScrollableTabsContent value="tab2">
            <div className="p-8 text-sm">
              <h4 className="mb-4 text-lg font-semibold">Password Settings</h4>
              <p className="mb-4">
                Change your password here. After saving, you&apos;ll be logged
                out.
              </p>
              <p className="mb-4">
                At vero eos et accusamus et iusto odio dignissimos ducimus qui
                blanditiis praesentium voluptatum deleniti atque corrupti quos
                dolores et quas molestias excepturi sint occaecati cupiditate
                non provident.
              </p>
              <p className="mb-4">
                Similique sunt in culpa qui officia deserunt mollitia animi, id
                est laborum et dolorum fuga. Et harum quidem rerum facilis est
                et expedita distinctio.
              </p>
              <p className="mb-4">
                Nam libero tempore, cum soluta nobis est eligendi optio cumque
                nihil impedit quo minus id quod maxime placeat facere possimus,
                omnis voluptas assumenda est, omnis dolor repellendus.
              </p>
              <p>
                Temporibus autem quibusdam et aut officiis debitis aut rerum
                necessitatibus saepe eveniet ut et voluptates repudiandae sint
                et molestiae non recusandae.
              </p>
            </div>
          </ScrollableTabsContent>
          <ScrollableTabsContent value="tab3">
            <div className="p-8 text-sm">
              <h4 className="mb-4 text-lg font-semibold">General Settings</h4>
              <p className="mb-4">Update your preferences and settings here.</p>
              <p className="mb-4">
                Neque porro quisquam est, qui dolorem ipsum quia dolor sit amet,
                consectetur, adipisci velit, sed quia non numquam eius modi
                tempora incidunt ut labore et dolore magnam aliquam quaerat
                voluptatem.
              </p>
              <p className="mb-4">
                Ut enim ad minima veniam, quis nostrum exercitationem ullam
                corporis suscipit laboriosam, nisi ut aliquid ex ea commodi
                consequatur? Quis autem vel eum iure reprehenderit qui in ea
                voluptate velit esse quam nihil molestiae consequatur.
              </p>
              <p className="mb-4">
                Vel illum qui dolorem eum fugiat quo voluptas nulla pariatur? At
                vero eos et accusamus et iusto odio dignissimos ducimus qui
                blanditiis praesentium voluptatum deleniti atque corrupti quos
                dolores.
              </p>
              <p>
                Et quas molestias excepturi sint occaecati cupiditate non
                provident, similique sunt in culpa qui officia deserunt mollitia
                animi, id est laborum et dolorum fuga.
              </p>
            </div>
          </ScrollableTabsContent>
        </ScrollableTabs>
      </div>
    </div>
  ),
 } satisfies Story;
--- a/autogpt_platform/frontend/src/components/molecules/ScrollableTabs/ScrollableTabs.tsx
+++ b/autogpt_platform/frontend/src/components/molecules/ScrollableTabs/ScrollableTabs.tsx
@@ -1,59 +0,0 @@
 "use client";
 import { cn } from "@/lib/utils";
 import { Children } from "react";
 import { ScrollableTabsContent } from "./components/ScrollableTabsContent";
 import { ScrollableTabsList } from "./components/ScrollableTabsList";
 import { ScrollableTabsTrigger } from "./components/ScrollableTabsTrigger";
 import { ScrollableTabsContext } from "./context";
 import { findContentElements, findListElement } from "./helpers";
 import { useScrollableTabsInternal } from "./useScrollableTabs";
 interface Props {
  children?: React.ReactNode;
  className?: string;
  defaultValue?: string;
 }
 export function ScrollableTabs({ children, className, defaultValue }: Props) {
  const {
    activeValue,
    setActiveValue,
    registerContent,
    scrollToSection,
    scrollContainer,
    contentContainerRef,
  } = useScrollableTabsInternal({ defaultValue });
  const childrenArray = Children.toArray(children);
