docs: add credentials prerequisites to create-basic-agent guide (#11913)

## Summary
Addresses #11785 - users were encountering `openai_api_key_credentials`
errors when following the create-basic-agent guide because it didn't
mention the need to configure API credentials before using AI blocks.

## Changes
Added a **Prerequisites** section to
`docs/platform/create-basic-agent.md` explaining:
- **Cloud users:** Go to Profile → Integrations to add API keys
- **Self-hosted (Docker):** Add keys to `autogpt_platform/backend/.env`
and restart services

Also added a note that the Calculator example doesn't need credentials,
making it a good first test.

## Related
- Issue: #11785

README.md

@@ -54,7 +54,7 @@ Before proceeding with the installation, ensure your system meets the following
 ### Updated Setup Instructions:
 We've moved to a fully maintained and regularly updated documentation site.
 
-👉 [Follow the official self-hosting guide here](https://docs.agpt.co/platform/getting-started/)
+👉 [Follow the official self-hosting guide here](https://agpt.co/docs/platform/getting-started/getting-started)
 
 
 This tutorial assumes you have Docker, VSCode, git and npm installed.

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

@@ -1834,6 +1834,11 @@ async def _execute_long_running_tool(
             tool_call_id=tool_call_id,
             result=error_response.model_dump_json(),
         )
+        # Generate LLM continuation so user sees explanation even for errors
+        try:
+            await _generate_llm_continuation(session_id=session_id, user_id=user_id)
+        except Exception as llm_err:
+            logger.warning(f"Failed to generate LLM continuation for error: {llm_err}")
     finally:
         await _mark_operation_completed(tool_call_id)
 

autogpt_platform/backend/backend/api/features/chat/tools/agent_generator/__init__.py

@@ -2,30 +2,54 @@
 
 from .core import (
     AgentGeneratorNotConfiguredError,
+    AgentJsonValidationError,
+    AgentSummary,
+    DecompositionResult,
+    DecompositionStep,
+    LibraryAgentSummary,
+    MarketplaceAgentSummary,
     decompose_goal,
+    enrich_library_agents_from_steps,
+    extract_search_terms_from_steps,
+    extract_uuids_from_text,
     generate_agent,
     generate_agent_patch,
     get_agent_as_json,
+    get_all_relevant_agents_for_generation,
+    get_library_agent_by_graph_id,
+    get_library_agent_by_id,
+    get_library_agents_for_generation,
     json_to_graph,
     save_agent_to_library,
+    search_marketplace_agents_for_generation,
 )
 from .errors import get_user_message_for_error
 from .service import health_check as check_external_service_health
 from .service import is_external_service_configured
 
 __all__ = [
-    # Core functions
+    "AgentGeneratorNotConfiguredError",
+    "AgentJsonValidationError",
+    "AgentSummary",
+    "DecompositionResult",
+    "DecompositionStep",
+    "LibraryAgentSummary",
+    "MarketplaceAgentSummary",
+    "check_external_service_health",
     "decompose_goal",
+    "enrich_library_agents_from_steps",
+    "extract_search_terms_from_steps",
+    "extract_uuids_from_text",
     "generate_agent",
     "generate_agent_patch",
-    "save_agent_to_library",
     "get_agent_as_json",
-    "json_to_graph",
+    "get_all_relevant_agents_for_generation",
-    # Exceptions
+    "get_library_agent_by_graph_id",
-    "AgentGeneratorNotConfiguredError",
+    "get_library_agent_by_id",
-    # Service
+    "get_library_agents_for_generation",
-    "is_external_service_configured",
-    "check_external_service_health",
-    # Error handling
     "get_user_message_for_error",
+    "is_external_service_configured",
+    "json_to_graph",
+    "save_agent_to_library",
+    "search_marketplace_agents_for_generation",
 ]

autogpt_platform/backend/backend/api/features/chat/tools/agent_generator/core.py

@@ -1,11 +1,21 @@
 """Core agent generation functions."""
 
 import logging
+import re
 import uuid
-from typing import Any
+from typing import Any, NotRequired, TypedDict
 
 from backend.api.features.library import db as library_db
-from backend.data.graph import Graph, Link, Node, create_graph
+from backend.api.features.store import db as store_db
+from backend.data.graph import (
+    Graph,
+    Link,
+    Node,
+    create_graph,
+    get_graph,
+    get_graph_all_versions,
+)
+from backend.util.exceptions import DatabaseError, NotFoundError
 
 from .service import (
     decompose_goal_external,
@@ -16,6 +26,74 @@ from .service import (
 
 logger = logging.getLogger(__name__)
 
+AGENT_EXECUTOR_BLOCK_ID = "e189baac-8c20-45a1-94a7-55177ea42565"
+
+
+class ExecutionSummary(TypedDict):
+    """Summary of a single execution for quality assessment."""
+
+    status: str
+    correctness_score: NotRequired[float]
+    activity_summary: NotRequired[str]
+
+
+class LibraryAgentSummary(TypedDict):
+    """Summary of a library agent for sub-agent composition.
+
+    Includes recent executions to help the LLM decide whether to use this agent.
+    Each execution shows status, correctness_score (0-1), and activity_summary.
+    """
+
+    graph_id: str
+    graph_version: int
+    name: str
+    description: str
+    input_schema: dict[str, Any]
+    output_schema: dict[str, Any]
+    recent_executions: NotRequired[list[ExecutionSummary]]
+
+
+class MarketplaceAgentSummary(TypedDict):
+    """Summary of a marketplace agent for sub-agent composition."""
+
+    name: str
+    description: str
+    sub_heading: str
+    creator: str
+    is_marketplace_agent: bool
+
+
+class DecompositionStep(TypedDict, total=False):
+    """A single step in decomposed instructions."""
+
+    description: str
+    action: str
+    block_name: str
+    tool: str
+    name: str
+
+
+class DecompositionResult(TypedDict, total=False):
+    """Result from decompose_goal - can be instructions, questions, or error."""
+
+    type: str
+    steps: list[DecompositionStep]
+    questions: list[dict[str, Any]]
+    error: str
+    error_type: str
+
+
+AgentSummary = LibraryAgentSummary | MarketplaceAgentSummary | dict[str, Any]
+
+
+def _to_dict_list(
+    agents: list[AgentSummary] | list[dict[str, Any]] | None,
+) -> list[dict[str, Any]] | None:
+    """Convert typed agent summaries to plain dicts for external service calls."""
+    if agents is None:
+        return None
+    return [dict(a) for a in agents]
+
 
 class AgentGeneratorNotConfiguredError(Exception):
     """Raised when the external Agent Generator service is not configured."""
@@ -36,15 +114,414 @@ def _check_service_configured() -> None:
         )
 
 
-async def decompose_goal(description: str, context: str = "") -> dict[str, Any] | None:
+_UUID_PATTERN = re.compile(
+    r"[a-f0-9]{8}-[a-f0-9]{4}-4[a-f0-9]{3}-[89ab][a-f0-9]{3}-[a-f0-9]{12}",
+    re.IGNORECASE,
+)
+
+
+def extract_uuids_from_text(text: str) -> list[str]:
+    """Extract all UUID v4 strings from text.
+
+    Args:
+        text: Text that may contain UUIDs (e.g., user's goal description)
+
+    Returns:
+        List of unique UUIDs found in the text (lowercase)
+    """
+    matches = _UUID_PATTERN.findall(text)
+    return list({m.lower() for m in matches})
+
+
+async def get_library_agent_by_id(
+    user_id: str, agent_id: str
+) -> LibraryAgentSummary | None:
+    """Fetch a specific library agent by its ID (library agent ID or graph_id).
+
+    This function tries multiple lookup strategies:
+    1. First tries to find by graph_id (AgentGraph primary key)
+    2. If not found, tries to find by library agent ID (LibraryAgent primary key)
+
+    This handles both cases:
+    - User provides graph_id (e.g., from AgentExecutorBlock)
+    - User provides library agent ID (e.g., from library URL)
+
+    Args:
+        user_id: The user ID
+        agent_id: The ID to look up (can be graph_id or library agent ID)
+
+    Returns:
+        LibraryAgentSummary if found, None otherwise
+    """
+    try:
+        agent = await library_db.get_library_agent_by_graph_id(user_id, agent_id)
+        if agent:
+            logger.debug(f"Found library agent by graph_id: {agent.name}")
+            return LibraryAgentSummary(
+                graph_id=agent.graph_id,
+                graph_version=agent.graph_version,
+                name=agent.name,
+                description=agent.description,
+                input_schema=agent.input_schema,
+                output_schema=agent.output_schema,
+            )
+    except DatabaseError:
+        raise
+    except Exception as e:
+        logger.debug(f"Could not fetch library agent by graph_id {agent_id}: {e}")
+
+    try:
+        agent = await library_db.get_library_agent(agent_id, user_id)
+        if agent:
+            logger.debug(f"Found library agent by library_id: {agent.name}")
+            return LibraryAgentSummary(
+                graph_id=agent.graph_id,
+                graph_version=agent.graph_version,
+                name=agent.name,
+                description=agent.description,
+                input_schema=agent.input_schema,
+                output_schema=agent.output_schema,
+            )
+    except NotFoundError:
+        logger.debug(f"Library agent not found by library_id: {agent_id}")
+    except DatabaseError:
+        raise
+    except Exception as e:
+        logger.warning(
+            f"Could not fetch library agent by library_id {agent_id}: {e}",
+            exc_info=True,
+        )
+
+    return None
+
+
+get_library_agent_by_graph_id = get_library_agent_by_id
+
+
+async def get_library_agents_for_generation(
+    user_id: str,
+    search_query: str | None = None,
+    exclude_graph_id: str | None = None,
+    max_results: int = 15,
+) -> list[LibraryAgentSummary]:
+    """Fetch user's library agents formatted for Agent Generator.
+
+    Uses search-based fetching to return relevant agents instead of all agents.
+    This is more scalable for users with large libraries.
+
+    Includes recent_executions list to help the LLM assess agent quality:
+    - Each execution has status, correctness_score (0-1), and activity_summary
+    - This gives the LLM concrete examples of recent performance
+
+    Args:
+        user_id: The user ID
+        search_query: Optional search term to find relevant agents (user's goal/description)
+        exclude_graph_id: Optional graph ID to exclude (prevents circular references)
+        max_results: Maximum number of agents to return (default 15)
+
+    Returns:
+        List of LibraryAgentSummary with schemas and recent executions for sub-agent composition
+    """
+    try:
+        response = await library_db.list_library_agents(
+            user_id=user_id,
+            search_term=search_query,
+            page=1,
+            page_size=max_results,
+            include_executions=True,
+        )
+
+        results: list[LibraryAgentSummary] = []
+        for agent in response.agents:
+            if exclude_graph_id is not None and agent.graph_id == exclude_graph_id:
+                continue
+
+            summary = LibraryAgentSummary(
+                graph_id=agent.graph_id,
+                graph_version=agent.graph_version,
+                name=agent.name,
+                description=agent.description,
+                input_schema=agent.input_schema,
+                output_schema=agent.output_schema,
+            )
+            if agent.recent_executions:
+                exec_summaries: list[ExecutionSummary] = []
+                for ex in agent.recent_executions:
+                    exec_sum = ExecutionSummary(status=ex.status)
+                    if ex.correctness_score is not None:
+                        exec_sum["correctness_score"] = ex.correctness_score
+                    if ex.activity_summary:
+                        exec_sum["activity_summary"] = ex.activity_summary
+                    exec_summaries.append(exec_sum)
+                summary["recent_executions"] = exec_summaries
+            results.append(summary)
+        return results
+    except DatabaseError:
+        raise
+    except Exception as e:
+        logger.warning(f"Failed to fetch library agents: {e}")
+        return []
+
+
+async def search_marketplace_agents_for_generation(
+    search_query: str,
+    max_results: int = 10,
+) -> list[MarketplaceAgentSummary]:
+    """Search marketplace agents formatted for Agent Generator.
+
+    Note: This returns basic agent info. Full input/output schemas would require
+    additional graph fetches and is a potential future enhancement.
+
+    Args:
+        search_query: Search term to find relevant public agents
+        max_results: Maximum number of agents to return (default 10)
+
+    Returns:
+        List of MarketplaceAgentSummary (without detailed schemas for now)
+    """
+    try:
+        response = await store_db.get_store_agents(
+            search_query=search_query,
+            page=1,
+            page_size=max_results,
+        )
+
+        results: list[MarketplaceAgentSummary] = []
+        for agent in response.agents:
+            results.append(
+                MarketplaceAgentSummary(
+                    name=agent.agent_name,
+                    description=agent.description,
+                    sub_heading=agent.sub_heading,
+                    creator=agent.creator,
+                    is_marketplace_agent=True,
+                )
+            )
+        return results
+    except Exception as e:
+        logger.warning(f"Failed to search marketplace agents: {e}")
+        return []
+
+
+async def get_all_relevant_agents_for_generation(
+    user_id: str,
+    search_query: str | None = None,
+    exclude_graph_id: str | None = None,
+    include_library: bool = True,
+    include_marketplace: bool = True,
+    max_library_results: int = 15,
+    max_marketplace_results: int = 10,
+) -> list[AgentSummary]:
+    """Fetch relevant agents from library and/or marketplace.
+
+    Searches both user's library and marketplace by default.
+    Explicitly mentioned UUIDs in the search query are always looked up.
+
+    Args:
+        user_id: The user ID
+        search_query: Search term to find relevant agents (user's goal/description)
+        exclude_graph_id: Optional graph ID to exclude (prevents circular references)
+        include_library: Whether to search user's library (default True)
+        include_marketplace: Whether to also search marketplace (default True)
+        max_library_results: Max library agents to return (default 15)
+        max_marketplace_results: Max marketplace agents to return (default 10)
+
+    Returns:
+        List of AgentSummary, library agents first (with full schemas),
+        then marketplace agents (basic info only)
+    """
+    agents: list[AgentSummary] = []
+    seen_graph_ids: set[str] = set()
+
+    if search_query:
+        mentioned_uuids = extract_uuids_from_text(search_query)
+        for graph_id in mentioned_uuids:
+            if graph_id == exclude_graph_id:
+                continue
+            agent = await get_library_agent_by_graph_id(user_id, graph_id)
+            agent_graph_id = agent.get("graph_id") if agent else None
+            if agent and agent_graph_id and agent_graph_id not in seen_graph_ids:
+                agents.append(agent)
+                seen_graph_ids.add(agent_graph_id)
+                logger.debug(
+                    f"Found explicitly mentioned agent: {agent.get('name') or 'Unknown'}"
+                )
+
+    if include_library:
+        library_agents = await get_library_agents_for_generation(
+            user_id=user_id,
+            search_query=search_query,
+            exclude_graph_id=exclude_graph_id,
+            max_results=max_library_results,
+        )
+        for agent in library_agents:
+            graph_id = agent.get("graph_id")
+            if graph_id and graph_id not in seen_graph_ids:
+                agents.append(agent)
+                seen_graph_ids.add(graph_id)
+
+    if include_marketplace and search_query:
+        marketplace_agents = await search_marketplace_agents_for_generation(
+            search_query=search_query,
+            max_results=max_marketplace_results,
+        )
+        library_names: set[str] = set()
+        for a in agents:
+            name = a.get("name")
+            if name and isinstance(name, str):
+                library_names.add(name.lower())
+        for agent in marketplace_agents:
+            agent_name = agent.get("name")
+            if agent_name and isinstance(agent_name, str):
+                if agent_name.lower() not in library_names:
+                    agents.append(agent)
+
+    return agents
+
+
+def extract_search_terms_from_steps(
+    decomposition_result: DecompositionResult | dict[str, Any],
+) -> list[str]:
+    """Extract search terms from decomposed instruction steps.
+
+    Analyzes the decomposition result to extract relevant keywords
+    for additional library agent searches.
+
+    Args:
+        decomposition_result: Result from decompose_goal containing steps
+
+    Returns:
+        List of unique search terms extracted from steps
+    """
+    search_terms: list[str] = []
+
+    if decomposition_result.get("type") != "instructions":
+        return search_terms
+
+    steps = decomposition_result.get("steps", [])
+    if not steps:
+        return search_terms
+
+    step_keys: list[str] = ["description", "action", "block_name", "tool", "name"]
+
+    for step in steps:
+        for key in step_keys:
+            value = step.get(key)  # type: ignore[union-attr]
+            if isinstance(value, str) and len(value) > 3:
+                search_terms.append(value)
+
+    seen: set[str] = set()
+    unique_terms: list[str] = []
+    for term in search_terms:
+        term_lower = term.lower()
+        if term_lower not in seen:
+            seen.add(term_lower)
+            unique_terms.append(term)
+
+    return unique_terms
+
+
+async def enrich_library_agents_from_steps(
+    user_id: str,
+    decomposition_result: DecompositionResult | dict[str, Any],
+    existing_agents: list[AgentSummary] | list[dict[str, Any]],
+    exclude_graph_id: str | None = None,
+    include_marketplace: bool = True,
+    max_additional_results: int = 10,
+) -> list[AgentSummary] | list[dict[str, Any]]:
+    """Enrich library agents list with additional searches based on decomposed steps.
+
+    This implements two-phase search: after decomposition, we search for additional
+    relevant agents based on the specific steps identified.
+
+    Args:
+        user_id: The user ID
+        decomposition_result: Result from decompose_goal containing steps
+        existing_agents: Already fetched library agents from initial search
+        exclude_graph_id: Optional graph ID to exclude
+        include_marketplace: Whether to also search marketplace
+        max_additional_results: Max additional agents per search term (default 10)
+
+    Returns:
+        Combined list of library agents (existing + newly discovered)
+    """
+    search_terms = extract_search_terms_from_steps(decomposition_result)
+
+    if not search_terms:
+        return existing_agents
+
+    existing_ids: set[str] = set()
+    existing_names: set[str] = set()
+
+    for agent in existing_agents:
+        agent_name = agent.get("name")
+        if agent_name and isinstance(agent_name, str):
+            existing_names.add(agent_name.lower())
+        graph_id = agent.get("graph_id")  # type: ignore[call-overload]
+        if graph_id and isinstance(graph_id, str):
+            existing_ids.add(graph_id)
+
+    all_agents: list[AgentSummary] | list[dict[str, Any]] = list(existing_agents)
+
+    for term in search_terms[:3]:
+        try:
+            additional_agents = await get_all_relevant_agents_for_generation(
+                user_id=user_id,
+                search_query=term,
+                exclude_graph_id=exclude_graph_id,
+                include_marketplace=include_marketplace,
+                max_library_results=max_additional_results,
+                max_marketplace_results=5,
+            )
+
+            for agent in additional_agents:
+                agent_name = agent.get("name")
+                if not agent_name or not isinstance(agent_name, str):
+                    continue
+                agent_name_lower = agent_name.lower()
+
+                if agent_name_lower in existing_names:
+                    continue
+
+                graph_id = agent.get("graph_id")  # type: ignore[call-overload]
+                if graph_id and graph_id in existing_ids:
+                    continue
+
+                all_agents.append(agent)
+                existing_names.add(agent_name_lower)
+                if graph_id and isinstance(graph_id, str):
+                    existing_ids.add(graph_id)
+
+        except DatabaseError:
+            logger.error(f"Database error searching for agents with term '{term}'")
+            raise
+        except Exception as e:
+            logger.warning(
+                f"Failed to search for additional agents with term '{term}': {e}"
+            )
+
+    logger.debug(
+        f"Enriched library agents: {len(existing_agents)} initial + "
+        f"{len(all_agents) - len(existing_agents)} additional = {len(all_agents)} total"
+    )
+
+    return all_agents
+
+
+async def decompose_goal(
+    description: str,
+    context: str = "",
+    library_agents: list[AgentSummary] | None = None,
+) -> DecompositionResult | None:
     """Break down a goal into steps or return clarifying questions.
 
