fix(backend/copilot): prevent double upload in timeout handling

Previous fix created NEW task after timeout, causing double upload:
- Original shielded task still running
- New task also uploading same transcript

Correct fix: Create task FIRST, then shield it. If timeout occurs,
track the SAME task (no double upload).

Fixes double-upload bug in b8c65e3d2

autogpt_platform/backend/backend/api/external/v1/routes.py

@@ -1,7 +1,7 @@
 import logging
 import urllib.parse
 from collections import defaultdict
-from typing import Annotated, Any, Optional, Sequence
+from typing import Annotated, Any, Literal, Optional, Sequence
 
 from fastapi import APIRouter, Body, HTTPException, Security
 from prisma.enums import AgentExecutionStatus, APIKeyPermission
@@ -9,10 +9,9 @@ from pydantic import BaseModel, Field
 from typing_extensions import TypedDict
 
 import backend.api.features.store.cache as store_cache
-import backend.api.features.store.db as store_db
 import backend.api.features.store.model as store_model
 import backend.blocks
-from backend.api.external.middleware import require_auth, require_permission
+from backend.api.external.middleware import require_permission
 from backend.data import execution as execution_db
 from backend.data import graph as graph_db
 from backend.data import user as user_db
@@ -231,13 +230,13 @@ async def get_graph_execution_results(
 @v1_router.get(
     path="/store/agents",
     tags=["store"],
-    dependencies=[Security(require_auth)],  # data is public; auth required as anti-DDoS
+    dependencies=[Security(require_permission(APIKeyPermission.READ_STORE))],
     response_model=store_model.StoreAgentsResponse,
 )
 async def get_store_agents(
     featured: bool = False,
     creator: str | None = None,
-    sorted_by: store_db.StoreAgentsSortOptions | None = None,
+    sorted_by: Literal["rating", "runs", "name", "updated_at"] | None = None,
     search_query: str | None = None,
     category: str | None = None,
     page: int = 1,
@@ -279,7 +278,7 @@ async def get_store_agents(
 @v1_router.get(
     path="/store/agents/{username}/{agent_name}",
     tags=["store"],
-    dependencies=[Security(require_auth)],  # data is public; auth required as anti-DDoS
+    dependencies=[Security(require_permission(APIKeyPermission.READ_STORE))],
     response_model=store_model.StoreAgentDetails,
 )
 async def get_store_agent(
@@ -307,13 +306,13 @@ async def get_store_agent(
 @v1_router.get(
     path="/store/creators",
     tags=["store"],
-    dependencies=[Security(require_auth)],  # data is public; auth required as anti-DDoS
+    dependencies=[Security(require_permission(APIKeyPermission.READ_STORE))],
     response_model=store_model.CreatorsResponse,
 )
 async def get_store_creators(
     featured: bool = False,
     search_query: str | None = None,
-    sorted_by: store_db.StoreCreatorsSortOptions | None = None,
+    sorted_by: Literal["agent_rating", "agent_runs", "num_agents"] | None = None,
     page: int = 1,
     page_size: int = 20,
 ) -> store_model.CreatorsResponse:
@@ -349,7 +348,7 @@ async def get_store_creators(
 @v1_router.get(
     path="/store/creators/{username}",
     tags=["store"],
-    dependencies=[Security(require_auth)],  # data is public; auth required as anti-DDoS
+    dependencies=[Security(require_permission(APIKeyPermission.READ_STORE))],
     response_model=store_model.CreatorDetails,
 )
 async def get_store_creator(

autogpt_platform/backend/backend/api/features/admin/store_admin_routes.py

@@ -24,13 +24,14 @@ router = fastapi.APIRouter(
 @router.get(
     "/listings",
     summary="Get Admin Listings History",
+    response_model=store_model.StoreListingsWithVersionsResponse,
 )
 async def get_admin_listings_with_versions(
     status: typing.Optional[prisma.enums.SubmissionStatus] = None,
     search: typing.Optional[str] = None,
     page: int = 1,
     page_size: int = 20,
-) -> store_model.StoreListingsWithVersionsAdminViewResponse:
+):
     """
     Get store listings with their version history for admins.
 
@@ -44,26 +45,36 @@ async def get_admin_listings_with_versions(
         page_size: Number of items per page
 
     Returns:
-        Paginated listings with their versions
+        StoreListingsWithVersionsResponse with listings and their versions
     """
-    listings = await store_db.get_admin_listings_with_versions(
-        status=status,
-        search_query=search,
-        page=page,
-        page_size=page_size,
-    )
-    return listings
+    try:
+        listings = await store_db.get_admin_listings_with_versions(
+            status=status,
+            search_query=search,
+            page=page,
+            page_size=page_size,
+        )
+        return listings
+    except Exception as e:
+        logger.exception("Error getting admin listings with versions: %s", e)
+        return fastapi.responses.JSONResponse(
+            status_code=500,
+            content={
+                "detail": "An error occurred while retrieving listings with versions"
+            },
+        )
 
 
 @router.post(
     "/submissions/{store_listing_version_id}/review",
     summary="Review Store Submission",
+    response_model=store_model.StoreSubmission,
 )
 async def review_submission(
     store_listing_version_id: str,
     request: store_model.ReviewSubmissionRequest,
     user_id: str = fastapi.Security(autogpt_libs.auth.get_user_id),
-) -> store_model.StoreSubmissionAdminView:
+):
     """
     Review a store listing submission.
 
@@ -73,24 +84,31 @@ async def review_submission(
         user_id: Authenticated admin user performing the review
 
     Returns:
-        StoreSubmissionAdminView with updated review information
+        StoreSubmission with updated review information
     """
-    already_approved = await store_db.check_submission_already_approved(
-        store_listing_version_id=store_listing_version_id,
-    )
-    submission = await store_db.review_store_submission(
-        store_listing_version_id=store_listing_version_id,
-        is_approved=request.is_approved,
-        external_comments=request.comments,
-        internal_comments=request.internal_comments or "",
-        reviewer_id=user_id,
-    )
+    try:
+        already_approved = await store_db.check_submission_already_approved(
+            store_listing_version_id=store_listing_version_id,
+        )
+        submission = await store_db.review_store_submission(
+            store_listing_version_id=store_listing_version_id,
+            is_approved=request.is_approved,
+            external_comments=request.comments,
+            internal_comments=request.internal_comments or "",
+            reviewer_id=user_id,
+        )
 
-    state_changed = already_approved != request.is_approved
-    # Clear caches whenever approval state changes, since store visibility can change
-    if state_changed:
-        store_cache.clear_all_caches()
-    return submission
+        state_changed = already_approved != request.is_approved
+        # Clear caches when the request is approved as it updates what is shown on the store
+        if state_changed:
+            store_cache.clear_all_caches()
+        return submission
+    except Exception as e:
+        logger.exception("Error reviewing submission: %s", e)
+        return fastapi.responses.JSONResponse(
+            status_code=500,
+            content={"detail": "An error occurred while reviewing the submission"},
+        )
 
 
 @router.get(

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

@@ -805,6 +805,7 @@ async def resume_session_stream(
 @router.patch(
     "/sessions/{session_id}/assign-user",
     dependencies=[Security(auth.requires_user)],
+    status_code=200,
 )
 async def session_assign_user(
     session_id: str,

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

@@ -8,6 +8,7 @@ import prisma.errors
 import prisma.models
 import prisma.types
 
+import backend.api.features.store.exceptions as store_exceptions
 import backend.api.features.store.image_gen as store_image_gen
 import backend.api.features.store.media as store_media
 import backend.data.graph as graph_db
@@ -250,7 +251,7 @@ async def get_library_agent(id: str, user_id: str) -> library_model.LibraryAgent
         The requested LibraryAgent.
 
     Raises:
-        NotFoundError: If the specified agent does not exist.
+        AgentNotFoundError: If the specified agent does not exist.
         DatabaseError: If there's an error during retrieval.
     """
     library_agent = await prisma.models.LibraryAgent.prisma().find_first(
@@ -397,7 +398,6 @@ async def create_library_agent(
     hitl_safe_mode: bool = True,
     sensitive_action_safe_mode: bool = False,
     create_library_agents_for_sub_graphs: bool = True,
-    folder_id: str | None = None,
 ) -> list[library_model.LibraryAgent]:
     """
     Adds an agent to the user's library (LibraryAgent table).
@@ -414,18 +414,12 @@ async def create_library_agent(
         If the graph has sub-graphs, the parent graph will always be the first entry in the list.
 
     Raises:
-        NotFoundError: If the specified agent does not exist.
+        AgentNotFoundError: If the specified agent does not exist.
         DatabaseError: If there's an error during creation or if image generation fails.
     """
     logger.info(
         f"Creating library agent for graph #{graph.id} v{graph.version}; user:<redacted>"
     )
-
-    # Authorization: FK only checks existence, not ownership.
-    # Verify the folder belongs to this user to prevent cross-user nesting.
-    if folder_id:
-        await get_folder(folder_id, user_id)
-
     graph_entries = (
         [graph, *graph.sub_graphs] if create_library_agents_for_sub_graphs else [graph]
     )
@@ -438,6 +432,7 @@ async def create_library_agent(
                         isCreatedByUser=(user_id == user_id),
                         useGraphIsActiveVersion=True,
                         User={"connect": {"id": user_id}},
+                        # Creator={"connect": {"id": user_id}},
                         AgentGraph={
                             "connect": {
                                 "graphVersionId": {
@@ -453,11 +448,6 @@ async def create_library_agent(
                                 sensitive_action_safe_mode=sensitive_action_safe_mode,
                             ).model_dump()
                         ),
-                        **(
-                            {"Folder": {"connect": {"id": folder_id}}}
-                            if folder_id and graph_entry is graph
-                            else {}
-                        ),
                     ),
                     include=library_agent_include(
                         user_id, include_nodes=False, include_executions=False
@@ -539,7 +529,6 @@ async def update_agent_version_in_library(
 async def create_graph_in_library(
     graph: graph_db.Graph,
     user_id: str,
-    folder_id: str | None = None,
 ) -> tuple[graph_db.GraphModel, library_model.LibraryAgent]:
     """Create a new graph and add it to the user's library."""
     graph.version = 1
@@ -553,7 +542,6 @@ async def create_graph_in_library(
         user_id=user_id,
         sensitive_action_safe_mode=True,
         create_library_agents_for_sub_graphs=False,
-        folder_id=folder_id,
     )
 
     if created_graph.is_active:
@@ -829,7 +817,7 @@ async def add_store_agent_to_library(
         The newly created LibraryAgent if successfully added, the existing corresponding one if any.
 
     Raises:
-        NotFoundError: If the store listing or associated agent is not found.
+        AgentNotFoundError: If the store listing or associated agent is not found.
         DatabaseError: If there's an issue creating the LibraryAgent record.
     """
     logger.debug(
@@ -844,7 +832,7 @@ async def add_store_agent_to_library(
     )
     if not store_listing_version or not store_listing_version.AgentGraph:
         logger.warning(f"Store listing version not found: {store_listing_version_id}")
-        raise NotFoundError(
+        raise store_exceptions.AgentNotFoundError(
             f"Store listing version {store_listing_version_id} not found or invalid"
         )
 
@@ -858,7 +846,7 @@ async def add_store_agent_to_library(
         include_subgraphs=False,
     )
     if not graph_model:
-        raise NotFoundError(
+        raise store_exceptions.AgentNotFoundError(
             f"Graph #{graph.id} v{graph.version} not found or accessible"
         )
 
@@ -1493,67 +1481,6 @@ async def bulk_move_agents_to_folder(
     return [library_model.LibraryAgent.from_db(agent) for agent in agents]
 
 
-def collect_tree_ids(
-    nodes: list[library_model.LibraryFolderTree],
-    visited: set[str] | None = None,
-) -> list[str]:
-    """Collect all folder IDs from a folder tree."""
-    if visited is None:
-        visited = set()
-    ids: list[str] = []
-    for n in nodes:
-        if n.id in visited:
-            continue
-        visited.add(n.id)
-        ids.append(n.id)
-        ids.extend(collect_tree_ids(n.children, visited))
-    return ids
-
-
-async def get_folder_agent_summaries(
-    user_id: str, folder_id: str
-) -> list[dict[str, str | None]]:
-    """Get a lightweight list of agents in a folder (id, name, description)."""
-    all_agents: list[library_model.LibraryAgent] = []
-    for page in itertools.count(1):
-        resp = await list_library_agents(
-            user_id=user_id, folder_id=folder_id, page=page
-        )
-        all_agents.extend(resp.agents)
-        if page >= resp.pagination.total_pages:
-            break
-    return [
-        {"id": a.id, "name": a.name, "description": a.description} for a in all_agents
-    ]
-
-
-async def get_root_agent_summaries(
-    user_id: str,
-) -> list[dict[str, str | None]]:
-    """Get a lightweight list of root-level agents (folderId IS NULL)."""
-    all_agents: list[library_model.LibraryAgent] = []
-    for page in itertools.count(1):
-        resp = await list_library_agents(
-            user_id=user_id, include_root_only=True, page=page
-        )
-        all_agents.extend(resp.agents)
-        if page >= resp.pagination.total_pages:
-            break
-    return [
-        {"id": a.id, "name": a.name, "description": a.description} for a in all_agents
-    ]
-
-
-async def get_folder_agents_map(
-    user_id: str, folder_ids: list[str]
-) -> dict[str, list[dict[str, str | None]]]:
-    """Get agent summaries for multiple folders concurrently."""
-    results = await asyncio.gather(
-        *(get_folder_agent_summaries(user_id, fid) for fid in folder_ids)
-    )
-    return dict(zip(folder_ids, results))
-
-
 ##############################################
 ########### Presets DB Functions #############
 ##############################################

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

@@ -4,6 +4,7 @@ import prisma.enums
 import prisma.models
 import pytest
 
+import backend.api.features.store.exceptions
 from backend.data.db import connect
 from backend.data.includes import library_agent_include
 
@@ -217,7 +218,7 @@ async def test_add_agent_to_library_not_found(mocker):
     )
 
     # Call function and verify exception
-    with pytest.raises(db.NotFoundError):
+    with pytest.raises(backend.api.features.store.exceptions.AgentNotFoundError):
         await db.add_store_agent_to_library("version123", "test-user")
 
     # Verify mock called correctly

autogpt_platform/backend/backend/api/features/store/cache.py

@@ -1,3 +1,5 @@
+from typing import Literal
+
 from backend.util.cache import cached
 
 from . import db as store_db
@@ -21,7 +23,7 @@ def clear_all_caches():
 async def _get_cached_store_agents(
     featured: bool,
     creator: str | None,
-    sorted_by: store_db.StoreAgentsSortOptions | None,
+    sorted_by: Literal["rating", "runs", "name", "updated_at"] | None,
     search_query: str | None,
     category: str | None,
     page: int,
@@ -55,7 +57,7 @@ async def _get_cached_agent_details(
 async def _get_cached_store_creators(
     featured: bool,
     search_query: str | None,
-    sorted_by: store_db.StoreCreatorsSortOptions | None,
+    sorted_by: Literal["agent_rating", "agent_runs", "num_agents"] | None,
     page: int,
     page_size: int,
 ):
@@ -73,4 +75,4 @@ async def _get_cached_store_creators(
 @cached(maxsize=100, ttl_seconds=300, shared_cache=True)
 async def _get_cached_creator_details(username: str):
     """Cached helper to get creator details."""
-    return await store_db.get_store_creator(username=username.lower())
+    return await store_db.get_store_creator_details(username=username.lower())

autogpt_platform/backend/backend/api/features/store/db_test.py

@@ -26,7 +26,7 @@ async def test_get_store_agents(mocker):
     mock_agents = [
         prisma.models.StoreAgent(
             listing_id="test-id",
-            listing_version_id="version123",
+            storeListingVersionId="version123",
             slug="test-agent",
             agent_name="Test Agent",
             agent_video=None,
@@ -40,11 +40,11 @@ async def test_get_store_agents(mocker):
             runs=10,
             rating=4.5,
             versions=["1.0"],
-            graph_id="test-graph-id",
-            graph_versions=["1"],
+            agentGraphVersions=["1"],
+            agentGraphId="test-graph-id",
             updated_at=datetime.now(),
             is_available=False,
-            use_for_onboarding=False,
+            useForOnboarding=False,
         )
     ]
 
@@ -68,10 +68,10 @@ async def test_get_store_agents(mocker):
 
 @pytest.mark.asyncio(loop_scope="session")
 async def test_get_store_agent_details(mocker):
-    # Mock data - StoreAgent view already contains the active version data
+    # Mock data
     mock_agent = prisma.models.StoreAgent(
         listing_id="test-id",
-        listing_version_id="version123",
+        storeListingVersionId="version123",
         slug="test-agent",
         agent_name="Test Agent",
         agent_video="video.mp4",
@@ -85,38 +85,102 @@ async def test_get_store_agent_details(mocker):
         runs=10,
         rating=4.5,
         versions=["1.0"],
-        graph_id="test-graph-id",
-        graph_versions=["1"],
+        agentGraphVersions=["1"],
+        agentGraphId="test-graph-id",
         updated_at=datetime.now(),
-        is_available=True,
-        use_for_onboarding=False,
+        is_available=False,
+        useForOnboarding=False,
     )
 
-    # Mock StoreAgent prisma call
+    # Mock active version agent (what we want to return for active version)
+    mock_active_agent = prisma.models.StoreAgent(
+        listing_id="test-id",
+        storeListingVersionId="active-version-id",
+        slug="test-agent",
+        agent_name="Test Agent Active",
+        agent_video="active_video.mp4",
+        agent_image=["active_image.jpg"],
+        featured=False,
+        creator_username="creator",
+        creator_avatar="avatar.jpg",
+        sub_heading="Test heading active",
+        description="Test description active",
+        categories=["test"],
+        runs=15,
+        rating=4.8,
+        versions=["1.0", "2.0"],
+        agentGraphVersions=["1", "2"],
+        agentGraphId="test-graph-id-active",
+        updated_at=datetime.now(),
+        is_available=True,
+        useForOnboarding=False,
+    )
+
+    # Create a mock StoreListing result
+    mock_store_listing = mocker.MagicMock()
+    mock_store_listing.activeVersionId = "active-version-id"
+    mock_store_listing.hasApprovedVersion = True
+    mock_store_listing.ActiveVersion = mocker.MagicMock()
+    mock_store_listing.ActiveVersion.recommendedScheduleCron = None
+
+    # Mock StoreAgent prisma call - need to handle multiple calls
     mock_store_agent = mocker.patch("prisma.models.StoreAgent.prisma")
-    mock_store_agent.return_value.find_first = mocker.AsyncMock(return_value=mock_agent)
+
+    # Set up side_effect to return different results for different calls
+    def mock_find_first_side_effect(*args, **kwargs):
+        where_clause = kwargs.get("where", {})
+        if "storeListingVersionId" in where_clause:
+            # Second call for active version
+            return mock_active_agent
+        else:
+            # First call for initial lookup
+            return mock_agent
+
+    mock_store_agent.return_value.find_first = mocker.AsyncMock(
+        side_effect=mock_find_first_side_effect
+    )
+
+    # Mock Profile prisma call
+    mock_profile = mocker.MagicMock()
+    mock_profile.userId = "user-id-123"
+    mock_profile_db = mocker.patch("prisma.models.Profile.prisma")
+    mock_profile_db.return_value.find_first = mocker.AsyncMock(
+        return_value=mock_profile
+    )
+
+    # Mock StoreListing prisma call
+    mock_store_listing_db = mocker.patch("prisma.models.StoreListing.prisma")
+    mock_store_listing_db.return_value.find_first = mocker.AsyncMock(
+        return_value=mock_store_listing
+    )
 
     # Call function
     result = await db.get_store_agent_details("creator", "test-agent")
 
-    # Verify results - constructed from the StoreAgent view
+    # Verify results - should use active version data
     assert result.slug == "test-agent"
-    assert result.agent_name == "Test Agent"
-    assert result.active_version_id == "version123"
+    assert result.agent_name == "Test Agent Active"  # From active version
+    assert result.active_version_id == "active-version-id"
     assert result.has_approved_version is True
-    assert result.store_listing_version_id == "version123"
-    assert result.graph_id == "test-graph-id"
-    assert result.runs == 10
-    assert result.rating == 4.5
+    assert (
+        result.store_listing_version_id == "active-version-id"
+    )  # Should be active version ID
 
-    # Verify single StoreAgent lookup
-    mock_store_agent.return_value.find_first.assert_called_once_with(
+    # Verify mocks called correctly - now expecting 2 calls
+    assert mock_store_agent.return_value.find_first.call_count == 2
+
+    # Check the specific calls
+    calls = mock_store_agent.return_value.find_first.call_args_list
+    assert calls[0] == mocker.call(
         where={"creator_username": "creator", "slug": "test-agent"}
     )
+    assert calls[1] == mocker.call(where={"storeListingVersionId": "active-version-id"})
+
+    mock_store_listing_db.return_value.find_first.assert_called_once()
 
 
 @pytest.mark.asyncio(loop_scope="session")
-async def test_get_store_creator(mocker):
+async def test_get_store_creator_details(mocker):
     # Mock data
     mock_creator_data = prisma.models.Creator(
         name="Test Creator",
@@ -138,7 +202,7 @@ async def test_get_store_creator(mocker):
     mock_creator.return_value.find_unique.return_value = mock_creator_data
 
     # Call function
-    result = await db.get_store_creator("creator")
+    result = await db.get_store_creator_details("creator")
 
     # Verify results
     assert result.username == "creator"
@@ -154,110 +218,61 @@ async def test_get_store_creator(mocker):
 
 @pytest.mark.asyncio(loop_scope="session")
 async def test_create_store_submission(mocker):
-    now = datetime.now()
-
-    # Mock agent graph (with no pending submissions) and user with profile
-    mock_profile = prisma.models.Profile(
-        id="profile-id",
-        userId="user-id",
-        name="Test User",
-        username="testuser",
-        description="Test",
-        isFeatured=False,
-        links=[],
-        createdAt=now,
-        updatedAt=now,
-    )
-    mock_user = prisma.models.User(
-        id="user-id",
-        email="test@example.com",
-        createdAt=now,
-        updatedAt=now,
-        Profile=[mock_profile],
-        emailVerified=True,
-        metadata="{}",  # type: ignore[reportArgumentType]
-        integrations="",
-        maxEmailsPerDay=1,
-        notifyOnAgentRun=True,
-        notifyOnZeroBalance=True,
-        notifyOnLowBalance=True,
-        notifyOnBlockExecutionFailed=True,
-        notifyOnContinuousAgentError=True,
-        notifyOnDailySummary=True,
-        notifyOnWeeklySummary=True,
-        notifyOnMonthlySummary=True,
-        notifyOnAgentApproved=True,
-        notifyOnAgentRejected=True,
-        timezone="Europe/Delft",
-    )
+    # Mock data
     mock_agent = prisma.models.AgentGraph(
         id="agent-id",
         version=1,
         userId="user-id",
-        createdAt=now,
+        createdAt=datetime.now(),
         isActive=True,
-        StoreListingVersions=[],
-        User=mock_user,
     )
 
-    # Mock the created StoreListingVersion (returned by create)
-    mock_store_listing_obj = prisma.models.StoreListing(
+    mock_listing = prisma.models.StoreListing(
         id="listing-id",
-        createdAt=now,
-        updatedAt=now,
+        createdAt=datetime.now(),
+        updatedAt=datetime.now(),
         isDeleted=False,
         hasApprovedVersion=False,
         slug="test-agent",
         agentGraphId="agent-id",
-        owningUserId="user-id",
-        useForOnboarding=False,
-    )
-    mock_version = prisma.models.StoreListingVersion(
-        id="version-id",
-        agentGraphId="agent-id",
         agentGraphVersion=1,
-        name="Test Agent",
-        description="Test description",
-        createdAt=now,
-        updatedAt=now,
-        subHeading="",
-        imageUrls=[],
-        categories=[],
-        isFeatured=False,
-        isDeleted=False,
-        version=1,
-        storeListingId="listing-id",
-        submissionStatus=prisma.enums.SubmissionStatus.PENDING,
-        isAvailable=True,
-        submittedAt=now,
-        StoreListing=mock_store_listing_obj,
+        owningUserId="user-id",
+        Versions=[
+            prisma.models.StoreListingVersion(
+                id="version-id",
+                agentGraphId="agent-id",
+                agentGraphVersion=1,
+                name="Test Agent",
+                description="Test description",
+                createdAt=datetime.now(),
+                updatedAt=datetime.now(),
+                subHeading="Test heading",
+                imageUrls=["image.jpg"],
+                categories=["test"],
+                isFeatured=False,
+                isDeleted=False,
+                version=1,
+                storeListingId="listing-id",
+                submissionStatus=prisma.enums.SubmissionStatus.PENDING,
+                isAvailable=True,
+            )
+        ],
+        useForOnboarding=False,
     )
 
     # Mock prisma calls
     mock_agent_graph = mocker.patch("prisma.models.AgentGraph.prisma")
     mock_agent_graph.return_value.find_first = mocker.AsyncMock(return_value=mock_agent)
 
-    # Mock transaction context manager
-    mock_tx = mocker.MagicMock()
-    mocker.patch(
-        "backend.api.features.store.db.transaction",
-        return_value=mocker.AsyncMock(
-            __aenter__=mocker.AsyncMock(return_value=mock_tx),
-            __aexit__=mocker.AsyncMock(return_value=False),
-        ),
-    )
-
-    mock_sl = mocker.patch("prisma.models.StoreListing.prisma")
-    mock_sl.return_value.find_unique = mocker.AsyncMock(return_value=None)
-
-    mock_slv = mocker.patch("prisma.models.StoreListingVersion.prisma")
-    mock_slv.return_value.create = mocker.AsyncMock(return_value=mock_version)
+    mock_store_listing = mocker.patch("prisma.models.StoreListing.prisma")
+    mock_store_listing.return_value.find_first = mocker.AsyncMock(return_value=None)
+    mock_store_listing.return_value.create = mocker.AsyncMock(return_value=mock_listing)
 
     # Call function
     result = await db.create_store_submission(
         user_id="user-id",
-        graph_id="agent-id",
-        graph_version=1,
+        agent_id="agent-id",
+        agent_version=1,
         slug="test-agent",
         name="Test Agent",
         description="Test description",
@@ -266,11 +281,11 @@ async def test_create_store_submission(mocker):
     # Verify results
     assert result.name == "Test Agent"
     assert result.description == "Test description"
-    assert result.listing_version_id == "version-id"
+    assert result.store_listing_version_id == "version-id"
 
     # Verify mocks called correctly
     mock_agent_graph.return_value.find_first.assert_called_once()
-    mock_slv.return_value.create.assert_called_once()
+    mock_store_listing.return_value.create.assert_called_once()
 
 
 @pytest.mark.asyncio(loop_scope="session")
@@ -303,6 +318,7 @@ async def test_update_profile(mocker):
         description="Test description",
         links=["link1"],
         avatar_url="avatar.jpg",
+        is_featured=False,
     )
 
     # Call function
@@ -373,7 +389,7 @@ async def test_get_store_agents_with_search_and_filters_parameterized():
         creators=["creator1'; DROP TABLE Users; --", "creator2"],
         category="AI'; DELETE FROM StoreAgent; --",
         featured=True,
-        sorted_by=db.StoreAgentsSortOptions.RATING,
+        sorted_by="rating",
         page=1,
         page_size=20,
     )

autogpt_platform/backend/backend/api/features/store/exceptions.py

@@ -57,6 +57,12 @@ class StoreError(ValueError):
     pass
 
 
+class AgentNotFoundError(NotFoundError):
+    """Raised when an agent is not found"""
+
+    pass
+
+
 class CreatorNotFoundError(NotFoundError):
     """Raised when a creator is not found"""
 

autogpt_platform/backend/backend/api/features/store/hybrid_search.py

@@ -568,7 +568,7 @@ async def hybrid_search(
             SELECT uce."contentId" as "storeListingVersionId"
             FROM {{schema_prefix}}"UnifiedContentEmbedding" uce
             INNER JOIN {{schema_prefix}}"StoreAgent" sa
-                ON uce."contentId" = sa.listing_version_id
+                ON uce."contentId" = sa."storeListingVersionId"
             WHERE uce."contentType" = 'STORE_AGENT'::{{schema_prefix}}"ContentType"
             AND uce."userId" IS NULL
             AND uce.search @@ plainto_tsquery('english', {query_param})
@@ -582,7 +582,7 @@ async def hybrid_search(
                 SELECT uce."contentId", uce.embedding
                 FROM {{schema_prefix}}"UnifiedContentEmbedding" uce
                 INNER JOIN {{schema_prefix}}"StoreAgent" sa
-                    ON uce."contentId" = sa.listing_version_id
+                    ON uce."contentId" = sa."storeListingVersionId"
                 WHERE uce."contentType" = 'STORE_AGENT'::{{schema_prefix}}"ContentType"
                 AND uce."userId" IS NULL
                 AND {where_clause}
@@ -605,7 +605,7 @@ async def hybrid_search(
                 sa.featured,
                 sa.is_available,
                 sa.updated_at,
-                sa.graph_id,
+                sa."agentGraphId",
                 -- Searchable text for BM25 reranking
                 COALESCE(sa.agent_name, '') || ' ' || COALESCE(sa.sub_heading, '') || ' ' || COALESCE(sa.description, '') as searchable_text,
                 -- Semantic score
@@ -627,9 +627,9 @@ async def hybrid_search(
                 sa.runs as popularity_raw
             FROM candidates c
             INNER JOIN {{schema_prefix}}"StoreAgent" sa
-                ON c."storeListingVersionId" = sa.listing_version_id
+                ON c."storeListingVersionId" = sa."storeListingVersionId"
             INNER JOIN {{schema_prefix}}"UnifiedContentEmbedding" uce
-                ON sa.listing_version_id = uce."contentId"
+                ON sa."storeListingVersionId" = uce."contentId"
                 AND uce."contentType" = 'STORE_AGENT'::{{schema_prefix}}"ContentType"
         ),
         max_vals AS (
@@ -665,7 +665,7 @@ async def hybrid_search(
                 featured,
                 is_available,
                 updated_at,
-                graph_id,
+                "agentGraphId",
                 searchable_text,
                 semantic_score,
                 lexical_score,