  const listElement = findListElement(childrenArray);
  const contentElements = findContentElements(childrenArray);
  return (
    <ScrollableTabsContext.Provider
      value={{
        activeValue,
        setActiveValue,
        registerContent,
        scrollToSection,
        scrollContainer,
      }}
    >
      <div className={cn("relative flex flex-col", className)}>
        {listElement}
        <div
          ref={(node) => {
            if (contentContainerRef) {
              contentContainerRef.current = node;
            }
          }}
          className="max-h-[64rem] overflow-y-auto scrollbar-thin scrollbar-track-transparent scrollbar-thumb-zinc-300 dark:scrollbar-thumb-zinc-700"
        >
          <div className="min-h-full pb-[200px]">{contentElements}</div>
        </div>
      </div>
    </ScrollableTabsContext.Provider>
  );
 }
 export { ScrollableTabsContent, ScrollableTabsList, ScrollableTabsTrigger };
--- a/autogpt_platform/frontend/src/components/molecules/ScrollableTabs/components/ScrollableTabsContent.tsx
+++ b/autogpt_platform/frontend/src/components/molecules/ScrollableTabs/components/ScrollableTabsContent.tsx
@@ -1,48 +0,0 @@
 "use client";
 import { cn } from "@/lib/utils";
 import * as React from "react";
 import { useScrollableTabs } from "../context";
 interface Props extends React.HTMLAttributes<HTMLDivElement> {
  value: string;
 }
 export const ScrollableTabsContent = React.forwardRef<HTMLDivElement, Props>(
  function ScrollableTabsContent(
    { className, value, children, ...props },
    ref,
  ) {
    const { registerContent } = useScrollableTabs();
    const contentRef = React.useRef<HTMLDivElement>(null);
    React.useEffect(() => {
      if (contentRef.current) {
        registerContent(value, contentRef.current);
      }
      return () => {
        registerContent(value, null);
      };
    }, [value, registerContent]);
    return (
      <div
        ref={(node) => {
          if (typeof ref === "function") ref(node);
          else if (ref) ref.current = node;
          // eslint-disable-next-line @typescript-eslint/ban-ts-comment
          // @ts-ignore
          contentRef.current = node;
        }}
        data-scrollable-tab-content
        data-value={value}
        className={cn("focus-visible:outline-none", className)}
        {...props}
      >
        {children}
      </div>
    );
  },
 );
 ScrollableTabsContent.displayName = "ScrollableTabsContent";
--- a/autogpt_platform/frontend/src/components/molecules/ScrollableTabs/components/ScrollableTabsList.tsx
+++ b/autogpt_platform/frontend/src/components/molecules/ScrollableTabs/components/ScrollableTabsList.tsx
@@ -1,52 +0,0 @@
 "use client";
 import { cn } from "@/lib/utils";
 import * as React from "react";
 import { useScrollableTabs } from "../context";
 export const ScrollableTabsList = React.forwardRef<
  HTMLDivElement,
  React.HTMLAttributes<HTMLDivElement>
 >(function ScrollableTabsList({ className, children, ...props }, ref) {
  const { activeValue } = useScrollableTabs();
  const [activeTabElement, setActiveTabElement] =
    React.useState<HTMLElement | null>(null);
  React.useEffect(() => {
    const activeButton = Array.from(
      document.querySelectorAll<HTMLElement>(
        '[data-scrollable-tab-trigger][data-value="' + activeValue + '"]',
      ),
    )[0];
    if (activeButton) {
      setActiveTabElement(activeButton);
    }
  }, [activeValue]);
  return (
    <div className="relative" ref={ref}>
      <div
        className={cn(
          "inline-flex w-full items-center justify-start border-b border-zinc-100",
          className,
        )}
        {...props}
      >
        {children}
      </div>
      {activeTabElement && (
        <div
          className="transition-left transition-right absolute bottom-0 h-0.5 bg-purple-600 duration-200 ease-in-out"
          style={{
            left: activeTabElement.offsetLeft,
            width: activeTabElement.offsetWidth,
            willChange: "left, width",
          }}
        />
      )}
    </div>
  );
 });
 ScrollableTabsList.displayName = "ScrollableTabsList";
--- a/autogpt_platform/frontend/src/components/molecules/ScrollableTabs/components/ScrollableTabsTrigger.tsx