     Args:
         description: Natural language goal description
         context: Additional context (e.g., answers to previous questions)
+        library_agents: User's library agents available for sub-agent composition
 
     Returns:
-        Dict with either:
+        DecompositionResult with either:
         - {"type": "clarifying_questions", "questions": [...]}
         - {"type": "instructions", "steps": [...]}
         Or None on error
@@ -54,14 +531,21 @@ async def decompose_goal(description: str, context: str = "") -> dict[str, Any]
     """
     _check_service_configured()
     logger.info("Calling external Agent Generator service for decompose_goal")
-    return await decompose_goal_external(description, context)
+    result = await decompose_goal_external(
+        description, context, _to_dict_list(library_agents)
+    )
+    return result  # type: ignore[return-value]
 
 
-async def generate_agent(instructions: dict[str, Any]) -> dict[str, Any] | None:
+async def generate_agent(
+    instructions: DecompositionResult | dict[str, Any],
+    library_agents: list[AgentSummary] | list[dict[str, Any]] | None = None,
+) -> dict[str, Any] | None:
     """Generate agent JSON from instructions.
 
     Args:
         instructions: Structured instructions from decompose_goal
+        library_agents: User's library agents available for sub-agent composition
 
     Returns:
         Agent JSON dict, error dict {"type": "error", ...}, or None on error
@@ -71,12 +555,12 @@ async def generate_agent(instructions: dict[str, Any]) -> dict[str, Any] | None:
     """
     _check_service_configured()
     logger.info("Calling external Agent Generator service for generate_agent")
-    result = await generate_agent_external(instructions)
+    result = await generate_agent_external(
+        dict(instructions), _to_dict_list(library_agents)
+    )
     if result:
-        # Check if it's an error response - pass through as-is
         if isinstance(result, dict) and result.get("type") == "error":
             return result
-        # Ensure required fields for successful agent generation
         if "id" not in result:
             result["id"] = str(uuid.uuid4())
         if "version" not in result:
@@ -86,6 +570,12 @@ async def generate_agent(instructions: dict[str, Any]) -> dict[str, Any] | None:
     return result
 
 
+class AgentJsonValidationError(Exception):
+    """Raised when agent JSON is invalid or missing required fields."""
+
+    pass
+
+
 def json_to_graph(agent_json: dict[str, Any]) -> Graph:
     """Convert agent JSON dict to Graph model.
 
@@ -94,25 +584,55 @@ def json_to_graph(agent_json: dict[str, Any]) -> Graph:
 
     Returns:
         Graph ready for saving
+
+    Raises:
+        AgentJsonValidationError: If required fields are missing from nodes or links
     """
     nodes = []
-    for n in agent_json.get("nodes", []):
+    for idx, n in enumerate(agent_json.get("nodes", [])):
+        block_id = n.get("block_id")
+        if not block_id:
+            node_id = n.get("id", f"index_{idx}")
+            raise AgentJsonValidationError(
+                f"Node '{node_id}' is missing required field 'block_id'"
+            )
         node = Node(
             id=n.get("id", str(uuid.uuid4())),
-            block_id=n["block_id"],
+            block_id=block_id,
             input_default=n.get("input_default", {}),
             metadata=n.get("metadata", {}),
         )
         nodes.append(node)
 
     links = []
-    for link_data in agent_json.get("links", []):
+    for idx, link_data in enumerate(agent_json.get("links", [])):
+        source_id = link_data.get("source_id")
+        sink_id = link_data.get("sink_id")
+        source_name = link_data.get("source_name")
+        sink_name = link_data.get("sink_name")
+
+        missing_fields = []
+        if not source_id:
+            missing_fields.append("source_id")
+        if not sink_id:
+            missing_fields.append("sink_id")
+        if not source_name:
+            missing_fields.append("source_name")
+        if not sink_name:
+            missing_fields.append("sink_name")
+
+        if missing_fields:
+            link_id = link_data.get("id", f"index_{idx}")
+            raise AgentJsonValidationError(
+                f"Link '{link_id}' is missing required fields: {', '.join(missing_fields)}"
+            )
+
         link = Link(
             id=link_data.get("id", str(uuid.uuid4())),
-            source_id=link_data["source_id"],
+            source_id=source_id,
-            sink_id=link_data["sink_id"],
+            sink_id=sink_id,
-            source_name=link_data["source_name"],
+            source_name=source_name,
-            sink_name=link_data["sink_name"],
+            sink_name=sink_name,
             is_static=link_data.get("is_static", False),
         )
         links.append(link)
@@ -133,22 +653,40 @@ def _reassign_node_ids(graph: Graph) -> None:
 
     This is needed when creating a new version to avoid unique constraint violations.
     """
-    # Create mapping from old node IDs to new UUIDs
     id_map = {node.id: str(uuid.uuid4()) for node in graph.nodes}
 
-    # Reassign node IDs
     for node in graph.nodes:
         node.id = id_map[node.id]
 
-    # Update link references to use new node IDs
     for link in graph.links:
-        link.id = str(uuid.uuid4())  # Also give links new IDs
+        link.id = str(uuid.uuid4())
         if link.source_id in id_map:
             link.source_id = id_map[link.source_id]
         if link.sink_id in id_map:
             link.sink_id = id_map[link.sink_id]
 
 
+def _populate_agent_executor_user_ids(agent_json: dict[str, Any], user_id: str) -> None:
+    """Populate user_id in AgentExecutorBlock nodes.
+
+    The external agent generator creates AgentExecutorBlock nodes with empty user_id.
+    This function fills in the actual user_id so sub-agents run with correct permissions.
+
+    Args:
+        agent_json: Agent JSON dict (modified in place)
+        user_id: User ID to set
+    """
+    for node in agent_json.get("nodes", []):
+        if node.get("block_id") == AGENT_EXECUTOR_BLOCK_ID:
+            input_default = node.get("input_default") or {}
+            if not input_default.get("user_id"):
+                input_default["user_id"] = user_id
+                node["input_default"] = input_default
+                logger.debug(
+                    f"Set user_id for AgentExecutorBlock node {node.get('id')}"
+                )
+
+
 async def save_agent_to_library(
     agent_json: dict[str, Any], user_id: str, is_update: bool = False
 ) -> tuple[Graph, Any]:
@@ -162,33 +700,27 @@ async def save_agent_to_library(
     Returns:
         Tuple of (created Graph, LibraryAgent)
     """
-    from backend.data.graph import get_graph_all_versions
+    # Populate user_id in AgentExecutorBlock nodes before conversion
+    _populate_agent_executor_user_ids(agent_json, user_id)
 
     graph = json_to_graph(agent_json)
 
     if is_update:
-        # For updates, keep the same graph ID but increment version
-        # and reassign node/link IDs to avoid conflicts
         if graph.id:
             existing_versions = await get_graph_all_versions(graph.id, user_id)
             if existing_versions:
                 latest_version = max(v.version for v in existing_versions)
                 graph.version = latest_version + 1
-                # Reassign node IDs (but keep graph ID the same)
                 _reassign_node_ids(graph)
                 logger.info(f"Updating agent {graph.id} to version {graph.version}")
     else:
-        # For new agents, always generate a fresh UUID to avoid collisions
         graph.id = str(uuid.uuid4())
         graph.version = 1
-        # Reassign all node IDs as well
         _reassign_node_ids(graph)
         logger.info(f"Creating new agent with ID {graph.id}")
 
-    # Save to database
     created_graph = await create_graph(graph, user_id)
 
-    # Add to user's library (or update existing library agent)
     library_agents = await library_db.create_library_agent(
         graph=created_graph,
         user_id=user_id,
@@ -200,25 +732,31 @@ async def save_agent_to_library(
 
 
 async def get_agent_as_json(
-    graph_id: str, user_id: str | None
+    agent_id: str, user_id: str | None
 ) -> dict[str, Any] | None:
     """Fetch an agent and convert to JSON format for editing.
 
     Args:
-        graph_id: Graph ID or library agent ID
+        agent_id: Graph ID or library agent ID
         user_id: User ID
 
     Returns:
         Agent as JSON dict or None if not found
     """
-    from backend.data.graph import get_graph
+    graph = await get_graph(agent_id, version=None, user_id=user_id)
+
+    if not graph and user_id:
+        try:
+            library_agent = await library_db.get_library_agent(agent_id, user_id)
+            graph = await get_graph(
+                library_agent.graph_id, version=None, user_id=user_id
+            )
+        except NotFoundError:
+            pass
 
-    # Try to get the graph (version=None gets the active version)
-    graph = await get_graph(graph_id, version=None, user_id=user_id)
     if not graph:
         return None
 
-    # Convert to JSON format
     nodes = []
     for node in graph.nodes:
         nodes.append(
@@ -256,7 +794,9 @@ async def get_agent_as_json(
 
 
 async def generate_agent_patch(
-    update_request: str, current_agent: dict[str, Any]
+    update_request: str,
+    current_agent: dict[str, Any],
+    library_agents: list[AgentSummary] | None = None,
 ) -> dict[str, Any] | None:
     """Update an existing agent using natural language.
 
@@ -268,6 +808,7 @@ async def generate_agent_patch(
     Args:
         update_request: Natural language description of changes
         current_agent: Current agent JSON
+        library_agents: User's library agents available for sub-agent composition
 
     Returns:
         Updated agent JSON, clarifying questions dict {"type": "clarifying_questions", ...},
@@ -278,4 +819,6 @@ async def generate_agent_patch(
     """
     _check_service_configured()
     logger.info("Calling external Agent Generator service for generate_agent_patch")
-    return await generate_agent_patch_external(update_request, current_agent)
+    return await generate_agent_patch_external(
+        update_request, current_agent, _to_dict_list(library_agents)
+    )

autogpt_platform/backend/backend/api/features/chat/tools/agent_generator/errors.py

@@ -1,11 +1,43 @@
 """Error handling utilities for agent generator."""
 
+import re
+
+
+def _sanitize_error_details(details: str) -> str:
+    """Sanitize error details to remove sensitive information.
+
+    Strips common patterns that could expose internal system info:
+    - File paths (Unix and Windows)
+    - Database connection strings
+    - URLs with credentials
+    - Stack trace internals
+
+    Args:
+        details: Raw error details string
+
+    Returns:
+        Sanitized error details safe for user display
+    """
+    sanitized = re.sub(
+        r"/[a-zA-Z0-9_./\-]+\.(py|js|ts|json|yaml|yml)", "[path]", details
+    )
+    sanitized = re.sub(r"[A-Z]:\\[a-zA-Z0-9_\\.\\-]+", "[path]", sanitized)
+    sanitized = re.sub(
+        r"(postgres|mysql|mongodb|redis)://[^\s]+", "[database_url]", sanitized
+    )
+    sanitized = re.sub(r"https?://[^:]+:[^@]+@[^\s]+", "[url]", sanitized)
+    sanitized = re.sub(r", line \d+", "", sanitized)
+    sanitized = re.sub(r'File "[^"]+",?', "", sanitized)
+
+    return sanitized.strip()
+
 
 def get_user_message_for_error(
     error_type: str,
     operation: str = "process the request",
     llm_parse_message: str | None = None,
     validation_message: str | None = None,
+    error_details: str | None = None,
 ) -> str:
     """Get a user-friendly error message based on error type.
 
@@ -19,25 +51,45 @@ def get_user_message_for_error(
             message (e.g., "analyze the goal", "generate the agent")
         llm_parse_message: Custom message for llm_parse_error type
         validation_message: Custom message for validation_error type
+        error_details: Optional additional details about the error
 
     Returns:
         User-friendly error message suitable for display to the user
     """
+    base_message = ""
+
     if error_type == "llm_parse_error":
-        return (
+        base_message = (
             llm_parse_message
             or "The AI had trouble processing this request. Please try again."
         )
     elif error_type == "validation_error":
-        return (
+        base_message = (
             validation_message
-            or "The request failed validation. Please try rephrasing."
+            or "The generated agent failed validation. "
+            "This usually happens when the agent structure doesn't match "
+            "what the platform expects. Please try simplifying your goal "
+            "or breaking it into smaller parts."
         )
     elif error_type == "patch_error":
-        return "Failed to apply the changes. Please try a different approach."
+        base_message = (
+            "Failed to apply the changes. The modification couldn't be "
+            "validated. Please try a different approach or simplify the change."
+        )
     elif error_type in ("timeout", "llm_timeout"):
-        return "The request took too long. Please try again."
+        base_message = (
+            "The request took too long to process. This can happen with "
+            "complex agents. Please try again or simplify your goal."
+        )
     elif error_type in ("rate_limit", "llm_rate_limit"):
-        return "The service is currently busy. Please try again in a moment."
+        base_message = "The service is currently busy. Please try again in a moment."
     else:
-        return f"Failed to {operation}. Please try again."
+        base_message = f"Failed to {operation}. Please try again."
+
+    if error_details:
+        details = _sanitize_error_details(error_details)
+        if len(details) > 200:
+            details = details[:200] + "..."
+        base_message += f"\n\nTechnical details: {details}"
+
+    return base_message

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

@@ -117,13 +117,16 @@ def _get_client() -> httpx.AsyncClient:
 
 
 async def decompose_goal_external(
-    description: str, context: str = ""
+    description: str,
+    context: str = "",
+    library_agents: list[dict[str, Any]] | None = None,
 ) -> dict[str, Any] | None:
     """Call the external service to decompose a goal.
 
     Args:
         description: Natural language goal description
         context: Additional context (e.g., answers to previous questions)
+        library_agents: User's library agents available for sub-agent composition
 
     Returns:
         Dict with either:
@@ -141,6 +144,8 @@ async def decompose_goal_external(
     if context:
         # The external service uses user_instruction for additional context
         payload["user_instruction"] = context
+    if library_agents:
+        payload["library_agents"] = library_agents
 
     try:
         response = await client.post("/api/decompose-description", json=payload)
@@ -207,21 +212,25 @@ async def decompose_goal_external(
 
 async def generate_agent_external(
     instructions: dict[str, Any],
+    library_agents: list[dict[str, Any]] | None = None,
 ) -> dict[str, Any] | None:
     """Call the external service to generate an agent from instructions.
 
     Args:
         instructions: Structured instructions from decompose_goal
+        library_agents: User's library agents available for sub-agent composition
 
     Returns:
         Agent JSON dict on success, or error dict {"type": "error", ...} on error
     """
     client = _get_client()
 
+    payload: dict[str, Any] = {"instructions": instructions}
+    if library_agents:
+        payload["library_agents"] = library_agents
+
     try:
-        response = await client.post(
+        response = await client.post("/api/generate-agent", json=payload)
-            "/api/generate-agent", json={"instructions": instructions}
-        )
         response.raise_for_status()
         data = response.json()
 
@@ -229,8 +238,7 @@ async def generate_agent_external(
             error_msg = data.get("error", "Unknown error from Agent Generator")
             error_type = data.get("error_type", "unknown")
             logger.error(
-                f"Agent Generator generation failed: {error_msg} "
+                f"Agent Generator generation failed: {error_msg} (type: {error_type})"
-                f"(type: {error_type})"
             )
             return _create_error_response(error_msg, error_type)
 
@@ -251,27 +259,31 @@ async def generate_agent_external(
 
 
 async def generate_agent_patch_external(
-    update_request: str, current_agent: dict[str, Any]
+    update_request: str,
+    current_agent: dict[str, Any],
+    library_agents: list[dict[str, Any]] | None = None,
 ) -> dict[str, Any] | None:
     """Call the external service to generate a patch for an existing agent.
 