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

@@ -1,14 +1,11 @@
 import datetime
-from typing import TYPE_CHECKING, List, Self
+from typing import List
 
 import prisma.enums
 import pydantic
 
 from backend.util.models import Pagination
 
-if TYPE_CHECKING:
-    import prisma.models
-
 
 class ChangelogEntry(pydantic.BaseModel):
     version: str
@@ -16,9 +13,9 @@ class ChangelogEntry(pydantic.BaseModel):
     date: datetime.datetime
 
 
-class MyUnpublishedAgent(pydantic.BaseModel):
-    graph_id: str
-    graph_version: int
+class MyAgent(pydantic.BaseModel):
+    agent_id: str
+    agent_version: int
     agent_name: str
     agent_image: str | None = None
     description: str
@@ -26,8 +23,8 @@ class MyUnpublishedAgent(pydantic.BaseModel):
     recommended_schedule_cron: str | None = None
 
 
-class MyUnpublishedAgentsResponse(pydantic.BaseModel):
-    agents: list[MyUnpublishedAgent]
+class MyAgentsResponse(pydantic.BaseModel):
+    agents: list[MyAgent]
     pagination: Pagination
 
 
@@ -43,21 +40,6 @@ class StoreAgent(pydantic.BaseModel):
     rating: float
     agent_graph_id: str
 
-    @classmethod
-    def from_db(cls, agent: "prisma.models.StoreAgent") -> "StoreAgent":
-        return cls(
-            slug=agent.slug,
-            agent_name=agent.agent_name,
-            agent_image=agent.agent_image[0] if agent.agent_image else "",
-            creator=agent.creator_username or "Needs Profile",
-            creator_avatar=agent.creator_avatar or "",
-            sub_heading=agent.sub_heading,
-            description=agent.description,
-            runs=agent.runs,
-            rating=agent.rating,
-            agent_graph_id=agent.graph_id,
-        )
-
 
 class StoreAgentsResponse(pydantic.BaseModel):
     agents: list[StoreAgent]
@@ -80,192 +62,81 @@ class StoreAgentDetails(pydantic.BaseModel):
     runs: int
     rating: float
     versions: list[str]
-    graph_id: str
-    graph_versions: list[str]
+    agentGraphVersions: list[str]
+    agentGraphId: str
     last_updated: datetime.datetime
     recommended_schedule_cron: str | None = None
 
-    active_version_id: str
-    has_approved_version: bool
+    active_version_id: str | None = None
+    has_approved_version: bool = False
 
     # Optional changelog data when include_changelog=True
     changelog: list[ChangelogEntry] | None = None
 
-    @classmethod
-    def from_db(cls, agent: "prisma.models.StoreAgent") -> "StoreAgentDetails":
-        return cls(
-            store_listing_version_id=agent.listing_version_id,
-            slug=agent.slug,
-            agent_name=agent.agent_name,
-            agent_video=agent.agent_video or "",
-            agent_output_demo=agent.agent_output_demo or "",
-            agent_image=agent.agent_image,
-            creator=agent.creator_username or "",
-            creator_avatar=agent.creator_avatar or "",
-            sub_heading=agent.sub_heading,
-            description=agent.description,
-            categories=agent.categories,
-            runs=agent.runs,
-            rating=agent.rating,
-            versions=agent.versions,
-            graph_id=agent.graph_id,
-            graph_versions=agent.graph_versions,
-            last_updated=agent.updated_at,
-            recommended_schedule_cron=agent.recommended_schedule_cron,
-            active_version_id=agent.listing_version_id,
-            has_approved_version=True,  # StoreAgent view only has approved agents
-        )
 
-
-class Profile(pydantic.BaseModel):
-    """Marketplace user profile (only attributes that the user can update)"""
-
-    username: str
+class Creator(pydantic.BaseModel):
     name: str
+    username: str
     description: str
-    avatar_url: str | None
-    links: list[str]
-
-
-class ProfileDetails(Profile):
-    """Marketplace user profile (including read-only fields)"""
-
-    is_featured: bool
-
-    @classmethod
-    def from_db(cls, profile: "prisma.models.Profile") -> "ProfileDetails":
-        return cls(
-            name=profile.name,
-            username=profile.username,
-            avatar_url=profile.avatarUrl,
-            description=profile.description,
-            links=profile.links,
-            is_featured=profile.isFeatured,
-        )
-
-
-class CreatorDetails(ProfileDetails):
-    """Marketplace creator profile details, including aggregated stats"""
-
+    avatar_url: str
     num_agents: int
-    agent_runs: int
     agent_rating: float
-    top_categories: list[str]
-
-    @classmethod
-    def from_db(cls, creator: "prisma.models.Creator") -> "CreatorDetails":  # type: ignore[override]
-        return cls(
-            name=creator.name,
-            username=creator.username,
-            avatar_url=creator.avatar_url,
-            description=creator.description,
-            links=creator.links,
-            is_featured=creator.is_featured,
-            num_agents=creator.num_agents,
-            agent_runs=creator.agent_runs,
-            agent_rating=creator.agent_rating,
-            top_categories=creator.top_categories,
-        )
+    agent_runs: int
+    is_featured: bool
 
 
 class CreatorsResponse(pydantic.BaseModel):
-    creators: List[CreatorDetails]
+    creators: List[Creator]
     pagination: Pagination
 
 
-class StoreSubmission(pydantic.BaseModel):
-    # From StoreListing:
-    listing_id: str
-    user_id: str
-    slug: str
+class CreatorDetails(pydantic.BaseModel):
+    name: str
+    username: str
+    description: str
+    links: list[str]
+    avatar_url: str
+    agent_rating: float
+    agent_runs: int
+    top_categories: list[str]
 
-    # From StoreListingVersion:
-    listing_version_id: str
-    listing_version: int
-    graph_id: str
-    graph_version: int
+
+class Profile(pydantic.BaseModel):
+    name: str
+    username: str
+    description: str
+    links: list[str]
+    avatar_url: str
+    is_featured: bool = False
+
+
+class StoreSubmission(pydantic.BaseModel):
+    listing_id: str
+    agent_id: str
+    agent_version: int
     name: str
     sub_heading: str
+    slug: str
     description: str
-    instructions: str | None
-    categories: list[str]
+    instructions: str | None = None
     image_urls: list[str]
-    video_url: str | None
-    agent_output_demo_url: str | None
-
-    submitted_at: datetime.datetime | None
-    changes_summary: str | None
+    date_submitted: datetime.datetime
     status: prisma.enums.SubmissionStatus
-    reviewed_at: datetime.datetime | None = None
+    runs: int
+    rating: float
+    store_listing_version_id: str | None = None
+    version: int | None = None  # Actual version number from the database
+
     reviewer_id: str | None = None
     review_comments: str | None = None  # External comments visible to creator
+    internal_comments: str | None = None  # Private notes for admin use only
+    reviewed_at: datetime.datetime | None = None
+    changes_summary: str | None = None
 
-    # Aggregated from AgentGraphExecutions and StoreListingReviews:
-    run_count: int = 0
-    review_count: int = 0
-    review_avg_rating: float = 0.0
-
-    @classmethod
-    def from_db(cls, _sub: "prisma.models.StoreSubmission") -> Self:
-        """Construct from the StoreSubmission Prisma view."""
-        return cls(
-            listing_id=_sub.listing_id,
-            user_id=_sub.user_id,
-            slug=_sub.slug,
-            listing_version_id=_sub.listing_version_id,
-            listing_version=_sub.listing_version,
-            graph_id=_sub.graph_id,
-            graph_version=_sub.graph_version,
-            name=_sub.name,
-            sub_heading=_sub.sub_heading,
-            description=_sub.description,
-            instructions=_sub.instructions,
-            categories=_sub.categories,
-            image_urls=_sub.image_urls,
-            video_url=_sub.video_url,
-            agent_output_demo_url=_sub.agent_output_demo_url,
-            submitted_at=_sub.submitted_at,
-            changes_summary=_sub.changes_summary,
-            status=_sub.status,
-            reviewed_at=_sub.reviewed_at,
-            reviewer_id=_sub.reviewer_id,
-            review_comments=_sub.review_comments,
-            run_count=_sub.run_count,
-            review_count=_sub.review_count,
-            review_avg_rating=_sub.review_avg_rating,
-        )
-
-    @classmethod
-    def from_listing_version(cls, _lv: "prisma.models.StoreListingVersion") -> Self:
-        """
-        Construct from the StoreListingVersion Prisma model (with StoreListing included)
-        """
-        if not (_l := _lv.StoreListing):
-            raise ValueError("StoreListingVersion must have included StoreListing")
-
-        return cls(
-            listing_id=_l.id,
-            user_id=_l.owningUserId,
-            slug=_l.slug,
-            listing_version_id=_lv.id,
-            listing_version=_lv.version,
-            graph_id=_lv.agentGraphId,
-            graph_version=_lv.agentGraphVersion,
-            name=_lv.name,
-            sub_heading=_lv.subHeading,
-            description=_lv.description,
-            instructions=_lv.instructions,
-            categories=_lv.categories,
-            image_urls=_lv.imageUrls,
-            video_url=_lv.videoUrl,
-            agent_output_demo_url=_lv.agentOutputDemoUrl,
-            submitted_at=_lv.submittedAt,
-            changes_summary=_lv.changesSummary,
-            status=_lv.submissionStatus,
-            reviewed_at=_lv.reviewedAt,
-            reviewer_id=_lv.reviewerId,
-            review_comments=_lv.reviewComments,
-        )
+    # Additional fields for editing
+    video_url: str | None = None
+    agent_output_demo_url: str | None = None
+    categories: list[str] = []
 
 
 class StoreSubmissionsResponse(pydantic.BaseModel):
@@ -273,12 +144,33 @@ class StoreSubmissionsResponse(pydantic.BaseModel):
     pagination: Pagination
 
 
+class StoreListingWithVersions(pydantic.BaseModel):
+    """A store listing with its version history"""
+
+    listing_id: str
+    slug: str
+    agent_id: str
+    agent_version: int
+    active_version_id: str | None = None
+    has_approved_version: bool = False
+    creator_email: str | None = None
+    latest_version: StoreSubmission | None = None
+    versions: list[StoreSubmission] = []
+
+
+class StoreListingsWithVersionsResponse(pydantic.BaseModel):
+    """Response model for listings with version history"""
+
+    listings: list[StoreListingWithVersions]
+    pagination: Pagination
+
+
 class StoreSubmissionRequest(pydantic.BaseModel):
-    graph_id: str = pydantic.Field(
-        ..., min_length=1, description="Graph ID cannot be empty"
+    agent_id: str = pydantic.Field(
+        ..., min_length=1, description="Agent ID cannot be empty"
     )
-    graph_version: int = pydantic.Field(
-        ..., gt=0, description="Graph version must be greater than 0"
+    agent_version: int = pydantic.Field(
+        ..., gt=0, description="Agent version must be greater than 0"
     )
     slug: str
     name: str
@@ -306,42 +198,12 @@ class StoreSubmissionEditRequest(pydantic.BaseModel):
     recommended_schedule_cron: str | None = None
 
 
-class StoreSubmissionAdminView(StoreSubmission):
-    internal_comments: str | None  # Private admin notes
-
-    @classmethod
-    def from_db(cls, _sub: "prisma.models.StoreSubmission") -> Self:
-        return cls(
-            **StoreSubmission.from_db(_sub).model_dump(),
-            internal_comments=_sub.internal_comments,
-        )
-
-    @classmethod
-    def from_listing_version(cls, _lv: "prisma.models.StoreListingVersion") -> Self:
-        return cls(
-            **StoreSubmission.from_listing_version(_lv).model_dump(),
-            internal_comments=_lv.internalComments,
-        )
-
-
-class StoreListingWithVersionsAdminView(pydantic.BaseModel):
-    """A store listing with its version history"""
-
-    listing_id: str
-    graph_id: str
-    slug: str
-    active_listing_version_id: str | None = None
-    has_approved_version: bool = False
-    creator_email: str | None = None
-    latest_version: StoreSubmissionAdminView | None = None
-    versions: list[StoreSubmissionAdminView] = []
-
-
-class StoreListingsWithVersionsAdminViewResponse(pydantic.BaseModel):
-    """Response model for listings with version history"""
-
-    listings: list[StoreListingWithVersionsAdminView]
-    pagination: Pagination
+class ProfileDetails(pydantic.BaseModel):
+    name: str
+    username: str
+    description: str
+    links: list[str]
+    avatar_url: str | None = None
 
 
 class StoreReview(pydantic.BaseModel):

autogpt_platform/backend/backend/api/features/store/model_test.py

@@ -0,0 +1,203 @@
+import datetime
+
+import prisma.enums
+
+from . import model as store_model
+
+
+def test_pagination():
+    pagination = store_model.Pagination(
+        total_items=100, total_pages=5, current_page=2, page_size=20
+    )
+    assert pagination.total_items == 100
+    assert pagination.total_pages == 5
+    assert pagination.current_page == 2
+    assert pagination.page_size == 20
+
+
+def test_store_agent():
+    agent = store_model.StoreAgent(
+        slug="test-agent",
+        agent_name="Test Agent",
+        agent_image="test.jpg",
+        creator="creator1",
+        creator_avatar="avatar.jpg",
+        sub_heading="Test subheading",
+        description="Test description",
+        runs=50,
+        rating=4.5,
+        agent_graph_id="test-graph-id",
+    )
+    assert agent.slug == "test-agent"
+    assert agent.agent_name == "Test Agent"
+    assert agent.runs == 50
+    assert agent.rating == 4.5
+    assert agent.agent_graph_id == "test-graph-id"
+
+
+def test_store_agents_response():
+    response = store_model.StoreAgentsResponse(
+        agents=[
+            store_model.StoreAgent(
+                slug="test-agent",
+                agent_name="Test Agent",
+                agent_image="test.jpg",
+                creator="creator1",
+                creator_avatar="avatar.jpg",
+                sub_heading="Test subheading",
+                description="Test description",
+                runs=50,
+                rating=4.5,
+                agent_graph_id="test-graph-id",
+            )
+        ],
+        pagination=store_model.Pagination(
+            total_items=1, total_pages=1, current_page=1, page_size=20
+        ),
+    )
+    assert len(response.agents) == 1
+    assert response.pagination.total_items == 1
+
+
+def test_store_agent_details():
+    details = store_model.StoreAgentDetails(
+        store_listing_version_id="version123",
+        slug="test-agent",
+        agent_name="Test Agent",
+        agent_video="video.mp4",
+        agent_output_demo="demo.mp4",
+        agent_image=["image1.jpg", "image2.jpg"],
+        creator="creator1",
+        creator_avatar="avatar.jpg",
+        sub_heading="Test subheading",
+        description="Test description",
+        categories=["cat1", "cat2"],
+        runs=50,
+        rating=4.5,
+        versions=["1.0", "2.0"],
+        agentGraphVersions=["1", "2"],
+        agentGraphId="test-graph-id",
+        last_updated=datetime.datetime.now(),
+    )
+    assert details.slug == "test-agent"
+    assert len(details.agent_image) == 2
+    assert len(details.categories) == 2
+    assert len(details.versions) == 2
+
+
+def test_creator():
+    creator = store_model.Creator(
+        agent_rating=4.8,
+        agent_runs=1000,
+        name="Test Creator",
+        username="creator1",
+        description="Test description",
+        avatar_url="avatar.jpg",
+        num_agents=5,
+        is_featured=False,
+    )
+    assert creator.name == "Test Creator"
+    assert creator.num_agents == 5
+
+
+def test_creators_response():
+    response = store_model.CreatorsResponse(
+        creators=[
+            store_model.Creator(
+                agent_rating=4.8,
+                agent_runs=1000,
+                name="Test Creator",
+                username="creator1",
+                description="Test description",
+                avatar_url="avatar.jpg",
+                num_agents=5,
+                is_featured=False,
+            )
+        ],
+        pagination=store_model.Pagination(
+            total_items=1, total_pages=1, current_page=1, page_size=20
+        ),
+    )
+    assert len(response.creators) == 1
+    assert response.pagination.total_items == 1
+
+
+def test_creator_details():
+    details = store_model.CreatorDetails(
+        name="Test Creator",
+        username="creator1",
+        description="Test description",
+        links=["link1.com", "link2.com"],
+        avatar_url="avatar.jpg",
+        agent_rating=4.8,
+        agent_runs=1000,
+        top_categories=["cat1", "cat2"],
+    )
+    assert details.name == "Test Creator"
+    assert len(details.links) == 2
+    assert details.agent_rating == 4.8
+    assert len(details.top_categories) == 2
+
+
+def test_store_submission():
+    submission = store_model.StoreSubmission(
+        listing_id="listing123",
+        agent_id="agent123",
+        agent_version=1,
+        sub_heading="Test subheading",
+        name="Test Agent",
+        slug="test-agent",
+        description="Test description",
+        image_urls=["image1.jpg", "image2.jpg"],
+        date_submitted=datetime.datetime(2023, 1, 1),
+        status=prisma.enums.SubmissionStatus.PENDING,
+        runs=50,
+        rating=4.5,
+    )
+    assert submission.name == "Test Agent"
+    assert len(submission.image_urls) == 2
+    assert submission.status == prisma.enums.SubmissionStatus.PENDING
+
+
+def test_store_submissions_response():
+    response = store_model.StoreSubmissionsResponse(
+        submissions=[
+            store_model.StoreSubmission(
+                listing_id="listing123",
+                agent_id="agent123",
+                agent_version=1,
+                sub_heading="Test subheading",
+                name="Test Agent",
+                slug="test-agent",
+                description="Test description",
+                image_urls=["image1.jpg"],
+                date_submitted=datetime.datetime(2023, 1, 1),
+                status=prisma.enums.SubmissionStatus.PENDING,
+                runs=50,
+                rating=4.5,
+            )
+        ],
+        pagination=store_model.Pagination(
+            total_items=1, total_pages=1, current_page=1, page_size=20
+        ),
+    )
+    assert len(response.submissions) == 1
+    assert response.pagination.total_items == 1
+
+
+def test_store_submission_request():
+    request = store_model.StoreSubmissionRequest(
+        agent_id="agent123",
+        agent_version=1,
+        slug="test-agent",
+        name="Test Agent",
+        sub_heading="Test subheading",
+        video_url="video.mp4",
+        image_urls=["image1.jpg", "image2.jpg"],
+        description="Test description",
+        categories=["cat1", "cat2"],
+    )
+    assert request.agent_id == "agent123"
+    assert request.agent_version == 1
+    assert len(request.image_urls) == 2
+    assert len(request.categories) == 2

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

@@ -1,17 +1,16 @@
 import logging
 import tempfile
+import typing
 import urllib.parse
+from typing import Literal
 
 import autogpt_libs.auth
 import fastapi
 import fastapi.responses
 import prisma.enums
-from fastapi import Query, Security
-from pydantic import BaseModel
 
 import backend.data.graph
 import backend.util.json
-from backend.util.exceptions import NotFoundError
 from backend.util.models import Pagination
 
 from . import cache as store_cache
@@ -35,15 +34,22 @@ router = fastapi.APIRouter()
     "/profile",
     summary="Get user profile",
     tags=["store", "private"],
-    dependencies=[Security(autogpt_libs.auth.requires_user)],
+    dependencies=[fastapi.Security(autogpt_libs.auth.requires_user)],
+    response_model=store_model.ProfileDetails,
 )
 async def get_profile(
-    user_id: str = Security(autogpt_libs.auth.get_user_id),
-) -> store_model.ProfileDetails:
-    """Get the profile details for the authenticated user."""
+    user_id: str = fastapi.Security(autogpt_libs.auth.get_user_id),
+):
+    """
+    Get the profile details for the authenticated user.
+    Cached for 1 hour per user.
+    """
     profile = await store_db.get_user_profile(user_id)
     if profile is None:
-        raise NotFoundError("User does not have a profile yet")
+        return fastapi.responses.JSONResponse(
+            status_code=404,
+            content={"detail": "Profile not found"},
+        )
     return profile
 
 
@@ -51,17 +57,98 @@ async def get_profile(
     "/profile",
     summary="Update user profile",
     tags=["store", "private"],
-    dependencies=[Security(autogpt_libs.auth.requires_user)],
+    dependencies=[fastapi.Security(autogpt_libs.auth.requires_user)],
+    response_model=store_model.CreatorDetails,
 )
 async def update_or_create_profile(
     profile: store_model.Profile,
-    user_id: str = Security(autogpt_libs.auth.get_user_id),
-) -> store_model.ProfileDetails:
-    """Update the store profile for the authenticated user."""
+    user_id: str = fastapi.Security(autogpt_libs.auth.get_user_id),
+):
+    """
+    Update the store profile for the authenticated user.
+
+    Args:
+        profile (Profile): The updated profile details
+        user_id (str): ID of the authenticated user
+
+    Returns:
+        CreatorDetails: The updated profile
+
+    Raises:
+        HTTPException: If there is an error updating the profile
+    """
     updated_profile = await store_db.update_profile(user_id=user_id, profile=profile)
     return updated_profile
 
 
+##############################################
+############### Agent Endpoints ##############
+##############################################
+
+
+@router.get(
+    "/agents",
+    summary="List store agents",
+    tags=["store", "public"],
+    response_model=store_model.StoreAgentsResponse,
+)
+async def get_agents(
+    featured: bool = False,
+    creator: str | None = None,
+    sorted_by: Literal["rating", "runs", "name", "updated_at"] | None = None,
+    search_query: str | None = None,
+    category: str | None = None,
+    page: int = 1,
+    page_size: int = 20,
+):
+    """
+    Get a paginated list of agents from the store with optional filtering and sorting.
+
+    Args:
+        featured (bool, optional): Filter to only show featured agents. Defaults to False.
+        creator (str | None, optional): Filter agents by creator username. Defaults to None.
+        sorted_by (str | None, optional): Sort agents by "runs" or "rating". Defaults to None.
+        search_query (str | None, optional): Search agents by name, subheading and description. Defaults to None.
+        category (str | None, optional): Filter agents by category. Defaults to None.
+        page (int, optional): Page number for pagination. Defaults to 1.
+        page_size (int, optional): Number of agents per page. Defaults to 20.
+
+    Returns:
+        StoreAgentsResponse: Paginated list of agents matching the filters
+
+    Raises:
+        HTTPException: If page or page_size are less than 1
+
+    Used for:
+    - Home Page Featured Agents
+    - Home Page Top Agents
+    - Search Results
+    - Agent Details - Other Agents By Creator
+    - Agent Details - Similar Agents
+    - Creator Details - Agents By Creator
+    """
+    if page < 1:
+        raise fastapi.HTTPException(
+            status_code=422, detail="Page must be greater than 0"
+        )
+
+    if page_size < 1:
+        raise fastapi.HTTPException(
+            status_code=422, detail="Page size must be greater than 0"
+        )
+
+    agents = await store_cache._get_cached_store_agents(
+        featured=featured,
+        creator=creator,
+        sorted_by=sorted_by,
+        search_query=search_query,
+        category=category,
+        page=page,
+        page_size=page_size,
+    )
+    return agents
+
+
 ##############################################
 ############### Search Endpoints #############
 ##############################################
@@ -71,30 +158,60 @@ async def update_or_create_profile(
     "/search",
     summary="Unified search across all content types",
     tags=["store", "public"],
+    response_model=store_model.UnifiedSearchResponse,
 )
 async def unified_search(
     query: str,
-    content_types: list[prisma.enums.ContentType] | None = Query(
+    content_types: list[str] | None = fastapi.Query(
         default=None,
-        description="Content types to search. If not specified, searches all.",
+        description="Content types to search: STORE_AGENT, BLOCK, DOCUMENTATION. If not specified, searches all.",
     ),
-    page: int = Query(ge=1, default=1),
-    page_size: int = Query(ge=1, default=20),
-    user_id: str | None = Security(
+    page: int = 1,
+    page_size: int = 20,
+    user_id: str | None = fastapi.Security(
         autogpt_libs.auth.get_optional_user_id, use_cache=False
     ),
-) -> store_model.UnifiedSearchResponse:
+):
     """
-    Search across all content types (marketplace agents, blocks, documentation)
-    using hybrid search.
+    Search across all content types (store agents, blocks, documentation) using hybrid search.
 