+++ b/autogpt_platform/frontend/src/components/molecules/ScrollableTabs/components/ScrollableTabsTrigger.tsx
@@ -1,53 +0,0 @@
 "use client";
 import { cn } from "@/lib/utils";
 import * as React from "react";
 import { useScrollableTabs } from "../context";
 interface Props extends React.ButtonHTMLAttributes<HTMLButtonElement> {
  value: string;
 }
 export const ScrollableTabsTrigger = React.forwardRef<HTMLButtonElement, Props>(
  function ScrollableTabsTrigger(
    { className, value, children, ...props },
    ref,
  ) {
    const { activeValue, scrollToSection } = useScrollableTabs();
    const elementRef = React.useRef<HTMLButtonElement>(null);
    const isActive = activeValue === value;
    function handleClick(e: React.MouseEvent<HTMLButtonElement>) {
      e.preventDefault();
      e.stopPropagation();
      scrollToSection(value);
      props.onClick?.(e);
    }
    return (
      <button
        type="button"
        ref={(node) => {
          if (typeof ref === "function") ref(node);
          else if (ref) ref.current = node;
          // eslint-disable-next-line @typescript-eslint/ban-ts-comment
          // @ts-ignore
          elementRef.current = node;
        }}
        data-scrollable-tab-trigger
        data-value={value}
        onClick={handleClick}
        className={cn(
          "relative inline-flex items-center justify-center whitespace-nowrap px-3 py-3 font-sans text-[0.875rem] font-medium leading-[1.5rem] text-zinc-700 transition-all focus-visible:outline-none focus-visible:ring-2 focus-visible:ring-neutral-400 focus-visible:ring-offset-2 disabled:pointer-events-none disabled:opacity-50",
          isActive && "text-purple-600",
          className,
        )}
        {...props}
      >
        {children}
      </button>
    );
  },
 );
 ScrollableTabsTrigger.displayName = "ScrollableTabsTrigger";
--- a/autogpt_platform/frontend/src/components/molecules/ScrollableTabs/context.ts
+++ b/autogpt_platform/frontend/src/components/molecules/ScrollableTabs/context.ts
@@ -1,22 +0,0 @@
 import * as React from "react";
 import { createContext, useContext } from "react";
 interface ScrollableTabsContextValue {
  activeValue: string | null;
  setActiveValue: React.Dispatch<React.SetStateAction<string | null>>;
  registerContent: (value: string, element: HTMLElement | null) => void;
  scrollToSection: (value: string) => void;
  scrollContainer: HTMLElement | null;
 }
 export const ScrollableTabsContext = createContext<
  ScrollableTabsContextValue | undefined
 >(undefined);
 export function useScrollableTabs() {
  const context = useContext(ScrollableTabsContext);
  if (!context) {
    throw new Error("useScrollableTabs must be used within a ScrollableTabs");
  }
  return context;
 }
--- a/autogpt_platform/frontend/src/components/molecules/ScrollableTabs/helpers.ts
+++ b/autogpt_platform/frontend/src/components/molecules/ScrollableTabs/helpers.ts
@@ -1,48 +0,0 @@
 import * as React from "react";
 const HEADER_OFFSET = 100;
 export function calculateScrollPosition(
  elementRect: DOMRect,
  containerRect: DOMRect,
  currentScrollTop: number,
 ): number {
  const elementTopRelativeToContainer =
    elementRect.top - containerRect.top + currentScrollTop - HEADER_OFFSET;
  return Math.max(0, elementTopRelativeToContainer);
 }
 function hasDisplayName(
  type: unknown,
  displayName: string,
 ): type is { displayName: string } {
  return (
    typeof type === "object" &&
    type !== null &&
    "displayName" in type &&
    (type as { displayName: unknown }).displayName === displayName
  );
 }
 export function findListElement(
  children: React.ReactNode[],
 ): React.ReactElement | undefined {
  return children.find(
    (child) =>
      React.isValidElement(child) &&
      hasDisplayName(child.type, "ScrollableTabsList"),
  ) as React.ReactElement | undefined;
 }
 export function findContentElements(
  children: React.ReactNode[],
 ): React.ReactNode[] {
  return children.filter(
    (child) =>
      !(
        React.isValidElement(child) &&
        hasDisplayName(child.type, "ScrollableTabsList")
      ),
  );
 }
--- a/autogpt_platform/frontend/src/components/molecules/ScrollableTabs/useScrollableTabs.ts