     Args:
         update_request: Natural language description of changes
         current_agent: Current agent JSON
+        library_agents: User's library agents available for sub-agent composition
 
     Returns:
         Updated agent JSON, clarifying questions dict, or error dict on error
     """
     client = _get_client()
 
+    payload: dict[str, Any] = {
+        "update_request": update_request,
+        "current_agent_json": current_agent,
+    }
+    if library_agents:
+        payload["library_agents"] = library_agents
+
     try:
-        response = await client.post(
+        response = await client.post("/api/update-agent", json=payload)
-            "/api/update-agent",
-            json={
-                "update_request": update_request,
-                "current_agent_json": current_agent,
-            },
-        )
         response.raise_for_status()
         data = response.json()
 

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

@@ -1,11 +1,11 @@
 """Shared agent search functionality for find_agent and find_library_agent tools."""
 
 import logging
-from typing import Any, Literal
+import re
+from typing import Literal
 
 from backend.api.features.library import db as library_db
 from backend.api.features.store import db as store_db
-from backend.data.graph import get_graph
 from backend.util.exceptions import DatabaseError, NotFoundError
 
 from .models import (
@@ -15,36 +15,88 @@ from .models import (
     NoResultsResponse,
     ToolResponseBase,
 )
-from .utils import fetch_graph_from_store_slug
 
 logger = logging.getLogger(__name__)
 
 SearchSource = Literal["marketplace", "library"]
 
+_UUID_PATTERN = re.compile(
+    r"^[a-f0-9]{8}-[a-f0-9]{4}-4[a-f0-9]{3}-[89ab][a-f0-9]{3}-[a-f0-9]{12}$",
+    re.IGNORECASE,
+)
 
-async def _fetch_input_schema_for_store_agent(
+
-    creator: str, slug: str
+def _is_uuid(text: str) -> bool:
-) -> dict[str, Any] | None:
+    """Check if text is a valid UUID v4."""
-    """Fetch input schema for a marketplace agent. Returns None on error."""
+    return bool(_UUID_PATTERN.match(text.strip()))
+
+
+async def _get_library_agent_by_id(user_id: str, agent_id: str) -> AgentInfo | None:
+    """Fetch a library agent by ID (library agent ID or graph_id).
+
+    Tries multiple lookup strategies:
+    1. First by graph_id (AgentGraph primary key)
+    2. Then by library agent ID (LibraryAgent primary key)
+
+    Args:
+        user_id: The user ID
+        agent_id: The ID to look up (can be graph_id or library agent ID)
+
+    Returns:
+        AgentInfo if found, None otherwise
+    """
     try:
-        graph, _ = await fetch_graph_from_store_slug(creator, slug)
+        agent = await library_db.get_library_agent_by_graph_id(user_id, agent_id)
-        if graph and graph.input_schema:
+        if agent:
-            return graph.input_schema.get("properties", {})
+            logger.debug(f"Found library agent by graph_id: {agent.name}")
+            return AgentInfo(
+                id=agent.id,
+                name=agent.name,
+                description=agent.description or "",
+                source="library",
+                in_library=True,
+                creator=agent.creator_name,
+                status=agent.status.value,
+                can_access_graph=agent.can_access_graph,
+                has_external_trigger=agent.has_external_trigger,
+                new_output=agent.new_output,
+                graph_id=agent.graph_id,
+            )
+    except DatabaseError:
+        raise
     except Exception as e:
-        logger.debug(f"Could not fetch input schema for {creator}/{slug}: {e}")
+        logger.warning(
-    return None
+            f"Could not fetch library agent by graph_id {agent_id}: {e}",
+            exc_info=True,
+        )
 
-
-async def _fetch_input_schema_for_library_agent(
-    graph_id: str, graph_version: int, user_id: str
-) -> dict[str, Any] | None:
-    """Fetch input schema for a library agent. Returns None on error."""
     try:
-        graph = await get_graph(graph_id, graph_version, user_id=user_id)
+        agent = await library_db.get_library_agent(agent_id, user_id)
-        if graph and graph.input_schema:
+        if agent:
-            return graph.input_schema.get("properties", {})
+            logger.debug(f"Found library agent by library_id: {agent.name}")
+            return AgentInfo(
+                id=agent.id,
+                name=agent.name,
+                description=agent.description or "",
+                source="library",
+                in_library=True,
+                creator=agent.creator_name,
+                status=agent.status.value,
+                can_access_graph=agent.can_access_graph,
+                has_external_trigger=agent.has_external_trigger,
+                new_output=agent.new_output,
+                graph_id=agent.graph_id,
+            )
+    except NotFoundError:
+        logger.debug(f"Library agent not found by library_id: {agent_id}")
+    except DatabaseError:
+        raise
     except Exception as e:
-        logger.debug(f"Could not fetch input schema for graph {graph_id}: {e}")
+        logger.warning(
+            f"Could not fetch library agent by library_id {agent_id}: {e}",
+            exc_info=True,
+        )
+
     return None
 
 
@@ -83,10 +135,6 @@ async def search_agents(
             logger.info(f"Searching marketplace for: {query}")
             results = await store_db.get_store_agents(search_query=query, page_size=5)
             for agent in results.agents:
-                # Fetch input schema for this agent
-                inputs = await _fetch_input_schema_for_store_agent(
-                    agent.creator, agent.slug
-                )
                 agents.append(
                     AgentInfo(
                         id=f"{agent.creator}/{agent.slug}",
@@ -99,37 +147,39 @@ async def search_agents(
                         rating=agent.rating,
                         runs=agent.runs,
                         is_featured=False,
-                        inputs=inputs,
                     )
                 )
-        else:  # library
+        else:
-            logger.info(f"Searching user library for: {query}")
+            if _is_uuid(query):
-            results = await library_db.list_library_agents(
+                logger.info(f"Query looks like UUID, trying direct lookup: {query}")
-                user_id=user_id,  # type: ignore[arg-type]
+                agent = await _get_library_agent_by_id(user_id, query)  # type: ignore[arg-type]
-                search_term=query,
+                if agent:
-                page_size=10,
+                    agents.append(agent)
-            )
+                    logger.info(f"Found agent by direct ID lookup: {agent.name}")
-            for agent in results.agents:
+
-                # Fetch input schema for this agent
+            if not agents:
-                inputs = await _fetch_input_schema_for_library_agent(
+                logger.info(f"Searching user library for: {query}")
-                    agent.graph_id, agent.graph_version, user_id  # type: ignore[arg-type]
+                results = await library_db.list_library_agents(
+                    user_id=user_id,  # type: ignore[arg-type]
+                    search_term=query,
+                    page_size=10,
                 )
-                agents.append(
+                for agent in results.agents:
-                    AgentInfo(
+                    agents.append(
-                        id=agent.id,
+                        AgentInfo(
-                        name=agent.name,
+                            id=agent.id,
-                        description=agent.description or "",
+                            name=agent.name,
-                        source="library",
+                            description=agent.description or "",
-                        in_library=True,
+                            source="library",
-                        creator=agent.creator_name,
+                            in_library=True,
-                        status=agent.status.value,
+                            creator=agent.creator_name,
-                        can_access_graph=agent.can_access_graph,
+                            status=agent.status.value,
-                        has_external_trigger=agent.has_external_trigger,
+                            can_access_graph=agent.can_access_graph,
-                        new_output=agent.new_output,
+                            has_external_trigger=agent.has_external_trigger,
-                        graph_id=agent.graph_id,
+                            new_output=agent.new_output,
-                        inputs=inputs,
+                            graph_id=agent.graph_id,
+                        )
                     )
-                )
         logger.info(f"Found {len(agents)} agents in {source}")
     except NotFoundError:
         pass

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

@@ -8,7 +8,9 @@ from backend.api.features.chat.model import ChatSession
 from .agent_generator import (
     AgentGeneratorNotConfiguredError,
     decompose_goal,
+    enrich_library_agents_from_steps,
     generate_agent,
+    get_all_relevant_agents_for_generation,
     get_user_message_for_error,
     save_agent_to_library,
 )
@@ -103,9 +105,24 @@ class CreateAgentTool(BaseTool):
                 session_id=session_id,
             )
 
-        # Step 1: Decompose goal into steps
+        library_agents = None
+        if user_id:
+            try:
+                library_agents = await get_all_relevant_agents_for_generation(
+                    user_id=user_id,
+                    search_query=description,
+                    include_marketplace=True,
+                )
+                logger.debug(
+                    f"Found {len(library_agents)} relevant agents for sub-agent composition"
+                )
+            except Exception as e:
+                logger.warning(f"Failed to fetch library agents: {e}")
+
         try:
-            decomposition_result = await decompose_goal(description, context)
+            decomposition_result = await decompose_goal(
+                description, context, library_agents
+            )
         except AgentGeneratorNotConfiguredError:
             return ErrorResponse(
                 message=(
@@ -124,7 +141,6 @@ class CreateAgentTool(BaseTool):
                 session_id=session_id,
             )
 
-        # Check if the result is an error from the external service
         if decomposition_result.get("type") == "error":
             error_msg = decomposition_result.get("error", "Unknown error")
             error_type = decomposition_result.get("error_type", "unknown")
@@ -144,7 +160,6 @@ class CreateAgentTool(BaseTool):
                 session_id=session_id,
             )
 
-        # Check if LLM returned clarifying questions
         if decomposition_result.get("type") == "clarifying_questions":
             questions = decomposition_result.get("questions", [])
             return ClarificationNeededResponse(
@@ -163,7 +178,6 @@ class CreateAgentTool(BaseTool):
                 session_id=session_id,
             )
 
-        # Check for unachievable/vague goals
         if decomposition_result.get("type") == "unachievable_goal":
             suggested = decomposition_result.get("suggested_goal", "")
             reason = decomposition_result.get("reason", "")
@@ -190,9 +204,22 @@ class CreateAgentTool(BaseTool):
                 session_id=session_id,
             )
 
-        # Step 2: Generate agent JSON (external service handles fixing and validation)
+        if user_id and library_agents is not None:
+            try:
+                library_agents = await enrich_library_agents_from_steps(
+                    user_id=user_id,
+                    decomposition_result=decomposition_result,
+                    existing_agents=library_agents,
+                    include_marketplace=True,
+                )
+                logger.debug(
+                    f"After enrichment: {len(library_agents)} total agents for sub-agent composition"
+                )
+            except Exception as e:
+                logger.warning(f"Failed to enrich library agents from steps: {e}")
+
         try:
-            agent_json = await generate_agent(decomposition_result)
+            agent_json = await generate_agent(decomposition_result, library_agents)
         except AgentGeneratorNotConfiguredError:
             return ErrorResponse(
                 message=(
@@ -211,7 +238,6 @@ class CreateAgentTool(BaseTool):
                 session_id=session_id,
             )
 
-        # Check if the result is an error from the external service
         if isinstance(agent_json, dict) and agent_json.get("type") == "error":
             error_msg = agent_json.get("error", "Unknown error")
             error_type = agent_json.get("error_type", "unknown")
@@ -219,7 +245,12 @@ class CreateAgentTool(BaseTool):
                 error_type,
                 operation="generate the agent",
                 llm_parse_message="The AI had trouble generating the agent. Please try again or simplify your goal.",
-                validation_message="The generated agent failed validation. Please try rephrasing your goal.",
+                validation_message=(
+                    "I wasn't able to create a valid agent for this request. "
+                    "The generated workflow had some structural issues. "
+                    "Please try simplifying your goal or breaking it into smaller steps."
+                ),
+                error_details=error_msg,
             )
             return ErrorResponse(
                 message=user_message,
@@ -237,7 +268,6 @@ class CreateAgentTool(BaseTool):
         node_count = len(agent_json.get("nodes", []))
         link_count = len(agent_json.get("links", []))
 
-        # Step 3: Preview or save
         if not save:
             return AgentPreviewResponse(
                 message=(
@@ -252,7 +282,6 @@ class CreateAgentTool(BaseTool):
                 session_id=session_id,
             )
 
-        # Save to library
         if not user_id:
             return ErrorResponse(
                 message="You must be logged in to save agents.",
@@ -270,7 +299,7 @@ class CreateAgentTool(BaseTool):
                 agent_id=created_graph.id,
                 agent_name=created_graph.name,
                 library_agent_id=library_agent.id,
-                library_agent_link=f"/library/{library_agent.id}",
+                library_agent_link=f"/library/agents/{library_agent.id}",
                 agent_page_link=f"/build?flowID={created_graph.id}",
                 session_id=session_id,
             )

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

@@ -9,6 +9,7 @@ from .agent_generator import (
     AgentGeneratorNotConfiguredError,
     generate_agent_patch,
     get_agent_as_json,
+    get_all_relevant_agents_for_generation,
     get_user_message_for_error,
     save_agent_to_library,
 )
@@ -117,7 +118,6 @@ class EditAgentTool(BaseTool):
                 session_id=session_id,
             )
 
-        # Step 1: Fetch current agent
         current_agent = await get_agent_as_json(agent_id, user_id)
 
         if current_agent is None:
@@ -127,14 +127,30 @@ class EditAgentTool(BaseTool):
                 session_id=session_id,
             )
 
-        # Build the update request with context
+        library_agents = None
+        if user_id:
+            try:
+                graph_id = current_agent.get("id")
+                library_agents = await get_all_relevant_agents_for_generation(
+                    user_id=user_id,
+                    search_query=changes,
+                    exclude_graph_id=graph_id,
+                    include_marketplace=True,
+                )
+                logger.debug(
+                    f"Found {len(library_agents)} relevant agents for sub-agent composition"
+                )
+            except Exception as e:
+                logger.warning(f"Failed to fetch library agents: {e}")
+
         update_request = changes
         if context:
             update_request = f"{changes}\n\nAdditional context:\n{context}"
 
-        # Step 2: Generate updated agent (external service handles fixing and validation)
         try:
-            result = await generate_agent_patch(update_request, current_agent)
+            result = await generate_agent_patch(
+                update_request, current_agent, library_agents
+            )
         except AgentGeneratorNotConfiguredError:
             return ErrorResponse(
                 message=(
@@ -153,7 +169,6 @@ class EditAgentTool(BaseTool):
                 session_id=session_id,
             )
 
-        # Check if the result is an error from the external service
         if isinstance(result, dict) and result.get("type") == "error":
             error_msg = result.get("error", "Unknown error")
             error_type = result.get("error_type", "unknown")
@@ -162,6 +177,7 @@ class EditAgentTool(BaseTool):
                 operation="generate the changes",
                 llm_parse_message="The AI had trouble generating the changes. Please try again or simplify your request.",
                 validation_message="The generated changes failed validation. Please try rephrasing your request.",
+                error_details=error_msg,
             )
             return ErrorResponse(
                 message=user_message,
@@ -175,7 +191,6 @@ class EditAgentTool(BaseTool):
                 session_id=session_id,
             )
 
-        # Check if LLM returned clarifying questions
         if result.get("type") == "clarifying_questions":
             questions = result.get("questions", [])
             return ClarificationNeededResponse(
@@ -194,7 +209,6 @@ class EditAgentTool(BaseTool):
                 session_id=session_id,
             )
 
-        # Result is the updated agent JSON
         updated_agent = result
 
         agent_name = updated_agent.get("name", "Updated Agent")
@@ -202,7 +216,6 @@ class EditAgentTool(BaseTool):
         node_count = len(updated_agent.get("nodes", []))
         link_count = len(updated_agent.get("links", []))
 
-        # Step 3: Preview or save
         if not save:
             return AgentPreviewResponse(
                 message=(
@@ -218,7 +231,6 @@ class EditAgentTool(BaseTool):
                 session_id=session_id,
             )
 
-        # Save to library (creates a new version)
         if not user_id:
             return ErrorResponse(
                 message="You must be logged in to save agents.",
@@ -236,7 +248,7 @@ class EditAgentTool(BaseTool):
                 agent_id=created_graph.id,
                 agent_name=created_graph.name,
                 library_agent_id=library_agent.id,
-                library_agent_link=f"/library/{library_agent.id}",
+                library_agent_link=f"/library/agents/{library_agent.id}",
                 agent_page_link=f"/build?flowID={created_graph.id}",
                 session_id=session_id,
             )

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

@@ -68,10 +68,6 @@ class AgentInfo(BaseModel):
     has_external_trigger: bool | None = None
     new_output: bool | None = None
     graph_id: str | None = None
-    inputs: dict[str, Any] | None = Field(
-        default=None,
-        description="Input schema for the agent (properties from input_schema)",
-    )
 
 
 class AgentsFoundResponse(ToolResponseBase):

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

@@ -273,27 +273,6 @@ class RunAgentTool(BaseTool):
             input_properties = graph.input_schema.get("properties", {})
             required_fields = set(graph.input_schema.get("required", []))
             provided_inputs = set(params.inputs.keys())
-            valid_fields = set(input_properties.keys())
-
-            # Check for unknown fields - reject early with helpful message
-            unknown_fields = provided_inputs - valid_fields
-            if unknown_fields:
-                valid_list = ", ".join(sorted(valid_fields)) if valid_fields else "none"
-                return AgentDetailsResponse(
-                    message=(
-                        f"Unknown input field(s) provided: {', '.join(sorted(unknown_fields))}. "
-                        f"Valid fields for '{graph.name}': {valid_list}. "
-                        "Please check the field names and try again."
-                    ),
-                    session_id=session_id,
-                    agent=self._build_agent_details(
-                        graph,
-                        extract_credentials_from_schema(graph.credentials_input_schema),
-                    ),
-                    user_authenticated=True,
-                    graph_id=graph.id,
-                    graph_version=graph.version,
-                )
 
             # If agent has inputs but none were provided AND use_defaults is not set,
             # always show what's available first so user can decide

autogpt_platform/backend/backend/api/features/library/db.py

@@ -39,6 +39,7 @@ async def list_library_agents(
     sort_by: library_model.LibraryAgentSort = library_model.LibraryAgentSort.UPDATED_AT,
     page: int = 1,
     page_size: int = 50,
+    include_executions: bool = False,
 ) -> library_model.LibraryAgentResponse:
     """
     Retrieves a paginated list of LibraryAgent records for a given user.
@@ -49,6 +50,9 @@ async def list_library_agents(
         sort_by: Sorting field (createdAt, updatedAt, isFavorite, isCreatedByUser).
         page: Current page (1-indexed).
         page_size: Number of items per page.
+        include_executions: Whether to include execution data for status calculation.
+            Defaults to False for performance (UI fetches status separately).
+            Set to True when accurate status/metrics are needed (e.g., agent generator).
 