     Combines semantic (embedding-based) and lexical (text-based) search for best results.
+
+    Args:
+        query: The search query string
+        content_types: Optional list of content types to filter by (STORE_AGENT, BLOCK, DOCUMENTATION)
+        page: Page number for pagination (default 1)
+        page_size: Number of results per page (default 20)
+        user_id: Optional authenticated user ID (for user-scoped content in future)
+
+    Returns:
+        UnifiedSearchResponse: Paginated list of search results with relevance scores
     """
+    if page < 1:
+        raise fastapi.HTTPException(
+            status_code=422, detail="Page must be greater than 0"
+        )
+
+    if page_size < 1:
+        raise fastapi.HTTPException(
+            status_code=422, detail="Page size must be greater than 0"
+        )
+
+    # Convert string content types to enum
+    content_type_enums: list[prisma.enums.ContentType] | None = None
+    if content_types:
+        try:
+            content_type_enums = [prisma.enums.ContentType(ct) for ct in content_types]
+        except ValueError as e:
+            raise fastapi.HTTPException(
+                status_code=422,
+                detail=f"Invalid content type. Valid values: STORE_AGENT, BLOCK, DOCUMENTATION. Error: {e}",
+            )
 
     # Perform unified hybrid search
     results, total = await store_hybrid_search.unified_hybrid_search(
         query=query,
-        content_types=content_types,
+        content_types=content_type_enums,
         user_id=user_id,
         page=page,
         page_size=page_size,
@@ -128,69 +245,22 @@ async def unified_search(
     )
 
 
-##############################################
-############### Agent Endpoints ##############
-##############################################
-
-
-@router.get(
-    "/agents",
-    summary="List store agents",
-    tags=["store", "public"],
-)
-async def get_agents(
-    featured: bool = Query(
-        default=False, description="Filter to only show featured agents"
-    ),
-    creator: str | None = Query(
-        default=None, description="Filter agents by creator username"
-    ),
-    category: str | None = Query(default=None, description="Filter agents by category"),
-    search_query: str | None = Query(
-        default=None, description="Literal + semantic search on names and descriptions"
-    ),
-    sorted_by: store_db.StoreAgentsSortOptions | None = Query(
-        default=None,
-        description="Property to sort results by. Ignored if search_query is provided.",
-    ),
-    page: int = Query(ge=1, default=1),
-    page_size: int = Query(ge=1, default=20),
-) -> store_model.StoreAgentsResponse:
-    """
-    Get a paginated list of agents from the marketplace,
-    with optional filtering and sorting.
-
-    Used for:
-    - Home Page Featured Agents
-    - Home Page Top Agents
-    - Search Results
-    - Agent Details - Other Agents By Creator
-    - Agent Details - Similar Agents
-    - Creator Details - Agents By Creator
-    """
-    agents = await store_cache._get_cached_store_agents(
-        featured=featured,
-        creator=creator,
-        sorted_by=sorted_by,
-        search_query=search_query,
-        category=category,
-        page=page,
-        page_size=page_size,
-    )
-    return agents
-
-
 @router.get(
     "/agents/{username}/{agent_name}",
     summary="Get specific agent",
     tags=["store", "public"],
+    response_model=store_model.StoreAgentDetails,
 )
-async def get_agent_by_name(
+async def get_agent(
     username: str,
     agent_name: str,
-    include_changelog: bool = Query(default=False),
-) -> store_model.StoreAgentDetails:
-    """Get details of a marketplace agent"""
+    include_changelog: bool = fastapi.Query(default=False),
+):
+    """
+    This is only used on the AgentDetails Page.
+
+    It returns the store listing agents details.
+    """
     username = urllib.parse.unquote(username).lower()
     # URL decode the agent name since it comes from the URL path
     agent_name = urllib.parse.unquote(agent_name).lower()
@@ -200,82 +270,76 @@ async def get_agent_by_name(
     return agent
 
 
+@router.get(
+    "/graph/{store_listing_version_id}",
+    summary="Get agent graph",
+    tags=["store"],
+    dependencies=[fastapi.Security(autogpt_libs.auth.requires_user)],
+)
+async def get_graph_meta_by_store_listing_version_id(
+    store_listing_version_id: str,
+) -> backend.data.graph.GraphModelWithoutNodes:
+    """
+    Get Agent Graph from Store Listing Version ID.
+    """
+    graph = await store_db.get_available_graph(store_listing_version_id)
+    return graph
+
+
+@router.get(
+    "/agents/{store_listing_version_id}",
+    summary="Get agent by version",
+    tags=["store"],
+    dependencies=[fastapi.Security(autogpt_libs.auth.requires_user)],
+    response_model=store_model.StoreAgentDetails,
+)
+async def get_store_agent(store_listing_version_id: str):
+    """
+    Get Store Agent Details from Store Listing Version ID.
+    """
+    agent = await store_db.get_store_agent_by_version_id(store_listing_version_id)
+
+    return agent
+
+
 @router.post(
     "/agents/{username}/{agent_name}/review",
     summary="Create agent review",
     tags=["store"],
-    dependencies=[Security(autogpt_libs.auth.requires_user)],
+    dependencies=[fastapi.Security(autogpt_libs.auth.requires_user)],
+    response_model=store_model.StoreReview,
 )
-async def post_user_review_for_agent(
+async def create_review(
     username: str,
     agent_name: str,
     review: store_model.StoreReviewCreate,
-    user_id: str = Security(autogpt_libs.auth.get_user_id),
-) -> store_model.StoreReview:
-    """Post a user review on a marketplace agent listing"""
+    user_id: str = fastapi.Security(autogpt_libs.auth.get_user_id),
+):
+    """
+    Create a review for a store agent.
+
+    Args:
+        username: Creator's username
+        agent_name: Name/slug of the agent
+        review: Review details including score and optional comments
+        user_id: ID of authenticated user creating the review
+
+    Returns:
+        The created review
+    """
     username = urllib.parse.unquote(username).lower()
     agent_name = urllib.parse.unquote(agent_name).lower()
-
+    # Create the review
     created_review = await store_db.create_store_review(
         user_id=user_id,
         store_listing_version_id=review.store_listing_version_id,
         score=review.score,
         comments=review.comments,
     )
+
     return created_review
 
 
-@router.get(
-    "/listings/versions/{store_listing_version_id}",
-    summary="Get agent by version",
-    tags=["store"],
-    dependencies=[Security(autogpt_libs.auth.requires_user)],
-)
-async def get_agent_by_listing_version(
-    store_listing_version_id: str,
-) -> store_model.StoreAgentDetails:
-    agent = await store_db.get_store_agent_by_version_id(store_listing_version_id)
-    return agent
-
-
-@router.get(
-    "/listings/versions/{store_listing_version_id}/graph",
-    summary="Get agent graph",
-    tags=["store"],
-    dependencies=[Security(autogpt_libs.auth.requires_user)],
-)
-async def get_graph_meta_by_store_listing_version_id(
-    store_listing_version_id: str,
-) -> backend.data.graph.GraphModelWithoutNodes:
-    """Get outline of graph belonging to a specific marketplace listing version"""
-    graph = await store_db.get_available_graph(store_listing_version_id)
-    return graph
-
-
-@router.get(
-    "/listings/versions/{store_listing_version_id}/graph/download",
-    summary="Download agent file",
-    tags=["store", "public"],
-)
-async def download_agent_file(
-    store_listing_version_id: str,
-) -> fastapi.responses.FileResponse:
-    """Download agent graph file for a specific marketplace listing version"""
-    graph_data = await store_db.get_agent(store_listing_version_id)
-    file_name = f"agent_{graph_data.id}_v{graph_data.version or 'latest'}.json"
-
-    # Sending graph as a stream (similar to marketplace v1)
-    with tempfile.NamedTemporaryFile(
-        mode="w", suffix=".json", delete=False
-    ) as tmp_file:
-        tmp_file.write(backend.util.json.dumps(graph_data))
-        tmp_file.flush()
-
-        return fastapi.responses.FileResponse(
-            tmp_file.name, filename=file_name, media_type="application/json"
-        )
-
-
 ##############################################
 ############# Creator Endpoints #############
 ##############################################
@@ -285,19 +349,37 @@ async def download_agent_file(
     "/creators",
     summary="List store creators",
     tags=["store", "public"],
+    response_model=store_model.CreatorsResponse,
 )
 async def get_creators(
-    featured: bool = Query(
-        default=False, description="Filter to only show featured creators"
-    ),
-    search_query: str | None = Query(
-        default=None, description="Literal + semantic search on names and descriptions"
-    ),
-    sorted_by: store_db.StoreCreatorsSortOptions | None = None,
-    page: int = Query(ge=1, default=1),
-    page_size: int = Query(ge=1, default=20),
-) -> store_model.CreatorsResponse:
-    """List or search marketplace creators"""
+    featured: bool = False,
+    search_query: str | None = None,
+    sorted_by: Literal["agent_rating", "agent_runs", "num_agents"] | None = None,
+    page: int = 1,
+    page_size: int = 20,
+):
+    """
+    This is needed for:
+    - Home Page Featured Creators
+    - Search Results Page
+
+    ---
+
+    To support this functionality we need:
+    - featured: bool - to limit the list to just featured agents
+    - search_query: str - vector search based on the creators profile description.
+    - sorted_by: [agent_rating, agent_runs] -
+    """
+    if page < 1:
+        raise fastapi.HTTPException(
+            status_code=422, detail="Page must be greater than 0"
+        )
+
+    if page_size < 1:
+        raise fastapi.HTTPException(
+            status_code=422, detail="Page size must be greater than 0"
+        )
+
     creators = await store_cache._get_cached_store_creators(
         featured=featured,
         search_query=search_query,
@@ -309,12 +391,18 @@ async def get_creators(
 
 
 @router.get(
-    "/creators/{username}",
+    "/creator/{username}",
     summary="Get creator details",
     tags=["store", "public"],
+    response_model=store_model.CreatorDetails,
 )
-async def get_creator(username: str) -> store_model.CreatorDetails:
-    """Get details on a marketplace creator"""
+async def get_creator(
+    username: str,
+):
+    """
+    Get the details of a creator.
+    - Creator Details Page
+    """
     username = urllib.parse.unquote(username).lower()
     creator = await store_cache._get_cached_creator_details(username=username)
     return creator
@@ -326,17 +414,20 @@ async def get_creator(username: str) -> store_model.CreatorDetails:
 
 
 @router.get(
-    "/my-unpublished-agents",
+    "/myagents",
     summary="Get my agents",
     tags=["store", "private"],
-    dependencies=[Security(autogpt_libs.auth.requires_user)],
+    dependencies=[fastapi.Security(autogpt_libs.auth.requires_user)],
+    response_model=store_model.MyAgentsResponse,
 )
-async def get_my_unpublished_agents(
-    user_id: str = Security(autogpt_libs.auth.get_user_id),
-    page: int = Query(ge=1, default=1),
-    page_size: int = Query(ge=1, default=20),
-) -> store_model.MyUnpublishedAgentsResponse:
-    """List the authenticated user's unpublished agents"""
+async def get_my_agents(
+    user_id: str = fastapi.Security(autogpt_libs.auth.get_user_id),
+    page: typing.Annotated[int, fastapi.Query(ge=1)] = 1,
+    page_size: typing.Annotated[int, fastapi.Query(ge=1)] = 20,
+):
+    """
+    Get user's own agents.
+    """
     agents = await store_db.get_my_agents(user_id, page=page, page_size=page_size)
     return agents
 
@@ -345,17 +436,28 @@ async def get_my_unpublished_agents(
     "/submissions/{submission_id}",
     summary="Delete store submission",
     tags=["store", "private"],
-    dependencies=[Security(autogpt_libs.auth.requires_user)],
+    dependencies=[fastapi.Security(autogpt_libs.auth.requires_user)],
+    response_model=bool,
 )
 async def delete_submission(
     submission_id: str,
-    user_id: str = Security(autogpt_libs.auth.get_user_id),
-) -> bool:
-    """Delete a marketplace listing submission"""
+    user_id: str = fastapi.Security(autogpt_libs.auth.get_user_id),
+):
+    """
+    Delete a store listing submission.
+
+    Args:
+        user_id (str): ID of the authenticated user
+        submission_id (str): ID of the submission to be deleted
+
+    Returns:
+        bool: True if the submission was successfully deleted, False otherwise
+    """
     result = await store_db.delete_store_submission(
         user_id=user_id,
         submission_id=submission_id,
     )
+
     return result
 
 
@@ -363,14 +465,37 @@ async def delete_submission(
     "/submissions",
     summary="List my submissions",
     tags=["store", "private"],
-    dependencies=[Security(autogpt_libs.auth.requires_user)],
+    dependencies=[fastapi.Security(autogpt_libs.auth.requires_user)],
+    response_model=store_model.StoreSubmissionsResponse,
 )
 async def get_submissions(
-    user_id: str = Security(autogpt_libs.auth.get_user_id),
-    page: int = Query(ge=1, default=1),
-    page_size: int = Query(ge=1, default=20),
-) -> store_model.StoreSubmissionsResponse:
-    """List the authenticated user's marketplace listing submissions"""
+    user_id: str = fastapi.Security(autogpt_libs.auth.get_user_id),
+    page: int = 1,
+    page_size: int = 20,
+):
+    """
+    Get a paginated list of store submissions for the authenticated user.
+
+    Args:
+        user_id (str): ID of the authenticated user
+        page (int, optional): Page number for pagination. Defaults to 1.
+        page_size (int, optional): Number of submissions per page. Defaults to 20.
+
+    Returns:
+        StoreListingsResponse: Paginated list of store submissions
+
+    Raises:
+        HTTPException: If page or page_size are less than 1
+    """
+    if page < 1:
+        raise fastapi.HTTPException(
+            status_code=422, detail="Page must be greater than 0"
+        )
+
+    if page_size < 1:
+        raise fastapi.HTTPException(
+            status_code=422, detail="Page size must be greater than 0"
+        )
     listings = await store_db.get_store_submissions(
         user_id=user_id,
         page=page,
@@ -383,17 +508,30 @@ async def get_submissions(
     "/submissions",
     summary="Create store submission",
     tags=["store", "private"],
-    dependencies=[Security(autogpt_libs.auth.requires_user)],
+    dependencies=[fastapi.Security(autogpt_libs.auth.requires_user)],
+    response_model=store_model.StoreSubmission,
 )
 async def create_submission(
     submission_request: store_model.StoreSubmissionRequest,
-    user_id: str = Security(autogpt_libs.auth.get_user_id),
-) -> store_model.StoreSubmission:
-    """Submit a new marketplace listing for review"""
+    user_id: str = fastapi.Security(autogpt_libs.auth.get_user_id),
+):
+    """
+    Create a new store listing submission.
+
+    Args:
+        submission_request (StoreSubmissionRequest): The submission details
+        user_id (str): ID of the authenticated user submitting the listing
+
+    Returns:
+        StoreSubmission: The created store submission
+
+    Raises:
+        HTTPException: If there is an error creating the submission
+    """
     result = await store_db.create_store_submission(
         user_id=user_id,
-        graph_id=submission_request.graph_id,
-        graph_version=submission_request.graph_version,
+        agent_id=submission_request.agent_id,
+        agent_version=submission_request.agent_version,
         slug=submission_request.slug,
         name=submission_request.name,
         video_url=submission_request.video_url,
@@ -406,6 +544,7 @@ async def create_submission(
         changes_summary=submission_request.changes_summary or "Initial Submission",
         recommended_schedule_cron=submission_request.recommended_schedule_cron,
     )
+
     return result
 
 
@@ -413,14 +552,28 @@ async def create_submission(
     "/submissions/{store_listing_version_id}",
     summary="Edit store submission",
     tags=["store", "private"],
-    dependencies=[Security(autogpt_libs.auth.requires_user)],
+    dependencies=[fastapi.Security(autogpt_libs.auth.requires_user)],
+    response_model=store_model.StoreSubmission,
 )
 async def edit_submission(
     store_listing_version_id: str,
     submission_request: store_model.StoreSubmissionEditRequest,
-    user_id: str = Security(autogpt_libs.auth.get_user_id),
-) -> store_model.StoreSubmission:
-    """Update a pending marketplace listing submission"""
+    user_id: str = fastapi.Security(autogpt_libs.auth.get_user_id),
+):
+    """
+    Edit an existing store listing submission.
+
+    Args:
+        store_listing_version_id (str): ID of the store listing version to edit
+        submission_request (StoreSubmissionRequest): The updated submission details
+        user_id (str): ID of the authenticated user editing the listing
+
+    Returns:
+        StoreSubmission: The updated store submission
+
+    Raises:
+        HTTPException: If there is an error editing the submission
+    """
     result = await store_db.edit_store_submission(
         user_id=user_id,
         store_listing_version_id=store_listing_version_id,
@@ -435,6 +588,7 @@ async def edit_submission(
         changes_summary=submission_request.changes_summary,
         recommended_schedule_cron=submission_request.recommended_schedule_cron,
     )
+
     return result
 
 
@@ -442,61 +596,115 @@ async def edit_submission(
     "/submissions/media",
     summary="Upload submission media",
     tags=["store", "private"],
-    dependencies=[Security(autogpt_libs.auth.requires_user)],
+    dependencies=[fastapi.Security(autogpt_libs.auth.requires_user)],
 )
 async def upload_submission_media(
     file: fastapi.UploadFile,
-    user_id: str = Security(autogpt_libs.auth.get_user_id),
-) -> str:
-    """Upload media for a marketplace listing submission"""
+    user_id: str = fastapi.Security(autogpt_libs.auth.get_user_id),
+):
+    """
+    Upload media (images/videos) for a store listing submission.
+
+    Args:
+        file (UploadFile): The media file to upload
+        user_id (str): ID of the authenticated user uploading the media
+
+    Returns:
+        str: URL of the uploaded media file
+
+    Raises:
+        HTTPException: If there is an error uploading the media
+    """
     media_url = await store_media.upload_media(user_id=user_id, file=file)
     return media_url
 
 
-class ImageURLResponse(BaseModel):
-    image_url: str
-
-
 @router.post(
     "/submissions/generate_image",
     summary="Generate submission image",
     tags=["store", "private"],
-    dependencies=[Security(autogpt_libs.auth.requires_user)],
+    dependencies=[fastapi.Security(autogpt_libs.auth.requires_user)],
 )
 async def generate_image(
-    graph_id: str,
-    user_id: str = Security(autogpt_libs.auth.get_user_id),
-) -> ImageURLResponse:
+    agent_id: str,
+    user_id: str = fastapi.Security(autogpt_libs.auth.get_user_id),
+) -> fastapi.responses.Response:
     """
-    Generate an image for a marketplace listing submission based on the properties
-    of a given graph.
+    Generate an image for a store listing submission.
+
+    Args:
+        agent_id (str): ID of the agent to generate an image for
+        user_id (str): ID of the authenticated user
+
+    Returns:
+        JSONResponse: JSON containing the URL of the generated image
     """
-    graph = await backend.data.graph.get_graph(
-        graph_id=graph_id, version=None, user_id=user_id
+    agent = await backend.data.graph.get_graph(
+        graph_id=agent_id, version=None, user_id=user_id
     )
 
-    if not graph:
-        raise NotFoundError(f"Agent graph #{graph_id} not found")
+    if not agent:
+        raise fastapi.HTTPException(
+            status_code=404, detail=f"Agent with ID {agent_id} not found"
+        )
     # Use .jpeg here since we are generating JPEG images
-    filename = f"agent_{graph_id}.jpeg"
+    filename = f"agent_{agent_id}.jpeg"
 
     existing_url = await store_media.check_media_exists(user_id, filename)
     if existing_url:
-        logger.info(f"Using existing image for agent graph {graph_id}")
-        return ImageURLResponse(image_url=existing_url)
+        logger.info(f"Using existing image for agent {agent_id}")
+        return fastapi.responses.JSONResponse(content={"image_url": existing_url})
     # Generate agent image as JPEG
-    image = await store_image_gen.generate_agent_image(agent=graph)
+    image = await store_image_gen.generate_agent_image(agent=agent)
 
     # Create UploadFile with the correct filename and content_type
     image_file = fastapi.UploadFile(
         file=image,
         filename=filename,
     )
+
     image_url = await store_media.upload_media(
         user_id=user_id, file=image_file, use_file_name=True
     )
 
-    return ImageURLResponse(image_url=image_url)
+    return fastapi.responses.JSONResponse(content={"image_url": image_url})
+
+
+@router.get(
+    "/download/agents/{store_listing_version_id}",
+    summary="Download agent file",
+    tags=["store", "public"],
+)
+async def download_agent_file(
+    store_listing_version_id: str = fastapi.Path(
+        ..., description="The ID of the agent to download"
+    ),
+) -> fastapi.responses.FileResponse:
+    """
+    Download the agent file by streaming its content.
+
+    Args:
+        store_listing_version_id (str): The ID of the agent to download
+
+    Returns:
+        StreamingResponse: A streaming response containing the agent's graph data.
+
+    Raises:
+        HTTPException: If the agent is not found or an unexpected error occurs.
+    """
+    graph_data = await store_db.get_agent(store_listing_version_id)
+    file_name = f"agent_{graph_data.id}_v{graph_data.version or 'latest'}.json"
+
+    # Sending graph as a stream (similar to marketplace v1)
+    with tempfile.NamedTemporaryFile(
+        mode="w", suffix=".json", delete=False
+    ) as tmp_file:
+        tmp_file.write(backend.util.json.dumps(graph_data))
+        tmp_file.flush()
+
+        return fastapi.responses.FileResponse(
+            tmp_file.name, filename=file_name, media_type="application/json"
+        )
 
 
 ##############################################

autogpt_platform/backend/backend/api/features/store/routes_test.py

@@ -8,8 +8,6 @@ import pytest
 import pytest_mock
 from pytest_snapshot.plugin import Snapshot
 
-from backend.api.features.store.db import StoreAgentsSortOptions
-
 from . import model as store_model
 from . import routes as store_routes
 
@@ -198,7 +196,7 @@ def test_get_agents_sorted(
     mock_db_call.assert_called_once_with(
         featured=False,
         creators=None,
-        sorted_by=StoreAgentsSortOptions.RUNS,
+        sorted_by="runs",
         search_query=None,
         category=None,
         page=1,
@@ -382,11 +380,9 @@ def test_get_agent_details(
         runs=100,
         rating=4.5,
         versions=["1.0.0", "1.1.0"],
-        graph_versions=["1", "2"],
-        graph_id="test-graph-id",
+        agentGraphVersions=["1", "2"],
+        agentGraphId="test-graph-id",
         last_updated=FIXED_NOW,
-        active_version_id="test-version-id",
-        has_approved_version=True,
     )
     mock_db_call = mocker.patch("backend.api.features.store.db.get_store_agent_details")
     mock_db_call.return_value = mocked_value
@@ -439,17 +435,15 @@ def test_get_creators_pagination(
 ) -> None:
     mocked_value = store_model.CreatorsResponse(
         creators=[
-            store_model.CreatorDetails(
+            store_model.Creator(
                 name=f"Creator {i}",
                 username=f"creator{i}",
-                avatar_url=f"avatar{i}.jpg",
                 description=f"Creator {i} description",
-                links=[f"user{i}.link.com"],
-                is_featured=False,
+                avatar_url=f"avatar{i}.jpg",
                 num_agents=1,
-                agent_runs=100,
                 agent_rating=4.5,
-                top_categories=["cat1", "cat2", "cat3"],
+                agent_runs=100,
+                is_featured=False,
             )
             for i in range(5)
         ],
@@ -502,19 +496,19 @@ def test_get_creator_details(
     mocked_value = store_model.CreatorDetails(
         name="Test User",
         username="creator1",
-        avatar_url="avatar.jpg",
         description="Test creator description",
         links=["link1.com", "link2.com"],
-        is_featured=True,
-        num_agents=5,
-        agent_runs=1000,
+        avatar_url="avatar.jpg",
         agent_rating=4.8,
+        agent_runs=1000,
         top_categories=["category1", "category2"],
     )
-    mock_db_call = mocker.patch("backend.api.features.store.db.get_store_creator")
+    mock_db_call = mocker.patch(
+        "backend.api.features.store.db.get_store_creator_details"
+    )
     mock_db_call.return_value = mocked_value
 
-    response = client.get("/creators/creator1")
+    response = client.get("/creator/creator1")
     assert response.status_code == 200
 
     data = store_model.CreatorDetails.model_validate(response.json())
@@ -534,26 +528,19 @@ def test_get_submissions_success(
         submissions=[
             store_model.StoreSubmission(
                 listing_id="test-listing-id",
-                user_id="test-user-id",
-                slug="test-agent",
-                listing_version_id="test-version-id",
-                listing_version=1,
-                graph_id="test-agent-id",
-                graph_version=1,
                 name="Test Agent",
-                sub_heading="Test agent subheading",
                 description="Test agent description",
-                instructions="Click the button!",
-                categories=["test-category"],
                 image_urls=["test.jpg"],
-                video_url="test.mp4",
-                agent_output_demo_url="demo_video.mp4",
-                submitted_at=FIXED_NOW,
-                changes_summary="Initial Submission",
+                date_submitted=FIXED_NOW,
                 status=prisma.enums.SubmissionStatus.APPROVED,
-                run_count=50,
-                review_count=5,
-                review_avg_rating=4.2,
+                runs=50,
+                rating=4.2,
+                agent_id="test-agent-id",
+                agent_version=1,
+                sub_heading="Test agent subheading",
+                slug="test-agent",
+                video_url="test.mp4",
+                categories=["test-category"],
             )
         ],
         pagination=store_model.Pagination(

autogpt_platform/backend/backend/api/features/store/test_cache_delete.py

@@ -11,7 +11,6 @@ import pytest
 from backend.util.models import Pagination
 
 from . import cache as store_cache
-from .db import StoreAgentsSortOptions
 from .model import StoreAgent, StoreAgentsResponse
 
 
@@ -216,7 +215,7 @@ class TestCacheDeletion:
             await store_cache._get_cached_store_agents(
                 featured=True,
                 creator="testuser",
-                sorted_by=StoreAgentsSortOptions.RATING,
+                sorted_by="rating",
                 search_query="AI assistant",
                 category="productivity",
                 page=2,
@@ -228,7 +227,7 @@ class TestCacheDeletion:
             deleted = store_cache._get_cached_store_agents.cache_delete(
                 featured=True,
                 creator="testuser",
-                sorted_by=StoreAgentsSortOptions.RATING,
+                sorted_by="rating",
                 search_query="AI assistant",
                 category="productivity",
                 page=2,
@@ -240,7 +239,7 @@ class TestCacheDeletion:
             deleted = store_cache._get_cached_store_agents.cache_delete(
                 featured=True,
                 creator="testuser",
-                sorted_by=StoreAgentsSortOptions.RATING,
+                sorted_by="rating",
                 search_query="AI assistant",
                 category="productivity",
                 page=2,

autogpt_platform/backend/backend/api/features/v1.py

@@ -449,6 +449,7 @@ async def execute_graph_block(
 async def upload_file(
     user_id: Annotated[str, Security(get_user_id)],
     file: UploadFile = File(...),
+    provider: str = "gcs",
     expiration_hours: int = 24,
 ) -> UploadFileResponse:
     """
@@ -511,6 +512,7 @@ async def upload_file(
     storage_path = await cloud_storage.store_file(
         content=content,
         filename=file_name,
+        provider=provider,
         expiration_hours=expiration_hours,
         user_id=user_id,
     )

autogpt_platform/backend/backend/api/features/v1_test.py

@@ -515,6 +515,7 @@ async def test_upload_file_success(test_user_id: str):
         result = await upload_file(
             file=upload_file_mock,
             user_id=test_user_id,
+            provider="gcs",
             expiration_hours=24,
         )
 
@@ -532,6 +533,7 @@ async def test_upload_file_success(test_user_id: str):
         mock_handler.store_file.assert_called_once_with(
             content=file_content,
             filename="test.txt",
+            provider="gcs",
             expiration_hours=24,
             user_id=test_user_id,
         )

autogpt_platform/backend/backend/api/rest_api.py

@@ -55,7 +55,6 @@ from backend.util.exceptions import (
     MissingConfigError,
     NotAuthorizedError,
     NotFoundError,
-    PreconditionFailed,
 )
 from backend.util.feature_flag import initialize_launchdarkly, shutdown_launchdarkly
 from backend.util.service import UnhealthyServiceError
@@ -276,7 +275,6 @@ app.add_exception_handler(RequestValidationError, validation_error_handler)
 app.add_exception_handler(pydantic.ValidationError, validation_error_handler)
 app.add_exception_handler(MissingConfigError, handle_internal_http_error(503))
 app.add_exception_handler(ValueError, handle_internal_http_error(400))
-app.add_exception_handler(PreconditionFailed, handle_internal_http_error(428))
 app.add_exception_handler(Exception, handle_internal_http_error(500))
 
 app.include_router(backend.api.features.v1.v1_router, tags=["v1"], prefix="/api")