+++ b/autogpt_platform/frontend/src/components/molecules/ScrollableTabs/useScrollableTabs.ts
@@ -1,60 +0,0 @@
 import { useCallback, useRef, useState } from "react";
 import { calculateScrollPosition } from "./helpers";
 interface Args {
  defaultValue?: string;
 }
 export function useScrollableTabsInternal({ defaultValue }: Args) {
  const [activeValue, setActiveValue] = useState<string | null>(
    defaultValue || null,
  );
  const contentRefs = useRef<Map<string, HTMLElement>>(new Map());
  const contentContainerRef = useRef<HTMLDivElement | null>(null);
  function registerContent(value: string, element: HTMLElement | null) {
    if (element) {
      contentRefs.current.set(value, element);
    } else {
      contentRefs.current.delete(value);
    }
  }
  function scrollToSection(value: string) {
    const element = contentRefs.current.get(value);
    const scrollContainer = contentContainerRef.current;
    if (!element || !scrollContainer) return;
    setActiveValue(value);
    const containerRect = scrollContainer.getBoundingClientRect();
    const elementRect = element.getBoundingClientRect();
    const currentScrollTop = scrollContainer.scrollTop;
    const scrollTop = calculateScrollPosition(
      elementRect,
      containerRect,
      currentScrollTop,
    );
    const maxScrollTop =
      scrollContainer.scrollHeight - scrollContainer.clientHeight;
    const clampedScrollTop = Math.min(Math.max(0, scrollTop), maxScrollTop);
    scrollContainer.scrollTo({
      top: clampedScrollTop,
      behavior: "smooth",
    });
  }
  const memoizedRegisterContent = useCallback(registerContent, []);
  const memoizedScrollToSection = useCallback(scrollToSection, []);
  return {
    activeValue,
    setActiveValue,
    registerContent: memoizedRegisterContent,
    scrollToSection: memoizedScrollToSection,
    scrollContainer: contentContainerRef.current,
    contentContainerRef,
  };
 }
--- a/autogpt_platform/frontend/src/services/feature-flags/use-get-flag.ts
+++ b/autogpt_platform/frontend/src/services/feature-flags/use-get-flag.ts
@@ -48,7 +48,7 @@ const mockFlags = {
  [Flag.AGENT_FAVORITING]: false,
  [Flag.MARKETPLACE_SEARCH_TERMS]: DEFAULT_SEARCH_TERMS,
  [Flag.ENABLE_PLATFORM_PAYMENT]: false,
-  [Flag.CHAT]: false,
+  [Flag.CHAT]: true,
 };
 export function useGetFlag<T extends Flag>(flag: T): FlagValues[T] | null {
--- a/autogpt_platform/frontend/tailwind.config.ts
+++ b/autogpt_platform/frontend/tailwind.config.ts
@@ -1,10 +1,10 @@
 import scrollbar from "tailwind-scrollbar";
 import type { Config } from "tailwindcss";
 import tailwindcssAnimate from "tailwindcss-animate";
 import scrollbar from "tailwind-scrollbar";
 import { colors } from "./src/components/styles/colors";
 const config = {
-  darkMode: ["class", ".dark-mode"], // ignore dark: prefix classes for now until we fully support dark mode
+  darkMode: ["class"],
  content: ["./src/**/*.{ts,tsx}"],
  prefix: "",
  theme: {
Author	SHA1	Message	Date
Otto	9b20f4cd13	refactor: simplify ExecutionQueue docstrings and move test file - Trim verbose BUG FIX docstring to concise 3-line note - Remove redundant method docstrings (add, get, empty) - Move test file to backend/data/ with proper pytest conventions - Add note about ProcessPoolExecutor migration for future devs Co-authored-by: Zamil Majdy <majdyz@users.noreply.github.com>	2026-02-08 16:11:35 +00:00
Nikhil Bhagat	a3d0f9cbd2	fix(backend): format test_execution_queue.py and remove unused variable	2025-12-14 19:37:29 +05:45
Nikhil Bhagat	02ddb51446	Added test_execution_queue.py and test the execution part and the test got passed	2025-12-14 19:05:14 +05:45
Nikhil Bhagat	750e096f15	fix(backend): replace multiprocessing.Manager().Queue() with queue.Queue() ExecutionQueue was unnecessarily using multiprocessing.Manager().Queue() which spawns a subprocess for IPC. Since ExecutionQueue is only accessed from threads within the same process, queue.Queue() is sufficient and more efficient. - Eliminates unnecessary subprocess spawning per graph execution - Removes IPC overhead for queue operations - Prevents potential resource leaks from Manager processes - Improves scalability for concurrent graph executions	2025-12-14 19:04:14 +05:45