     Returns:
         A LibraryAgentResponse containing the list of agents and pagination details.
@@ -76,7 +80,6 @@ async def list_library_agents(
         "isArchived": False,
     }
 
-    # Build search filter if applicable
     if search_term:
         where_clause["OR"] = [
             {
@@ -93,7 +96,6 @@ async def list_library_agents(
             },
         ]
 
-    # Determine sorting
     order_by: prisma.types.LibraryAgentOrderByInput | None = None
 
     if sort_by == library_model.LibraryAgentSort.CREATED_AT:
@@ -105,7 +107,7 @@ async def list_library_agents(
         library_agents = await prisma.models.LibraryAgent.prisma().find_many(
             where=where_clause,
             include=library_agent_include(
-                user_id, include_nodes=False, include_executions=False
+                user_id, include_nodes=False, include_executions=include_executions
             ),
             order=order_by,
             skip=(page - 1) * page_size,

autogpt_platform/backend/backend/api/features/library/model.py

@@ -9,6 +9,7 @@ import pydantic
 from backend.data.block import BlockInput
 from backend.data.graph import GraphModel, GraphSettings, GraphTriggerInfo
 from backend.data.model import CredentialsMetaInput, is_credentials_field_name
+from backend.util.json import loads as json_loads
 from backend.util.models import Pagination
 
 if TYPE_CHECKING:
@@ -16,10 +17,10 @@ if TYPE_CHECKING:
 
 
 class LibraryAgentStatus(str, Enum):
-    COMPLETED = "COMPLETED"  # All runs completed
+    COMPLETED = "COMPLETED"
-    HEALTHY = "HEALTHY"  # Agent is running (not all runs have completed)
+    HEALTHY = "HEALTHY"
-    WAITING = "WAITING"  # Agent is queued or waiting to start
+    WAITING = "WAITING"
-    ERROR = "ERROR"  # Agent is in an error state
+    ERROR = "ERROR"
 
 
 class MarketplaceListingCreator(pydantic.BaseModel):
@@ -39,6 +40,30 @@ class MarketplaceListing(pydantic.BaseModel):
     creator: MarketplaceListingCreator
 
 
+class RecentExecution(pydantic.BaseModel):
+    """Summary of a recent execution for quality assessment.
+
+    Used by the LLM to understand the agent's recent performance with specific examples
+    rather than just aggregate statistics.
+    """
+
+    status: str
+    correctness_score: float | None = None
+    activity_summary: str | None = None
+
+
+def _parse_settings(settings: dict | str | None) -> GraphSettings:
+    """Parse settings from database, handling both dict and string formats."""
+    if settings is None:
+        return GraphSettings()
+    try:
+        if isinstance(settings, str):
+            settings = json_loads(settings)
+        return GraphSettings.model_validate(settings)
+    except Exception:
+        return GraphSettings()
+
+
 class LibraryAgent(pydantic.BaseModel):
     """
     Represents an agent in the library, including metadata for display and
@@ -48,7 +73,7 @@ class LibraryAgent(pydantic.BaseModel):
     id: str
     graph_id: str
     graph_version: int
-    owner_user_id: str  # ID of user who owns/created this agent graph
+    owner_user_id: str
 
     image_url: str | None
 
@@ -64,7 +89,7 @@ class LibraryAgent(pydantic.BaseModel):
     description: str
     instructions: str | None = None
 
-    input_schema: dict[str, Any]  # Should be BlockIOObjectSubSchema in frontend
+    input_schema: dict[str, Any]
     output_schema: dict[str, Any]
     credentials_input_schema: dict[str, Any] | None = pydantic.Field(
         description="Input schema for credentials required by the agent",
@@ -81,25 +106,19 @@ class LibraryAgent(pydantic.BaseModel):
     )
     trigger_setup_info: Optional[GraphTriggerInfo] = None
 
-    # Indicates whether there's a new output (based on recent runs)
     new_output: bool
-
+    execution_count: int = 0
-    # Whether the user can access the underlying graph
+    success_rate: float | None = None
+    avg_correctness_score: float | None = None
+    recent_executions: list[RecentExecution] = pydantic.Field(
+        default_factory=list,
+        description="List of recent executions with status, score, and summary",
+    )
     can_access_graph: bool
-
-    # Indicates if this agent is the latest version
     is_latest_version: bool
-
-    # Whether the agent is marked as favorite by the user
     is_favorite: bool
-
-    # Recommended schedule cron (from marketplace agents)
     recommended_schedule_cron: str | None = None
-
-    # User-specific settings for this library agent
     settings: GraphSettings = pydantic.Field(default_factory=GraphSettings)
-
-    # Marketplace listing information if the agent has been published
     marketplace_listing: Optional["MarketplaceListing"] = None
 
     @staticmethod
@@ -123,7 +142,6 @@ class LibraryAgent(pydantic.BaseModel):
         agent_updated_at = agent.AgentGraph.updatedAt
         lib_agent_updated_at = agent.updatedAt
 
-        # Compute updated_at as the latest between library agent and graph
         updated_at = (
             max(agent_updated_at, lib_agent_updated_at)
             if agent_updated_at
@@ -136,7 +154,6 @@ class LibraryAgent(pydantic.BaseModel):
             creator_name = agent.Creator.name or "Unknown"
             creator_image_url = agent.Creator.avatarUrl or ""
 
-        # Logic to calculate status and new_output
         week_ago = datetime.datetime.now(datetime.timezone.utc) - datetime.timedelta(
             days=7
         )
@@ -145,13 +162,55 @@ class LibraryAgent(pydantic.BaseModel):
         status = status_result.status
         new_output = status_result.new_output
 
-        # Check if user can access the graph
+        execution_count = len(executions)
-        can_access_graph = agent.AgentGraph.userId == agent.userId
+        success_rate: float | None = None
+        avg_correctness_score: float | None = None
+        if execution_count > 0:
+            success_count = sum(
+                1
+                for e in executions
+                if e.executionStatus == prisma.enums.AgentExecutionStatus.COMPLETED
+            )
+            success_rate = (success_count / execution_count) * 100
 
-        # Hard-coded to True until a method to check is implemented
+            correctness_scores = []
+            for e in executions:
+                if e.stats and isinstance(e.stats, dict):
+                    score = e.stats.get("correctness_score")
+                    if score is not None and isinstance(score, (int, float)):
+                        correctness_scores.append(float(score))
+            if correctness_scores:
+                avg_correctness_score = sum(correctness_scores) / len(
+                    correctness_scores
+                )
+
+        recent_executions: list[RecentExecution] = []
+        for e in executions:
+            exec_score: float | None = None
+            exec_summary: str | None = None
+            if e.stats and isinstance(e.stats, dict):
+                score = e.stats.get("correctness_score")
+                if score is not None and isinstance(score, (int, float)):
+                    exec_score = float(score)
+                summary = e.stats.get("activity_status")
+                if summary is not None and isinstance(summary, str):
+                    exec_summary = summary
+            exec_status = (
+                e.executionStatus.value
+                if hasattr(e.executionStatus, "value")
+                else str(e.executionStatus)
+            )
+            recent_executions.append(
+                RecentExecution(
+                    status=exec_status,
+                    correctness_score=exec_score,
+                    activity_summary=exec_summary,
+                )
+            )
+
+        can_access_graph = agent.AgentGraph.userId == agent.userId
         is_latest_version = True
 
-        # Build marketplace_listing if available
         marketplace_listing_data = None
         if store_listing and store_listing.ActiveVersion and profile:
             creator_data = MarketplaceListingCreator(
@@ -190,11 +249,15 @@ class LibraryAgent(pydantic.BaseModel):
             has_sensitive_action=graph.has_sensitive_action,
             trigger_setup_info=graph.trigger_setup_info,
             new_output=new_output,
+            execution_count=execution_count,
+            success_rate=success_rate,
+            avg_correctness_score=avg_correctness_score,
+            recent_executions=recent_executions,
             can_access_graph=can_access_graph,
             is_latest_version=is_latest_version,
             is_favorite=agent.isFavorite,
             recommended_schedule_cron=agent.AgentGraph.recommendedScheduleCron,
-            settings=GraphSettings.model_validate(agent.settings),
+            settings=_parse_settings(agent.settings),
             marketplace_listing=marketplace_listing_data,
         )
 
@@ -220,18 +283,15 @@ def _calculate_agent_status(
     if not executions:
         return AgentStatusResult(status=LibraryAgentStatus.COMPLETED, new_output=False)
 
-    # Track how many times each execution status appears
     status_counts = {status: 0 for status in prisma.enums.AgentExecutionStatus}
     new_output = False
 
     for execution in executions:
-        # Check if there's a completed run more recent than `recent_threshold`
         if execution.createdAt >= recent_threshold:
             if execution.executionStatus == prisma.enums.AgentExecutionStatus.COMPLETED:
                 new_output = True
         status_counts[execution.executionStatus] += 1
 
-    # Determine the final status based on counts
     if status_counts[prisma.enums.AgentExecutionStatus.FAILED] > 0:
         return AgentStatusResult(status=LibraryAgentStatus.ERROR, new_output=new_output)
     elif status_counts[prisma.enums.AgentExecutionStatus.QUEUED] > 0:

autogpt_platform/backend/snapshots/lib_agts_search

@@ -31,6 +31,10 @@
       "has_sensitive_action": false,
       "trigger_setup_info": null,
       "new_output": false,
+      "execution_count": 0,
+      "success_rate": null,
+      "avg_correctness_score": null,
+      "recent_executions": [],
       "can_access_graph": true,
       "is_latest_version": true,
       "is_favorite": false,
@@ -72,6 +76,10 @@
       "has_sensitive_action": false,
       "trigger_setup_info": null,
       "new_output": false,
+      "execution_count": 0,
+      "success_rate": null,
+      "avg_correctness_score": null,
+      "recent_executions": [],
       "can_access_graph": false,
       "is_latest_version": true,
       "is_favorite": false,

autogpt_platform/backend/test/agent_generator/test_core_integration.py

@@ -57,7 +57,8 @@ class TestDecomposeGoal:
 
             result = await core.decompose_goal("Build a chatbot")
 
-            mock_external.assert_called_once_with("Build a chatbot", "")
+            # library_agents defaults to None
+            mock_external.assert_called_once_with("Build a chatbot", "", None)
             assert result == expected_result
 
     @pytest.mark.asyncio
@@ -74,7 +75,8 @@ class TestDecomposeGoal:
 
             await core.decompose_goal("Build a chatbot", "Use Python")
 
-            mock_external.assert_called_once_with("Build a chatbot", "Use Python")
+            # library_agents defaults to None
+            mock_external.assert_called_once_with("Build a chatbot", "Use Python", None)
 
     @pytest.mark.asyncio
     async def test_returns_none_on_service_failure(self):
@@ -109,7 +111,8 @@ class TestGenerateAgent:
             instructions = {"type": "instructions", "steps": ["Step 1"]}
             result = await core.generate_agent(instructions)
 
-            mock_external.assert_called_once_with(instructions)
+            # library_agents defaults to None
+            mock_external.assert_called_once_with(instructions, None)
             # Result should have id, version, is_active added if not present
             assert result is not None
             assert result["name"] == "Test Agent"
@@ -174,7 +177,8 @@ class TestGenerateAgentPatch:
             current_agent = {"nodes": [], "links": []}
             result = await core.generate_agent_patch("Add a node", current_agent)
 
-            mock_external.assert_called_once_with("Add a node", current_agent)
+            # library_agents defaults to None
+            mock_external.assert_called_once_with("Add a node", current_agent, None)
             assert result == expected_result
 