autogpt_platform/backend/backend/blocks/smart_agent.py

@@ -1,847 +0,0 @@
-import logging
-import os
-import re
-from concurrent.futures import Future
-from enum import Enum
-from typing import TYPE_CHECKING, Any, Literal, NamedTuple
-
-from claude_agent_sdk import query
-from claude_agent_sdk.types import (
-    AssistantMessage,
-    ClaudeAgentOptions,
-    TextBlock,
-    ToolUseBlock,
-)
-from pydantic import BaseModel, SecretStr
-
-from backend.blocks._base import (
-    Block,
-    BlockCategory,
-    BlockOutput,
-    BlockSchemaInput,
-    BlockSchemaOutput,
-    BlockType,
-)
-from backend.blocks.agent import AgentExecutorBlock
-from backend.blocks.smart_decision_maker import SmartDecisionMakerBlock
-from backend.data.dynamic_fields import is_tool_pin
-from backend.data.execution import ExecutionContext, NodeExecutionEntry
-from backend.data.model import (
-    APIKeyCredentials,
-    CredentialsField,
-    CredentialsMetaInput,
-    SchemaField,
-)
-from backend.integrations.providers import ProviderName
-from backend.util import json
-from backend.util.clients import get_database_manager_async_client
-
-if TYPE_CHECKING:
-    from backend.data.graph import Link, Node
-    from backend.executor.manager import ExecutionProcessor
-
-logger = logging.getLogger(__name__)
-
-
-class ToolInfo(BaseModel):
-    """Processed tool call information."""
-
-    tool_call: Any  # The original tool call object from LLM response
-    tool_name: str  # The function name
-    tool_def: dict[str, Any]  # The tool definition from tool_functions
-    input_data: dict[str, Any]  # Processed input data ready for tool execution
-    field_mapping: dict[str, str]  # Field name mapping for the tool
-
-
-class ExecutionParams(BaseModel):
-    """Tool execution parameters."""
-
-    user_id: str
-    graph_id: str
-    node_id: str
-    graph_version: int
-    graph_exec_id: str
-    node_exec_id: str
-    execution_context: "ExecutionContext"
-
-
-class MockToolCall:
-    """Shim that gives ToolInfo a .id and .function attribute from raw call data."""
-
-    def __init__(self, tool_id: str, name: str, args: dict[str, Any]):
-        self.id = tool_id
-        self.function = type(
-            "Function", (), {"name": name, "arguments": json.dumps(args)}
-        )()
-
-
-def _create_tool_response(call_id: str, content: str) -> dict[str, Any]:
-    """Create a tool response in the correct format."""
-    # Anthropics format: tool IDs typically start with "toolu_"
-    if call_id.startswith("toolu_"):
-        return {
-            "role": "user",
-            "type": "message",
-            "content": [
-                {"tool_use_id": call_id, "type": "tool_result", "content": content}
-            ],
-        }
-    # OpenAI format: tool IDs typically start with "call_".
-    # Or default fallback (if the tool_id doesn't match any known prefix)
-    return {"role": "tool", "tool_call_id": call_id, "content": content}
-
-
-class ModelMetadata(NamedTuple):
-    provider: str
-    context_window: int
-    max_output_tokens: int | None
-
-
-class AgentModel(str, Enum):
-    """Available models for the Smart Agent."""
-
-    # Claude 4.x models (latest)
-    CLAUDE_4_1_OPUS = "claude-opus-4-1-20250805"
-    CLAUDE_4_OPUS = "claude-opus-4-20250514"
-    CLAUDE_4_SONNET = "claude-sonnet-4-20250514"
-    CLAUDE_4_5_OPUS = "claude-opus-4-5-20251101"
-    CLAUDE_4_5_SONNET = "claude-sonnet-4-5-20250929"
-    CLAUDE_4_5_HAIKU = "claude-haiku-4-5-20251001"
-
-    # Claude 3.x models (stable)
-    CLAUDE_3_7_SONNET = "claude-3-7-sonnet-20250219"
-    CLAUDE_3_HAIKU = "claude-3-haiku-20240307"
-
-    @property
-    def metadata(self) -> ModelMetadata:
-        return AGENT_MODEL_METADATA[self]
-
-    @property
-    def provider(self) -> str:
-        return self.metadata.provider
-
-
-# Agent model metadata mapping
-AGENT_MODEL_METADATA = {
-    # Claude 4.x models
-    AgentModel.CLAUDE_4_1_OPUS: ModelMetadata(ProviderName.ANTHROPIC, 500000, 4096),
-    AgentModel.CLAUDE_4_OPUS: ModelMetadata(ProviderName.ANTHROPIC, 500000, 4096),
-    AgentModel.CLAUDE_4_SONNET: ModelMetadata(ProviderName.ANTHROPIC, 500000, 4096),
-    AgentModel.CLAUDE_4_5_OPUS: ModelMetadata(ProviderName.ANTHROPIC, 500000, 8192),
-    AgentModel.CLAUDE_4_5_SONNET: ModelMetadata(ProviderName.ANTHROPIC, 500000, 8192),
-    AgentModel.CLAUDE_4_5_HAIKU: ModelMetadata(ProviderName.ANTHROPIC, 200000, 4096),
-    # Claude 3.x models
-    AgentModel.CLAUDE_3_7_SONNET: ModelMetadata(ProviderName.ANTHROPIC, 200000, 4096),
-    AgentModel.CLAUDE_3_HAIKU: ModelMetadata(ProviderName.ANTHROPIC, 200000, 4096),
-}
-
-# Anthropic-only credentials for Claude models
-ClaudeCredentials = CredentialsMetaInput[
-    Literal[ProviderName.ANTHROPIC], Literal["api_key"]
-]
-
-
-def ClaudeCredentialsField() -> ClaudeCredentials:
-    return CredentialsField(
-        description="Anthropic API key for Claude Agent SDK access.",
-        discriminator="model",
-        discriminator_mapping={
-            model.value: model.metadata.provider for model in AgentModel
-        },
-    )
-
-
-# Test credentials for Claude models
-TEST_CLAUDE_CREDENTIALS = APIKeyCredentials(
-    id="test-claude-creds",
-    provider=ProviderName.ANTHROPIC,
-    api_key=SecretStr("mock-anthropic-api-key"),
-    title="Mock Anthropic API key",
-    expires_at=None,
-)
-TEST_CLAUDE_CREDENTIALS_INPUT = {
-    "provider": TEST_CLAUDE_CREDENTIALS.provider,
-    "id": TEST_CLAUDE_CREDENTIALS.id,
-    "type": TEST_CLAUDE_CREDENTIALS.type,
-    "title": TEST_CLAUDE_CREDENTIALS.title,
-}
-
-
-class SmartAgentBlock(Block):
-    """
-    A smart agent block that uses Claude Agent SDK for native agent capabilities
-    while executing AutoGPT tool nodes.
-
-    This block combines Claude's native agent functionality with AutoGPT's tool ecosystem:
-    - Uses Claude Agent SDK for core agent intelligence
-    - Discovers connected AutoGPT tool nodes like SmartDecisionMaker
-    - When Claude calls tools, executes the actual AutoGPT tool nodes
-    - Provides Claude with the tool execution results
-    """
-
-    class Input(BlockSchemaInput):
-        task: str = SchemaField(
-            description="The task for the agent to complete. Be specific about your requirements.",
-            placeholder="Analyze the data file and create a summary report with key insights...",
-        )
-        model: AgentModel = SchemaField(
-            title="Model",
-            default=AgentModel.CLAUDE_4_5_SONNET,
-            description="The model to use for the agent.",
-            advanced=False,
-        )
-        credentials: ClaudeCredentials = ClaudeCredentialsField()
-        max_iterations: int = SchemaField(
-            default=15,
-            description="Maximum number of agent iterations. Use -1 for unlimited (use carefully!).",
-            advanced=False,
-        )
-        system_prompt: str = SchemaField(
-            title="System Prompt",
-            default="You are a helpful AI assistant with access to tools. Think step by step about which tools to use to complete the task efficiently. When you have completed the objective, provide a clear summary of the results.",
-            description="System prompt to guide the agent's behavior.",
-            advanced=True,
-        )
-        working_directory: str = SchemaField(
-            default="/tmp/smart_agent",
-            description="Working directory for the agent.",
-            advanced=True,
-        )
-
-    class Output(BlockSchemaOutput):
-        result: str = SchemaField(
-            description="The final result or answer from the agent."
-        )
-        iterations_used: int = SchemaField(
-            description="Number of iterations used to complete the task."
-        )
-        tools_used: list[str] = SchemaField(
-            description="List of AutoGPT tools used during execution.",
-            default_factory=list,
-        )
-        success: bool = SchemaField(
-            description="Whether the task was completed successfully."
-        )
-        error: str = SchemaField(
-            default="", description="Error message if the task failed."
-        )
-        # Tool output pins for connecting to other blocks (like SmartDecisionMakerBlock)
-        tools: Any = SchemaField(
-            description="Tool calls output for connecting to other AutoGPT blocks."
-        )
-        conversations: list[Any] = SchemaField(
-            description="Conversation history with Claude Agent SDK.",
-            default_factory=list,
-        )
-
-    def __init__(self):
-        super().__init__(
-            id="dbe509c8-5078-49c5-ba1a-41a9ef9b459a",
-            description=(
-                "An AI agent powered by Claude Agent SDK that executes connected AutoGPT tool nodes. "
-                "Combines Claude's native agent capabilities with AutoGPT's tool ecosystem."
-            ),
-            categories={BlockCategory.AI},
-            block_type=BlockType.AI,
-            input_schema=SmartAgentBlock.Input,
-            output_schema=SmartAgentBlock.Output,
-            test_input={
-                "task": "What tools are available?",
-                "credentials": TEST_CLAUDE_CREDENTIALS_INPUT,
-                "model": AgentModel.CLAUDE_4_5_SONNET,
-            },
-            test_output=[],
-            test_credentials=TEST_CLAUDE_CREDENTIALS,
-        )
-
-    @staticmethod
-    def cleanup(s: str):
-        """Clean up block names for use as tool function names."""
-        return re.sub(r"[^a-zA-Z0-9_-]", "_", s).lower()
-
-    async def _create_tool_node_signatures(
-        self,
-        node_id: str,
-    ) -> list[dict[str, Any]]:
-        """
-        Creates function signatures for connected tools.
-        Args:
-            node_id: The node_id for which to create function signatures.
-        Returns:
-            List of function signatures for tools
-        """
-        db_client = get_database_manager_async_client()
-        tools = [
-            (link, node)
-            for link, node in await db_client.get_connected_output_nodes(node_id)
-            if is_tool_pin(link.source_name) and link.source_id == node_id
-        ]
-        if not tools:
-            raise ValueError("There is no next node to execute.")
-        return_tool_functions: list[dict[str, Any]] = []
-        grouped_tool_links: dict[str, tuple["Node", list["Link"]]] = {}
-        for link, node in tools:
-            if link.sink_id not in grouped_tool_links:
-                grouped_tool_links[link.sink_id] = (node, [link])
-            else:
-                grouped_tool_links[link.sink_id][1].append(link)
-        for sink_node, links in grouped_tool_links.values():
-            if not sink_node:
-                raise ValueError(f"Sink node not found: {links[0].sink_id}")
-            if sink_node.block_id == AgentExecutorBlock().id:
-                tool_func = (
-                    await SmartDecisionMakerBlock._create_agent_function_signature(
-                        sink_node, links
-                    )
-                )
-            else:
-                tool_func = (
-                    await SmartDecisionMakerBlock._create_block_function_signature(
-                        sink_node, links
-                    )
-                )
-            return_tool_functions.append(tool_func)
-        return return_tool_functions
-
-    async def _execute_single_tool_with_manager(
-        self,
-        tool_info: ToolInfo,
-        execution_params: ExecutionParams,
-        execution_processor: "ExecutionProcessor",
-    ) -> dict:
-        """Execute a single tool using the execution manager for proper integration."""
-        tool_call = tool_info.tool_call
-        tool_def = tool_info.tool_def
-        raw_input_data = tool_info.input_data
-
-        # Get sink node and field mapping
-        sink_node_id = tool_def["function"]["_sink_node_id"]
-
-        # Use proper database operations for tool execution
-        db_client = get_database_manager_async_client()
-
-        # Get target node
-        target_node = await db_client.get_node(sink_node_id)
-        if not target_node:
-            raise ValueError(f"Target node {sink_node_id} not found")
-
-        # Create proper node execution using upsert_execution_input
-        node_exec_result = None
-        final_input_data = None
-
-        # Add all inputs to the execution
-        if not raw_input_data:
-            raise ValueError(f"Tool call has no input data: {tool_call}")
-
-        for input_name, input_value in raw_input_data.items():
-            node_exec_result, final_input_data = await db_client.upsert_execution_input(
-                node_id=sink_node_id,
-                graph_exec_id=execution_params.graph_exec_id,
-                input_name=input_name,
-                input_data=input_value,
-            )
-
-        assert node_exec_result is not None, "node_exec_result should not be None"
-
-        # Create NodeExecutionEntry for execution manager
-        node_exec_entry = NodeExecutionEntry(
-            user_id=execution_params.user_id,
-            graph_exec_id=execution_params.graph_exec_id,
-            graph_id=execution_params.graph_id,
-            graph_version=execution_params.graph_version,
-            node_exec_id=node_exec_result.node_exec_id,
-            node_id=sink_node_id,
-            block_id=target_node.block_id,
-            inputs=final_input_data or {},
-            execution_context=execution_params.execution_context,
-        )
-
-        # Use the execution manager to execute the tool node
-        try:
-            # Get NodeExecutionProgress from the execution manager's running nodes
-            node_exec_progress = execution_processor.running_node_execution[
-                sink_node_id
-            ]
-
-            # Use the execution manager's own graph stats
-            graph_stats_pair = (
-                execution_processor.execution_stats,
-                execution_processor.execution_stats_lock,
-            )
-
-            # Create a completed future for the task tracking system
-            node_exec_future = Future()
-            node_exec_progress.add_task(
-                node_exec_id=node_exec_result.node_exec_id,
-                task=node_exec_future,
-            )
-
-            # Execute the node directly since we're in the SmartAgent context
-            node_exec_future.set_result(
-                await execution_processor.on_node_execution(
-                    node_exec=node_exec_entry,
-                    node_exec_progress=node_exec_progress,
-                    nodes_input_masks=None,
-                    graph_stats_pair=graph_stats_pair,
-                )
-            )
-
-            # Get outputs from database after execution completes using database manager client
-            node_outputs = await db_client.get_execution_outputs_by_node_exec_id(
-                node_exec_result.node_exec_id
-            )
-
-            # Create tool response
-            tool_response_content = (
-                json.dumps(node_outputs)
-                if node_outputs
-                else "Tool executed successfully"
-            )
-            return _create_tool_response(tool_call.id, tool_response_content)
-        except Exception as e:
-            logger.error(f"Tool execution with manager failed: {e}")
-            # Return error response
-            return _create_tool_response(
-                tool_call.id, f"Tool execution failed: {str(e)}"
-            )
-
-    def _setup_environment(
-        self, credentials: APIKeyCredentials, working_dir: str
-    ) -> dict[str, str]:
-        """Setup environment for Claude Agent SDK."""
-        os.makedirs(working_dir, exist_ok=True)
-        env = os.environ.copy()
-        env["ANTHROPIC_API_KEY"] = credentials.api_key.get_secret_value()
-        return env
-
-    def _build_tool_descriptions_for_claude(
-        self, tool_functions: list[dict[str, Any]]
-    ) -> str:
-        """Build description of available AutoGPT tools for Claude."""
-        if not tool_functions:
-            return "No tools are currently connected to this agent."
-
-        tool_descriptions = ["Available AutoGPT tools:"]
-        for tool_def in tool_functions:
-            func_def = tool_def.get("function", {})
-            name = func_def.get("name", "unknown")
-            description = func_def.get("description", "No description")
-            tool_descriptions.append(f"- {name}: {description}")
-
-        tool_descriptions.append(
-            "\nWhen you need to use a tool, call it with function calling syntax."
-        )
-        return "\n".join(tool_descriptions)
-
-    def _extract_tool_calls_from_claude_message(
-        self, message: AssistantMessage
-    ) -> list[dict[str, Any]]:
-        """Extract tool calls from Claude Agent SDK message."""
-        tool_calls = []
-        for content_block in message.content:
-            if isinstance(content_block, ToolUseBlock):
-                tool_calls.append(
-                    {
-                        "id": content_block.id,
-                        "function": {
-                            "name": content_block.name,
-                            "arguments": content_block.input,
-                        },
-                    }
-                )
-        return tool_calls
-
-    def _extract_text_content_from_claude_message(
-        self, message: AssistantMessage
-    ) -> str:
-        """Extract text content from Claude Agent SDK message."""
-        text_parts = []
-        for content_block in message.content:
-            if isinstance(content_block, TextBlock):
-                text_parts.append(content_block.text)
-        return "".join(text_parts)
-
-    def _format_conversation_for_claude(self, conversation: list[dict]) -> str:
-        """Format conversation history for Claude Agent SDK."""
-        formatted = []
-        for msg in conversation:
-            role = msg.get("role", "user")
-            content = msg.get("content", "")
-
-            if role == "tool":
-                # Format tool response
-                tool_id = msg.get("tool_call_id", "unknown")
-                formatted.append(f"Tool result ({tool_id}): {content}")
-            else:
-                # Simple format for user/assistant messages
-                formatted.append(f"{role.title()}: {content}")
-
-        return "\n\n".join(formatted)
-
-    def _normalize_tool_args(self, tool_args: Any) -> dict:
-        """Normalize tool arguments to dict format."""
-        if isinstance(tool_args, str):
-            return json.loads(tool_args)
-        elif isinstance(tool_args, dict):
-            return tool_args
-        else:
-            return dict(tool_args) if tool_args else {}
-
-    def _create_tool_info_from_claude_call(
-        self, tool_call: dict[str, Any], tool_functions: list[dict[str, Any]]
-    ) -> ToolInfo:
-        """Convert Claude tool call to AutoGPT ToolInfo format."""
-        tool_name = tool_call["function"]["name"]
-        tool_args = self._normalize_tool_args(tool_call["function"]["arguments"])
-        tool_id = tool_call["id"]
-
-        # Find the AutoGPT tool definition
-        tool_def = next(
-            (
-                tf
-                for tf in tool_functions
-                if tf.get("function", {}).get("name") == tool_name
-            ),
-            None,
-        )
-
-        if not tool_def:
-            raise ValueError(f"AutoGPT tool '{tool_name}' not found")
-
-        # Build input data from arguments
-        field_mapping = tool_def["function"].get("_field_mapping", {})
-        expected_args = tool_def["function"]["parameters"].get("properties", {})
-
-        input_data = {
-            field_mapping.get(clean_arg_name, clean_arg_name): tool_args.get(
-                clean_arg_name
-            )
-            for clean_arg_name in expected_args
-        }
-
-        return ToolInfo(
-            tool_call=MockToolCall(tool_id, tool_name, tool_args),
-            tool_name=tool_name,
-            tool_def=tool_def,
-            input_data=input_data,
-            field_mapping=field_mapping,
-        )
-
-    async def _attempt_claude_call_with_validation(
-        self,
-        prompt: str,
-        options: ClaudeAgentOptions,
-    ) -> AssistantMessage:
-        """Claude SDK call - let generator cleanup happen naturally to avoid cancel scope issues."""
-        try:
-            # Simple approach: don't try to manually manage the generator lifecycle
-            async for message in query(prompt=prompt, options=options):
-                if isinstance(message, AssistantMessage):
-                    return message
-
-            raise ValueError("No AssistantMessage received from Claude SDK")
-
-        except Exception as e:
-            logger.error(f"Claude SDK call failed: {e}")
-            raise
-        # Note: No finally block - let the generator be cleaned up naturally by garbage collection
-
-    async def _execute_tools_agent_mode(
-        self,
-        input_data: Input,
-        credentials,
-        tool_functions: list[dict[str, Any]],
-        graph_exec_id: str,
-        node_id: str,
-        node_exec_id: str,
-        user_id: str,
-        graph_id: str,
-        graph_version: int,
-        execution_context: ExecutionContext,
-        execution_processor: "ExecutionProcessor",
-    ):
-        """Execute tools in agent mode with a loop until finished, following SmartDecisionMakerBlock pattern."""
-        max_iterations = input_data.max_iterations
-        iteration = 0
-
-        # Execution parameters for tool execution
-        execution_params = ExecutionParams(
-            user_id=user_id,
-            graph_id=graph_id,
-            node_id=node_id,
-            graph_version=graph_version,
-            graph_exec_id=graph_exec_id,
-            node_exec_id=node_exec_id,
-            execution_context=execution_context,
-        )
-
-        # Build enhanced task prompt with tool descriptions
-        tool_descriptions = self._build_tool_descriptions_for_claude(tool_functions)
-        enhanced_task = f"""{input_data.task}
-
-{tool_descriptions}
-
-Complete the task step by step using the available tools as needed."""
-
-        # Start conversation with enhanced task
-        current_conversation = [{"role": "user", "content": enhanced_task}]
-
-        while max_iterations < 0 or iteration < max_iterations:
-            iteration += 1
-            logger.debug(f"Claude agent mode iteration {iteration}")
-
-            # Prepare conversation for this iteration
-            iteration_conversation = list(current_conversation)
-
-            # On the last iteration, add encouragement to finish
-            if max_iterations > 0 and iteration == max_iterations:
-                last_iteration_message = {
-                    "role": "system",
-                    "content": f"This is your last iteration ({iteration}/{max_iterations}). "
-                    "Try to complete the task with the information you have. "
-                    "Prefer finishing with a clear response rather than making additional tool calls.",
-                }
-                iteration_conversation.append(last_iteration_message)
-
-            # Format conversation for Claude SDK
-            conversation_text = self._format_conversation_for_claude(
-                iteration_conversation
-            )
-
-            # Setup Claude options for this iteration
-            claude_options = ClaudeAgentOptions(
-                system_prompt=input_data.system_prompt,
-                model=input_data.model.value,
-                max_turns=1,  # Single turn per iteration
-                cwd=input_data.working_directory,
-                env=self._setup_environment(credentials, input_data.working_directory),
-                permission_mode="bypassPermissions",
-            )
-
-            # Get Claude response
-            logger.debug(f"Claude agent iteration {iteration}: Making Claude SDK call")
-            try:
-                claude_response = await self._attempt_claude_call_with_validation(
-                    conversation_text, claude_options
-                )
-                logger.debug(f"Claude agent iteration {iteration}: Received response")
-            except Exception as e:
-                logger.error(
-                    f"Claude agent iteration {iteration}: Call failed with {type(e).__name__}: {str(e)}"
-                )
-                yield (
-                    "error",
-                    f"Claude call failed in agent mode iteration {iteration}: {str(e)}",
-                )
-                return
-
-            # Process tool calls
-            tool_calls = self._extract_tool_calls_from_claude_message(claude_response)
-            text_content = self._extract_text_content_from_claude_message(
-                claude_response
-            )
-
-            # Add Claude's response to conversation
-            assistant_message = {
-                "role": "assistant",
-                "content": text_content,
-                "tool_calls": tool_calls if tool_calls else [],
-            }
-            current_conversation.append(assistant_message)
-
-            # If no tool calls, we're done
-            if not tool_calls:
-                yield "finished", text_content
-                yield "conversations", current_conversation
-                return
-
-            # Execute tools and collect responses
-            tool_outputs = []
-            for tool_call in tool_calls:
-                # Convert tool call to ToolInfo format for AutoGPT execution
-                tool_info = self._create_tool_info_from_claude_call(
-                    tool_call, tool_functions
-                )
-
-                try:
-                    # Execute via AutoGPT's execution manager
-                    tool_response = await self._execute_single_tool_with_manager(
-                        tool_info, execution_params, execution_processor
-                    )
-                    tool_outputs.append(tool_response)
-                except Exception as e:
-                    logger.error(f"Tool execution failed: {e}")
-                    error_response = _create_tool_response(
-                        tool_call["id"], f"Error: {str(e)}"
-                    )
-                    tool_outputs.append(error_response)
-
-            # Add tool results to conversation
-            current_conversation.extend(tool_outputs)
-
-            # Yield intermediate conversation state
-            yield "conversations", current_conversation
-
-        # If we reach max iterations, yield the current state
-        if max_iterations < 0:
-            yield "finished", f"Agent mode completed after {iteration} iterations"
-        else:
-            yield (
-                "finished",
-                f"Agent mode completed after {max_iterations} iterations (limit reached)",
-            )
-        yield "conversations", current_conversation
-
-    async def _execute_single_call_mode(
-        self,
-        input_data: Input,  # Used for configuration and consistency with agent mode
-        tool_functions: list[dict[str, Any]],
-        enhanced_task: str,
-        claude_options: ClaudeAgentOptions | None,
-    ):
-        """Execute single call mode and yield tool outputs for external execution."""
-        # Create Claude options for single call if not provided
-        if claude_options is None:
-            claude_options = ClaudeAgentOptions(
-                system_prompt=input_data.system_prompt,
-                model=input_data.model.value,
-                max_turns=1,  # Single call mode
-                cwd=input_data.working_directory,
-                permission_mode="bypassPermissions",
-            )
-        else:
-            # Override max_turns to 1 for single call
-            claude_options.max_turns = 1
-
-        try:
-            claude_response = await self._attempt_claude_call_with_validation(
-                enhanced_task, claude_options
-            )
-        except Exception as e:
-            yield "error", f"Claude SDK error: {str(e)}"
-            yield "success", False
-            return
-
-        if claude_response:
-            text_content = self._extract_text_content_from_claude_message(
-                claude_response
-            )
-            tool_calls = self._extract_tool_calls_from_claude_message(claude_response)
-
-            if not tool_calls:
-                # No tool calls - just return the result
-                yield "result", text_content
-                yield "success", True
-                yield "tools", []  # No tools used
-                return
-
-            # Process and yield tool calls for external execution
-            for tool_call in tool_calls:
-                tool_name = tool_call["function"]["name"]
-                tool_args = self._normalize_tool_args(
-                    tool_call["function"]["arguments"]
-                )
-
-                # Find the tool definition (fallback to first if only one available)
-                tool_def = next(
-                    (
-                        tool
-                        for tool in tool_functions
-                        if tool["function"]["name"] == tool_name
-                    ),
-                    tool_functions[0] if len(tool_functions) == 1 else None,
-                )
-                if not tool_def:
-                    continue
-
-                # Get field mapping and sink node ID
-                field_mapping = tool_def["function"].get("_field_mapping", {})
-                sink_node_id = tool_def["function"]["_sink_node_id"]
-                expected_args = tool_def["function"]["parameters"].get(
-                    "properties", tool_args.keys()
-                )
-
-                # Yield tool outputs like SmartDecisionMakerBlock
-                for clean_arg_name in expected_args:
-                    original_field_name = field_mapping.get(
-                        clean_arg_name, clean_arg_name
-                    )
-                    arg_value = tool_args.get(clean_arg_name)
-
-                    # Create the same emit key format as SmartDecisionMakerBlock
-                    sanitized_arg_name = self.cleanup(original_field_name)
-                    emit_key = f"tools_^_{sink_node_id}_~_{sanitized_arg_name}"
-
-                    logger.debug(f"Yielding tool output: {emit_key}")
-                    yield emit_key, arg_value
-
-            # Yield conversation and tool results
-            yield (
-                "conversations",
-                [
-                    {
-                        "role": "assistant",
-                        "content": text_content,
-                        "tool_calls": tool_calls,
-                    }
-                ],
-            )
-            yield "tools", tool_calls
-            yield "success", True
-            return
-
-        # If no messages received
-        yield "error", "No response from Claude Agent SDK"
-        yield "success", False
-
-    async def run(
-        self,
-        input_data: Input,
-        *,
-        credentials: APIKeyCredentials,
-        graph_id: str,
-        node_id: str,
-        graph_exec_id: str,
-        node_exec_id: str,
-        user_id: str,
-        graph_version: int,
-        execution_context: ExecutionContext,
-        execution_processor: "ExecutionProcessor",
-        **kwargs,  # Additional execution context parameters
-    ) -> BlockOutput:
-        _ = kwargs  # Suppress unused parameter warning
-        # Validate credentials
-        if credentials.provider != ProviderName.ANTHROPIC:
-            error_msg = f"SmartAgentBlock requires Anthropic/Claude credentials, but received {credentials.provider} credentials. Please configure Anthropic API key credentials."
-            logger.error(error_msg)
-            yield "error", error_msg
-            yield "success", False
-            return
-        # Discover connected AutoGPT tool nodes
-        try:
-            tool_functions = await self._create_tool_node_signatures(node_id)
-        except ValueError as e:
-            if "no next node" in str(e).lower():
-                # Agent can work without tools - just provide Claude with reasoning capability
-                tool_functions = []
-                logger.info("No tools connected - running as pure Claude Agent")
-            else:
-                raise
-
-        yield "tool_functions", json.dumps(tool_functions)
-
-        # Always run Claude Agent SDK in agent mode (iterative execution)
-        async for result in self._execute_tools_agent_mode(
-            input_data=input_data,
-            credentials=credentials,
-            tool_functions=tool_functions,
-            graph_exec_id=graph_exec_id,
-            node_id=node_id,
-            node_exec_id=node_exec_id,
-            user_id=user_id,
-            graph_id=graph_id,
-            graph_version=graph_version,
-            execution_context=execution_context,
-            execution_processor=execution_processor,
-        ):
-            yield result

autogpt_platform/backend/backend/blocks/system/store_operations.py

@@ -1,8 +1,8 @@
 import logging
+from typing import Literal
 
 from pydantic import BaseModel
 
-from backend.api.features.store.db import StoreAgentsSortOptions
 from backend.blocks._base import (
     Block,
     BlockCategory,
@@ -176,8 +176,8 @@ class SearchStoreAgentsBlock(Block):
         category: str | None = SchemaField(
             description="Filter by category", default=None
         )
-        sort_by: StoreAgentsSortOptions = SchemaField(
-            description="How to sort the results", default=StoreAgentsSortOptions.RATING
+        sort_by: Literal["rating", "runs", "name", "updated_at"] = SchemaField(
+            description="How to sort the results", default="rating"
         )
         limit: int = SchemaField(
             description="Maximum number of results to return", default=10, ge=1, le=100
@@ -278,7 +278,7 @@ class SearchStoreAgentsBlock(Block):
         self,
         query: str | None = None,
         category: str | None = None,
-        sort_by: StoreAgentsSortOptions = StoreAgentsSortOptions.RATING,
+        sort_by: Literal["rating", "runs", "name", "updated_at"] = "rating",
         limit: int = 10,
     ) -> SearchAgentsResponse:
         """

autogpt_platform/backend/backend/blocks/test/test_store_operations.py

@@ -2,7 +2,6 @@ from unittest.mock import MagicMock
 
 import pytest
 
-from backend.api.features.store.db import StoreAgentsSortOptions
 from backend.blocks.system.library_operations import (
     AddToLibraryFromStoreBlock,
     LibraryAgent,
@@ -122,10 +121,7 @@ async def test_search_store_agents_block(mocker):
     )
 
     input_data = block.Input(
-        query="test",
-        category="productivity",
-        sort_by=StoreAgentsSortOptions.RATING,  # type: ignore[reportArgumentType]
-        limit=10,
+        query="test", category="productivity", sort_by="rating", limit=10
     )
 
     outputs = {}

autogpt_platform/backend/backend/copilot/baseline/service.py

@@ -22,7 +22,6 @@ from backend.copilot.model import (
     update_session_title,
     upsert_chat_session,
 )
-from backend.copilot.prompting import get_baseline_supplement
 from backend.copilot.response_model import (
     StreamBaseResponse,
     StreamError,
@@ -177,17 +176,14 @@ async def stream_chat_completion_baseline(
     # changes from concurrent chats updating business understanding.
     is_first_turn = len(session.messages) <= 1
     if is_first_turn:
-        base_system_prompt, _ = await _build_system_prompt(
+        system_prompt, _ = await _build_system_prompt(
             user_id, has_conversation_history=False
         )
     else:
-        base_system_prompt, _ = await _build_system_prompt(
+        system_prompt, _ = await _build_system_prompt(
             user_id=None, has_conversation_history=True
         )
 
-    # Append tool documentation and technical notes
-    system_prompt = base_system_prompt + get_baseline_supplement()
-
     # Compress context if approaching the model's token limit
     messages_for_context = await _compress_session_messages(session.messages)
 

autogpt_platform/backend/backend/copilot/prompting.py

@@ -1,191 +0,0 @@
-"""Centralized prompt building logic for CoPilot.
-
-This module contains all prompt construction functions and constants,
-handling the distinction between:
-- SDK mode vs Baseline mode (tool documentation needs)
-- Local mode vs E2B mode (storage/filesystem differences)
-"""
-
-from backend.copilot.tools import TOOL_REGISTRY
-
-# Shared technical notes that apply to both SDK and baseline modes
-_SHARED_TOOL_NOTES = """\
-
-### Sharing files with the user
-After saving a file to the persistent workspace with `write_workspace_file`,
-share it with the user by embedding the `download_url` from the response in
-your message as a Markdown link or image:
-
-- **Any file** — shows as a clickable download link:
-  `[report.csv](workspace://file_id#text/csv)`
-- **Image** — renders inline in chat:
-  `![chart](workspace://file_id#image/png)`
-- **Video** — renders inline in chat with player controls:
-  `![recording](workspace://file_id#video/mp4)`
-
-The `download_url` field in the `write_workspace_file` response is already
-in the correct format — paste it directly after the `(` in the Markdown.
-
-### Sub-agent tasks
-- When using the Task tool, NEVER set `run_in_background` to true.
-  All tasks must run in the foreground.
-"""
-
-
-# Environment-specific supplement templates
-def _build_storage_supplement(
-    working_dir: str,
-    sandbox_type: str,
-    storage_system_1_name: str,
-    storage_system_1_characteristics: list[str],
-    storage_system_1_persistence: list[str],
-    file_move_name_1_to_2: str,
-    file_move_name_2_to_1: str,
-) -> str:
-    """Build storage/filesystem supplement for a specific environment.
-
-    Template function handles all formatting (bullets, indentation, markdown).
-    Callers provide clean data as lists of strings.
-
-    Args:
-        working_dir: Working directory path
-        sandbox_type: Description of bash_exec sandbox
-        storage_system_1_name: Name of primary storage (ephemeral or cloud)
-        storage_system_1_characteristics: List of characteristic descriptions
-        storage_system_1_persistence: List of persistence behavior descriptions
-        file_move_name_1_to_2: Direction label for primary→persistent
-        file_move_name_2_to_1: Direction label for persistent→primary
-    """
-    # Format lists as bullet points with proper indentation
-    characteristics = "\n".join(f"   - {c}" for c in storage_system_1_characteristics)
-    persistence = "\n".join(f"   - {p}" for p in storage_system_1_persistence)
-
-    return f"""
-
-## Tool notes
-
-### Shell commands
-- The SDK built-in Bash tool is NOT available.  Use the `bash_exec` MCP tool
-  for shell commands — it runs {sandbox_type}.
-
-### Working directory
-- Your working directory is: `{working_dir}`
-- All SDK file tools AND `bash_exec` operate on the same filesystem
-- Use relative paths or absolute paths under `{working_dir}` for all file operations
-
-### Two storage systems — CRITICAL to understand
-
-1. **{storage_system_1_name}** (`{working_dir}`):
-{characteristics}
-{persistence}
-
-2. **Persistent workspace** (cloud storage):
-   - Files here **survive across sessions indefinitely**
-
-### Moving files between storages
-- **{file_move_name_1_to_2}**: Copy to persistent workspace
-- **{file_move_name_2_to_1}**: Download for processing
-
-### File persistence
-Important files (code, configs, outputs) should be saved to workspace to ensure they persist.
-{_SHARED_TOOL_NOTES}"""
-
-
-# Pre-built supplements for common environments
-def _get_local_storage_supplement(cwd: str) -> str:
-    """Local ephemeral storage (files lost between turns)."""
-    return _build_storage_supplement(
-        working_dir=cwd,
-        sandbox_type="in a network-isolated sandbox",
-        storage_system_1_name="Ephemeral working directory",
-        storage_system_1_characteristics=[
-            "Shared by SDK Read/Write/Edit/Glob/Grep tools AND `bash_exec`",
-        ],
-        storage_system_1_persistence=[
-            "Files here are **lost between turns** — do NOT rely on them persisting",
-            "Use for temporary work: running scripts, processing data, etc.",
-        ],
-        file_move_name_1_to_2="Ephemeral → Persistent",
-        file_move_name_2_to_1="Persistent → Ephemeral",
-    )
-
-
-def _get_cloud_sandbox_supplement() -> str:
-    """Cloud persistent sandbox (files survive across turns in session)."""
-    return _build_storage_supplement(
-        working_dir="/home/user",
-        sandbox_type="in a cloud sandbox with full internet access",
-        storage_system_1_name="Cloud sandbox",
-        storage_system_1_characteristics=[
-            "Shared by all file tools AND `bash_exec` — same filesystem",
-            "Full Linux environment with internet access",
-        ],
-        storage_system_1_persistence=[
-            "Files **persist across turns** within the current session",
-            "Lost when the session expires (12 h inactivity)",
-        ],
-        file_move_name_1_to_2="Sandbox → Persistent",
-        file_move_name_2_to_1="Persistent → Sandbox",
-    )
-
-
-def _generate_tool_documentation() -> str:
-    """Auto-generate tool documentation from TOOL_REGISTRY.
-
-    NOTE: This is ONLY used in baseline mode (direct OpenAI API).
-    SDK mode doesn't need it since Claude gets tool schemas automatically.
-
-    This generates a complete list of available tools with their descriptions,
-    ensuring the documentation stays in sync with the actual tool implementations.
-    All workflow guidance is now embedded in individual tool descriptions.
-
-    Only documents tools that are available in the current environment
-    (checked via tool.is_available property).
-    """
-    docs = "\n## AVAILABLE TOOLS\n\n"
-
-    # Sort tools alphabetically for consistent output
-    # Filter by is_available to match get_available_tools() behavior
-    for name in sorted(TOOL_REGISTRY.keys()):
-        tool = TOOL_REGISTRY[name]
-        if not tool.is_available:
-            continue
-        schema = tool.as_openai_tool()
-        desc = schema["function"].get("description", "No description available")
-        # Format as bullet list with tool name in code style
-        docs += f"- **`{name}`**: {desc}\n"
-
-    return docs
-
-
-def get_sdk_supplement(use_e2b: bool, cwd: str = "") -> str:
-    """Get the supplement for SDK mode (Claude Agent SDK).
-
-    SDK mode does NOT include tool documentation because Claude automatically
-    receives tool schemas from the SDK. Only includes technical notes about
-    storage systems and execution environment.
-
-    Args:
-        use_e2b: Whether E2B cloud sandbox is being used
-        cwd: Current working directory (only used in local_storage mode)
-
-    Returns:
-        The supplement string to append to the system prompt
-    """
-    if use_e2b:
-        return _get_cloud_sandbox_supplement()
-    return _get_local_storage_supplement(cwd)
-
-
-def get_baseline_supplement() -> str:
-    """Get the supplement for baseline mode (direct OpenAI API).
-
-    Baseline mode INCLUDES auto-generated tool documentation because the
-    direct API doesn't automatically provide tool schemas to Claude.
-    Also includes shared technical notes (but NOT SDK-specific environment details).
-
-    Returns:
-        The supplement string to append to the system prompt
-    """
-    tool_docs = _generate_tool_documentation()
-    return tool_docs + _SHARED_TOOL_NOTES

autogpt_platform/backend/backend/copilot/sdk/service.py

@@ -44,7 +44,6 @@ from ..model import (
     update_session_title,
     upsert_chat_session,
 )
-from ..prompting import get_sdk_supplement
 from ..response_model import (
     StreamBaseResponse,
     StreamError,
@@ -147,6 +146,140 @@ _SDK_CWD_PREFIX = WORKSPACE_PREFIX
 _HEARTBEAT_INTERVAL = 10.0  # seconds
 
 
+# Appended to the system prompt to inform the agent about available tools.
+# The SDK built-in Bash is NOT available — use mcp__copilot__bash_exec instead,
+# which has kernel-level network isolation (unshare --net).
+_SHARED_TOOL_NOTES = """\
+
+### Sharing files with the user
+After saving a file to the persistent workspace with `write_workspace_file`,
+share it with the user by embedding the `download_url` from the response in
+your message as a Markdown link or image:
+
+- **Any file** — shows as a clickable download link:
+  `[report.csv](workspace://file_id#text/csv)`
+- **Image** — renders inline in chat:
+  `![chart](workspace://file_id#image/png)`
+- **Video** — renders inline in chat with player controls:
+  `![recording](workspace://file_id#video/mp4)`
+
+The `download_url` field in the `write_workspace_file` response is already
+in the correct format — paste it directly after the `(` in the Markdown.
+
+### Long-running tools
+Long-running tools (create_agent, edit_agent, etc.) are handled
+asynchronously.  You will receive an immediate response; the actual result
+is delivered to the user via a background stream.
+
+### Large tool outputs
+When a tool output exceeds the display limit, it is automatically saved to
+the persistent workspace.  The truncated output includes a
+`<tool-output-truncated>` tag with the workspace path.  Use
+`read_workspace_file(path="...", offset=N, length=50000)` to retrieve
+additional sections.
+
+### Sub-agent tasks
+- When using the Task tool, NEVER set `run_in_background` to true.
+  All tasks must run in the foreground.
+"""
+
+
+_LOCAL_TOOL_SUPPLEMENT = (
+    """
+
+## Tool notes
+
+### Shell commands
+- The SDK built-in Bash tool is NOT available.  Use the `bash_exec` MCP tool
+  for shell commands — it runs in a network-isolated sandbox.
+
+### Working directory
+- Your working directory is: `{cwd}`
+- All SDK Read/Write/Edit/Glob/Grep tools AND `bash_exec` operate inside this
+  directory.  This is the ONLY writable path — do not attempt to read or write
+  anywhere else on the filesystem.
+- Use relative paths or absolute paths under `{cwd}` for all file operations.
+
+### Two storage systems — CRITICAL to understand
+
+1. **Ephemeral working directory** (`{cwd}`):
+   - Shared by SDK Read/Write/Edit/Glob/Grep tools AND `bash_exec`
+   - Files here are **lost between turns** — do NOT rely on them persisting
+   - Use for temporary work: running scripts, processing data, etc.
+
+2. **Persistent workspace** (cloud storage):
+   - Files here **survive across turns and sessions**
+   - Use `write_workspace_file` to save important files (code, outputs, configs)
+   - Use `read_workspace_file` to retrieve previously saved files
+   - Use `list_workspace_files` to see what files you've saved before
+   - Call `list_workspace_files(include_all_sessions=True)` to see files from
+     all sessions
+
+### Moving files between ephemeral and persistent storage
+- **Ephemeral → Persistent**: Use `write_workspace_file` with either:
+  - `content` param (plain text) — for text files
+  - `source_path` param — to copy any file directly from the ephemeral dir
+- **Persistent → Ephemeral**: Use `read_workspace_file` with `save_to_path`
+  param to download a workspace file to the ephemeral dir for processing
+
+### File persistence workflow
+When you create or modify important files (code, configs, outputs), you MUST:
+1. Save them using `write_workspace_file` so they persist
+2. At the start of a new turn, call `list_workspace_files` to see what files
+   are available from previous turns
+"""
+    + _SHARED_TOOL_NOTES
+)
+
+
+_E2B_TOOL_SUPPLEMENT = (
+    """
+
+## Tool notes
+
+### Shell commands
+- The SDK built-in Bash tool is NOT available.  Use the `bash_exec` MCP tool
+  for shell commands — it runs in a cloud sandbox with full internet access.
+
+### Working directory
+- Your working directory is: `/home/user` (cloud sandbox)
+- All file tools (`read_file`, `write_file`, `edit_file`, `glob`, `grep`)
+  AND `bash_exec` operate on the **same cloud sandbox filesystem**.
+- Files created by `bash_exec` are immediately visible to `read_file` and
+  vice-versa — they share one filesystem.
+- Use relative paths (resolved from `/home/user`) or absolute paths.
+
+### Two storage systems — CRITICAL to understand
+
+1. **Cloud sandbox** (`/home/user`):
+   - Shared by all file tools AND `bash_exec` — same filesystem
+   - Files **persist across turns** within the current session
+   - Full Linux environment with internet access
+   - Lost when the session expires (12 h inactivity)
+
+2. **Persistent workspace** (cloud storage):
+   - Files here **survive across sessions indefinitely**
+   - Use `write_workspace_file` to save important files permanently
+   - Use `read_workspace_file` to retrieve previously saved files
+   - Use `list_workspace_files` to see what files you've saved before
+   - Call `list_workspace_files(include_all_sessions=True)` to see files from
+     all sessions
+
+### Moving files between sandbox and persistent storage
+- **Sandbox → Persistent**: Use `write_workspace_file` with `source_path`
+  to copy from the sandbox to permanent storage
+- **Persistent → Sandbox**: Use `read_workspace_file` with `save_to_path`
+  to download into the sandbox for processing
+
+### File persistence workflow
+Important files that must survive beyond this session should be saved with
+`write_workspace_file`.  Sandbox files persist across turns but are lost
+when the session expires.
+"""
+    + _SHARED_TOOL_NOTES
+)
+
+
 STREAM_LOCK_PREFIX = "copilot:stream:lock:"
 
 
@@ -311,7 +444,6 @@ def _format_sdk_content_blocks(blocks: list) -> list[dict[str, Any]]:
     """Convert SDK content blocks to transcript format.
 
     Handles TextBlock, ToolUseBlock, ToolResultBlock, and ThinkingBlock.
-    Unknown block types are logged and skipped.
     """
     result: list[dict[str, Any]] = []
     for block in blocks or []:
@@ -327,14 +459,13 @@ def _format_sdk_content_blocks(blocks: list) -> list[dict[str, Any]]:
                 }
             )
         elif isinstance(block, ToolResultBlock):
-            tool_result_entry: dict[str, Any] = {
-                "type": "tool_result",
-                "tool_use_id": block.tool_use_id,
-                "content": block.content,
-            }
-            if block.is_error:
-                tool_result_entry["is_error"] = True
-            result.append(tool_result_entry)
+            result.append(
+                {
+                    "type": "tool_result",
+                    "tool_use_id": block.tool_use_id,
+                    "content": block.content,
+                }
+            )
         elif isinstance(block, ThinkingBlock):
             result.append(
                 {
@@ -343,11 +474,6 @@ def _format_sdk_content_blocks(blocks: list) -> list[dict[str, Any]]:
                     "signature": block.signature,
                 }
             )
-        else:
-            logger.warning(
-                f"[SDK] Unknown content block type: {type(block).__name__}. "
-                f"This may indicate a new SDK version with additional block types."
-            )
     return result
 
 
@@ -833,9 +959,10 @@ async def stream_chat_completion_sdk(
         )
 
         use_e2b = e2b_sandbox is not None
-        # Append appropriate supplement (Claude gets tool schemas automatically)
-        system_prompt = base_system_prompt + get_sdk_supplement(
-            use_e2b=use_e2b, cwd=sdk_cwd
+        system_prompt = base_system_prompt + (
+            _E2B_TOOL_SUPPLEMENT
+            if use_e2b
+            else _LOCAL_TOOL_SUPPLEMENT.format(cwd=sdk_cwd)
         )
 
         # Process transcript download result
@@ -853,7 +980,7 @@ async def stream_chat_completion_sdk(
             )
             if is_valid:
                 # Load previous FULL context into builder
-                transcript_builder.load_previous(dl.content, log_prefix=log_prefix)
+                transcript_builder.load_previous(dl.content)
                 resume_file = write_transcript_to_tempfile(
                     dl.content, session_id, sdk_cwd
                 )
@@ -1000,18 +1127,18 @@ async def stream_chat_completion_sdk(
                     json.dumps(user_msg) + "\n"
                 )
                 # Capture user message in transcript (multimodal)
-                transcript_builder.append_user(content=content_blocks)
+                transcript_builder.add_user_message(content=content_blocks)
             else:
                 await client.query(query_message, session_id=session_id)
-                # Capture actual user message in transcript (not the engineered query)
-                # query_message may include context wrappers, but transcript needs raw input
-                transcript_builder.append_user(content=current_message)
+                # Capture user message in transcript (text only)
+                transcript_builder.add_user_message(content=query_message)
 
             assistant_response = ChatMessage(role="assistant", content="")
             accumulated_tool_calls: list[dict[str, Any]] = []
             has_appended_assistant = False
             has_tool_results = False
             ended_with_stream_error = False
+
             # Use an explicit async iterator with non-cancelling heartbeats.
             # CRITICAL: we must NOT cancel __anext__() mid-flight — doing so
             # (via asyncio.timeout or wait_for) corrupts the SDK's internal
@@ -1082,6 +1209,15 @@ async def stream_chat_completion_sdk(
                         len(adapter.resolved_tool_calls),
                     )
 
+                    # Capture AssistantMessage in transcript
+                    if isinstance(sdk_msg, AssistantMessage):
+                        content_blocks = _format_sdk_content_blocks(sdk_msg.content)
+                        model_name = getattr(sdk_msg, "model", "")
+                        transcript_builder.add_assistant_message(
+                            content_blocks=content_blocks,
+                            model=model_name,
+                        )
+
                     # Race-condition fix: SDK hooks (PostToolUse) are
                     # executed asynchronously via start_soon() — the next
                     # message can arrive before the hook stashes output.
@@ -1212,37 +1348,22 @@ async def stream_chat_completion_sdk(
                                 has_appended_assistant = True
 
                         elif isinstance(response, StreamToolOutputAvailable):
-                            content = (
-                                response.output
-                                if isinstance(response.output, str)
-                                else json.dumps(response.output, ensure_ascii=False)
-                            )
                             session.messages.append(
                                 ChatMessage(
                                     role="tool",
-                                    content=content,
+                                    content=(
+                                        response.output
+                                        if isinstance(response.output, str)
+                                        else str(response.output)
+                                    ),
                                     tool_call_id=response.toolCallId,
                                 )
                             )
-                            transcript_builder.append_tool_result(
-                                tool_use_id=response.toolCallId,
-                                content=content,
-                            )
                             has_tool_results = True
 
                         elif isinstance(response, StreamFinish):
                             stream_completed = True
 
-                    # Append assistant entry AFTER convert_message so that
-                    # any stashed tool results from the previous turn are
-                    # recorded first, preserving the required API order:
-                    # assistant(tool_use) → tool_result → assistant(text).
-                    if isinstance(sdk_msg, AssistantMessage):
-                        transcript_builder.append_assistant(
-                            content_blocks=_format_sdk_content_blocks(sdk_msg.content),
-                            model=sdk_msg.model,
-                        )
-
             except asyncio.CancelledError:
                 # Task/generator was cancelled (e.g. client disconnect,
                 # server shutdown).  Log and let the safety-net / finally
@@ -1291,15 +1412,6 @@ async def stream_chat_completion_sdk(
                             type(response).__name__,
                             getattr(response, "toolName", "N/A"),
                         )
-                    if isinstance(response, StreamToolOutputAvailable):
-                        transcript_builder.append_tool_result(
-                            tool_use_id=response.toolCallId,
-                            content=(
-                                response.output
-                                if isinstance(response.output, str)
-                                else json.dumps(response.output, ensure_ascii=False)
-                            ),
-                        )
                     yield response
 
             # If the stream ended without a ResultMessage, the SDK
@@ -1442,10 +1554,8 @@ async def stream_chat_completion_sdk(
                         transcript_builder.entry_count,
                         len(transcript_content),
                     )
-                    # Shield upload from cancellation - let it complete even if
-                    # the finally block is interrupted. No timeout to avoid race
-                    # conditions where backgrounded uploads overwrite newer transcripts.
-                    await asyncio.shield(
+                    # Create task first so we have a reference if timeout occurs
+                    upload_task = asyncio.create_task(
                         upload_transcript(
                             user_id=user_id,
                             session_id=session_id,
@@ -1454,6 +1564,19 @@ async def stream_chat_completion_sdk(
                             log_prefix=log_prefix,
                         )
                     )
+                    try:
+                        async with asyncio.timeout(30):
+                            await asyncio.shield(upload_task)
+                    except TimeoutError:
+                        # Timeout fired but shield keeps upload running - track the
+                        # SAME task to prevent garbage collection (no double upload)
+                        logger.warning(
+                            "%s Transcript upload exceeded 30s timeout, "
+                            "continuing in background",
+                            log_prefix,
+                        )
+                        _background_tasks.add(upload_task)
+                        upload_task.add_done_callback(_background_tasks.discard)
             except Exception as upload_err:
                 logger.error(
                     "%s Transcript upload failed in finally: %s",

autogpt_platform/backend/backend/copilot/sdk/service_test.py

@@ -145,103 +145,3 @@ class TestPrepareFileAttachments:
 
         assert "Read tool" not in result.hint
         assert len(result.image_blocks) == 1
-
-
-class TestPromptSupplement:
-    """Tests for centralized prompt supplement generation."""
-
-    def test_sdk_supplement_excludes_tool_docs(self):
-        """SDK mode should NOT include tool documentation (Claude gets schemas automatically)."""
-        from backend.copilot.prompting import get_sdk_supplement
-
-        # Test both local and E2B modes
-        local_supplement = get_sdk_supplement(use_e2b=False, cwd="/tmp/test")
-        e2b_supplement = get_sdk_supplement(use_e2b=True, cwd="")
-
-        # Should NOT have tool list section
-        assert "## AVAILABLE TOOLS" not in local_supplement
-        assert "## AVAILABLE TOOLS" not in e2b_supplement
-
-        # Should still have technical notes
-        assert "## Tool notes" in local_supplement
-        assert "## Tool notes" in e2b_supplement
-
-    def test_baseline_supplement_includes_tool_docs(self):
-        """Baseline mode MUST include tool documentation (direct API needs it)."""
-        from backend.copilot.prompting import get_baseline_supplement
-
-        supplement = get_baseline_supplement()
-
-        # MUST have tool list section
-        assert "## AVAILABLE TOOLS" in supplement
-
-        # Should NOT have environment-specific notes (SDK-only)
-        assert "## Tool notes" not in supplement
-
-    def test_baseline_supplement_includes_key_tools(self):
-        """Baseline supplement should document all essential tools."""
-        from backend.copilot.prompting import get_baseline_supplement
-        from backend.copilot.tools import TOOL_REGISTRY
-
-        docs = get_baseline_supplement()
-
-        # Core agent workflow tools (always available)
-        assert "`create_agent`" in docs
-        assert "`run_agent`" in docs
-        assert "`find_library_agent`" in docs
-        assert "`edit_agent`" in docs
-
-        # MCP integration (always available)
-        assert "`run_mcp_tool`" in docs
-
-        # Folder management (always available)
-        assert "`create_folder`" in docs
-
-        # Browser tools only if available (Playwright may not be installed in CI)
-        if (
-            TOOL_REGISTRY.get("browser_navigate")
-            and TOOL_REGISTRY["browser_navigate"].is_available
-        ):
-            assert "`browser_navigate`" in docs
-
-    def test_baseline_supplement_includes_workflows(self):
-        """Baseline supplement should include workflow guidance in tool descriptions."""
-        from backend.copilot.prompting import get_baseline_supplement
-
-        docs = get_baseline_supplement()
-
-        # Workflows are now in individual tool descriptions (not separate sections)
-        # Check that key workflow concepts appear in tool descriptions
-        assert "suggested_goal" in docs or "clarifying_questions" in docs
-        assert "run_mcp_tool" in docs
-
-    def test_baseline_supplement_completeness(self):
-        """All available tools from TOOL_REGISTRY should appear in baseline supplement."""
-        from backend.copilot.prompting import get_baseline_supplement
-        from backend.copilot.tools import TOOL_REGISTRY
-
-        docs = get_baseline_supplement()
-
-        # Verify each available registered tool is documented
-        # (matches _generate_tool_documentation which filters by is_available)
-        for tool_name, tool in TOOL_REGISTRY.items():
-            if not tool.is_available:
-                continue
-            assert (
-                f"`{tool_name}`" in docs
-            ), f"Tool '{tool_name}' missing from baseline supplement"
-
-    def test_baseline_supplement_no_duplicate_tools(self):
-        """No tool should appear multiple times in baseline supplement."""
-        from backend.copilot.prompting import get_baseline_supplement
-        from backend.copilot.tools import TOOL_REGISTRY
-
-        docs = get_baseline_supplement()
-
-        # Count occurrences of each available tool in the entire supplement
-        for tool_name, tool in TOOL_REGISTRY.items():
-            if not tool.is_available:
-                continue
-            # Count how many times this tool appears as a bullet point
-            count = docs.count(f"- **`{tool_name}`**")
-            assert count == 1, f"Tool '{tool_name}' appears {count} times (should be 1)"

autogpt_platform/backend/backend/copilot/sdk/transcript.py

@@ -10,14 +10,13 @@ Storage is handled via ``WorkspaceStorageBackend`` (GCS in prod, local
 filesystem for self-hosted) — no DB column needed.
 """
 
+import json
 import logging
 import os
 import re
 import time
 from dataclasses import dataclass
 
-from backend.util import json
-
 logger = logging.getLogger(__name__)
 
 # UUIDs are hex + hyphens; strip everything else to prevent path injection.
@@ -69,14 +68,17 @@ def strip_progress_entries(content: str) -> str:
     # Parse entries, keeping the original line alongside the parsed dict.
     parsed: list[tuple[str, dict | None]] = []
     for line in lines:
-        parsed.append((line, json.loads(line, fallback=None)))
+        try:
+            parsed.append((line, json.loads(line)))
+        except json.JSONDecodeError:
+            parsed.append((line, None))
 
     # First pass: identify stripped UUIDs and build parent map.
     stripped_uuids: set[str] = set()
     uuid_to_parent: dict[str, str] = {}
 
     for _line, entry in parsed:
-        if not isinstance(entry, dict):
+        if entry is None:
             continue
         uid = entry.get("uuid", "")
         parent = entry.get("parentUuid", "")
@@ -89,7 +91,7 @@ def strip_progress_entries(content: str) -> str:
     # Preserve original line when no reparenting is required.
     reparented: set[str] = set()
     for _line, entry in parsed:
-        if not isinstance(entry, dict):
+        if entry is None:
             continue
         parent = entry.get("parentUuid", "")
         original_parent = parent
@@ -103,7 +105,7 @@ def strip_progress_entries(content: str) -> str:
 
     result_lines: list[str] = []
     for line, entry in parsed:
-        if not isinstance(entry, dict):
+        if entry is None:
             result_lines.append(line)
             continue
         if entry.get("type", "") in STRIPPABLE_TYPES:
@@ -223,11 +225,12 @@ def validate_transcript(content: str | None) -> bool:
     for line in lines:
         if not line.strip():
             continue
-        entry = json.loads(line, fallback=None)
-        if not isinstance(entry, dict):
+        try:
+            entry = json.loads(line)
+            if entry.get("type") == "assistant":
+                has_assistant = True
+        except json.JSONDecodeError:
             return False
-        if entry.get("type") == "assistant":
-            has_assistant = True
 
     return has_assistant
 
@@ -307,8 +310,10 @@ async def upload_transcript(
         # Log entry types for debugging — helps identify why validation failed
         entry_types: list[str] = []
         for line in stripped.strip().split("\n"):
-            entry = json.loads(line, fallback={"type": "INVALID_JSON"})
-            entry_types.append(entry.get("type", "?"))
+            try:
+                entry_types.append(json.loads(line).get("type", "?"))
+            except json.JSONDecodeError:
+                entry_types.append("INVALID_JSON")
         logger.warning(
             "%s Skipping upload — stripped content not valid "
             "(types=%s, stripped_len=%d, raw_len=%d)",
@@ -391,10 +396,10 @@ async def download_transcript(
             meta_path = f"local://{mwid}/{mfid}/{mfname}"
 
         meta_data = await storage.retrieve(meta_path)
-        meta = json.loads(meta_data.decode("utf-8"), fallback={})
+        meta = json.loads(meta_data.decode("utf-8"))
         message_count = meta.get("message_count", 0)
         uploaded_at = meta.get("uploaded_at", 0.0)
-    except (FileNotFoundError, Exception):
+    except (FileNotFoundError, json.JSONDecodeError, Exception):
         pass  # No metadata — treat as unknown (msg_count=0 → always fill gap)
 
     logger.info(f"{log_prefix} Downloaded {len(content)}B (msg_count={message_count})")

autogpt_platform/backend/backend/copilot/sdk/transcript_builder.py

@@ -11,16 +11,13 @@ Flow:
 The transcript is never incremental - always the complete atomic state.
 """
 
+import json
 import logging
 from typing import Any
 from uuid import uuid4
 
 from pydantic import BaseModel
 
-from backend.util import json
-
-from .transcript import STRIPPABLE_TYPES
-
 logger = logging.getLogger(__name__)
 
 
@@ -44,16 +41,7 @@ class TranscriptBuilder:
         self._entries: list[TranscriptEntry] = []
         self._last_uuid: str | None = None
 
-    def _last_is_assistant(self) -> bool:
-        return bool(self._entries) and self._entries[-1].type == "assistant"
-
-    def _last_message_id(self) -> str:
-        """Return the message.id of the last entry, or '' if none."""
-        if self._entries:
-            return self._entries[-1].message.get("id", "")
-        return ""
-
-    def load_previous(self, content: str, log_prefix: str = "[Transcript]") -> None:
+    def load_previous(self, content: str) -> None:
         """Load complete previous transcript.
 