     @pytest.mark.asyncio

autogpt_platform/backend/test/agent_generator/test_library_agents.py

@@ -0,0 +1,841 @@
+"""
+Tests for library agent fetching functionality in agent generator.
+
+This test suite verifies the search-based library agent fetching,
+including the combination of library and marketplace agents.
+"""
+
+from unittest.mock import AsyncMock, MagicMock, patch
+
+import pytest
+
+from backend.api.features.chat.tools.agent_generator import core
+
+
+class TestGetLibraryAgentsForGeneration:
+    """Test get_library_agents_for_generation function."""
+
+    @pytest.mark.asyncio
+    async def test_fetches_agents_with_search_term(self):
+        """Test that search_term is passed to the library db."""
+        # Create a mock agent with proper attribute values
+        mock_agent = MagicMock()
+        mock_agent.graph_id = "agent-123"
+        mock_agent.graph_version = 1
+        mock_agent.name = "Email Agent"
+        mock_agent.description = "Sends emails"
+        mock_agent.input_schema = {"properties": {}}
+        mock_agent.output_schema = {"properties": {}}
+        mock_agent.recent_executions = []
+
+        mock_response = MagicMock()
+        mock_response.agents = [mock_agent]
+
+        with patch.object(
+            core.library_db,
+            "list_library_agents",
+            new_callable=AsyncMock,
+            return_value=mock_response,
+        ) as mock_list:
+            result = await core.get_library_agents_for_generation(
+                user_id="user-123",
+                search_query="send email",
+            )
+
+            mock_list.assert_called_once_with(
+                user_id="user-123",
+                search_term="send email",
+                page=1,
+                page_size=15,
+                include_executions=True,
+            )
+
+        # Verify result format
+        assert len(result) == 1
+        assert result[0]["graph_id"] == "agent-123"
+        assert result[0]["name"] == "Email Agent"
+
+    @pytest.mark.asyncio
+    async def test_excludes_specified_graph_id(self):
+        """Test that agents with excluded graph_id are filtered out."""
+        mock_response = MagicMock()
+        mock_response.agents = [
+            MagicMock(
+                graph_id="agent-123",
+                graph_version=1,
+                name="Agent 1",
+                description="First agent",
+                input_schema={},
+                output_schema={},
+                recent_executions=[],
+            ),
+            MagicMock(
+                graph_id="agent-456",
+                graph_version=1,
+                name="Agent 2",
+                description="Second agent",
+                input_schema={},
+                output_schema={},
+                recent_executions=[],
+            ),
+        ]
+
+        with patch.object(
+            core.library_db,
+            "list_library_agents",
+            new_callable=AsyncMock,
+            return_value=mock_response,
+        ):
+            result = await core.get_library_agents_for_generation(
+                user_id="user-123",
+                exclude_graph_id="agent-123",
+            )
+
+        # Verify the excluded agent is not in results
+        assert len(result) == 1
+        assert result[0]["graph_id"] == "agent-456"
+
+    @pytest.mark.asyncio
+    async def test_respects_max_results(self):
+        """Test that max_results parameter limits the page_size."""
+        mock_response = MagicMock()
+        mock_response.agents = []
+
+        with patch.object(
+            core.library_db,
+            "list_library_agents",
+            new_callable=AsyncMock,
+            return_value=mock_response,
+        ) as mock_list:
+            await core.get_library_agents_for_generation(
+                user_id="user-123",
+                max_results=5,
+            )
+
+            mock_list.assert_called_once_with(
+                user_id="user-123",
+                search_term=None,
+                page=1,
+                page_size=5,
+                include_executions=True,
+            )
+
+
+class TestSearchMarketplaceAgentsForGeneration:
+    """Test search_marketplace_agents_for_generation function."""
+
+    @pytest.mark.asyncio
+    async def test_searches_marketplace_with_query(self):
+        """Test that marketplace is searched with the query."""
+        mock_response = MagicMock()
+        mock_response.agents = [
+            MagicMock(
+                agent_name="Public Agent",
+                description="A public agent",
+                sub_heading="Does something useful",
+                creator="creator-1",
+            )
+        ]
+
+        # The store_db is dynamically imported, so patch the import path
+        with patch(
+            "backend.api.features.store.db.get_store_agents",
+            new_callable=AsyncMock,
+            return_value=mock_response,
+        ) as mock_search:
+            result = await core.search_marketplace_agents_for_generation(
+                search_query="automation",
+                max_results=10,
+            )
+
+            mock_search.assert_called_once_with(
+                search_query="automation",
+                page=1,
+                page_size=10,
+            )
+
+        assert len(result) == 1
+        assert result[0]["name"] == "Public Agent"
+        assert result[0]["is_marketplace_agent"] is True
+
+    @pytest.mark.asyncio
+    async def test_handles_marketplace_error_gracefully(self):
+        """Test that marketplace errors don't crash the function."""
+        with patch(
+            "backend.api.features.store.db.get_store_agents",
+            new_callable=AsyncMock,
+            side_effect=Exception("Marketplace unavailable"),
+        ):
+            result = await core.search_marketplace_agents_for_generation(
+                search_query="test"
+            )
+
+        # Should return empty list, not raise exception
+        assert result == []
+
+
+class TestGetAllRelevantAgentsForGeneration:
+    """Test get_all_relevant_agents_for_generation function."""
+
+    @pytest.mark.asyncio
+    async def test_combines_library_and_marketplace_agents(self):
+        """Test that agents from both sources are combined."""
+        library_agents = [
+            {
+                "graph_id": "lib-123",
+                "graph_version": 1,
+                "name": "Library Agent",
+                "description": "From library",
+                "input_schema": {},
+                "output_schema": {},
+            }
+        ]
+
+        marketplace_agents = [
+            {
+                "name": "Market Agent",
+                "description": "From marketplace",
+                "sub_heading": "Sub heading",
+                "creator": "creator-1",
+                "is_marketplace_agent": True,
+            }
+        ]
+
+        with patch.object(
+            core,
+            "get_library_agents_for_generation",
+            new_callable=AsyncMock,
+            return_value=library_agents,
+        ):
+            with patch.object(
+                core,
+                "search_marketplace_agents_for_generation",
+                new_callable=AsyncMock,
+                return_value=marketplace_agents,
+            ):
+                result = await core.get_all_relevant_agents_for_generation(
+                    user_id="user-123",
+                    search_query="test query",
+                    include_marketplace=True,
+                )
+
+        # Library agents should come first
+        assert len(result) == 2
+        assert result[0]["name"] == "Library Agent"
+        assert result[1]["name"] == "Market Agent"
+
+    @pytest.mark.asyncio
+    async def test_deduplicates_by_name(self):
+        """Test that marketplace agents with same name as library are excluded."""
+        library_agents = [
+            {
+                "graph_id": "lib-123",
+                "graph_version": 1,
+                "name": "Shared Agent",
+                "description": "From library",
+                "input_schema": {},
+                "output_schema": {},
+            }
+        ]
+
+        marketplace_agents = [
+            {
+                "name": "Shared Agent",  # Same name, should be deduplicated
+                "description": "From marketplace",
+                "sub_heading": "Sub heading",
+                "creator": "creator-1",
+                "is_marketplace_agent": True,
+            },
+            {
+                "name": "Unique Agent",
+                "description": "Only in marketplace",
+                "sub_heading": "Sub heading",
+                "creator": "creator-2",
+                "is_marketplace_agent": True,
+            },
+        ]
+
+        with patch.object(
+            core,
+            "get_library_agents_for_generation",
+            new_callable=AsyncMock,
+            return_value=library_agents,
+        ):
+            with patch.object(
+                core,
+                "search_marketplace_agents_for_generation",
+                new_callable=AsyncMock,
+                return_value=marketplace_agents,
+            ):
+                result = await core.get_all_relevant_agents_for_generation(
+                    user_id="user-123",
+                    search_query="test",
+                    include_marketplace=True,
+                )
+
+        # Shared Agent from marketplace should be excluded
+        assert len(result) == 2
+        names = [a["name"] for a in result]
+        assert "Shared Agent" in names
+        assert "Unique Agent" in names
+
+    @pytest.mark.asyncio
+    async def test_skips_marketplace_when_disabled(self):
+        """Test that marketplace is not searched when include_marketplace=False."""
+        library_agents = [
+            {
+                "graph_id": "lib-123",
+                "graph_version": 1,
+                "name": "Library Agent",
+                "description": "From library",
+                "input_schema": {},
+                "output_schema": {},
+            }
+        ]
+
+        with patch.object(
+            core,
+            "get_library_agents_for_generation",
+            new_callable=AsyncMock,
+            return_value=library_agents,
+        ):
+            with patch.object(
+                core,
+                "search_marketplace_agents_for_generation",
+                new_callable=AsyncMock,
+            ) as mock_marketplace:
+                result = await core.get_all_relevant_agents_for_generation(
+                    user_id="user-123",
+                    search_query="test",
+                    include_marketplace=False,
+                )
+
+        # Marketplace should not be called
+        mock_marketplace.assert_not_called()
+        assert len(result) == 1
+
+    @pytest.mark.asyncio
+    async def test_skips_marketplace_when_no_search_query(self):
+        """Test that marketplace is not searched without a search query."""
+        library_agents = [
+            {
+                "graph_id": "lib-123",
+                "graph_version": 1,
+                "name": "Library Agent",
+                "description": "From library",
+                "input_schema": {},
+                "output_schema": {},
+            }
+        ]
+
+        with patch.object(
+            core,
+            "get_library_agents_for_generation",
+            new_callable=AsyncMock,
+            return_value=library_agents,
+        ):
+            with patch.object(
+                core,
+                "search_marketplace_agents_for_generation",
+                new_callable=AsyncMock,
+            ) as mock_marketplace:
+                result = await core.get_all_relevant_agents_for_generation(
+                    user_id="user-123",
+                    search_query=None,  # No search query
+                    include_marketplace=True,
+                )
+
+        # Marketplace should not be called without search query
+        mock_marketplace.assert_not_called()
+        assert len(result) == 1
+
+
+class TestExtractSearchTermsFromSteps:
+    """Test extract_search_terms_from_steps function."""
+
+    def test_extracts_terms_from_instructions_type(self):
+        """Test extraction from valid instructions decomposition result."""
+        decomposition_result = {
+            "type": "instructions",
+            "steps": [
+                {
+                    "description": "Send an email notification",
+                    "block_name": "GmailSendBlock",
+                },
+                {"description": "Fetch weather data", "action": "Get weather API"},
+            ],
+        }
+
+        result = core.extract_search_terms_from_steps(decomposition_result)
+
+        assert "Send an email notification" in result
+        assert "GmailSendBlock" in result
+        assert "Fetch weather data" in result
+        assert "Get weather API" in result
+
+    def test_returns_empty_for_non_instructions_type(self):
+        """Test that non-instructions types return empty list."""
+        decomposition_result = {
+            "type": "clarifying_questions",
+            "questions": [{"question": "What email?"}],
+        }
+
+        result = core.extract_search_terms_from_steps(decomposition_result)
+
+        assert result == []
+
+    def test_deduplicates_terms_case_insensitively(self):
+        """Test that duplicate terms are removed (case-insensitive)."""
+        decomposition_result = {
+            "type": "instructions",
+            "steps": [
+                {"description": "Send Email", "name": "send email"},
+                {"description": "Other task"},
+            ],
+        }
+
+        result = core.extract_search_terms_from_steps(decomposition_result)
+
+        # Should only have one "send email" variant
+        email_terms = [t for t in result if "email" in t.lower()]
+        assert len(email_terms) == 1
+
+    def test_filters_short_terms(self):
+        """Test that terms with 3 or fewer characters are filtered out."""
+        decomposition_result = {
+            "type": "instructions",
+            "steps": [
+                {"description": "ab", "action": "xyz"},  # Both too short
+                {"description": "Valid term here"},
+            ],
+        }
+
+        result = core.extract_search_terms_from_steps(decomposition_result)
+
+        assert "ab" not in result
+        assert "xyz" not in result
+        assert "Valid term here" in result
+
+    def test_handles_empty_steps(self):
+        """Test handling of empty steps list."""
+        decomposition_result = {
+            "type": "instructions",
+            "steps": [],
+        }
+
+        result = core.extract_search_terms_from_steps(decomposition_result)
+
+        assert result == []
+
+
+class TestEnrichLibraryAgentsFromSteps:
+    """Test enrich_library_agents_from_steps function."""
+
+    @pytest.mark.asyncio
+    async def test_enriches_with_additional_agents(self):
+        """Test that additional agents are found based on steps."""
+        existing_agents = [
+            {
+                "graph_id": "existing-123",
+                "graph_version": 1,
+                "name": "Existing Agent",
+                "description": "Already fetched",
+                "input_schema": {},
+                "output_schema": {},
+            }
+        ]
+
+        additional_agents = [
+            {
+                "graph_id": "new-456",
+                "graph_version": 1,
+                "name": "Email Agent",
+                "description": "For sending emails",
+                "input_schema": {},
+                "output_schema": {},
+            }
+        ]
+
+        decomposition_result = {
+            "type": "instructions",
+            "steps": [
+                {"description": "Send email notification"},
+            ],
+        }
+
+        with patch.object(
+            core,
+            "get_all_relevant_agents_for_generation",
+            new_callable=AsyncMock,
+            return_value=additional_agents,
+        ):
+            result = await core.enrich_library_agents_from_steps(
+                user_id="user-123",
+                decomposition_result=decomposition_result,
+                existing_agents=existing_agents,
+            )
+
+        # Should have both existing and new agents
+        assert len(result) == 2
+        names = [a["name"] for a in result]
+        assert "Existing Agent" in names
+        assert "Email Agent" in names
+
+    @pytest.mark.asyncio
+    async def test_deduplicates_by_graph_id(self):
+        """Test that agents with same graph_id are not duplicated."""
+        existing_agents = [
+            {
+                "graph_id": "agent-123",
+                "graph_version": 1,
+                "name": "Existing Agent",
+                "description": "Already fetched",
+                "input_schema": {},
+                "output_schema": {},
+            }
+        ]
+
+        # Additional search returns same agent
+        additional_agents = [
+            {
+                "graph_id": "agent-123",  # Same ID
+                "graph_version": 1,
+                "name": "Existing Agent Copy",
+                "description": "Same agent different name",
+                "input_schema": {},
+                "output_schema": {},
+            }
+        ]
+
+        decomposition_result = {
+            "type": "instructions",
+            "steps": [{"description": "Some action"}],
+        }
+
+        with patch.object(
+            core,
+            "get_all_relevant_agents_for_generation",
+            new_callable=AsyncMock,
+            return_value=additional_agents,
+        ):
+            result = await core.enrich_library_agents_from_steps(
+                user_id="user-123",
+                decomposition_result=decomposition_result,
+                existing_agents=existing_agents,
+            )
+
+        # Should not duplicate
+        assert len(result) == 1
+
+    @pytest.mark.asyncio
+    async def test_deduplicates_by_name(self):
+        """Test that agents with same name are not duplicated."""
+        existing_agents = [
+            {
+                "graph_id": "agent-123",
+                "graph_version": 1,
+                "name": "Email Agent",
+                "description": "Already fetched",
+                "input_schema": {},
+                "output_schema": {},
+            }
+        ]
+
+        # Additional search returns agent with same name but different ID
+        additional_agents = [
+            {
+                "graph_id": "agent-456",  # Different ID
+                "graph_version": 1,
+                "name": "Email Agent",  # Same name
+                "description": "Different agent same name",
+                "input_schema": {},
+                "output_schema": {},
+            }
+        ]
+
+        decomposition_result = {
+            "type": "instructions",
+            "steps": [{"description": "Send email"}],
+        }
+
+        with patch.object(
+            core,
+            "get_all_relevant_agents_for_generation",
+            new_callable=AsyncMock,
+            return_value=additional_agents,
+        ):
+            result = await core.enrich_library_agents_from_steps(
+                user_id="user-123",
+                decomposition_result=decomposition_result,
+                existing_agents=existing_agents,
+            )
+
+        # Should not duplicate by name
+        assert len(result) == 1
+        assert result[0].get("graph_id") == "agent-123"  # Original kept
+
+    @pytest.mark.asyncio
+    async def test_returns_existing_when_no_steps(self):
+        """Test that existing agents are returned when no search terms extracted."""
+        existing_agents = [
+            {
+                "graph_id": "existing-123",
+                "graph_version": 1,
+                "name": "Existing Agent",
+                "description": "Already fetched",
+                "input_schema": {},
+                "output_schema": {},
+            }
+        ]
+
+        decomposition_result = {
+            "type": "clarifying_questions",  # Not instructions type
+            "questions": [],
+        }
+
+        result = await core.enrich_library_agents_from_steps(
+            user_id="user-123",
+            decomposition_result=decomposition_result,
+            existing_agents=existing_agents,
+        )
+
+        # Should return existing unchanged
+        assert result == existing_agents
+
+    @pytest.mark.asyncio
+    async def test_limits_search_terms_to_three(self):
+        """Test that only first 3 search terms are used."""
+        existing_agents = []
+
+        decomposition_result = {
+            "type": "instructions",
+            "steps": [
+                {"description": "First action"},
+                {"description": "Second action"},
+                {"description": "Third action"},
+                {"description": "Fourth action"},
+                {"description": "Fifth action"},
+            ],
+        }
+
+        call_count = 0
+
+        async def mock_get_agents(*args, **kwargs):
+            nonlocal call_count
+            call_count += 1
+            return []
+
+        with patch.object(
+            core,
+            "get_all_relevant_agents_for_generation",
+            side_effect=mock_get_agents,
+        ):
+            await core.enrich_library_agents_from_steps(
+                user_id="user-123",
+                decomposition_result=decomposition_result,
+                existing_agents=existing_agents,
+            )
+
+        # Should only make 3 calls (limited to first 3 terms)
+        assert call_count == 3
+
+
+class TestExtractUuidsFromText:
+    """Test extract_uuids_from_text function."""
+
+    def test_extracts_single_uuid(self):
+        """Test extraction of a single UUID from text."""
+        text = "Use my agent 46631191-e8a8-486f-ad90-84f89738321d for this task"
+        result = core.extract_uuids_from_text(text)
+        assert len(result) == 1
+        assert "46631191-e8a8-486f-ad90-84f89738321d" in result
+
+    def test_extracts_multiple_uuids(self):
+        """Test extraction of multiple UUIDs from text."""
+        text = (
+            "Combine agents 11111111-1111-4111-8111-111111111111 "
+            "and 22222222-2222-4222-9222-222222222222"
+        )
+        result = core.extract_uuids_from_text(text)
+        assert len(result) == 2
+        assert "11111111-1111-4111-8111-111111111111" in result
+        assert "22222222-2222-4222-9222-222222222222" in result
+
+    def test_deduplicates_uuids(self):
+        """Test that duplicate UUIDs are deduplicated."""
+        text = (
+            "Use 46631191-e8a8-486f-ad90-84f89738321d twice: "
+            "46631191-e8a8-486f-ad90-84f89738321d"
+        )
+        result = core.extract_uuids_from_text(text)
+        assert len(result) == 1
+
+    def test_normalizes_to_lowercase(self):
+        """Test that UUIDs are normalized to lowercase."""
+        text = "Use 46631191-E8A8-486F-AD90-84F89738321D"
+        result = core.extract_uuids_from_text(text)
+        assert result[0] == "46631191-e8a8-486f-ad90-84f89738321d"
+
+    def test_returns_empty_for_no_uuids(self):
+        """Test that empty list is returned when no UUIDs found."""
+        text = "Create an email agent that sends notifications"
+        result = core.extract_uuids_from_text(text)
+        assert result == []
+
+    def test_ignores_invalid_uuids(self):
+        """Test that invalid UUID-like strings are ignored."""
+        text = "Not a valid UUID: 12345678-1234-1234-1234-123456789abc"
+        result = core.extract_uuids_from_text(text)
+        # UUID v4 requires specific patterns (4 in third group, 8/9/a/b in fourth)
+        assert len(result) == 0
+
+
+class TestGetLibraryAgentById:
+    """Test get_library_agent_by_id function (and its alias get_library_agent_by_graph_id)."""
+
+    @pytest.mark.asyncio
+    async def test_returns_agent_when_found_by_graph_id(self):
+        """Test that agent is returned when found by graph_id."""
+        mock_agent = MagicMock()
+        mock_agent.graph_id = "agent-123"
+        mock_agent.graph_version = 1
+        mock_agent.name = "Test Agent"
+        mock_agent.description = "Test description"
+        mock_agent.input_schema = {"properties": {}}
+        mock_agent.output_schema = {"properties": {}}
+
+        with patch.object(
+            core.library_db,
+            "get_library_agent_by_graph_id",
+            new_callable=AsyncMock,
+            return_value=mock_agent,
+        ):
+            result = await core.get_library_agent_by_id("user-123", "agent-123")
+
+        assert result is not None
+        assert result["graph_id"] == "agent-123"
+        assert result["name"] == "Test Agent"
+
+    @pytest.mark.asyncio
+    async def test_falls_back_to_library_agent_id(self):
+        """Test that lookup falls back to library agent ID when graph_id not found."""
+        mock_agent = MagicMock()
+        mock_agent.graph_id = "graph-456"  # Different from the lookup ID
+        mock_agent.graph_version = 1
+        mock_agent.name = "Library Agent"
+        mock_agent.description = "Found by library ID"
+        mock_agent.input_schema = {"properties": {}}
+        mock_agent.output_schema = {"properties": {}}
+
+        with (
+            patch.object(
+                core.library_db,
+                "get_library_agent_by_graph_id",
+                new_callable=AsyncMock,
+                return_value=None,  # Not found by graph_id
+            ),
+            patch.object(
+                core.library_db,
+                "get_library_agent",
+                new_callable=AsyncMock,
+                return_value=mock_agent,  # Found by library ID
+            ),
+        ):
+            result = await core.get_library_agent_by_id("user-123", "library-id-123")
+
+        assert result is not None
+        assert result["graph_id"] == "graph-456"
+        assert result["name"] == "Library Agent"
+
+    @pytest.mark.asyncio
+    async def test_returns_none_when_not_found_by_either_method(self):
+        """Test that None is returned when agent not found by either method."""
+        with (
+            patch.object(
+                core.library_db,
+                "get_library_agent_by_graph_id",
+                new_callable=AsyncMock,
+                return_value=None,
+            ),
+            patch.object(
+                core.library_db,
+                "get_library_agent",
+                new_callable=AsyncMock,
+                side_effect=core.NotFoundError("Not found"),
+            ),
+        ):
+            result = await core.get_library_agent_by_id("user-123", "nonexistent")
+
+        assert result is None
+
+    @pytest.mark.asyncio
+    async def test_returns_none_on_exception(self):
+        """Test that None is returned when exception occurs in both lookups."""
+        with (
+            patch.object(
+                core.library_db,
+                "get_library_agent_by_graph_id",
+                new_callable=AsyncMock,
+                side_effect=Exception("Database error"),
+            ),
+            patch.object(
+                core.library_db,
+                "get_library_agent",
+                new_callable=AsyncMock,
+                side_effect=Exception("Database error"),
+            ),
+        ):
+            result = await core.get_library_agent_by_id("user-123", "agent-123")
+
+        assert result is None
+
+    @pytest.mark.asyncio
+    async def test_alias_works(self):
+        """Test that get_library_agent_by_graph_id is an alias for get_library_agent_by_id."""
+        assert core.get_library_agent_by_graph_id is core.get_library_agent_by_id
+
+
+class TestGetAllRelevantAgentsWithUuids:
+    """Test UUID extraction in get_all_relevant_agents_for_generation."""
+
+    @pytest.mark.asyncio
+    async def test_fetches_explicitly_mentioned_agents(self):
+        """Test that agents mentioned by UUID are fetched directly."""
+        mock_agent = MagicMock()
+        mock_agent.graph_id = "46631191-e8a8-486f-ad90-84f89738321d"
+        mock_agent.graph_version = 1
+        mock_agent.name = "Mentioned Agent"
+        mock_agent.description = "Explicitly mentioned"
+        mock_agent.input_schema = {}
+        mock_agent.output_schema = {}
+
+        mock_response = MagicMock()
+        mock_response.agents = []
+
+        with (
+            patch.object(
+                core.library_db,
+                "get_library_agent_by_graph_id",
+                new_callable=AsyncMock,
+                return_value=mock_agent,
+            ),
+            patch.object(
+                core.library_db,
+                "list_library_agents",
+                new_callable=AsyncMock,
+                return_value=mock_response,
+            ),
+        ):
+            result = await core.get_all_relevant_agents_for_generation(
+                user_id="user-123",
+                search_query="Use agent 46631191-e8a8-486f-ad90-84f89738321d",
+                include_marketplace=False,
+            )
+
+        assert len(result) == 1
+        assert result[0].get("graph_id") == "46631191-e8a8-486f-ad90-84f89738321d"
+        assert result[0].get("name") == "Mentioned Agent"
+
+
+if __name__ == "__main__":
+    pytest.main([__file__, "-v"])

autogpt_platform/backend/test/agent_generator/test_service.py

@@ -433,5 +433,139 @@ class TestGetBlocksExternal:
         assert result is None
 
 
+class TestLibraryAgentsPassthrough:
+    """Test that library_agents are passed correctly in all requests."""
+
+    def setup_method(self):
+        """Reset client singleton before each test."""
+        service._settings = None
+        service._client = None
+
+    @pytest.mark.asyncio
+    async def test_decompose_goal_passes_library_agents(self):
+        """Test that library_agents are included in decompose goal payload."""
+        library_agents = [
+            {
+                "graph_id": "agent-123",
+                "graph_version": 1,
+                "name": "Email Sender",
+                "description": "Sends emails",
+                "input_schema": {"properties": {"to": {"type": "string"}}},
+                "output_schema": {"properties": {"sent": {"type": "boolean"}}},
+            },
+        ]
+
+        mock_response = MagicMock()
+        mock_response.json.return_value = {
+            "success": True,
+            "type": "instructions",
+            "steps": ["Step 1"],
+        }
+        mock_response.raise_for_status = MagicMock()
+
+        mock_client = AsyncMock()
+        mock_client.post.return_value = mock_response
+
+        with patch.object(service, "_get_client", return_value=mock_client):
+            await service.decompose_goal_external(
+                "Send an email",
+                library_agents=library_agents,
+            )
+
+        # Verify library_agents was passed in the payload
+        call_args = mock_client.post.call_args
+        assert call_args[1]["json"]["library_agents"] == library_agents
+
+    @pytest.mark.asyncio
+    async def test_generate_agent_passes_library_agents(self):
+        """Test that library_agents are included in generate agent payload."""
+        library_agents = [
+            {
+                "graph_id": "agent-456",
+                "graph_version": 2,
+                "name": "Data Fetcher",
+                "description": "Fetches data from API",
+                "input_schema": {"properties": {"url": {"type": "string"}}},
+                "output_schema": {"properties": {"data": {"type": "object"}}},
+            },
+        ]
+
+        mock_response = MagicMock()
+        mock_response.json.return_value = {
+            "success": True,
+            "agent_json": {"name": "Test Agent", "nodes": []},
+        }
+        mock_response.raise_for_status = MagicMock()
+
+        mock_client = AsyncMock()
+        mock_client.post.return_value = mock_response
+
+        with patch.object(service, "_get_client", return_value=mock_client):
+            await service.generate_agent_external(
+                {"steps": ["Step 1"]},
+                library_agents=library_agents,
+            )
+
+        # Verify library_agents was passed in the payload
+        call_args = mock_client.post.call_args
+        assert call_args[1]["json"]["library_agents"] == library_agents
+
+    @pytest.mark.asyncio
+    async def test_generate_agent_patch_passes_library_agents(self):
+        """Test that library_agents are included in patch generation payload."""
+        library_agents = [
+            {
+                "graph_id": "agent-789",
+                "graph_version": 1,
+                "name": "Slack Notifier",
+                "description": "Sends Slack messages",
+                "input_schema": {"properties": {"message": {"type": "string"}}},
+                "output_schema": {"properties": {"success": {"type": "boolean"}}},
+            },
+        ]
+
+        mock_response = MagicMock()
+        mock_response.json.return_value = {
+            "success": True,
+            "agent_json": {"name": "Updated Agent", "nodes": []},
+        }
+        mock_response.raise_for_status = MagicMock()
+
+        mock_client = AsyncMock()
+        mock_client.post.return_value = mock_response
+
+        with patch.object(service, "_get_client", return_value=mock_client):
+            await service.generate_agent_patch_external(
+                "Add error handling",
+                {"name": "Original Agent", "nodes": []},
+                library_agents=library_agents,
+            )
+
+        # Verify library_agents was passed in the payload
+        call_args = mock_client.post.call_args
+        assert call_args[1]["json"]["library_agents"] == library_agents
+
+    @pytest.mark.asyncio
+    async def test_decompose_goal_without_library_agents(self):
+        """Test that decompose goal works without library_agents."""
+        mock_response = MagicMock()
+        mock_response.json.return_value = {
+            "success": True,
+            "type": "instructions",
+            "steps": ["Step 1"],
+        }
+        mock_response.raise_for_status = MagicMock()
+
+        mock_client = AsyncMock()
+        mock_client.post.return_value = mock_response
+
+        with patch.object(service, "_get_client", return_value=mock_client):
+            await service.decompose_goal_external("Build a workflow")
+
+        # Verify library_agents was NOT passed when not provided
+        call_args = mock_client.post.call_args
+        assert "library_agents" not in call_args[1]["json"]
+
+
 if __name__ == "__main__":
     pytest.main([__file__, "-v"])

autogpt_platform/frontend/src/app/(platform)/build/components/legacy-builder/CustomNode/CustomNode.tsx