         This loads the FULL previous context. As new messages come in,
@@ -63,25 +51,19 @@ class TranscriptBuilder:
         if not content or not content.strip():
             return
 
-        lines = content.strip().split("\n")
-        for line_num, line in enumerate(lines, 1):
+        for line in content.strip().split("\n"):
             if not line.strip():
                 continue
 
-            data = json.loads(line, fallback=None)
-            if data is None:
-                logger.warning(
-                    "%s Failed to parse transcript line %d/%d",
-                    log_prefix,
-                    line_num,
-                    len(lines),
-                )
+            try:
+                data = json.loads(line)
+            except json.JSONDecodeError:
+                logger.warning("Failed to parse transcript line: %s", line[:100])
                 continue
 
-            # Load all non-strippable entries (user/assistant/system/etc.)
-            # Skip only STRIPPABLE_TYPES to match strip_progress_entries() behavior
-            entry_type = data.get("type", "")
-            if entry_type in STRIPPABLE_TYPES:
+            # Only load conversation messages (user/assistant)
+            # Skip metadata entries
+            if data.get("type") not in ("user", "assistant"):
                 continue
 
             entry = TranscriptEntry(
@@ -94,14 +76,15 @@ class TranscriptBuilder:
             self._last_uuid = entry.uuid
 
         logger.info(
-            "%s Loaded %d entries from previous transcript (last_uuid=%s)",
-            log_prefix,
+            "Loaded %d entries from previous transcript (last_uuid=%s)",
             len(self._entries),
             self._last_uuid[:12] if self._last_uuid else None,
         )
 
-    def append_user(self, content: str | list[dict], uuid: str | None = None) -> None:
-        """Append a user entry."""
+    def add_user_message(
+        self, content: str | list[dict], uuid: str | None = None
+    ) -> None:
+        """Add user message to the complete context."""
         msg_uuid = uuid or str(uuid4())
 
         self._entries.append(
@@ -114,34 +97,10 @@ class TranscriptBuilder:
         )
         self._last_uuid = msg_uuid
 
-    def append_tool_result(self, tool_use_id: str, content: str) -> None:
-        """Append a tool result as a user entry (one per tool call)."""
-        self.append_user(
-            content=[
-                {"type": "tool_result", "tool_use_id": tool_use_id, "content": content}
-            ]
-        )
-
-    def append_assistant(
-        self,
-        content_blocks: list[dict],
-        model: str = "",
-        stop_reason: str | None = None,
+    def add_assistant_message(
+        self, content_blocks: list[dict], model: str = ""
     ) -> None:
-        """Append an assistant entry.
-
-        Consecutive assistant entries automatically share the same message ID
-        so the CLI can merge them (thinking → text → tool_use) into a single
-        API message on ``--resume``.  A new ID is assigned whenever an
-        assistant entry follows a non-assistant entry (user message or tool
-        result), because that marks the start of a new API response.
-        """
-        message_id = (
-            self._last_message_id()
-            if self._last_is_assistant()
-            else f"msg_sdk_{uuid4().hex[:24]}"
-        )
-
+        """Add assistant message to the complete context."""
         msg_uuid = str(uuid4())
 
         self._entries.append(
@@ -152,11 +111,7 @@ class TranscriptBuilder:
                 message={
                     "role": "assistant",
                     "model": model,
-                    "id": message_id,
-                    "type": "message",
                     "content": content_blocks,
-                    "stop_reason": stop_reason,
-                    "stop_sequence": None,
                 },
             )
         )
@@ -165,9 +120,6 @@ class TranscriptBuilder:
     def to_jsonl(self) -> str:
         """Export complete context as JSONL.
 
-        Consecutive assistant entries are kept separate to match the
-        native CLI format — the SDK merges them internally on resume.
-
         Returns the FULL conversation state (all entries), not incremental.
         This output REPLACES any previous transcript.
         """

autogpt_platform/backend/backend/copilot/sdk/transcript_test.py

@@ -1,9 +1,8 @@
 """Unit tests for JSONL transcript management utilities."""
 
+import json
 import os
 
-from backend.util import json
-
 from .transcript import (
     STRIPPABLE_TYPES,
     strip_progress_entries,
@@ -257,9 +256,10 @@ class TestStripProgressEntries:
 
     def test_preserves_original_line_formatting(self):
         """Non-reparented entries keep their original JSON formatting."""
-        # orjson produces compact JSON - test that we preserve the exact input
-        # when no reparenting is needed (no re-serialization)
-        original_line = json.dumps(USER_MSG)
+        # Use pretty-printed JSON with spaces (as the CLI produces)
+        original_line = json.dumps(USER_MSG)  # default formatting with spaces
+        compact_line = json.dumps(USER_MSG, separators=(",", ":"))
+        assert original_line != compact_line  # precondition
 
         content = original_line + "\n" + json.dumps(ASST_MSG) + "\n"
         result = strip_progress_entries(content)

autogpt_platform/backend/backend/copilot/service.py

@@ -18,7 +18,7 @@ from langfuse.openai import (
 
 from backend.data.db_accessors import understanding_db
 from backend.data.understanding import format_understanding_for_prompt
-from backend.util.exceptions import NotAuthorizedError, NotFoundError
+from backend.util.exceptions import NotFoundError
 from backend.util.settings import AppEnvironment, Settings
 
 from .config import ChatConfig
@@ -34,9 +34,8 @@ client = LangfuseAsyncOpenAI(api_key=config.api_key, base_url=config.base_url)
 langfuse = get_client()
 
 # Default system prompt used when Langfuse is not configured
-# Provides minimal baseline tone and personality - all workflow, tools, and
-# technical details are provided via the supplement.
-DEFAULT_SYSTEM_PROMPT = """You are an AI automation assistant helping users build and run automations.
+# This is a snapshot of the "CoPilot Prompt" from Langfuse (version 11)
+DEFAULT_SYSTEM_PROMPT = """You are **Otto**, an AI Co-Pilot for AutoGPT and a Forward-Deployed Automation Engineer serving small business owners. Your mission is to help users automate business tasks with AI by delivering tangible value through working automations—not through documentation or lengthy explanations.
 
 Here is everything you know about the current user from previous interactions:
 
@@ -44,12 +43,113 @@ Here is everything you know about the current user from previous interactions:
 {users_information}
 </users_information>
 
-Your goal is to help users automate tasks by:
-- Understanding their needs and business context
-- Building and running working automations
-- Delivering tangible value through action, not just explanation
+## YOUR CORE MANDATE
 
-Be concise, proactive, and action-oriented. Bias toward showing working solutions over lengthy explanations."""
+You are action-oriented. Your success is measured by:
+- **Value Delivery**: Does the user think "wow, that was amazing" or "what was the point"?
+- **Demonstrable Proof**: Show working automations, not descriptions of what's possible
+- **Time Saved**: Focus on tangible efficiency gains
+- **Quality Output**: Deliver results that meet or exceed expectations
+
+## YOUR WORKFLOW
+
+Adapt flexibly to the conversation context. Not every interaction requires all stages:
+
+1. **Explore & Understand**: Learn about the user's business, tasks, and goals. Use `add_understanding` to capture important context that will improve future conversations.
+
+2. **Assess Automation Potential**: Help the user understand whether and how AI can automate their task.
+
+3. **Prepare for AI**: Provide brief, actionable guidance on prerequisites (data, access, etc.).
+
+4. **Discover or Create Agents**:
+   - **Always check the user's library first** with `find_library_agent` (these may be customized to their needs)
+   - Search the marketplace with `find_agent` for pre-built automations
+   - Find reusable components with `find_block`
+   - **For live integrations** (read a GitHub repo, query a database, post to Slack, etc.) consider `run_mcp_tool` — it connects directly to external services without building a full agent
+   - Create custom solutions with `create_agent` if nothing suitable exists
+   - Modify existing library agents with `edit_agent`
+   - **When `create_agent` returns `suggested_goal`**: Present the suggestion to the user and ask "Would you like me to proceed with this refined goal?" If they accept, call `create_agent` again with the suggested goal.
+   - **When `create_agent` returns `clarifying_questions`**: After the user answers, call `create_agent` again with the original description AND the answers in the `context` parameter.
+
+5. **Execute**: Run automations immediately, schedule them, or set up webhooks using `run_agent`. Test specific components with `run_block`.
+
+6. **Show Results**: Display outputs using `agent_output`.
+
+## AVAILABLE TOOLS
+
+**Understanding & Discovery:**
+- `add_understanding`: Create a memory about the user's business or use cases for future sessions
+- `search_docs`: Search platform documentation for specific technical information
+- `get_doc_page`: Retrieve full text of a specific documentation page
+
+**Agent Discovery:**
+- `find_library_agent`: Search the user's existing agents (CHECK HERE FIRST—these may be customized)
+- `find_agent`: Search the marketplace for pre-built automations
+- `find_block`: Find pre-written code units that perform specific tasks (agents are built from blocks)
+
+**Agent Creation & Editing:**
+- `create_agent`: Create a new automation agent
+- `edit_agent`: Modify an agent in the user's library
+
+**Execution & Output:**
+- `run_agent`: Run an agent now, schedule it, or set up a webhook trigger
+- `run_block`: Test or run a specific block independently
+- `agent_output`: View results from previous agent runs
+
+**MCP (Model Context Protocol) Servers:**
+- `run_mcp_tool`: Connect to any MCP server to discover and run its tools
+
+  **Two-step flow:**
+  1. `run_mcp_tool(server_url)` → returns a list of available tools. Each tool has `name`, `description`, and `input_schema` (JSON Schema). Read `input_schema.properties` to understand what arguments are needed.
+  2. `run_mcp_tool(server_url, tool_name, tool_arguments)` → executes the tool. Build `tool_arguments` as a flat `{{key: value}}` object matching the tool's `input_schema.properties`.
+
+  **Authentication:** If the MCP server requires credentials, the UI will show an OAuth connect button. Once the user connects and clicks Proceed, they will automatically send you a message confirming credentials are ready (e.g. "I've connected the MCP server credentials. Please retry run_mcp_tool..."). When you receive that confirmation, **immediately** call `run_mcp_tool` again with the exact same `server_url` — and the same `tool_name`/`tool_arguments` if you were already mid-execution. Do not ask the user what to do next; just retry.
+
+  **Finding server URLs (fastest → slowest):**
+  1. **Known hosted servers** — use directly, no lookup:
+     - Notion: `https://mcp.notion.com/mcp`
+     - Linear: `https://mcp.linear.app/mcp`
+     - Stripe: `https://mcp.stripe.com`
+     - Intercom: `https://mcp.intercom.com/mcp`
+     - Cloudflare: `https://mcp.cloudflare.com/mcp`
+     - Atlassian (Jira/Confluence): `https://mcp.atlassian.com/mcp`
+  2. **`web_search`** — use `web_search("{{service}} MCP server URL")` for any service not in the list above. This is the fastest way to find unlisted servers.
+  3. **Registry API** — `web_fetch("https://registry.modelcontextprotocol.io/v0.1/servers?search={{query}}&limit=10")` to browse what's available. Returns names + GitHub repo URLs but NOT the endpoint URL; follow up with `web_search` to find the actual endpoint.
+  - **Never** `web_fetch` the registry homepage — it is JavaScript-rendered and returns a blank page.
+
+  **When to use:** Use `run_mcp_tool` when the user wants to interact with an external service (GitHub, Slack, a database, a SaaS tool, etc.) via its MCP integration. Unlike `web_fetch` (which just retrieves a raw URL), MCP servers expose structured typed tools — prefer `run_mcp_tool` for any service with an MCP server, and `web_fetch` only for plain URL retrieval with no MCP server involved.
+
+  **CRITICAL**: `run_mcp_tool` is **always available** in your tool list. If the user explicitly provides an MCP server URL or asks you to call `run_mcp_tool`, you MUST use it — never claim it is unavailable, and never substitute `web_fetch` for an explicit MCP request.
+
+## BEHAVIORAL GUIDELINES
+
+**Be Concise:**
+- Target 2-5 short lines maximum
+- Make every word count—no repetition or filler
+- Use lightweight structure for scannability (bullets, numbered lists, short prompts)
+- Avoid jargon (blocks, slugs, cron) unless the user asks
+
+**Be Proactive:**
+- Suggest next steps before being asked
+- Anticipate needs based on conversation context and user information
+- Look for opportunities to expand scope when relevant
+- Reveal capabilities through action, not explanation
+
+**Use Tools Effectively:**
+- Select the right tool for each task
+- **Always check `find_library_agent` before searching the marketplace**
+- Use `add_understanding` to capture valuable business context
+- When tool calls fail, try alternative approaches
+- **For MCP integrations**: Known URL (see list) or `web_search("{{service}} MCP server URL")` → `run_mcp_tool(server_url)` → `run_mcp_tool(server_url, tool_name, tool_arguments)`. If credentials needed, UI prompts automatically; when user confirms, retry immediately with same arguments.
+
+**Handle Feedback Loops:**
+- When a tool returns a suggested alternative (like a refined goal), present it clearly and ask the user for confirmation before proceeding
+- When clarifying questions are answered, immediately re-call the tool with the accumulated context
+- Don't ask redundant questions if the user has already provided context in the conversation
+
+## CRITICAL REMINDER
+
+You are NOT a chatbot. You are NOT documentation. You are a partner who helps busy business owners get value quickly by showing proof through working automations. Bias toward action over explanation."""
 
 
 # ---------------------------------------------------------------------------
@@ -198,12 +298,6 @@ async def assign_user_to_session(
     session = await get_chat_session(session_id, None)
     if not session:
         raise NotFoundError(f"Session {session_id} not found")
-    if session.user_id is not None and session.user_id != user_id:
-        logger.warning(
-            f"[SECURITY] Attempt to claim session {session_id} by user {user_id}, "
-            f"but it already belongs to user {session.user_id}"
-        )
-        raise NotAuthorizedError(f"Not authorized to claim session {session_id}")
     session.user_id = user_id
     session = await upsert_chat_session(session)
     return session

autogpt_platform/backend/backend/copilot/tools/__init__.py

@@ -20,14 +20,6 @@ from .find_agent import FindAgentTool
 from .find_block import FindBlockTool
 from .find_library_agent import FindLibraryAgentTool
 from .get_doc_page import GetDocPageTool
-from .manage_folders import (
-    CreateFolderTool,
-    DeleteFolderTool,
-    ListFoldersTool,
-    MoveAgentsToFolderTool,
-    MoveFolderTool,
-    UpdateFolderTool,
-)
 from .run_agent import RunAgentTool
 from .run_block import RunBlockTool
 from .run_mcp_tool import RunMCPToolTool
@@ -55,13 +47,6 @@ TOOL_REGISTRY: dict[str, BaseTool] = {
     "find_agent": FindAgentTool(),
     "find_block": FindBlockTool(),
     "find_library_agent": FindLibraryAgentTool(),
-    # Folder management tools
-    "create_folder": CreateFolderTool(),
-    "list_folders": ListFoldersTool(),
-    "update_folder": UpdateFolderTool(),
-    "move_folder": MoveFolderTool(),
-    "delete_folder": DeleteFolderTool(),
-    "move_agents_to_folder": MoveAgentsToFolderTool(),
     "run_agent": RunAgentTool(),
     "run_block": RunBlockTool(),
     "run_mcp_tool": RunMCPToolTool(),

autogpt_platform/backend/backend/copilot/tools/_test_data.py

@@ -151,8 +151,8 @@ async def setup_test_data(server):
     unique_slug = f"test-agent-{str(uuid.uuid4())[:8]}"
     store_submission = await store_db.create_store_submission(
         user_id=user.id,
-        graph_id=created_graph.id,
-        graph_version=created_graph.version,
+        agent_id=created_graph.id,
+        agent_version=created_graph.version,
         slug=unique_slug,
         name="Test Agent",
         description="A simple test agent",
@@ -161,10 +161,10 @@ async def setup_test_data(server):
         image_urls=["https://example.com/image.jpg"],
     )
 
-    assert store_submission.listing_version_id is not None
+    assert store_submission.store_listing_version_id is not None
     # 4. Approve the store listing version
     await store_db.review_store_submission(
-        store_listing_version_id=store_submission.listing_version_id,
+        store_listing_version_id=store_submission.store_listing_version_id,
         is_approved=True,
         external_comments="Approved for testing",
         internal_comments="Test approval",
@@ -321,8 +321,8 @@ async def setup_llm_test_data(server):
     unique_slug = f"llm-test-agent-{str(uuid.uuid4())[:8]}"
     store_submission = await store_db.create_store_submission(
         user_id=user.id,
-        graph_id=created_graph.id,
-        graph_version=created_graph.version,
+        agent_id=created_graph.id,
+        agent_version=created_graph.version,
         slug=unique_slug,
         name="LLM Test Agent",
         description="An agent with LLM capabilities",
@@ -330,9 +330,9 @@ async def setup_llm_test_data(server):
         categories=["testing", "ai"],
         image_urls=["https://example.com/image.jpg"],
     )
-    assert store_submission.listing_version_id is not None
+    assert store_submission.store_listing_version_id is not None
     await store_db.review_store_submission(
-        store_listing_version_id=store_submission.listing_version_id,
+        store_listing_version_id=store_submission.store_listing_version_id,
         is_approved=True,
         external_comments="Approved for testing",
         internal_comments="Test approval for LLM agent",
@@ -476,8 +476,8 @@ async def setup_firecrawl_test_data(server):
     unique_slug = f"firecrawl-test-agent-{str(uuid.uuid4())[:8]}"
     store_submission = await store_db.create_store_submission(
         user_id=user.id,
-        graph_id=created_graph.id,
-        graph_version=created_graph.version,
+        agent_id=created_graph.id,
+        agent_version=created_graph.version,
         slug=unique_slug,
         name="Firecrawl Test Agent",
         description="An agent with Firecrawl integration (no credentials)",
@@ -485,9 +485,9 @@ async def setup_firecrawl_test_data(server):
         categories=["testing", "scraping"],
         image_urls=["https://example.com/image.jpg"],
     )
-    assert store_submission.listing_version_id is not None
+    assert store_submission.store_listing_version_id is not None
     await store_db.review_store_submission(
-        store_listing_version_id=store_submission.listing_version_id,
+        store_listing_version_id=store_submission.store_listing_version_id,
         is_approved=True,
         external_comments="Approved for testing",
         internal_comments="Test approval for Firecrawl agent",

autogpt_platform/backend/backend/copilot/tools/agent_generator/core.py

@@ -695,10 +695,7 @@ def json_to_graph(agent_json: dict[str, Any]) -> Graph:
 
 
 async def save_agent_to_library(
-    agent_json: dict[str, Any],
-    user_id: str,
-    is_update: bool = False,
-    folder_id: str | None = None,
+    agent_json: dict[str, Any], user_id: str, is_update: bool = False
 ) -> tuple[Graph, Any]:
     """Save agent to database and user's library.
 
@@ -706,7 +703,6 @@ async def save_agent_to_library(
         agent_json: Agent JSON dict
         user_id: User ID
         is_update: Whether this is an update to an existing agent
-        folder_id: Optional folder ID to place the agent in
 
     Returns:
         Tuple of (created Graph, LibraryAgent)
@@ -715,7 +711,7 @@ async def save_agent_to_library(
     db = library_db()
     if is_update:
         return await db.update_graph_in_library(graph, user_id)
-    return await db.create_graph_in_library(graph, user_id, folder_id=folder_id)
+    return await db.create_graph_in_library(graph, user_id)
 
 
 def graph_to_json(graph: Graph) -> dict[str, Any]:

autogpt_platform/backend/backend/copilot/tools/create_agent.py

@@ -39,13 +39,9 @@ class CreateAgentTool(BaseTool):
         return (
             "Create a new agent workflow from a natural language description. "
             "First generates a preview, then saves to library if save=true. "
-            "\n\nWorkflow: (1) Always check find_library_agent first for existing building blocks. "
-            "(2) Call create_agent with description and library_agent_ids. "
-            "(3) If response contains suggested_goal: Present to user, ask for confirmation, "
-            "then call again with the suggested goal if accepted. "
-            "(4) If response contains clarifying_questions: Present to user, collect answers, "
-            "then call again with original description AND answers in the context parameter. "
-            "\n\nThis feedback loop ensures the generated agent matches user intent."
+            "\n\nIMPORTANT: Before calling this tool, search for relevant existing agents "
+            "using find_library_agent that could be used as building blocks. "
+            "Pass their IDs in the library_agent_ids parameter so the generator can compose them."
         )
 
     @property
@@ -88,14 +84,6 @@ class CreateAgentTool(BaseTool):
                     ),
                     "default": True,
                 },
-                "folder_id": {
-                    "type": "string",
-                    "description": (
-                        "Optional folder ID to save the agent into. "
-                        "If not provided, the agent is saved at root level. "
-                        "Use list_folders to find available folders."
-                    ),
-                },
             },
             "required": ["description"],
         }
@@ -117,7 +105,6 @@ class CreateAgentTool(BaseTool):
         context = kwargs.get("context", "")
         library_agent_ids = kwargs.get("library_agent_ids", [])
         save = kwargs.get("save", True)
-        folder_id = kwargs.get("folder_id")
         session_id = session.session_id if session else None
 
         logger.info(
@@ -349,7 +336,7 @@ class CreateAgentTool(BaseTool):
 
         try:
             created_graph, library_agent = await save_agent_to_library(
-                agent_json, user_id, folder_id=folder_id
+                agent_json, user_id
             )
 
             logger.info(

autogpt_platform/backend/backend/copilot/tools/customize_agent.py

@@ -3,9 +3,9 @@
 import logging
 from typing import Any
 
+from backend.api.features.store.exceptions import AgentNotFoundError
 from backend.copilot.model import ChatSession
 from backend.data.db_accessors import store_db as get_store_db
-from backend.util.exceptions import NotFoundError
 
 from .agent_generator import (
     AgentGeneratorNotConfiguredError,
@@ -80,14 +80,6 @@ class CustomizeAgentTool(BaseTool):
                     ),
                     "default": True,
                 },
-                "folder_id": {
-                    "type": "string",
-                    "description": (
-                        "Optional folder ID to save the agent into. "
-                        "If not provided, the agent is saved at root level. "
-                        "Use list_folders to find available folders."
-                    ),
-                },
             },
             "required": ["agent_id", "modifications"],
         }
@@ -110,7 +102,6 @@ class CustomizeAgentTool(BaseTool):
         modifications = kwargs.get("modifications", "").strip()
         context = kwargs.get("context", "")
         save = kwargs.get("save", True)
-        folder_id = kwargs.get("folder_id")
         session_id = session.session_id if session else None
 
         if not agent_id:
@@ -149,7 +140,7 @@ class CustomizeAgentTool(BaseTool):
             agent_details = await store_db.get_store_agent_details(
                 username=creator_username, agent_name=agent_slug
             )
-        except NotFoundError:
+        except AgentNotFoundError:
             return ErrorResponse(
                 message=(
                     f"Could not find marketplace agent '{agent_id}'. "
@@ -319,7 +310,7 @@ class CustomizeAgentTool(BaseTool):
         # Save to user's library
         try:
             created_graph, library_agent = await save_agent_to_library(
-                customized_agent, user_id, is_update=False, folder_id=folder_id
+                customized_agent, user_id, is_update=False
             )
 
             return AgentSavedResponse(

autogpt_platform/backend/backend/copilot/tools/manage_folders.py

@@ -1,573 +0,0 @@
-"""Folder management tools for the copilot."""
-
-from typing import Any
-
-from backend.api.features.library import model as library_model
-from backend.api.features.library.db import collect_tree_ids
-from backend.copilot.model import ChatSession
-from backend.data.db_accessors import library_db
-
-from .base import BaseTool
-from .models import (
-    AgentsMovedToFolderResponse,
-    ErrorResponse,
-    FolderAgentSummary,
-    FolderCreatedResponse,
-    FolderDeletedResponse,
-    FolderInfo,
-    FolderListResponse,
-    FolderMovedResponse,
-    FolderTreeInfo,
-    FolderUpdatedResponse,
-    ToolResponseBase,
-)
-
-
-def _folder_to_info(
-    folder: library_model.LibraryFolder,
-    agents: list[FolderAgentSummary] | None = None,
-) -> FolderInfo:
-    """Convert a LibraryFolder DB model to a FolderInfo response model."""
-    return FolderInfo(
-        id=folder.id,
-        name=folder.name,
-        parent_id=folder.parent_id,
-        icon=folder.icon,
-        color=folder.color,
-        agent_count=folder.agent_count,
-        subfolder_count=folder.subfolder_count,
-        agents=agents,
-    )
-
-
-def _tree_to_info(
-    tree: library_model.LibraryFolderTree,
-    agents_map: dict[str, list[FolderAgentSummary]] | None = None,
-) -> FolderTreeInfo:
-    """Recursively convert a LibraryFolderTree to a FolderTreeInfo response."""
-    return FolderTreeInfo(
-        id=tree.id,
-        name=tree.name,
-        parent_id=tree.parent_id,
-        icon=tree.icon,
-        color=tree.color,
-        agent_count=tree.agent_count,
-        subfolder_count=tree.subfolder_count,
-        children=[_tree_to_info(child, agents_map) for child in tree.children],
-        agents=agents_map.get(tree.id) if agents_map else None,
-    )
-
-
-def _to_agent_summaries(
-    raw: list[dict[str, str | None]],
-) -> list[FolderAgentSummary]:
-    """Convert raw agent dicts to typed FolderAgentSummary models."""
-    return [
-        FolderAgentSummary(
-            id=a["id"] or "",
-            name=a["name"] or "",
-            description=a["description"] or "",
-        )
-        for a in raw
-    ]
-
-
-def _to_agent_summaries_map(
-    raw: dict[str, list[dict[str, str | None]]],
-) -> dict[str, list[FolderAgentSummary]]:
-    """Convert a folder-id-keyed dict of raw agents to typed summaries."""
-    return {fid: _to_agent_summaries(agents) for fid, agents in raw.items()}
-
-
-class CreateFolderTool(BaseTool):
-    """Tool for creating a library folder."""
-
-    @property
-    def name(self) -> str:
-        return "create_folder"
-
-    @property
-    def description(self) -> str:
-        return (
-            "Create a new folder in the user's library to organize agents. "
-            "Optionally nest it inside an existing folder using parent_id."
-        )
-
-    @property
-    def requires_auth(self) -> bool:
-        return True
-
-    @property
-    def parameters(self) -> dict[str, Any]:
-        return {
-            "type": "object",
-            "properties": {
-                "name": {
-                    "type": "string",
-                    "description": "Name for the new folder (max 100 chars).",
-                },
-                "parent_id": {
-                    "type": "string",
-                    "description": (
-                        "ID of the parent folder to nest inside. "
-                        "Omit to create at root level."
-                    ),
-                },
-                "icon": {
-                    "type": "string",
-                    "description": "Optional icon identifier for the folder.",
-                },
-                "color": {
-                    "type": "string",
-                    "description": "Optional hex color code (#RRGGBB).",
-                },
-            },
-            "required": ["name"],
-        }
-
-    async def _execute(
-        self, user_id: str | None, session: ChatSession, **kwargs
-    ) -> ToolResponseBase:
-        """Create a folder with the given name and optional parent/icon/color."""
-        assert user_id is not None  # guaranteed by requires_auth
-        name = (kwargs.get("name") or "").strip()
-        parent_id = kwargs.get("parent_id")
-        icon = kwargs.get("icon")
-        color = kwargs.get("color")
-        session_id = session.session_id if session else None
-
-        if not name:
-            return ErrorResponse(
-                message="Please provide a folder name.",
-                error="missing_name",
-                session_id=session_id,
-            )
-
-        try:
-            folder = await library_db().create_folder(
-                user_id=user_id,
-                name=name,
-                parent_id=parent_id,
-                icon=icon,
-                color=color,
-            )
-        except Exception as e:
-            return ErrorResponse(
-                message=f"Failed to create folder: {e}",
-                error="create_folder_failed",
-                session_id=session_id,
-            )
-
-        return FolderCreatedResponse(
-            message=f"Folder '{folder.name}' created successfully!",
-            folder=_folder_to_info(folder),
-            session_id=session_id,
-        )
-
-
-class ListFoldersTool(BaseTool):
-    """Tool for listing library folders."""
-
-    @property
-    def name(self) -> str:
-        return "list_folders"
-
-    @property
-    def description(self) -> str:
-        return (
-            "List the user's library folders. "
-            "Omit parent_id to get the full folder tree. "
-            "Provide parent_id to list only direct children of that folder. "
-            "Set include_agents=true to also return the agents inside each folder "
-            "and root-level agents not in any folder. Always set include_agents=true "
-            "when the user asks about agents, wants to see what's in their folders, "
-            "or mentions agents alongside folders."
-        )
-
-    @property
-    def requires_auth(self) -> bool:
-        return True
-
-    @property
-    def parameters(self) -> dict[str, Any]:
-        return {
-            "type": "object",
-            "properties": {
-                "parent_id": {
-                    "type": "string",
-                    "description": (
-                        "List children of this folder. "
-                        "Omit to get the full folder tree."
-                    ),
-                },
-                "include_agents": {
-                    "type": "boolean",
-                    "description": (
-                        "Whether to include the list of agents inside each folder. "
-                        "Defaults to false."
-                    ),
-                },
-            },
-            "required": [],
-        }
-
-    async def _execute(
-        self, user_id: str | None, session: ChatSession, **kwargs
-    ) -> ToolResponseBase:
-        """List folders as a flat list (by parent) or full tree."""
-        assert user_id is not None  # guaranteed by requires_auth
-        parent_id = kwargs.get("parent_id")
-        include_agents = kwargs.get("include_agents", False)
-        session_id = session.session_id if session else None
-
-        try:
-            if parent_id:
-                folders = await library_db().list_folders(
-                    user_id=user_id, parent_id=parent_id
-                )
-                raw_map = (
-                    await library_db().get_folder_agents_map(
-                        user_id, [f.id for f in folders]
-                    )
-                    if include_agents
-                    else None
-                )
-                agents_map = _to_agent_summaries_map(raw_map) if raw_map else None
-                return FolderListResponse(
-                    message=f"Found {len(folders)} folder(s).",
-                    folders=[
-                        _folder_to_info(f, agents_map.get(f.id) if agents_map else None)
-                        for f in folders
-                    ],
-                    count=len(folders),
-                    session_id=session_id,
-                )
-            else:
-                tree = await library_db().get_folder_tree(user_id=user_id)
-                all_ids = collect_tree_ids(tree)
-                agents_map = None
-                root_agents = None
-                if include_agents:
-                    raw_map = await library_db().get_folder_agents_map(user_id, all_ids)
-                    agents_map = _to_agent_summaries_map(raw_map)
-                    root_agents = _to_agent_summaries(
-                        await library_db().get_root_agent_summaries(user_id)
-                    )
-                return FolderListResponse(
-                    message=f"Found {len(all_ids)} folder(s) in your library.",
-                    tree=[_tree_to_info(t, agents_map) for t in tree],
-                    root_agents=root_agents,
-                    count=len(all_ids),
-                    session_id=session_id,
-                )
-        except Exception as e:
-            return ErrorResponse(
-                message=f"Failed to list folders: {e}",
-                error="list_folders_failed",
-                session_id=session_id,
-            )
-
-
-class UpdateFolderTool(BaseTool):
-    """Tool for updating a folder's properties."""
-
-    @property
-    def name(self) -> str:
-        return "update_folder"
-
-    @property
-    def description(self) -> str:
-        return "Update a folder's name, icon, or color."
-
-    @property
-    def requires_auth(self) -> bool:
-        return True
-
-    @property
-    def parameters(self) -> dict[str, Any]:
-        return {
-            "type": "object",
-            "properties": {
-                "folder_id": {
-                    "type": "string",
-                    "description": "ID of the folder to update.",
-                },
-                "name": {
-                    "type": "string",
-                    "description": "New name for the folder.",
-                },
-                "icon": {
-                    "type": "string",
-                    "description": "New icon identifier.",
-                },
-                "color": {
-                    "type": "string",
-                    "description": "New hex color code (#RRGGBB).",
-                },
-            },
-            "required": ["folder_id"],
-        }
-
-    async def _execute(
-        self, user_id: str | None, session: ChatSession, **kwargs
-    ) -> ToolResponseBase:
-        """Update a folder's name, icon, or color."""
-        assert user_id is not None  # guaranteed by requires_auth
-        folder_id = (kwargs.get("folder_id") or "").strip()
-        name = kwargs.get("name")
-        icon = kwargs.get("icon")
-        color = kwargs.get("color")
-        session_id = session.session_id if session else None
-
-        if not folder_id:
-            return ErrorResponse(
-                message="Please provide a folder_id.",
-                error="missing_folder_id",
-                session_id=session_id,
-            )
-
-        try:
-            folder = await library_db().update_folder(
-                folder_id=folder_id,
-                user_id=user_id,
-                name=name,
-                icon=icon,
-                color=color,
-            )
-        except Exception as e:
-            return ErrorResponse(
-                message=f"Failed to update folder: {e}",
-                error="update_folder_failed",
-                session_id=session_id,
-            )
-
-        return FolderUpdatedResponse(
-            message=f"Folder updated to '{folder.name}'.",
-            folder=_folder_to_info(folder),
-            session_id=session_id,
-        )
-
-
-class MoveFolderTool(BaseTool):
-    """Tool for moving a folder to a new parent."""
-
-    @property
-    def name(self) -> str:
-        return "move_folder"
-
-    @property
-    def description(self) -> str:
-        return (
-            "Move a folder to a different parent folder. "
-            "Set target_parent_id to null to move to root level."
-        )
-
-    @property
-    def requires_auth(self) -> bool:
-        return True
-
-    @property
-    def parameters(self) -> dict[str, Any]:
-        return {
-            "type": "object",
-            "properties": {
-                "folder_id": {
-                    "type": "string",
-                    "description": "ID of the folder to move.",
-                },
-                "target_parent_id": {
-                    "type": ["string", "null"],
-                    "description": (
-                        "ID of the new parent folder. "
-                        "Use null to move to root level."
-                    ),
-                },
-            },
-            "required": ["folder_id"],
-        }
-
-    async def _execute(
-        self, user_id: str | None, session: ChatSession, **kwargs
-    ) -> ToolResponseBase:
-        """Move a folder to a new parent or to root level."""
-        assert user_id is not None  # guaranteed by requires_auth
-        folder_id = (kwargs.get("folder_id") or "").strip()
-        target_parent_id = kwargs.get("target_parent_id")
-        session_id = session.session_id if session else None
-
-        if not folder_id:
-            return ErrorResponse(
-                message="Please provide a folder_id.",
-                error="missing_folder_id",
-                session_id=session_id,
-            )
-
-        try:
-            folder = await library_db().move_folder(
-                folder_id=folder_id,
-                user_id=user_id,
-                target_parent_id=target_parent_id,
-            )
-        except Exception as e:
-            return ErrorResponse(
-                message=f"Failed to move folder: {e}",
-                error="move_folder_failed",
-                session_id=session_id,
-            )
-
-        dest = "a subfolder" if target_parent_id else "root level"
-        return FolderMovedResponse(
-            message=f"Folder '{folder.name}' moved to {dest}.",
-            folder=_folder_to_info(folder),
-            target_parent_id=target_parent_id,
-            session_id=session_id,
-        )
-
-
-class DeleteFolderTool(BaseTool):
-    """Tool for deleting a folder."""
-
-    @property
-    def name(self) -> str:
-        return "delete_folder"
-
-    @property
-    def description(self) -> str:
-        return (
-            "Delete a folder from the user's library. "
-            "Agents inside the folder are moved to root level (not deleted)."
-        )
-
-    @property
-    def requires_auth(self) -> bool:
-        return True
-
-    @property
-    def parameters(self) -> dict[str, Any]:
-        return {
-            "type": "object",
-            "properties": {
-                "folder_id": {
-                    "type": "string",
-                    "description": "ID of the folder to delete.",
-                },
-            },
-            "required": ["folder_id"],
-        }
-
-    async def _execute(
-        self, user_id: str | None, session: ChatSession, **kwargs
-    ) -> ToolResponseBase:
-        """Soft-delete a folder; agents inside are moved to root level."""
-        assert user_id is not None  # guaranteed by requires_auth
-        folder_id = (kwargs.get("folder_id") or "").strip()
-        session_id = session.session_id if session else None
-
-        if not folder_id:
-            return ErrorResponse(
-                message="Please provide a folder_id.",
-                error="missing_folder_id",
-                session_id=session_id,
-            )
-
-        try:
-            await library_db().delete_folder(
-                folder_id=folder_id,
-                user_id=user_id,
-                soft_delete=True,
-            )
-        except Exception as e:
-            return ErrorResponse(
-                message=f"Failed to delete folder: {e}",
-                error="delete_folder_failed",
-                session_id=session_id,
-            )
-
-        return FolderDeletedResponse(
-            message="Folder deleted. Any agents inside were moved to root level.",
-            folder_id=folder_id,
-            session_id=session_id,
-        )
-
-
-class MoveAgentsToFolderTool(BaseTool):
-    """Tool for moving agents into a folder."""
-
-    @property
-    def name(self) -> str:
-        return "move_agents_to_folder"
-
-    @property
-    def description(self) -> str:
-        return (
-            "Move one or more agents to a folder. "
-            "Set folder_id to null to move agents to root level."
-        )
-
-    @property
-    def requires_auth(self) -> bool:
-        return True
-
-    @property
-    def parameters(self) -> dict[str, Any]:
-        return {
-            "type": "object",
-            "properties": {
-                "agent_ids": {
-                    "type": "array",
-                    "items": {"type": "string"},
-                    "description": "List of library agent IDs to move.",
-                },
-                "folder_id": {
-                    "type": ["string", "null"],
-                    "description": (
-                        "Target folder ID. Use null to move to root level."
-                    ),
-                },
-            },
-            "required": ["agent_ids"],
-        }
-
-    async def _execute(
-        self, user_id: str | None, session: ChatSession, **kwargs
-    ) -> ToolResponseBase:
-        """Move one or more agents to a folder or to root level."""
-        assert user_id is not None  # guaranteed by requires_auth
-        agent_ids = kwargs.get("agent_ids", [])
-        folder_id = kwargs.get("folder_id")
-        session_id = session.session_id if session else None
-
-        if not agent_ids:
-            return ErrorResponse(
-                message="Please provide at least one agent ID.",
-                error="missing_agent_ids",
-                session_id=session_id,
-            )
-
-        try:
-            moved = await library_db().bulk_move_agents_to_folder(
-                agent_ids=agent_ids,
-                folder_id=folder_id,
-                user_id=user_id,
-            )
-        except Exception as e:
-            return ErrorResponse(
-                message=f"Failed to move agents: {e}",
-                error="move_agents_failed",
-                session_id=session_id,
-            )
-
-        moved_ids = [a.id for a in moved]
-        agent_names = [a.name for a in moved]
-        dest = "the folder" if folder_id else "root level"
-        names_str = (
-            ", ".join(agent_names) if agent_names else f"{len(agent_ids)} agent(s)"
-        )
-        return AgentsMovedToFolderResponse(
-            message=f"Moved {names_str} to {dest}.",
-            agent_ids=moved_ids,
-            agent_names=agent_names,
-            folder_id=folder_id,
-            count=len(moved),
-            session_id=session_id,
-        )

autogpt_platform/backend/backend/copilot/tools/manage_folders_test.py

@@ -1,455 +0,0 @@
-"""Tests for folder management copilot tools."""
-
-from datetime import UTC, datetime
-from unittest.mock import AsyncMock, MagicMock, patch
-
-import pytest
-
-from backend.api.features.library import model as library_model
-from backend.copilot.tools.manage_folders import (
-    CreateFolderTool,
-    DeleteFolderTool,
-    ListFoldersTool,
-    MoveAgentsToFolderTool,
-    MoveFolderTool,
-    UpdateFolderTool,
-)
-from backend.copilot.tools.models import (
-    AgentsMovedToFolderResponse,
-    ErrorResponse,
-    FolderCreatedResponse,
-    FolderDeletedResponse,
-    FolderListResponse,
-    FolderMovedResponse,
-    FolderUpdatedResponse,
-)
-
-from ._test_data import make_session
-
-_TEST_USER_ID = "test-user-folders"
-_NOW = datetime.now(UTC)
-
-
-def _make_folder(
-    id: str = "folder-1",
-    name: str = "My Folder",
-    parent_id: str | None = None,
-    icon: str | None = None,
-    color: str | None = None,
-    agent_count: int = 0,
-    subfolder_count: int = 0,
-) -> library_model.LibraryFolder:
-    return library_model.LibraryFolder(
-        id=id,
-        user_id=_TEST_USER_ID,
-        name=name,
-        icon=icon,
-        color=color,
-        parent_id=parent_id,
-        created_at=_NOW,
-        updated_at=_NOW,
-        agent_count=agent_count,
-        subfolder_count=subfolder_count,
-    )
-
-
-def _make_tree(
-    id: str = "folder-1",
-    name: str = "Root",
-    children: list[library_model.LibraryFolderTree] | None = None,
-) -> library_model.LibraryFolderTree:
-    return library_model.LibraryFolderTree(
-        id=id,
-        user_id=_TEST_USER_ID,
-        name=name,
-        created_at=_NOW,
-        updated_at=_NOW,
-        children=children or [],
-    )
-
-
-def _make_library_agent(id: str = "agent-1", name: str = "Test Agent"):
-    agent = MagicMock()
-    agent.id = id
-    agent.name = name
-    return agent
-
-
-@pytest.fixture
-def session():
-    return make_session(_TEST_USER_ID)
-
-
-# ── CreateFolderTool ──
-
-
-@pytest.fixture
-def create_tool():
-    return CreateFolderTool()
-
-
-@pytest.mark.asyncio
-async def test_create_folder_missing_name(create_tool, session):
-    result = await create_tool._execute(user_id=_TEST_USER_ID, session=session, name="")
-    assert isinstance(result, ErrorResponse)
-    assert result.error == "missing_name"
-
-
-@pytest.mark.asyncio
-async def test_create_folder_none_name(create_tool, session):
-    result = await create_tool._execute(
-        user_id=_TEST_USER_ID, session=session, name=None
-    )
-    assert isinstance(result, ErrorResponse)
-    assert result.error == "missing_name"
-
-
-@pytest.mark.asyncio
-async def test_create_folder_success(create_tool, session):
-    folder = _make_folder(name="New Folder")
-    with patch("backend.copilot.tools.manage_folders.library_db") as mock_lib:
-        mock_lib.return_value.create_folder = AsyncMock(return_value=folder)
-        result = await create_tool._execute(
-            user_id=_TEST_USER_ID, session=session, name="New Folder"
-        )
-
-    assert isinstance(result, FolderCreatedResponse)
-    assert result.folder.name == "New Folder"
-    assert "New Folder" in result.message
-
-
-@pytest.mark.asyncio
-async def test_create_folder_db_error(create_tool, session):
-    with patch("backend.copilot.tools.manage_folders.library_db") as mock_lib:
-        mock_lib.return_value.create_folder = AsyncMock(
-            side_effect=Exception("db down")
-        )
-        result = await create_tool._execute(
-            user_id=_TEST_USER_ID, session=session, name="Folder"
-        )
-
-    assert isinstance(result, ErrorResponse)
-    assert result.error == "create_folder_failed"
-
-
-# ── ListFoldersTool ──
-
-
-@pytest.fixture
-def list_tool():
-    return ListFoldersTool()
-
-
-@pytest.mark.asyncio
-async def test_list_folders_by_parent(list_tool, session):
-    folders = [_make_folder(id="f1", name="A"), _make_folder(id="f2", name="B")]
-    with patch("backend.copilot.tools.manage_folders.library_db") as mock_lib:
-        mock_lib.return_value.list_folders = AsyncMock(return_value=folders)
-        result = await list_tool._execute(
-            user_id=_TEST_USER_ID, session=session, parent_id="parent-1"
-        )
-
-    assert isinstance(result, FolderListResponse)
-    assert result.count == 2
-    assert len(result.folders) == 2
-
-
-@pytest.mark.asyncio
-async def test_list_folders_tree(list_tool, session):
-    tree = [
-        _make_tree(id="r1", name="Root", children=[_make_tree(id="c1", name="Child")])
-    ]
-    with patch("backend.copilot.tools.manage_folders.library_db") as mock_lib:
-        mock_lib.return_value.get_folder_tree = AsyncMock(return_value=tree)
-        result = await list_tool._execute(user_id=_TEST_USER_ID, session=session)
-
-    assert isinstance(result, FolderListResponse)
-    assert result.count == 2  # root + child
-    assert result.tree is not None
-    assert len(result.tree) == 1
-
-
-@pytest.mark.asyncio
-async def test_list_folders_tree_with_agents_includes_root(list_tool, session):
-    tree = [_make_tree(id="r1", name="Root")]
-    raw_map = {"r1": [{"id": "a1", "name": "Foldered", "description": "In folder"}]}
-    root_raw = [{"id": "a2", "name": "Loose Agent", "description": "At root"}]
-    with patch("backend.copilot.tools.manage_folders.library_db") as mock_lib:
-        mock_lib.return_value.get_folder_tree = AsyncMock(return_value=tree)
-        mock_lib.return_value.get_folder_agents_map = AsyncMock(return_value=raw_map)
-        mock_lib.return_value.get_root_agent_summaries = AsyncMock(
-            return_value=root_raw
-        )
-        result = await list_tool._execute(
-            user_id=_TEST_USER_ID, session=session, include_agents=True
-        )
-
-    assert isinstance(result, FolderListResponse)
-    assert result.root_agents is not None
-    assert len(result.root_agents) == 1
-    assert result.root_agents[0].name == "Loose Agent"
-    assert result.tree is not None
-    assert result.tree[0].agents is not None
-    assert result.tree[0].agents[0].name == "Foldered"
-    mock_lib.return_value.get_root_agent_summaries.assert_awaited_once_with(
-        _TEST_USER_ID
-    )
-
-
-@pytest.mark.asyncio
-async def test_list_folders_tree_without_agents_no_root(list_tool, session):
-    tree = [_make_tree(id="r1", name="Root")]
-    with patch("backend.copilot.tools.manage_folders.library_db") as mock_lib:
-        mock_lib.return_value.get_folder_tree = AsyncMock(return_value=tree)
-        result = await list_tool._execute(
-            user_id=_TEST_USER_ID, session=session, include_agents=False
-        )
-
-    assert isinstance(result, FolderListResponse)
-    assert result.root_agents is None
-
-
-@pytest.mark.asyncio
-async def test_list_folders_db_error(list_tool, session):
-    with patch("backend.copilot.tools.manage_folders.library_db") as mock_lib:
-        mock_lib.return_value.get_folder_tree = AsyncMock(
-            side_effect=Exception("timeout")
-        )
-        result = await list_tool._execute(user_id=_TEST_USER_ID, session=session)
-
-    assert isinstance(result, ErrorResponse)
-    assert result.error == "list_folders_failed"
-
-
-# ── UpdateFolderTool ──
-
-
-@pytest.fixture
-def update_tool():
-    return UpdateFolderTool()
-
-
-@pytest.mark.asyncio
-async def test_update_folder_missing_id(update_tool, session):
-    result = await update_tool._execute(
-        user_id=_TEST_USER_ID, session=session, folder_id=""
-    )
-    assert isinstance(result, ErrorResponse)
-    assert result.error == "missing_folder_id"
-
-
-@pytest.mark.asyncio
-async def test_update_folder_none_id(update_tool, session):
-    result = await update_tool._execute(
-        user_id=_TEST_USER_ID, session=session, folder_id=None
-    )
-    assert isinstance(result, ErrorResponse)
-    assert result.error == "missing_folder_id"
-
-
-@pytest.mark.asyncio
-async def test_update_folder_success(update_tool, session):
-    folder = _make_folder(name="Renamed")
-    with patch("backend.copilot.tools.manage_folders.library_db") as mock_lib:
-        mock_lib.return_value.update_folder = AsyncMock(return_value=folder)
-        result = await update_tool._execute(
-            user_id=_TEST_USER_ID, session=session, folder_id="folder-1", name="Renamed"
-        )
-
-    assert isinstance(result, FolderUpdatedResponse)
-    assert result.folder.name == "Renamed"
-
-
-@pytest.mark.asyncio
-async def test_update_folder_db_error(update_tool, session):
-    with patch("backend.copilot.tools.manage_folders.library_db") as mock_lib:
-        mock_lib.return_value.update_folder = AsyncMock(
-            side_effect=Exception("not found")
-        )
-        result = await update_tool._execute(
-            user_id=_TEST_USER_ID, session=session, folder_id="folder-1", name="X"
-        )
-
-    assert isinstance(result, ErrorResponse)
-    assert result.error == "update_folder_failed"
-
-
-# ── MoveFolderTool ──
-
-
-@pytest.fixture
-def move_tool():
-    return MoveFolderTool()
-
-
-@pytest.mark.asyncio
-async def test_move_folder_missing_id(move_tool, session):
-    result = await move_tool._execute(
-        user_id=_TEST_USER_ID, session=session, folder_id=""
-    )
-    assert isinstance(result, ErrorResponse)
-    assert result.error == "missing_folder_id"
-
-
-@pytest.mark.asyncio
-async def test_move_folder_to_parent(move_tool, session):
-    folder = _make_folder(name="Moved")
-    with patch("backend.copilot.tools.manage_folders.library_db") as mock_lib:
-        mock_lib.return_value.move_folder = AsyncMock(return_value=folder)
-        result = await move_tool._execute(
-            user_id=_TEST_USER_ID,
-            session=session,
-            folder_id="folder-1",
-            target_parent_id="parent-1",
-        )
-
-    assert isinstance(result, FolderMovedResponse)
-    assert "subfolder" in result.message
-
-
-@pytest.mark.asyncio
-async def test_move_folder_to_root(move_tool, session):
-    folder = _make_folder(name="Moved")
-    with patch("backend.copilot.tools.manage_folders.library_db") as mock_lib:
-        mock_lib.return_value.move_folder = AsyncMock(return_value=folder)
-        result = await move_tool._execute(
-            user_id=_TEST_USER_ID,
-            session=session,
-            folder_id="folder-1",
-            target_parent_id=None,
-        )
-
-    assert isinstance(result, FolderMovedResponse)
-    assert "root level" in result.message
-
-
-@pytest.mark.asyncio
-async def test_move_folder_db_error(move_tool, session):
-    with patch("backend.copilot.tools.manage_folders.library_db") as mock_lib:
-        mock_lib.return_value.move_folder = AsyncMock(side_effect=Exception("circular"))
-        result = await move_tool._execute(
-            user_id=_TEST_USER_ID, session=session, folder_id="folder-1"
-        )
-
-    assert isinstance(result, ErrorResponse)
-    assert result.error == "move_folder_failed"
-
-
-# ── DeleteFolderTool ──
-
-
-@pytest.fixture
-def delete_tool():
-    return DeleteFolderTool()
-
-
-@pytest.mark.asyncio
-async def test_delete_folder_missing_id(delete_tool, session):
-    result = await delete_tool._execute(
-        user_id=_TEST_USER_ID, session=session, folder_id=""
-    )
-    assert isinstance(result, ErrorResponse)
-    assert result.error == "missing_folder_id"
-
-
-@pytest.mark.asyncio
-async def test_delete_folder_success(delete_tool, session):
-    with patch("backend.copilot.tools.manage_folders.library_db") as mock_lib:
-        mock_lib.return_value.delete_folder = AsyncMock(return_value=None)
-        result = await delete_tool._execute(
-            user_id=_TEST_USER_ID, session=session, folder_id="folder-1"
-        )
-
-    assert isinstance(result, FolderDeletedResponse)
-    assert result.folder_id == "folder-1"
-    assert "root level" in result.message
-
-
-@pytest.mark.asyncio
-async def test_delete_folder_db_error(delete_tool, session):
-    with patch("backend.copilot.tools.manage_folders.library_db") as mock_lib:
-        mock_lib.return_value.delete_folder = AsyncMock(
-            side_effect=Exception("permission denied")
-        )
-        result = await delete_tool._execute(
-            user_id=_TEST_USER_ID, session=session, folder_id="folder-1"
-        )
-
-    assert isinstance(result, ErrorResponse)
-    assert result.error == "delete_folder_failed"
-
-
-# ── MoveAgentsToFolderTool ──
-
-
-@pytest.fixture
-def move_agents_tool():
-    return MoveAgentsToFolderTool()
-
-
-@pytest.mark.asyncio
-async def test_move_agents_missing_ids(move_agents_tool, session):
-    result = await move_agents_tool._execute(
-        user_id=_TEST_USER_ID, session=session, agent_ids=[]
-    )
-    assert isinstance(result, ErrorResponse)
-    assert result.error == "missing_agent_ids"
-
-
-@pytest.mark.asyncio
-async def test_move_agents_success(move_agents_tool, session):
-    agents = [
-        _make_library_agent(id="a1", name="Agent Alpha"),
-        _make_library_agent(id="a2", name="Agent Beta"),
-    ]
-    with patch("backend.copilot.tools.manage_folders.library_db") as mock_lib:
-        mock_lib.return_value.bulk_move_agents_to_folder = AsyncMock(
-            return_value=agents
-        )
-        result = await move_agents_tool._execute(
-            user_id=_TEST_USER_ID,
-            session=session,
-            agent_ids=["a1", "a2"],
-            folder_id="folder-1",
-        )
-
-    assert isinstance(result, AgentsMovedToFolderResponse)
-    assert result.count == 2
-    assert result.agent_names == ["Agent Alpha", "Agent Beta"]
-    assert "Agent Alpha" in result.message
-    assert "Agent Beta" in result.message
-
-
-@pytest.mark.asyncio
-async def test_move_agents_to_root(move_agents_tool, session):
-    agents = [_make_library_agent(id="a1", name="Agent One")]
-    with patch("backend.copilot.tools.manage_folders.library_db") as mock_lib:
-        mock_lib.return_value.bulk_move_agents_to_folder = AsyncMock(
-            return_value=agents
-        )
-        result = await move_agents_tool._execute(
-            user_id=_TEST_USER_ID,
-            session=session,
-            agent_ids=["a1"],
-            folder_id=None,
-        )
-
-    assert isinstance(result, AgentsMovedToFolderResponse)
-    assert "root level" in result.message
-
-
-@pytest.mark.asyncio
-async def test_move_agents_db_error(move_agents_tool, session):
-    with patch("backend.copilot.tools.manage_folders.library_db") as mock_lib:
-        mock_lib.return_value.bulk_move_agents_to_folder = AsyncMock(
-            side_effect=Exception("folder not found")
-        )
-        result = await move_agents_tool._execute(
-            user_id=_TEST_USER_ID,
-            session=session,
-            agent_ids=["a1"],
-            folder_id="bad-folder",
-        )
-
-    assert isinstance(result, ErrorResponse)
-    assert result.error == "move_agents_failed"

autogpt_platform/backend/backend/copilot/tools/models.py

@@ -55,13 +55,6 @@ class ResponseType(str, Enum):
     # MCP tool types
     MCP_TOOLS_DISCOVERED = "mcp_tools_discovered"
     MCP_TOOL_OUTPUT = "mcp_tool_output"
-    # Folder management types
-    FOLDER_CREATED = "folder_created"
-    FOLDER_LIST = "folder_list"
-    FOLDER_UPDATED = "folder_updated"
-    FOLDER_MOVED = "folder_moved"
-    FOLDER_DELETED = "folder_deleted"
-    AGENTS_MOVED_TO_FOLDER = "agents_moved_to_folder"
 