@@ -857,7 +857,7 @@ export const CustomNode = React.memo(
     })();
 
     const hasAdvancedFields =
-      data.inputSchema &&
+      data.inputSchema?.properties &&
       Object.entries(data.inputSchema.properties).some(([key, value]) => {
         return (
           value.advanced === true && !data.inputSchema.required?.includes(key)

autogpt_platform/frontend/src/app/(platform)/library/components/__tests__/FavoritesSection.test.tsx

@@ -1,185 +0,0 @@
-import { describe, expect, test, afterEach } from "vitest";
-import { render, screen, waitFor } from "@/tests/integrations/test-utils";
-import { FavoritesSection } from "../FavoritesSection/FavoritesSection";
-import { server } from "@/mocks/mock-server";
-import { http, HttpResponse } from "msw";
-import {
-  mockAuthenticatedUser,
-  resetAuthState,
-} from "@/tests/integrations/helpers/mock-supabase-auth";
-
-const mockFavoriteAgent = {
-  id: "fav-agent-id",
-  graph_id: "fav-graph-id",
-  graph_version: 1,
-  owner_user_id: "test-owner-id",
-  image_url: null,
-  creator_name: "Test Creator",
-  creator_image_url: "https://example.com/avatar.png",
-  status: "READY",
-  created_at: new Date().toISOString(),
-  updated_at: new Date().toISOString(),
-  name: "Favorite Agent Name",
-  description: "Test favorite agent",
-  input_schema: {},
-  output_schema: {},
-  credentials_input_schema: null,
-  has_external_trigger: false,
-  has_human_in_the_loop: false,
-  has_sensitive_action: false,
-  new_output: false,
-  can_access_graph: true,
-  is_latest_version: true,
-  is_favorite: true,
-};
-
-describe("FavoritesSection", () => {
-  afterEach(() => {
-    resetAuthState();
-  });
-
-  test("renders favorites section when there are favorites", async () => {
-    mockAuthenticatedUser();
-
-    server.use(
-      http.get("*/api/library/agents/favorites*", () => {
-        return HttpResponse.json({
-          agents: [mockFavoriteAgent],
-          pagination: {
-            total_items: 1,
-            total_pages: 1,
-            current_page: 1,
-            page_size: 20,
-          },
-        });
-      }),
-    );
-
-    render(<FavoritesSection searchTerm="" />);
-
-    await waitFor(() => {
-      expect(screen.getByText(/favorites/i)).toBeInTheDocument();
-    });
-  });
-
-  test("renders favorite agent cards", async () => {
-    mockAuthenticatedUser();
-
-    server.use(
-      http.get("*/api/library/agents/favorites*", () => {
-        return HttpResponse.json({
-          agents: [mockFavoriteAgent],
-          pagination: {
-            total_items: 1,
-            total_pages: 1,
-            current_page: 1,
-            page_size: 20,
-          },
-        });
-      }),
-    );
-
-    render(<FavoritesSection searchTerm="" />);
-
-    await waitFor(() => {
-      expect(screen.getByText("Favorite Agent Name")).toBeInTheDocument();
-    });
-  });
-
-  test("shows agent count", async () => {
-    mockAuthenticatedUser();
-
-    server.use(
-      http.get("*/api/library/agents/favorites*", () => {
-        return HttpResponse.json({
-          agents: [mockFavoriteAgent],
-          pagination: {
-            total_items: 1,
-            total_pages: 1,
-            current_page: 1,
-            page_size: 20,
-          },
-        });
-      }),
-    );
-
-    render(<FavoritesSection searchTerm="" />);
-
-    await waitFor(() => {
-      expect(screen.getByTestId("agents-count")).toBeInTheDocument();
-    });
-  });
-
-  test("does not render when there are no favorites", async () => {
-    mockAuthenticatedUser();
-
-    server.use(
-      http.get("*/api/library/agents/favorites*", () => {
-        return HttpResponse.json({
-          agents: [],
-          pagination: {
-            total_items: 0,
-            total_pages: 0,
-            current_page: 1,
-            page_size: 20,
-          },
-        });
-      }),
-    );
-
-    const { container } = render(<FavoritesSection searchTerm="" />);
-
-    // Wait for loading to complete
-    await waitFor(() => {
-      // Component should return null when no favorites
-      expect(container.textContent).toBe("");
-    });
-  });
-
-  test("filters favorites based on search term", async () => {
-    mockAuthenticatedUser();
-
-    // Mock that returns different results based on search term
-    server.use(
-      http.get("*/api/library/agents/favorites*", ({ request }) => {
-        const url = new URL(request.url);
-        const searchTerm = url.searchParams.get("search_term");
-
-        if (searchTerm === "nonexistent") {
-          return HttpResponse.json({
-            agents: [],
-            pagination: {
-              total_items: 0,
-              total_pages: 0,
-              current_page: 1,
-              page_size: 20,
-            },
-          });
-        }
-
-        return HttpResponse.json({
-          agents: [mockFavoriteAgent],
-          pagination: {
-            total_items: 1,
-            total_pages: 1,
-            current_page: 1,
-            page_size: 20,
-          },
-        });
-      }),
-    );
-
-    const { rerender } = render(<FavoritesSection searchTerm="" />);
-
-    await waitFor(() => {
-      expect(screen.getByText("Favorite Agent Name")).toBeInTheDocument();
-    });
-
-    // Rerender with search term that yields no results
-    rerender(<FavoritesSection searchTerm="nonexistent" />);
-
-    await waitFor(() => {
-      expect(screen.queryByText("Favorite Agent Name")).not.toBeInTheDocument();
-    });
-  });
-});

autogpt_platform/frontend/src/app/(platform)/library/components/__tests__/LibraryAgentCard.test.tsx

@@ -1,122 +0,0 @@
-import { describe, expect, test, afterEach } from "vitest";
-import { render, screen } from "@/tests/integrations/test-utils";
-import { LibraryAgentCard } from "../LibraryAgentCard/LibraryAgentCard";
-import { LibraryAgent } from "@/app/api/__generated__/models/libraryAgent";
-import {
-  mockAuthenticatedUser,
-  resetAuthState,
-} from "@/tests/integrations/helpers/mock-supabase-auth";
-
-const mockAgent: LibraryAgent = {
-  id: "test-agent-id",
-  graph_id: "test-graph-id",
-  graph_version: 1,
-  owner_user_id: "test-owner-id",
-  image_url: null,
-  creator_name: "Test Creator",
-  creator_image_url: "https://example.com/avatar.png",
-  status: "READY",
-  created_at: new Date().toISOString(),
-  updated_at: new Date().toISOString(),
-  name: "Test Agent Name",
-  description: "Test agent description",
-  input_schema: {},
-  output_schema: {},
-  credentials_input_schema: null,
-  has_external_trigger: false,
-  has_human_in_the_loop: false,
-  has_sensitive_action: false,
-  new_output: false,
-  can_access_graph: true,
-  is_latest_version: true,
-  is_favorite: false,
-};
-
-describe("LibraryAgentCard", () => {
-  afterEach(() => {
-    resetAuthState();
-  });
-
-  test("renders agent name", () => {
-    mockAuthenticatedUser();
-    render(<LibraryAgentCard agent={mockAgent} />);
-
-    expect(screen.getByText("Test Agent Name")).toBeInTheDocument();
-  });
-
-  test("renders see runs link", () => {
-    mockAuthenticatedUser();
-    render(<LibraryAgentCard agent={mockAgent} />);
-
-    expect(screen.getByText(/see runs/i)).toBeInTheDocument();
-  });
-
-  test("renders open in builder link when can_access_graph is true", () => {
-    mockAuthenticatedUser();
-    render(<LibraryAgentCard agent={mockAgent} />);
-
-    expect(screen.getByText(/open in builder/i)).toBeInTheDocument();
-  });
-
-  test("does not render open in builder link when can_access_graph is false", () => {
-    mockAuthenticatedUser();
-    const agentWithoutAccess = { ...mockAgent, can_access_graph: false };
-    render(<LibraryAgentCard agent={agentWithoutAccess} />);
-
-    expect(screen.queryByText(/open in builder/i)).not.toBeInTheDocument();
-  });
-
-  test("shows 'FROM MARKETPLACE' label for marketplace agents", () => {
-    mockAuthenticatedUser();
-    const marketplaceAgent = {
-      ...mockAgent,
-      marketplace_listing: {
-        id: "listing-id",
-        name: "Marketplace Agent",
-        slug: "marketplace-agent",
-        creator: {
-          id: "creator-id",
-          name: "Creator Name",
-          slug: "creator-slug",
-        },
-      },
-    };
-    render(<LibraryAgentCard agent={marketplaceAgent} />);
-
-    expect(screen.getByText(/from marketplace/i)).toBeInTheDocument();
-  });
-
-  test("shows 'Built by you' label for user's own agents", () => {
-    mockAuthenticatedUser();
-    render(<LibraryAgentCard agent={mockAgent} />);
-
-    expect(screen.getByText(/built by you/i)).toBeInTheDocument();
-  });
-
-  test("renders favorite button", () => {
-    mockAuthenticatedUser();
-    render(<LibraryAgentCard agent={mockAgent} />);
-
-    // The favorite button should be present (as a heart icon button)
-    const card = screen.getByTestId("library-agent-card");
-    expect(card).toBeInTheDocument();
-  });
-
-  test("links to correct agent detail page", () => {
-    mockAuthenticatedUser();
-    render(<LibraryAgentCard agent={mockAgent} />);
-
-    const link = screen.getByTestId("library-agent-card-see-runs-link");
-    expect(link).toHaveAttribute("href", "/library/agents/test-agent-id");
-  });
-
-  test("links to correct builder page", () => {
-    mockAuthenticatedUser();
-    render(<LibraryAgentCard agent={mockAgent} />);
-
-    const builderLink = screen.getByTestId(
-      "library-agent-card-open-in-builder-link",
-    );
-    expect(builderLink).toHaveAttribute("href", "/build?flowID=test-graph-id");
-  });
-});

autogpt_platform/frontend/src/app/(platform)/library/components/__tests__/LibrarySearchBar.test.tsx

@@ -1,53 +0,0 @@
-import { describe, expect, test, vi } from "vitest";
-import { render, screen, fireEvent, waitFor } from "@/tests/integrations/test-utils";
-import { LibrarySearchBar } from "../LibrarySearchBar/LibrarySearchBar";
-
-describe("LibrarySearchBar", () => {
-  test("renders search input", () => {
-    const setSearchTerm = vi.fn();
-    render(<LibrarySearchBar setSearchTerm={setSearchTerm} />);
-
-    expect(screen.getByPlaceholderText(/search agents/i)).toBeInTheDocument();
-  });
-
-  test("renders search icon", () => {
-    const setSearchTerm = vi.fn();
-    const { container } = render(
-      <LibrarySearchBar setSearchTerm={setSearchTerm} />,
-    );
-
-    // Check for the magnifying glass icon (SVG element)
-    const searchIcon = container.querySelector("svg");
-    expect(searchIcon).toBeInTheDocument();
-  });
-
-  test("calls setSearchTerm on input change", async () => {
-    const setSearchTerm = vi.fn();
-    render(<LibrarySearchBar setSearchTerm={setSearchTerm} />);
-
-    const input = screen.getByPlaceholderText(/search agents/i);
-    fireEvent.change(input, { target: { value: "test query" } });
-
-    // The search bar uses debouncing, so we need to wait
-    await waitFor(
-      () => {
-        expect(setSearchTerm).toHaveBeenCalled();
-      },
-      { timeout: 1000 },
-    );
-  });
-
-  test("has correct test id", () => {
-    const setSearchTerm = vi.fn();
-    render(<LibrarySearchBar setSearchTerm={setSearchTerm} />);
-
-    expect(screen.getByTestId("search-bar")).toBeInTheDocument();
-  });
-
-  test("input has correct test id", () => {
-    const setSearchTerm = vi.fn();
-    render(<LibrarySearchBar setSearchTerm={setSearchTerm} />);
-
-    expect(screen.getByTestId("library-textbox")).toBeInTheDocument();
-  });
-});

autogpt_platform/frontend/src/app/(platform)/library/components/__tests__/LibrarySortMenu.test.tsx

@@ -1,53 +0,0 @@
-import { describe, expect, test, vi } from "vitest";
-import { render, screen, fireEvent, waitFor } from "@/tests/integrations/test-utils";
-import { LibrarySortMenu } from "../LibrarySortMenu/LibrarySortMenu";
-
-describe("LibrarySortMenu", () => {
-  test("renders sort dropdown", () => {
-    const setLibrarySort = vi.fn();
-    render(<LibrarySortMenu setLibrarySort={setLibrarySort} />);
-
-    expect(screen.getByTestId("sort-by-dropdown")).toBeInTheDocument();
-  });
-
-  test("shows 'sort by' label on larger screens", () => {
-    const setLibrarySort = vi.fn();
-    render(<LibrarySortMenu setLibrarySort={setLibrarySort} />);
-
-    expect(screen.getByText(/sort by/i)).toBeInTheDocument();
-  });
-
-  test("shows default placeholder text", () => {
-    const setLibrarySort = vi.fn();
-    render(<LibrarySortMenu setLibrarySort={setLibrarySort} />);
-
-    expect(screen.getByText(/last modified/i)).toBeInTheDocument();
-  });
-
-  test("opens dropdown when clicked", async () => {
-    const setLibrarySort = vi.fn();
-    render(<LibrarySortMenu setLibrarySort={setLibrarySort} />);
-
-    const trigger = screen.getByRole("combobox");
-    fireEvent.click(trigger);
-
-    await waitFor(() => {
-      expect(screen.getByText(/creation date/i)).toBeInTheDocument();
-    });
-  });
-
-  test("shows both sort options in dropdown", async () => {
-    const setLibrarySort = vi.fn();
-    render(<LibrarySortMenu setLibrarySort={setLibrarySort} />);
-
-    const trigger = screen.getByRole("combobox");
-    fireEvent.click(trigger);
-
-    await waitFor(() => {
-      expect(screen.getByText(/creation date/i)).toBeInTheDocument();
-      expect(
-        screen.getAllByText(/last modified/i).length,
-      ).toBeGreaterThanOrEqual(1);
-    });
-  });
-});

autogpt_platform/frontend/src/app/(platform)/library/components/__tests__/LibraryUploadAgentDialog.test.tsx

@@ -1,78 +0,0 @@
-import { describe, expect, test, afterEach } from "vitest";
-import { render, screen, fireEvent, waitFor } from "@/tests/integrations/test-utils";
-import LibraryUploadAgentDialog from "../LibraryUploadAgentDialog/LibraryUploadAgentDialog";
-import {
-  mockAuthenticatedUser,
-  resetAuthState,
-} from "@/tests/integrations/helpers/mock-supabase-auth";
-
-describe("LibraryUploadAgentDialog", () => {
-  afterEach(() => {
-    resetAuthState();
-  });
-
-  test("renders upload button", () => {
-    mockAuthenticatedUser();
-    render(<LibraryUploadAgentDialog />);
-
-    expect(
-      screen.getByRole("button", { name: /upload agent/i }),
-    ).toBeInTheDocument();
-  });
-
-  test("opens dialog when upload button is clicked", async () => {
-    mockAuthenticatedUser();
-    render(<LibraryUploadAgentDialog />);
-
-    const uploadButton = screen.getByRole("button", { name: /upload agent/i });
-    fireEvent.click(uploadButton);
-
-    await waitFor(() => {
-      expect(screen.getByText("Upload Agent")).toBeInTheDocument();
-    });
-  });
-
-  test("dialog contains agent name input", async () => {
-    mockAuthenticatedUser();
-    render(<LibraryUploadAgentDialog />);
-
-    const uploadButton = screen.getByRole("button", { name: /upload agent/i });
-    fireEvent.click(uploadButton);
-
-    await waitFor(() => {
-      expect(screen.getByLabelText(/agent name/i)).toBeInTheDocument();
-    });
-  });
-
-  test("dialog contains agent description input", async () => {
-    mockAuthenticatedUser();
-    render(<LibraryUploadAgentDialog />);
-
-    const uploadButton = screen.getByRole("button", { name: /upload agent/i });
-    fireEvent.click(uploadButton);
-
-    await waitFor(() => {
-      expect(screen.getByLabelText(/agent description/i)).toBeInTheDocument();
-    });
-  });
-
-  test("upload button is disabled when form is incomplete", async () => {
-    mockAuthenticatedUser();
-    render(<LibraryUploadAgentDialog />);
-
-    const triggerButton = screen.getByRole("button", { name: /upload agent/i });
-    fireEvent.click(triggerButton);
-
-    await waitFor(() => {
-      const submitButton = screen.getByRole("button", { name: /^upload$/i });
-      expect(submitButton).toBeDisabled();
-    });
-  });
-
-  test("has correct test id on trigger button", () => {
-    mockAuthenticatedUser();
-    render(<LibraryUploadAgentDialog />);
-
-    expect(screen.getByTestId("upload-agent-button")).toBeInTheDocument();
-  });
-});

autogpt_platform/frontend/src/app/(platform)/library/components/__tests__/auth-state.test.tsx

@@ -1,40 +0,0 @@
-import { describe, expect, test, afterEach } from "vitest";
-import { render, screen } from "@/tests/integrations/test-utils";
-import LibraryPage from "../../page";
-import {
-  mockAuthenticatedUser,
-  mockUnauthenticatedUser,
-  resetAuthState,
-} from "@/tests/integrations/helpers/mock-supabase-auth";
-
-describe("LibraryPage - Auth State", () => {
-  afterEach(() => {
-    resetAuthState();
-  });
-
-  test("renders page correctly when logged in", async () => {
-    mockAuthenticatedUser();
-    render(<LibraryPage />);
-
-    // Wait for upload button text to appear (indicates page is rendered)
-    expect(
-      await screen.findByText("Upload agent", { exact: false }),
-    ).toBeInTheDocument();
-
-    // Search bar should be visible
-    expect(screen.getByTestId("search-bar")).toBeInTheDocument();
-  });
-
-  test("renders page correctly when logged out", async () => {
-    mockUnauthenticatedUser();
-    render(<LibraryPage />);
-
-    // Wait for upload button text to appear (indicates page is rendered)
-    expect(
-      await screen.findByText("Upload agent", { exact: false }),
-    ).toBeInTheDocument();
-
-    // Search bar should still be visible
-    expect(screen.getByTestId("search-bar")).toBeInTheDocument();
-  });
-});

autogpt_platform/frontend/src/app/(platform)/library/components/__tests__/empty-state.test.tsx

@@ -1,82 +0,0 @@
-import { describe, expect, test, afterEach } from "vitest";
-import { render, screen, waitFor } from "@/tests/integrations/test-utils";
-import LibraryPage from "../../page";
-import { server } from "@/mocks/mock-server";
-import { http, HttpResponse } from "msw";
-import {
-  mockAuthenticatedUser,
-  resetAuthState,
-} from "@/tests/integrations/helpers/mock-supabase-auth";
-
-describe("LibraryPage - Empty State", () => {
-  afterEach(() => {
-    resetAuthState();
-  });
-
-  test("handles empty agents list gracefully", async () => {
-    mockAuthenticatedUser();
-
-    server.use(
-      http.get("*/api/library/agents*", () => {
-        return HttpResponse.json({
-          agents: [],
-          pagination: {
-            total_items: 0,
-            total_pages: 0,
-            current_page: 1,
-            page_size: 20,
-          },
-        });
-      }),
-      http.get("*/api/library/agents/favorites*", () => {
-        return HttpResponse.json({
-          agents: [],
-          pagination: {
-            total_items: 0,
-            total_pages: 0,
-            current_page: 1,
-            page_size: 20,
-          },
-        });
-      }),
-    );
-
-    render(<LibraryPage />);
-
-    // Page should still render without crashing
-    // Search bar should be visible even with no agents
-    expect(
-      await screen.findByPlaceholderText(/search agents/i),
-    ).toBeInTheDocument();
-
-    // Upload button should be visible
-    expect(
-      screen.getByRole("button", { name: /upload agent/i }),
-    ).toBeInTheDocument();
-  });
-
-  test("handles empty favorites gracefully", async () => {
-    mockAuthenticatedUser();
-
-    server.use(
-      http.get("*/api/library/agents/favorites*", () => {
-        return HttpResponse.json({
-          agents: [],
-          pagination: {
-            total_items: 0,
-            total_pages: 0,
-            current_page: 1,
-            page_size: 20,
-          },
-        });
-      }),
-    );
-
-    render(<LibraryPage />);
-
-    // Page should still render without crashing
-    expect(
-      await screen.findByPlaceholderText(/search agents/i),
-    ).toBeInTheDocument();
-  });
-});

autogpt_platform/frontend/src/app/(platform)/library/components/__tests__/error-handling.test.tsx

@@ -1,59 +0,0 @@
-import { describe, expect, test, afterEach } from "vitest";
-import { render, screen, waitFor } from "@/tests/integrations/test-utils";
-import LibraryPage from "../../page";
-import { server } from "@/mocks/mock-server";
-import {
-  mockAuthenticatedUser,
-  resetAuthState,
-} from "@/tests/integrations/helpers/mock-supabase-auth";
-import { create500Handler } from "@/tests/integrations/helpers/create-500-handler";
-import {
-  getGetV2ListLibraryAgentsMockHandler422,
-  getGetV2ListFavoriteLibraryAgentsMockHandler422,
-} from "@/app/api/__generated__/endpoints/library/library.msw";
-
-describe("LibraryPage - Error Handling", () => {
-  afterEach(() => {
-    resetAuthState();
-  });
-
-  test("handles API 422 error gracefully", async () => {
-    mockAuthenticatedUser();
-
-    server.use(getGetV2ListLibraryAgentsMockHandler422());
-
-    render(<LibraryPage />);
-
-    // Page should still render without crashing
-    // Search bar should be visible even with error
-    await waitFor(() => {
-      expect(screen.getByPlaceholderText(/search agents/i)).toBeInTheDocument();
-    });
-  });
-
-  test("handles favorites API 422 error gracefully", async () => {
-    mockAuthenticatedUser();
-
-    server.use(getGetV2ListFavoriteLibraryAgentsMockHandler422());
-
-    render(<LibraryPage />);
-
-    // Page should still render without crashing
-    await waitFor(() => {
-      expect(screen.getByPlaceholderText(/search agents/i)).toBeInTheDocument();
-    });
-  });
-
-  test("handles API 500 error gracefully", async () => {
-    mockAuthenticatedUser();
-
-    server.use(create500Handler("get", "*/api/library/agents*"));
-
-    render(<LibraryPage />);
-
-    // Page should still render without crashing
-    await waitFor(() => {
-      expect(screen.getByPlaceholderText(/search agents/i)).toBeInTheDocument();
-    });
-  });
-});

autogpt_platform/frontend/src/app/(platform)/library/components/__tests__/loading-state.test.tsx

@@ -1,55 +0,0 @@
-import { describe, expect, test, afterEach } from "vitest";
-import { render, screen } from "@/tests/integrations/test-utils";
-import LibraryPage from "../../page";
-import { server } from "@/mocks/mock-server";
-import { http, HttpResponse, delay } from "msw";
-import {
-  mockAuthenticatedUser,
-  resetAuthState,
-} from "@/tests/integrations/helpers/mock-supabase-auth";
-
-describe("LibraryPage - Loading State", () => {
-  afterEach(() => {
-    resetAuthState();
-  });
-
-  test("shows loading spinner while agents are being fetched", async () => {
-    mockAuthenticatedUser();
-
-    // Override handlers to add delay to simulate loading
-    server.use(
-      http.get("*/api/library/agents*", async () => {
-        await delay(500);
-        return HttpResponse.json({
-          agents: [],
-          pagination: {
-            total_items: 0,
-            total_pages: 0,
-            current_page: 1,
-            page_size: 20,
-          },
-        });
-      }),
-      http.get("*/api/library/agents/favorites*", async () => {
-        await delay(500);
-        return HttpResponse.json({
-          agents: [],
-          pagination: {
-            total_items: 0,
-            total_pages: 0,
-            current_page: 1,
-            page_size: 20,
-          },
-        });
-      }),
-    );
-
-    const { container } = render(<LibraryPage />);
-
-    // Check for loading spinner (LoadingSpinner component)
-    const loadingElements = container.querySelectorAll(
-      '[class*="animate-spin"]',
-    );
-    expect(loadingElements.length).toBeGreaterThan(0);
-  });
-});

autogpt_platform/frontend/src/app/(platform)/library/components/__tests__/rendering.test.tsx

@@ -1,65 +0,0 @@
-import { describe, expect, test, afterEach } from "vitest";
-import { render, screen, waitFor } from "@/tests/integrations/test-utils";
-import LibraryPage from "../../page";
-import {
-  mockAuthenticatedUser,
-  resetAuthState,
-} from "@/tests/integrations/helpers/mock-supabase-auth";
-
-describe("LibraryPage - Rendering", () => {
-  afterEach(() => {
-    resetAuthState();
-  });
-
-  test("renders search bar", async () => {
-    mockAuthenticatedUser();
-    render(<LibraryPage />);
-
-    expect(
-      await screen.findByPlaceholderText(/search agents/i),
-    ).toBeInTheDocument();
-  });
-
-  test("renders upload agent button", async () => {
-    mockAuthenticatedUser();
-    render(<LibraryPage />);
-
-    expect(
-      await screen.findByRole("button", { name: /upload agent/i }),
-    ).toBeInTheDocument();
-  });
-
-  test("renders agent cards when data is loaded", async () => {
-    mockAuthenticatedUser();
-    render(<LibraryPage />);
-
-    // Wait for agent cards to appear (from mock data)
-    await waitFor(() => {
-      const agentCards = screen.getAllByTestId("library-agent-card");
-      expect(agentCards.length).toBeGreaterThan(0);
-    });
-  });
-
-  test("agent cards display agent name", async () => {
-    mockAuthenticatedUser();
-    render(<LibraryPage />);
-
-    // Wait for agent cards and check they have names
-    await waitFor(() => {
-      const agentNames = screen.getAllByTestId("library-agent-card-name");
-      expect(agentNames.length).toBeGreaterThan(0);
-    });
-  });
-
-  test("agent cards have see runs link", async () => {
-    mockAuthenticatedUser();
-    render(<LibraryPage />);
-
-    await waitFor(() => {
-      const seeRunsLinks = screen.getAllByTestId(
-        "library-agent-card-see-runs-link",
-      );
-      expect(seeRunsLinks.length).toBeGreaterThan(0);
-    });
-  });
-});

autogpt_platform/frontend/src/app/api/openapi.json

@@ -7981,6 +7981,25 @@
             ]
           },
           "new_output": { "type": "boolean", "title": "New Output" },
+          "execution_count": {
+            "type": "integer",
+            "title": "Execution Count",
+            "default": 0
+          },
+          "success_rate": {
+            "anyOf": [{ "type": "number" }, { "type": "null" }],
+            "title": "Success Rate"
+          },
+          "avg_correctness_score": {
+            "anyOf": [{ "type": "number" }, { "type": "null" }],
+            "title": "Avg Correctness Score"
+          },
+          "recent_executions": {
+            "items": { "$ref": "#/components/schemas/RecentExecution" },
+            "type": "array",
+            "title": "Recent Executions",
+            "description": "List of recent executions with status, score, and summary"
+          },
           "can_access_graph": {
             "type": "boolean",
             "title": "Can Access Graph"
@@ -9374,6 +9393,23 @@
         "required": ["providers", "pagination"],
         "title": "ProviderResponse"
       },
+      "RecentExecution": {
+        "properties": {
+          "status": { "type": "string", "title": "Status" },
+          "correctness_score": {
+            "anyOf": [{ "type": "number" }, { "type": "null" }],
+            "title": "Correctness Score"
+          },
+          "activity_summary": {
+            "anyOf": [{ "type": "string" }, { "type": "null" }],
+            "title": "Activity Summary"
+          }
+        },
+        "type": "object",
+        "required": ["status"],
+        "title": "RecentExecution",
+        "description": "Summary of a recent execution for quality assessment.\n\nUsed by the LLM to understand the agent's recent performance with specific examples\nrather than just aggregate statistics."
+      },
       "RefundRequest": {
         "properties": {
           "id": { "type": "string", "title": "Id" },

autogpt_platform/frontend/src/components/contextual/Chat/components/ChatContainer/useChatContainerAiSdk.ts

@@ -1,246 +0,0 @@
-/**
- * useChatContainerAiSdk - ChatContainer hook using Vercel AI SDK
- *
- * This is a drop-in replacement for useChatContainer that uses @ai-sdk/react
- * instead of the custom streaming implementation. The API surface is identical
- * to enable easy A/B testing and gradual migration.
- */
-
-import type { SessionDetailResponse } from "@/app/api/__generated__/models/sessionDetailResponse";
-import { useEffect, useMemo, useRef } from "react";
-import type { UIMessage } from "ai";
-import { useAiSdkChat } from "../../useAiSdkChat";
-import { usePageContext } from "../../usePageContext";
-import type { ChatMessageData } from "../ChatMessage/useChatMessage";
-import {
-  filterAuthMessages,
-  hasSentInitialPrompt,
-  markInitialPromptSent,
-  processInitialMessages,
-} from "./helpers";
-
-// Helper to convert backend messages to AI SDK UIMessage format
-function convertToUIMessages(
-  messages: SessionDetailResponse["messages"],
-): UIMessage[] {
-  const result: UIMessage[] = [];
-
-  for (const msg of messages) {
-    if (!msg.role || !msg.content) continue;
-
-    // Create parts based on message type
-    const parts: UIMessage["parts"] = [];
-
-    if (msg.role === "user" || msg.role === "assistant") {
-      if (typeof msg.content === "string") {
-        parts.push({ type: "text", text: msg.content });
-      }
-    }
-
-    // Handle tool calls in assistant messages
-    if (msg.role === "assistant" && msg.tool_calls) {
-      for (const toolCall of msg.tool_calls as Array<{
-        id: string;
-        type: string;
-        function: { name: string; arguments: string };
-      }>) {
-        if (toolCall.type === "function") {
-          let args = {};
-          try {
-            args = JSON.parse(toolCall.function.arguments);
-          } catch {
-            // Keep empty args
-          }
-          parts.push({
-            type: `tool-${toolCall.function.name}` as `tool-${string}`,
-            toolCallId: toolCall.id,
-            toolName: toolCall.function.name,
-            state: "input-available",
-            input: args,
-          } as UIMessage["parts"][number]);
-        }
-      }
-    }
-
-    // Handle tool responses
-    if (msg.role === "tool" && msg.tool_call_id) {
-      // Find the matching tool call to get the name
-      const toolName = "unknown";
-      let output: unknown = msg.content;
-      try {
-        output =
-          typeof msg.content === "string"
-            ? JSON.parse(msg.content)
-            : msg.content;
-      } catch {
-        // Keep as string
-      }
-
-      parts.push({
-        type: `tool-${toolName}` as `tool-${string}`,
-        toolCallId: msg.tool_call_id as string,
-        toolName,
-        state: "output-available",
-        output,
-      } as UIMessage["parts"][number]);
-    }
-
-    if (parts.length > 0) {
-      result.push({
-        id: msg.id || `msg-${Date.now()}-${Math.random()}`,
-        role: msg.role === "tool" ? "assistant" : (msg.role as "user" | "assistant"),
-        parts,
-        createdAt: msg.created_at ? new Date(msg.created_at as string) : new Date(),
-      });
-    }
-  }
-
-  return result;
-}
-
-interface Args {
-  sessionId: string | null;
-  initialMessages: SessionDetailResponse["messages"];
-  initialPrompt?: string;
-  onOperationStarted?: () => void;
-}
-
-export function useChatContainerAiSdk({
-  sessionId,
-  initialMessages,
-  initialPrompt,
-  onOperationStarted,
-}: Args) {
-  const { capturePageContext } = usePageContext();
-  const sendMessageRef = useRef<
-    (
-      content: string,
-      isUserMessage?: boolean,
-      context?: { url: string; content: string },
-    ) => Promise<void>
-  >();
-
-  // Convert initial messages to AI SDK format
-  const uiMessages = useMemo(
-    () => convertToUIMessages(initialMessages),
-    [initialMessages],
-  );
-
-  const {
-    messages: aiSdkMessages,
-    streamingChunks,
-    isStreaming,
-    error,
-    isRegionBlockedModalOpen,
-    setIsRegionBlockedModalOpen,
-    sendMessage,
-    stopStreaming,
-  } = useAiSdkChat({
-    sessionId,
-    initialMessages: uiMessages,
-    onOperationStarted,
-  });
-
-  // Keep ref updated for initial prompt handling
-  sendMessageRef.current = sendMessage;
-
-  // Merge AI SDK messages with processed initial messages
-  // This ensures we show both historical messages and new streaming messages
-  const allMessages = useMemo(() => {
-    const processedInitial = processInitialMessages(initialMessages);
-
-    // Build a set of message keys for deduplication
-    const seenKeys = new Set<string>();
-    const result: ChatMessageData[] = [];
-
-    // Add processed initial messages first
-    for (const msg of processedInitial) {
-      const key = getMessageKey(msg);
-      if (!seenKeys.has(key)) {
-        seenKeys.add(key);
-        result.push(msg);
-      }
-    }
-
-    // Add AI SDK messages that aren't duplicates
-    for (const msg of aiSdkMessages) {
-      const key = getMessageKey(msg);
-      if (!seenKeys.has(key)) {
-        seenKeys.add(key);
-        result.push(msg);
-      }
-    }
-
-    return result;
-  }, [initialMessages, aiSdkMessages]);
-
-  // Handle initial prompt
-  useEffect(
-    function handleInitialPrompt() {
-      if (!initialPrompt || !sessionId) return;
-      if (initialMessages.length > 0) return;
-      if (hasSentInitialPrompt(sessionId)) return;
-
-      markInitialPromptSent(sessionId);
-      const context = capturePageContext();
-      sendMessageRef.current?.(initialPrompt, true, context);
-    },
-    [initialPrompt, sessionId, initialMessages.length, capturePageContext],
-  );
-
-  // Send message with page context
-  async function sendMessageWithContext(
-    content: string,
-    isUserMessage: boolean = true,
-  ) {
-    const context = capturePageContext();
-    await sendMessage(content, isUserMessage, context);
-  }
-
-  function handleRegionModalOpenChange(open: boolean) {
-    setIsRegionBlockedModalOpen(open);
-  }
-
-  function handleRegionModalClose() {
-    setIsRegionBlockedModalOpen(false);
-  }
-
-  return {
-    messages: filterAuthMessages(allMessages),
-    streamingChunks,
-    isStreaming,
-    error,
-    isRegionBlockedModalOpen,
-    setIsRegionBlockedModalOpen,
-    sendMessageWithContext,
-    handleRegionModalOpenChange,
-    handleRegionModalClose,
-    sendMessage,
-    stopStreaming,
-  };
-}
-
-// Helper to generate deduplication key for a message
-function getMessageKey(msg: ChatMessageData): string {
-  if (msg.type === "message") {
-    return `msg:${msg.role}:${msg.content}`;
-  } else if (msg.type === "tool_call") {
-    return `toolcall:${msg.toolId}`;
-  } else if (msg.type === "tool_response") {
-    return `toolresponse:${(msg as { toolId?: string }).toolId}`;
-  } else if (
-    msg.type === "operation_started" ||
-    msg.type === "operation_pending" ||
-    msg.type === "operation_in_progress"
-  ) {
-    const typedMsg = msg as {
-      toolId?: string;
-      operationId?: string;
-      toolCallId?: string;
-      toolName?: string;
-    };
-    return `op:${typedMsg.toolId || typedMsg.operationId || typedMsg.toolCallId || ""}:${typedMsg.toolName || ""}`;
-  } else {
-    return `${msg.type}:${JSON.stringify(msg).slice(0, 100)}`;
-  }
-}

autogpt_platform/frontend/src/components/contextual/Chat/components/ChatMessage/ChatMessage.tsx

@@ -156,11 +156,19 @@ export function ChatMessage({
   }
 
   if (isClarificationNeeded && message.type === "clarification_needed") {
+    const hasUserReplyAfter =
+      index >= 0 &&
+      messages
+        .slice(index + 1)
+        .some((m) => m.type === "message" && m.role === "user");
+
     return (
       <ClarificationQuestionsWidget
         questions={message.questions}
         message={message.message}
+        sessionId={message.sessionId}
         onSubmitAnswers={handleClarificationAnswers}
+        isAnswered={hasUserReplyAfter}
         className={className}
       />
     );

autogpt_platform/frontend/src/components/contextual/Chat/components/ClarificationQuestionsWidget/ClarificationQuestionsWidget.tsx

@@ -6,7 +6,7 @@ import { Input } from "@/components/atoms/Input/Input";
 import { Text } from "@/components/atoms/Text/Text";
 import { cn } from "@/lib/utils";
 import { CheckCircleIcon, QuestionIcon } from "@phosphor-icons/react";
-import { useState } from "react";
+import { useState, useEffect, useRef } from "react";
 
 export interface ClarifyingQuestion {
   question: string;
@@ -17,39 +17,96 @@ export interface ClarifyingQuestion {
 interface Props {
   questions: ClarifyingQuestion[];
   message: string;
+  sessionId?: string;
   onSubmitAnswers: (answers: Record<string, string>) => void;
   onCancel?: () => void;
+  isAnswered?: boolean;
   className?: string;
 }
 
+function getStorageKey(sessionId?: string): string | null {
+  if (!sessionId) return null;
+  return `clarification_answers_${sessionId}`;
+}
+
 export function ClarificationQuestionsWidget({
   questions,
   message,
+  sessionId,
   onSubmitAnswers,
   onCancel,
+  isAnswered = false,
   className,
 }: Props) {
   const [answers, setAnswers] = useState<Record<string, string>>({});
   const [isSubmitted, setIsSubmitted] = useState(false);
+  const lastSessionIdRef = useRef<string | undefined>(undefined);
+
+  useEffect(() => {
+    const storageKey = getStorageKey(sessionId);
+    if (!storageKey) {
+      setAnswers({});
+      setIsSubmitted(false);
+      lastSessionIdRef.current = sessionId;
+      return;
+    }
+
+    try {
+      const saved = localStorage.getItem(storageKey);
+      if (saved) {
+        const parsed = JSON.parse(saved) as Record<string, string>;
+        setAnswers(parsed);
+      } else {
+        setAnswers({});
+      }
+      setIsSubmitted(false);
+    } catch {
+      setAnswers({});
+      setIsSubmitted(false);
+    }
+    lastSessionIdRef.current = sessionId;
+  }, [sessionId]);
+
+  useEffect(() => {
+    if (lastSessionIdRef.current !== sessionId) {
+      return;
+    }
+    const storageKey = getStorageKey(sessionId);
+    if (!storageKey) return;
+
+    const hasAnswers = Object.values(answers).some((v) => v.trim());
+    try {
+      if (hasAnswers) {
+        localStorage.setItem(storageKey, JSON.stringify(answers));
+      } else {
+        localStorage.removeItem(storageKey);
+      }
+    } catch {}
+  }, [answers, sessionId]);
 
   function handleAnswerChange(keyword: string, value: string) {
     setAnswers((prev) => ({ ...prev, [keyword]: value }));
   }
 
   function handleSubmit() {
-    // Check if all questions are answered
     const allAnswered = questions.every((q) => answers[q.keyword]?.trim());
     if (!allAnswered) {
       return;
     }
     setIsSubmitted(true);
     onSubmitAnswers(answers);
+
+    const storageKey = getStorageKey(sessionId);
+    try {
+      if (storageKey) {
+        localStorage.removeItem(storageKey);
+      }
+    } catch {}
   }
 
   const allAnswered = questions.every((q) => answers[q.keyword]?.trim());
 
-  // Show submitted state after answers are submitted
+  if (isAnswered || isSubmitted) {
-  if (isSubmitted) {
     return (
       <div
         className={cn(

autogpt_platform/frontend/src/components/contextual/Chat/components/ToolResponseMessage/helpers.ts

@@ -30,9 +30,9 @@ export function getErrorMessage(result: unknown): string {
   }
   if (typeof result === "object" && result !== null) {
     const response = result as Record<string, unknown>;
-    if (response.error) return stripInternalReasoning(String(response.error));
     if (response.message)
       return stripInternalReasoning(String(response.message));
+    if (response.error) return stripInternalReasoning(String(response.error));
   }
   return "An error occurred";
 }
@@ -363,8 +363,8 @@ export function formatToolResponse(result: unknown, toolName: string): string {
 
     case "error":
       const errorMsg =
-        (response.error as string) || response.message || "An error occurred";
+        (response.message as string) || response.error || "An error occurred";
-      return `Error: ${errorMsg}`;
+      return stripInternalReasoning(String(errorMsg));
 
     case "no_results":
       const suggestions = (response.suggestions as string[]) || [];

autogpt_platform/frontend/src/components/contextual/Chat/useAiSdkChat.ts

@@ -1,421 +0,0 @@
-"use client";
-
-/**
- * useAiSdkChat - Vercel AI SDK integration for CoPilot Chat
- *
- * This hook wraps @ai-sdk/react's useChat to provide:
- * - Streaming chat with the existing Python backend (already AI SDK protocol compatible)
- * - Integration with existing session management
- * - Custom tool response parsing for AutoGPT-specific types
- * - Page context injection
- *
- * The Python backend already implements the AI SDK Data Stream Protocol (v1),
- * so this hook can communicate directly without any backend changes.
- */
-
-import { useChat as useAiSdkChatBase } from "@ai-sdk/react";
-import { DefaultChatTransport, type UIMessage } from "ai";
-import { useCallback, useEffect, useMemo, useRef, useState } from "react";
-import { toast } from "sonner";
-import type { ChatMessageData } from "./components/ChatMessage/useChatMessage";
-
-// Tool response types from the backend
-type OperationType =
-  | "operation_started"
-  | "operation_pending"
-  | "operation_in_progress";
-
-interface ToolOutputBase {
-  type: string;
-  [key: string]: unknown;
-}
-
-interface UseAiSdkChatOptions {
-  sessionId: string | null;
-  initialMessages?: UIMessage[];
-  onOperationStarted?: () => void;
-  onStreamingChange?: (isStreaming: boolean) => void;
-}
-
-/**
- * Parse tool output from AI SDK message parts into ChatMessageData format
- */
-function parseToolOutput(
-  toolCallId: string,
-  toolName: string,
-  output: unknown,
-): ChatMessageData | null {
-  if (!output) return null;
-
-  let parsed: ToolOutputBase;
-  try {
-    parsed =
-      typeof output === "string"
-        ? JSON.parse(output)
-        : (output as ToolOutputBase);
-  } catch {
-    return null;
-  }
-
-  const type = parsed.type;
-
-  // Handle operation status types
-  if (
-    type === "operation_started" ||
-    type === "operation_pending" ||
-    type === "operation_in_progress"
-  ) {
-    return {
-      type: type as OperationType,
-      toolId: toolCallId,
-      toolName: toolName,
-      operationId: (parsed.operation_id as string) || undefined,
-      message: (parsed.message as string) || undefined,
-      timestamp: new Date(),
-    } as ChatMessageData;
-  }
-
-  // Handle agent carousel
-  if (type === "agent_carousel" && Array.isArray(parsed.agents)) {
-    return {
-      type: "agent_carousel",
-      toolId: toolCallId,
-      toolName: toolName,
-      agents: parsed.agents,
-      timestamp: new Date(),
-    } as ChatMessageData;
-  }
-
-  // Handle execution started
-  if (type === "execution_started") {
-    return {
-      type: "execution_started",
-      toolId: toolCallId,
-      toolName: toolName,
-      graphId: parsed.graph_id as string,
-      graphVersion: parsed.graph_version as number,
-      graphExecId: parsed.graph_exec_id as string,
-      nodeExecIds: parsed.node_exec_ids as string[],
-      timestamp: new Date(),
-    } as ChatMessageData;
-  }
-
-  // Handle error responses
-  if (type === "error") {
-    return {
-      type: "tool_response",
-      toolId: toolCallId,
-      toolName: toolName,
-      result: parsed,
-      success: false,
-      timestamp: new Date(),
-    } as ChatMessageData;
-  }
-
-  // Handle clarification questions
-  if (type === "clarification_questions" && Array.isArray(parsed.questions)) {
-    return {
-      type: "clarification_questions",
-      toolId: toolCallId,
-      toolName: toolName,
-      questions: parsed.questions,
-      timestamp: new Date(),
-    } as ChatMessageData;
-  }
-
-  // Handle credentials needed
-  if (type === "credentials_needed" || type === "setup_requirements") {
-    const credentials = parsed.credentials as
-      | Array<{
-          provider: string;
-          provider_name: string;
-          credential_type: string;
-          scopes?: string[];
-        }>
-      | undefined;
-    if (credentials && credentials.length > 0) {
-      return {
-        type: "credentials_needed",
-        toolId: toolCallId,
-        toolName: toolName,
-        credentials: credentials,
-        timestamp: new Date(),
-      } as ChatMessageData;
-    }
-  }
-
-  // Default: generic tool response
-  return {
-    type: "tool_response",
-    toolId: toolCallId,
-    toolName: toolName,
-    result: parsed,
-    success: true,
-    timestamp: new Date(),
-  } as ChatMessageData;
-}
-
-/**
- * Convert AI SDK UIMessage parts to ChatMessageData array
- */
-function convertMessageToChatData(message: UIMessage): ChatMessageData[] {
-  const result: ChatMessageData[] = [];
-
-  for (const part of message.parts) {
-    switch (part.type) {
-      case "text":
-        if (part.text.trim()) {
-          result.push({
-            type: "message",
-            role: message.role as "user" | "assistant",
-            content: part.text,
-            timestamp: new Date(message.createdAt || Date.now()),
-          });
-        }
-        break;
-
-      default:
-        // Handle tool parts (tool-*)
-        if (part.type.startsWith("tool-")) {
-          const toolPart = part as {
-            type: string;
-            toolCallId: string;
-            toolName: string;
-            state: string;
-            input?: Record<string, unknown>;
-            output?: unknown;
-          };
-
-          // Show tool call in progress
-          if (
-            toolPart.state === "input-streaming" ||
-            toolPart.state === "input-available"
-          ) {
-            result.push({
-              type: "tool_call",
-              toolId: toolPart.toolCallId,
-              toolName: toolPart.toolName,
-              arguments: toolPart.input || {},
-              timestamp: new Date(),
-            });
-          }
-
-          // Parse tool output when available
-          if (
-            toolPart.state === "output-available" &&
-            toolPart.output !== undefined
-          ) {
-            const parsed = parseToolOutput(
-              toolPart.toolCallId,
-              toolPart.toolName,
-              toolPart.output,
-            );
-            if (parsed) {
-              result.push(parsed);
-            }
-          }
-
-          // Handle tool errors
-          if (toolPart.state === "output-error") {
-            result.push({
-              type: "tool_response",
-              toolId: toolPart.toolCallId,
-              toolName: toolPart.toolName,
-              response: {
-                type: "error",
-                message: (toolPart as { errorText?: string }).errorText,
-              },
-              success: false,
-              timestamp: new Date(),
-            } as ChatMessageData);
-          }
-        }
-        break;
-    }
-  }
-
-  return result;
-}
-
-export function useAiSdkChat({
-  sessionId,
-  initialMessages = [],
-  onOperationStarted,
-  onStreamingChange,
-}: UseAiSdkChatOptions) {
-  const [isRegionBlockedModalOpen, setIsRegionBlockedModalOpen] =
-    useState(false);
-  const previousSessionIdRef = useRef<string | null>(null);
-  const hasNotifiedOperationRef = useRef<Set<string>>(new Set());
-
-  // Create transport with session-specific endpoint
-  const transport = useMemo(() => {
-    if (!sessionId) return undefined;
-    return new DefaultChatTransport({
-      api: `/api/chat/sessions/${sessionId}/stream`,
-      headers: {
-        "Content-Type": "application/json",
-      },
-    });
-  }, [sessionId]);
-
-  const {
-    messages: aiMessages,
-    status,
-    error,
-    stop,
-    setMessages,
-    sendMessage: aiSendMessage,
-  } = useAiSdkChatBase({
-    transport,
-    initialMessages,
-    onError: (err) => {
-      console.error("[useAiSdkChat] Error:", err);
-
-      // Check for region blocking
-      if (
-        err.message?.toLowerCase().includes("not available in your region") ||
-        (err as { code?: string }).code === "MODEL_NOT_AVAILABLE_REGION"
-      ) {
-        setIsRegionBlockedModalOpen(true);
-        return;
-      }
-
-      toast.error("Chat Error", {
-        description: err.message || "An error occurred",
-      });
-    },
-    onFinish: ({ message }) => {
-      console.info("[useAiSdkChat] Message finished:", {
-        id: message.id,
-        partsCount: message.parts.length,
-      });
-    },
-  });
-
-  // Track streaming status
-  const isStreaming = status === "streaming" || status === "submitted";
-
-  // Notify parent of streaming changes
-  useEffect(() => {
-    onStreamingChange?.(isStreaming);
-  }, [isStreaming, onStreamingChange]);
-
-  // Handle session changes - reset state
-  useEffect(() => {
-    if (sessionId === previousSessionIdRef.current) return;
-
-    if (previousSessionIdRef.current && status === "streaming") {
-      stop();
-    }
-
-    previousSessionIdRef.current = sessionId;
-    hasNotifiedOperationRef.current = new Set();
-
-    if (sessionId) {
-      setMessages(initialMessages);
-    }
-  }, [sessionId, status, stop, setMessages, initialMessages]);
-
-  // Convert AI SDK messages to ChatMessageData format
-  const messages = useMemo(() => {
-    const result: ChatMessageData[] = [];
-
-    for (const message of aiMessages) {
-      const converted = convertMessageToChatData(message);
-      result.push(...converted);
-
-      // Check for operation_started and notify
-      for (const msg of converted) {
-        if (
-          msg.type === "operation_started" &&
-          !hasNotifiedOperationRef.current.has(
-            (msg as { toolId?: string }).toolId || "",
-          )
-        ) {
-          hasNotifiedOperationRef.current.add(
-            (msg as { toolId?: string }).toolId || "",
-          );
-          onOperationStarted?.();
-        }
-      }
-    }
-
-    return result;
-  }, [aiMessages, onOperationStarted]);
-
-  // Get streaming text chunks from the last assistant message
-  const streamingChunks = useMemo(() => {
-    if (!isStreaming) return [];
-
-    const lastMessage = aiMessages[aiMessages.length - 1];
-    if (!lastMessage || lastMessage.role !== "assistant") return [];
-
-    const chunks: string[] = [];
-    for (const part of lastMessage.parts) {
-      if (part.type === "text" && part.text) {
-        chunks.push(part.text);
-      }
-    }
-
-    return chunks;
-  }, [aiMessages, isStreaming]);
-
-  // Send message with optional context
-  const sendMessage = useCallback(
-    async (
-      content: string,
-      isUserMessage: boolean = true,
-      context?: { url: string; content: string },
-    ) => {
-      if (!sessionId || !transport) {
-        console.error("[useAiSdkChat] Cannot send message: no session");
-        return;
-      }
-
-      setIsRegionBlockedModalOpen(false);
-
-      try {
-        await aiSendMessage(
-          { text: content },
-          {
-            body: {
-              is_user_message: isUserMessage,
-              context: context || null,
-            },
-          },
-        );
-      } catch (err) {
-        console.error("[useAiSdkChat] Failed to send message:", err);
-
-        if (err instanceof Error && err.name === "AbortError") return;
-
-        toast.error("Failed to send message", {
-          description:
-            err instanceof Error ? err.message : "Failed to send message",
-        });
-      }
-    },
-    [sessionId, transport, aiSendMessage],
-  );
-
-  // Stop streaming
-  const stopStreaming = useCallback(() => {
-    stop();
-  }, [stop]);
-
-  return {
-    messages,
-    streamingChunks,
-    isStreaming,
-    error,
-    status,
-    isRegionBlockedModalOpen,
-    setIsRegionBlockedModalOpen,
-    sendMessage,
-    stopStreaming,
-    // Expose raw AI SDK state for advanced use cases
-    aiMessages,
-    setAiMessages: setMessages,
-  };
-}

docs/platform/create-basic-agent.md

@@ -4,6 +4,28 @@
 
 This guide walks through creating a simple question-answer AI agent using AutoGPT's visual builder. This is a basic example that can be expanded into more complex agents.
 
+## **Prerequisites**
+
+### **Cloud-Hosted AutoGPT**
+If you're using the cloud-hosted version at [agpt.co](https://agpt.co), you're ready to go! AI blocks come with **built-in credits** — no API keys required to get started. If you'd prefer to use your own API keys, you can add them via **Profile → Integrations**.
+
+### **Self-Hosted (Docker)**
+If you're running AutoGPT locally with Docker, you'll need to add your own API keys to `autogpt_platform/backend/.env`:
+
+```bash
+# Create or edit backend/.env
+OPENAI_API_KEY=sk-your-key-here
+ANTHROPIC_API_KEY=sk-ant-your-key-here
+# Add other provider keys as needed
+```
+
+After adding keys, restart the services:
+```bash
+docker compose down && docker compose up -d
+```
+
+**Note:** The Calculator example below doesn't require any API credentials — it's a good way to test your setup before adding AI blocks.
+
 ## **Example Agent: Q&A (with AI)**
 
 A step-by-step guide to creating a simple Q&A agent using input and output blocks.