 
 # Base response model
@@ -546,82 +539,3 @@ class BrowserScreenshotResponse(ToolResponseBase):
     type: ResponseType = ResponseType.BROWSER_SCREENSHOT
     file_id: str  # Workspace file ID — use read_workspace_file to retrieve
     filename: str
-
-
-# Folder management models
-
-
-class FolderAgentSummary(BaseModel):
-    """Lightweight agent info for folder listings."""
-
-    id: str
-    name: str
-    description: str = ""
-
-
-class FolderInfo(BaseModel):
-    """Information about a folder."""
-
-    id: str
-    name: str
-    parent_id: str | None = None
-    icon: str | None = None
-    color: str | None = None
-    agent_count: int = 0
-    subfolder_count: int = 0
-    agents: list[FolderAgentSummary] | None = None
-
-
-class FolderTreeInfo(FolderInfo):
-    """Folder with nested children for tree display."""
-
-    children: list["FolderTreeInfo"] = []
-
-
-class FolderCreatedResponse(ToolResponseBase):
-    """Response when a folder is created."""
-
-    type: ResponseType = ResponseType.FOLDER_CREATED
-    folder: FolderInfo
-
-
-class FolderListResponse(ToolResponseBase):
-    """Response for listing folders."""
-
-    type: ResponseType = ResponseType.FOLDER_LIST
-    folders: list[FolderInfo] = Field(default_factory=list)
-    tree: list[FolderTreeInfo] | None = None
-    root_agents: list[FolderAgentSummary] | None = None
-    count: int = 0
-
-
-class FolderUpdatedResponse(ToolResponseBase):
-    """Response when a folder is updated."""
-
-    type: ResponseType = ResponseType.FOLDER_UPDATED
-    folder: FolderInfo
-
-
-class FolderMovedResponse(ToolResponseBase):
-    """Response when a folder is moved."""
-
-    type: ResponseType = ResponseType.FOLDER_MOVED
-    folder: FolderInfo
-    target_parent_id: str | None = None
-
-
-class FolderDeletedResponse(ToolResponseBase):
-    """Response when a folder is deleted."""
-
-    type: ResponseType = ResponseType.FOLDER_DELETED
-    folder_id: str
-
-
-class AgentsMovedToFolderResponse(ToolResponseBase):
-    """Response when agents are moved to a folder."""
-
-    type: ResponseType = ResponseType.AGENTS_MOVED_TO_FOLDER
-    agent_ids: list[str]
-    agent_names: list[str] = []
-    folder_id: str | None = None
-    count: int = 0

autogpt_platform/backend/backend/copilot/tools/run_mcp_tool.py

@@ -53,15 +53,11 @@ class RunMCPToolTool(BaseTool):
     def description(self) -> str:
         return (
             "Connect to an MCP (Model Context Protocol) server to discover and execute its tools. "
-            "Two-step workflow: (1) Call with just `server_url` to discover available tools. "
-            "(2) Call again with `server_url`, `tool_name`, and `tool_arguments` to execute. "
-            "Known hosted servers (use directly): Notion (https://mcp.notion.com/mcp), "
-            "Linear (https://mcp.linear.app/mcp), Stripe (https://mcp.stripe.com), "
-            "Intercom (https://mcp.intercom.com/mcp), Cloudflare (https://mcp.cloudflare.com/mcp), "
-            "Atlassian/Jira (https://mcp.atlassian.com/mcp). "
-            "For other services, search the MCP registry at https://registry.modelcontextprotocol.io/. "
-            "Authentication: If the server requires credentials, user will be prompted to complete the MCP credential setup flow."
-            "Once connected and user confirms, retry the same call immediately."
+            "Call with just `server_url` to see available tools. "
+            "Then call again with `server_url`, `tool_name`, and `tool_arguments` to execute. "
+            "If the server requires authentication, the user will be prompted to connect it. "
+            "Find MCP servers at https://registry.modelcontextprotocol.io/ — hundreds of integrations "
+            "including GitHub, Postgres, Slack, filesystem, and more."
         )
 
     @property

autogpt_platform/backend/backend/data/db_manager.py

@@ -4,20 +4,11 @@ from typing import TYPE_CHECKING, Callable, Concatenate, ParamSpec, TypeVar, cas
 
 from backend.api.features.library.db import (
     add_store_agent_to_library,
-    bulk_move_agents_to_folder,
-    create_folder,
     create_graph_in_library,
     create_library_agent,
-    delete_folder,
-    get_folder_agents_map,
-    get_folder_tree,
     get_library_agent,
     get_library_agent_by_graph_id,
-    get_root_agent_summaries,
-    list_folders,
     list_library_agents,
-    move_folder,
-    update_folder,
     update_graph_in_library,
 )
 from backend.api.features.store.db import (
@@ -269,16 +260,6 @@ class DatabaseManager(AppService):
     update_graph_in_library = _(update_graph_in_library)
     validate_graph_execution_permissions = _(validate_graph_execution_permissions)
 
-    create_folder = _(create_folder)
-    list_folders = _(list_folders)
-    get_folder_tree = _(get_folder_tree)
-    update_folder = _(update_folder)
-    move_folder = _(move_folder)
-    delete_folder = _(delete_folder)
-    bulk_move_agents_to_folder = _(bulk_move_agents_to_folder)
-    get_folder_agents_map = _(get_folder_agents_map)
-    get_root_agent_summaries = _(get_root_agent_summaries)
-
     # ============ Onboarding ============ #
     increment_onboarding_runs = _(increment_onboarding_runs)
 
@@ -453,17 +434,6 @@ class DatabaseManagerAsyncClient(AppServiceClient):
     update_graph_in_library = d.update_graph_in_library
     validate_graph_execution_permissions = d.validate_graph_execution_permissions
 
-    # ============ Library Folders ============ #
-    create_folder = d.create_folder
-    list_folders = d.list_folders
-    get_folder_tree = d.get_folder_tree
-    update_folder = d.update_folder
-    move_folder = d.move_folder
-    delete_folder = d.delete_folder
-    bulk_move_agents_to_folder = d.bulk_move_agents_to_folder
-    get_folder_agents_map = d.get_folder_agents_map
-    get_root_agent_summaries = d.get_root_agent_summaries
-
     # ============ Onboarding ============ #
     increment_onboarding_runs = d.increment_onboarding_runs
 

autogpt_platform/backend/backend/data/execution.py

@@ -344,7 +344,7 @@ class GraphExecution(GraphExecutionMeta):
             ),
             **{
                 # input from webhook-triggered block
-                "payload": exec.input_data.get("payload")
+                "payload": exec.input_data["payload"]
                 for exec in complete_node_executions
                 if (
                     (block := get_block(exec.block_id))

autogpt_platform/backend/backend/data/graph_test.py

@@ -4,7 +4,6 @@ from unittest.mock import AsyncMock, patch
 from uuid import UUID
 
 import fastapi.exceptions
-import prisma
 import pytest
 from pytest_snapshot.plugin import Snapshot
 
@@ -251,8 +250,8 @@ async def test_clean_graph(server: SpinTestServer):
                     "_test_id": "node_with_secrets",
                     "input": "normal_value",
                     "control_test_input": "should be preserved",
-                    "api_key": "secret_api_key_123",  # Should be filtered # pragma: allowlist secret # noqa
-                    "password": "secret_password_456",  # Should be filtered # pragma: allowlist secret # noqa
+                    "api_key": "secret_api_key_123",  # Should be filtered
+                    "password": "secret_password_456",  # Should be filtered
                     "token": "secret_token_789",  # Should be filtered
                     "credentials": {  # Should be filtered
                         "id": "fake-github-credentials-id",
@@ -355,24 +354,9 @@ async def test_access_store_listing_graph(server: SpinTestServer):
         create_graph, DEFAULT_USER_ID
     )
 
-    # Ensure the default user has a Profile (required for store submissions)
-    existing_profile = await prisma.models.Profile.prisma().find_first(
-        where={"userId": DEFAULT_USER_ID}
-    )
-    if not existing_profile:
-        await prisma.models.Profile.prisma().create(
-            data=prisma.types.ProfileCreateInput(
-                userId=DEFAULT_USER_ID,
-                name="Default User",
-                username=f"default-user-{DEFAULT_USER_ID[:8]}",
-                description="Default test user profile",
-                links=[],
-            )
-        )
-
     store_submission_request = store.StoreSubmissionRequest(
-        graph_id=created_graph.id,
-        graph_version=created_graph.version,
+        agent_id=created_graph.id,
+        agent_version=created_graph.version,
         slug=created_graph.id,
         name="Test name",
         sub_heading="Test sub heading",
@@ -401,8 +385,8 @@ async def test_access_store_listing_graph(server: SpinTestServer):
         assert False, "Failed to create store listing"
 
     slv_id = (
-        store_listing.listing_version_id
-        if store_listing.listing_version_id is not None
+        store_listing.store_listing_version_id
+        if store_listing.store_listing_version_id is not None
         else None
     )
 

autogpt_platform/backend/backend/data/notifications.py

@@ -13,14 +13,7 @@ from prisma.types import (
 )
 
 # from backend.notifications.models import NotificationEvent
-from pydantic import (
-    BaseModel,
-    ConfigDict,
-    EmailStr,
-    Field,
-    field_validator,
-    model_validator,
-)
+from pydantic import BaseModel, ConfigDict, EmailStr, Field, field_validator
 
 from backend.util.exceptions import DatabaseError
 from backend.util.json import SafeJson
@@ -182,26 +175,10 @@ class RefundRequestData(BaseNotificationData):
     balance: int
 
 
-class _LegacyAgentFieldsMixin:
-    """Temporary patch to handle existing queued payloads"""
-
-    # FIXME: remove in next release
-
-    @model_validator(mode="before")
-    @classmethod
-    def _map_legacy_agent_fields(cls, values: Any):
-        if isinstance(values, dict):
-            if "graph_id" not in values and "agent_id" in values:
-                values["graph_id"] = values.pop("agent_id")
-            if "graph_version" not in values and "agent_version" in values:
-                values["graph_version"] = values.pop("agent_version")
-        return values
-
-
-class AgentApprovalData(_LegacyAgentFieldsMixin, BaseNotificationData):
+class AgentApprovalData(BaseNotificationData):
     agent_name: str
-    graph_id: str
-    graph_version: int
+    agent_id: str
+    agent_version: int
     reviewer_name: str
     reviewer_email: str
     comments: str
@@ -216,10 +193,10 @@ class AgentApprovalData(_LegacyAgentFieldsMixin, BaseNotificationData):
         return value
 
 
-class AgentRejectionData(_LegacyAgentFieldsMixin, BaseNotificationData):
+class AgentRejectionData(BaseNotificationData):
     agent_name: str
-    graph_id: str
-    graph_version: int
+    agent_id: str
+    agent_version: int
     reviewer_name: str
     reviewer_email: str
     comments: str

autogpt_platform/backend/backend/data/notifications_test.py

@@ -15,8 +15,8 @@ class TestAgentApprovalData:
         """Test creating valid AgentApprovalData."""
         data = AgentApprovalData(
             agent_name="Test Agent",
-            graph_id="test-agent-123",
-            graph_version=1,
+            agent_id="test-agent-123",
+            agent_version=1,
             reviewer_name="John Doe",
             reviewer_email="john@example.com",
             comments="Great agent, approved!",
@@ -25,8 +25,8 @@ class TestAgentApprovalData:
         )
 
         assert data.agent_name == "Test Agent"
-        assert data.graph_id == "test-agent-123"
-        assert data.graph_version == 1
+        assert data.agent_id == "test-agent-123"
+        assert data.agent_version == 1
         assert data.reviewer_name == "John Doe"
         assert data.reviewer_email == "john@example.com"
         assert data.comments == "Great agent, approved!"
@@ -40,8 +40,8 @@ class TestAgentApprovalData:
         ):
             AgentApprovalData(
                 agent_name="Test Agent",
-                graph_id="test-agent-123",
-                graph_version=1,
+                agent_id="test-agent-123",
+                agent_version=1,
                 reviewer_name="John Doe",
                 reviewer_email="john@example.com",
                 comments="Great agent, approved!",
@@ -53,8 +53,8 @@ class TestAgentApprovalData:
         """Test AgentApprovalData with empty comments."""
         data = AgentApprovalData(
             agent_name="Test Agent",
-            graph_id="test-agent-123",
-            graph_version=1,
+            agent_id="test-agent-123",
+            agent_version=1,
             reviewer_name="John Doe",
             reviewer_email="john@example.com",
             comments="",  # Empty comments
@@ -72,8 +72,8 @@ class TestAgentRejectionData:
         """Test creating valid AgentRejectionData."""
         data = AgentRejectionData(
             agent_name="Test Agent",
-            graph_id="test-agent-123",
-            graph_version=1,
+            agent_id="test-agent-123",
+            agent_version=1,
             reviewer_name="Jane Doe",
             reviewer_email="jane@example.com",
             comments="Please fix the security issues before resubmitting.",
@@ -82,8 +82,8 @@ class TestAgentRejectionData:
         )
 
         assert data.agent_name == "Test Agent"
-        assert data.graph_id == "test-agent-123"
-        assert data.graph_version == 1
+        assert data.agent_id == "test-agent-123"
+        assert data.agent_version == 1
         assert data.reviewer_name == "Jane Doe"
         assert data.reviewer_email == "jane@example.com"
         assert data.comments == "Please fix the security issues before resubmitting."
@@ -97,8 +97,8 @@ class TestAgentRejectionData:
         ):
             AgentRejectionData(
                 agent_name="Test Agent",
-                graph_id="test-agent-123",
-                graph_version=1,
+                agent_id="test-agent-123",
+                agent_version=1,
                 reviewer_name="Jane Doe",
                 reviewer_email="jane@example.com",
                 comments="Please fix the security issues.",
@@ -111,8 +111,8 @@ class TestAgentRejectionData:
         long_comment = "A" * 1000  # Very long comment
         data = AgentRejectionData(
             agent_name="Test Agent",
-            graph_id="test-agent-123",
-            graph_version=1,
+            agent_id="test-agent-123",
+            agent_version=1,
             reviewer_name="Jane Doe",
             reviewer_email="jane@example.com",
             comments=long_comment,
@@ -126,8 +126,8 @@ class TestAgentRejectionData:
         """Test that models can be serialized and deserialized."""
         original_data = AgentRejectionData(
             agent_name="Test Agent",
-            graph_id="test-agent-123",
-            graph_version=1,
+            agent_id="test-agent-123",
+            agent_version=1,
             reviewer_name="Jane Doe",
             reviewer_email="jane@example.com",
             comments="Please fix the issues.",
@@ -142,8 +142,8 @@ class TestAgentRejectionData:
         restored_data = AgentRejectionData.model_validate(data_dict)
 
         assert restored_data.agent_name == original_data.agent_name
-        assert restored_data.graph_id == original_data.graph_id
-        assert restored_data.graph_version == original_data.graph_version
+        assert restored_data.agent_id == original_data.agent_id
+        assert restored_data.agent_version == original_data.agent_version
         assert restored_data.reviewer_name == original_data.reviewer_name
         assert restored_data.reviewer_email == original_data.reviewer_email
         assert restored_data.comments == original_data.comments

autogpt_platform/backend/backend/data/onboarding.py

@@ -244,10 +244,7 @@ def _clean_and_split(text: str) -> list[str]:
 
 
 def _calculate_points(
-    agent: prisma.models.StoreAgent,
-    categories: list[str],
-    custom: list[str],
-    integrations: list[str],
+    agent, categories: list[str], custom: list[str], integrations: list[str]
 ) -> int:
     """
     Calculates the total points for an agent based on the specified criteria.
@@ -400,7 +397,7 @@ async def get_recommended_agents(user_id: str) -> list[StoreAgentDetails]:
     storeAgents = await prisma.models.StoreAgent.prisma().find_many(
         where={
             "is_available": True,
-            "use_for_onboarding": True,
+            "useForOnboarding": True,
         },
         order=[
             {"featured": "desc"},
@@ -410,7 +407,7 @@ async def get_recommended_agents(user_id: str) -> list[StoreAgentDetails]:
         take=100,
     )
 
-    # If not enough agents found, relax the use_for_onboarding filter
+    # If not enough agents found, relax the useForOnboarding filter
     if len(storeAgents) < 2:
         storeAgents = await prisma.models.StoreAgent.prisma().find_many(
             where=prisma.types.StoreAgentWhereInput(**where_clause),
@@ -423,7 +420,7 @@ async def get_recommended_agents(user_id: str) -> list[StoreAgentDetails]:
         )
 
     # Calculate points for the first X agents and choose the top 2
-    agent_points: list[tuple[prisma.models.StoreAgent, int]] = []
+    agent_points = []
     for agent in storeAgents[:POINTS_AGENT_COUNT]:
         points = _calculate_points(
             agent, categories, custom, user_onboarding.integrations
@@ -433,7 +430,28 @@ async def get_recommended_agents(user_id: str) -> list[StoreAgentDetails]:
     agent_points.sort(key=lambda x: x[1], reverse=True)
     recommended_agents = [agent for agent, _ in agent_points[:2]]
 
-    return [StoreAgentDetails.from_db(agent) for agent in recommended_agents]
+    return [
+        StoreAgentDetails(
+            store_listing_version_id=agent.storeListingVersionId,
+            slug=agent.slug,
+            agent_name=agent.agent_name,
+            agent_video=agent.agent_video or "",
+            agent_output_demo=agent.agent_output_demo or "",
+            agent_image=agent.agent_image,
+            creator=agent.creator_username,
+            creator_avatar=agent.creator_avatar,
+            sub_heading=agent.sub_heading,
+            description=agent.description,
+            categories=agent.categories,
+            runs=agent.runs,
+            rating=agent.rating,
+            versions=agent.versions,
+            agentGraphVersions=agent.agentGraphVersions,
+            agentGraphId=agent.agentGraphId,
+            last_updated=agent.updated_at,
+        )
+        for agent in recommended_agents
+    ]
 
 
 @cached(maxsize=1, ttl_seconds=300)  # Cache for 5 minutes since this rarely changes

autogpt_platform/backend/backend/executor/manager_test.py

@@ -2,7 +2,6 @@ import logging
 from unittest.mock import AsyncMock, patch
 
 import fastapi.responses
-import prisma
 import pytest
 
 import backend.api.features.library.model
@@ -498,24 +497,9 @@ async def test_store_listing_graph(server: SpinTestServer):
     test_user = await create_test_user()
     test_graph = await create_graph(server, create_test_graph(), test_user)
 
-    # Ensure the test user has a Profile (required for store submissions)
-    existing_profile = await prisma.models.Profile.prisma().find_first(
-        where={"userId": test_user.id}
-    )
-    if not existing_profile:
-        await prisma.models.Profile.prisma().create(
-            data=prisma.types.ProfileCreateInput(
-                userId=test_user.id,
-                name=test_user.name or "Test User",
-                username=f"test-user-{test_user.id[:8]}",
-                description="Test user profile",
-                links=[],
-            )
-        )
-
     store_submission_request = backend.api.features.store.model.StoreSubmissionRequest(
-        graph_id=test_graph.id,
-        graph_version=test_graph.version,
+        agent_id=test_graph.id,
+        agent_version=test_graph.version,
         slug=test_graph.id,
         name="Test name",
         sub_heading="Test sub heading",
@@ -533,8 +517,8 @@ async def test_store_listing_graph(server: SpinTestServer):
         assert False, "Failed to create store listing"
 
     slv_id = (
-        store_listing.listing_version_id
-        if store_listing.listing_version_id is not None
+        store_listing.store_listing_version_id
+        if store_listing.store_listing_version_id is not None
         else None
     )
 

autogpt_platform/backend/backend/executor/utils.py

@@ -15,7 +15,6 @@ from backend.data import graph as graph_db
 from backend.data import human_review as human_review_db
 from backend.data import onboarding as onboarding_db
 from backend.data import user as user_db
-from backend.data import workspace as workspace_db
 
 # Import dynamic field utilities from centralized location
 from backend.data.block import BlockInput, BlockOutputEntry
@@ -33,6 +32,7 @@ from backend.data.execution import (
 from backend.data.graph import GraphModel, Node
 from backend.data.model import USER_TIMEZONE_NOT_SET, CredentialsMetaInput, GraphInput
 from backend.data.rabbitmq import Exchange, ExchangeType, Queue, RabbitMQConfig
+from backend.data.workspace import get_or_create_workspace
 from backend.util.clients import (
     get_async_execution_event_bus,
     get_async_execution_queue,
@@ -481,22 +481,6 @@ async def _construct_starting_node_execution_input(
         if nodes_input_masks and (node_input_mask := nodes_input_masks.get(node.id)):
             input_data.update(node_input_mask)
 
-        # Webhook-triggered agents cannot be executed directly without payload data.
-        # Legitimate webhook triggers provide payload via nodes_input_masks above.
-        if (
-            block.block_type
-            in (
-                BlockType.WEBHOOK,
-                BlockType.WEBHOOK_MANUAL,
-            )
-            and "payload" not in input_data
-        ):
-            raise ValueError(
-                "This agent is triggered by an external event (webhook) "
-                "and cannot be executed directly. "
-                "Please use the appropriate trigger to run this agent."
-            )
-
         input_data, error = validate_exec(node, input_data)
         if input_data is None:
             raise ValueError(error)
@@ -847,9 +831,8 @@ async def add_graph_execution(
         udb = user_db
         gdb = graph_db
         odb = onboarding_db
-        wdb = workspace_db
     else:
-        edb = udb = gdb = odb = wdb = get_database_manager_async_client()
+        edb = udb = gdb = odb = get_database_manager_async_client()
 
     # Get or create the graph execution
     if graph_exec_id:
@@ -909,7 +892,7 @@ async def add_graph_execution(
     if execution_context is None:
         user = await udb.get_user_by_id(user_id)
         settings = await gdb.get_graph_settings(user_id=user_id, graph_id=graph_id)
-        workspace = await wdb.get_or_create_workspace(user_id)
+        workspace = await get_or_create_workspace(user_id)
 
         execution_context = ExecutionContext(
             # Execution identity

autogpt_platform/backend/backend/executor/utils_test.py

@@ -368,10 +368,12 @@ async def test_add_graph_execution_is_repeatable(mocker: MockerFixture):
     mock_get_event_bus = mocker.patch(
         "backend.executor.utils.get_async_execution_event_bus"
     )
-    mock_wdb = mocker.patch("backend.executor.utils.workspace_db")
     mock_workspace = mocker.MagicMock()
     mock_workspace.id = "test-workspace-id"
-    mock_wdb.get_or_create_workspace = mocker.AsyncMock(return_value=mock_workspace)
+    mocker.patch(
+        "backend.executor.utils.get_or_create_workspace",
+        new=mocker.AsyncMock(return_value=mock_workspace),
+    )
 
     # Setup mock returns
     # The function returns (graph, starting_nodes_input, compiled_nodes_input_masks, nodes_to_skip)
@@ -647,10 +649,12 @@ async def test_add_graph_execution_with_nodes_to_skip(mocker: MockerFixture):
     mock_get_event_bus = mocker.patch(
         "backend.executor.utils.get_async_execution_event_bus"
     )
-    mock_wdb = mocker.patch("backend.executor.utils.workspace_db")
     mock_workspace = mocker.MagicMock()
     mock_workspace.id = "test-workspace-id"
-    mock_wdb.get_or_create_workspace = mocker.AsyncMock(return_value=mock_workspace)
+    mocker.patch(
+        "backend.executor.utils.get_or_create_workspace",
+        new=mocker.AsyncMock(return_value=mock_workspace),
+    )
 
     # Setup returns - include nodes_to_skip in the tuple
     mock_validate.return_value = (

autogpt_platform/backend/backend/notifications/templates/agent_approved.html.jinja2

@@ -2,8 +2,8 @@
 {#
   Template variables:
   data.agent_name: the name of the approved agent
-  data.graph_id: the ID of the agent
-  data.graph_version: the version of the agent
+  data.agent_id: the ID of the agent
+  data.agent_version: the version of the agent
   data.reviewer_name: the name of the reviewer who approved it
   data.reviewer_email: the email of the reviewer
   data.comments: comments from the reviewer
@@ -70,4 +70,4 @@
   Thank you for contributing to the AutoGPT ecosystem! 🚀
 </p>
 
-{% endblock %}
+{% endblock %}

autogpt_platform/backend/backend/notifications/templates/agent_rejected.html.jinja2

@@ -2,8 +2,8 @@
 {#
   Template variables:
   data.agent_name: the name of the rejected agent
-  data.graph_id: the ID of the agent
-  data.graph_version: the version of the agent
+  data.agent_id: the ID of the agent
+  data.agent_version: the version of the agent
   data.reviewer_name: the name of the reviewer who rejected it
   data.reviewer_email: the email of the reviewer
   data.comments: comments from the reviewer explaining the rejection
@@ -74,4 +74,4 @@
   We're excited to see your improved agent submission! 🚀
 </p>
 
-{% endblock %}
+{% endblock %}

autogpt_platform/backend/backend/util/exceptions.py

@@ -64,10 +64,6 @@ class GraphNotInLibraryError(GraphNotAccessibleError):
     """Raised when attempting to execute a graph that is not / no longer in the user's library."""
 
 
-class PreconditionFailed(Exception):
-    """The user must do something else first before trying the current operation"""
-
-
 class InsufficientBalanceError(ValueError):
     user_id: str
     message: str

autogpt_platform/backend/backend/util/json.py

@@ -72,58 +72,19 @@ def dumps(
 
 T = TypeVar("T")
 
-# Sentinel value to detect when fallback is not provided
-_NO_FALLBACK = object()
+
+@overload
+def loads(data: str | bytes, *args, target_type: Type[T], **kwargs) -> T: ...
 
 
 @overload
-def loads(
-    data: str | bytes, *args, target_type: Type[T], fallback: T | None = None, **kwargs
-) -> T:
-    pass
-
-
-@overload
-def loads(data: str | bytes, *args, fallback: Any = None, **kwargs) -> Any:
-    pass
+def loads(data: str | bytes, *args, **kwargs) -> Any: ...
 
 
 def loads(
-    data: str | bytes,
-    *args,
-    target_type: Type[T] | None = None,
-    fallback: Any = _NO_FALLBACK,
-    **kwargs,
+    data: str | bytes, *args, target_type: Type[T] | None = None, **kwargs
 ) -> Any:
-    """Parse JSON with optional fallback on decode errors.
-
-    Args:
-        data: JSON string or bytes to parse
-        target_type: Optional type to validate/cast result to
-        fallback: Value to return on JSONDecodeError. If not provided, raises.
-        **kwargs: Additional arguments (unused, for compatibility)
-
-    Returns:
-        Parsed JSON data, or fallback value if parsing fails
-
-    Raises:
-        orjson.JSONDecodeError: Only if fallback is not provided
-
-    Examples:
-        >>> loads('{"valid": "json"}')
-        {'valid': 'json'}
-        >>> loads('invalid json', fallback=None)
-        None
-        >>> loads('invalid json', fallback={})
-        {}
-        >>> loads('invalid json')  # raises orjson.JSONDecodeError
-    """
-    try:
-        parsed = orjson.loads(data)
-    except orjson.JSONDecodeError:
-        if fallback is not _NO_FALLBACK:
-            return fallback
-        raise
+    parsed = orjson.loads(data)
 
     if target_type:
         return type_match(parsed, target_type)

autogpt_platform/backend/migrations/20260228114302_improve_store_entity_relations/migration.sql

@@ -1,32 +0,0 @@
-BEGIN;
-
--- Drop illogical column StoreListing.agentGraphVersion;
-ALTER TABLE "StoreListing" DROP CONSTRAINT "StoreListing_agentGraphId_agentGraphVersion_fkey";
-DROP INDEX "StoreListing_agentGraphId_agentGraphVersion_idx";
-ALTER TABLE "StoreListing" DROP COLUMN "agentGraphVersion";
-
--- Add uniqueness constraint to Profile.userId and remove invalid data
---
--- Delete any profiles with null userId (which is invalid and doesn't occur in theory)
-DELETE FROM "Profile" WHERE "userId" IS NULL;
---
--- Delete duplicate profiles per userId, keeping the most recently updated one
-DELETE FROM "Profile"
-WHERE "id" IN (
-  SELECT "id" FROM (
-    SELECT "id", ROW_NUMBER() OVER (
-      PARTITION BY "userId" ORDER BY "updatedAt" DESC, "id" DESC
-    ) AS rn
-    FROM "Profile"
-  ) ranked
-  WHERE rn > 1
-);
---
--- Add userId uniqueness constraint
-ALTER TABLE "Profile" ALTER COLUMN "userId" SET NOT NULL;
-CREATE UNIQUE INDEX "Profile_userId_key" ON "Profile"("userId");
-
--- Add formal relation StoreListing.owningUserId -> Profile.userId
-ALTER TABLE "StoreListing" ADD CONSTRAINT "StoreListing_owner_Profile_fkey" FOREIGN KEY ("owningUserId") REFERENCES "Profile"("userId") ON DELETE CASCADE ON UPDATE CASCADE;
-
-COMMIT;

autogpt_platform/backend/migrations/20260304123456_update_store_views/migration.sql

@@ -1,219 +0,0 @@
--- Update the StoreSubmission and StoreAgent views with additional fields, clearer field names, and faster joins.
--- Steps:
--- 1. Update `mv_agent_run_counts` to exclude runs by the agent's creator
---   a. Drop dependent views `StoreAgent` and `Creator`
---   b. Update `mv_agent_run_counts` and its index
---   c. Recreate `StoreAgent` view (with updates)
---   d. Restore `Creator` view
--- 2. Update `StoreSubmission` view
--- 3. Update `StoreListingReview` indices to make `StoreSubmission` query more efficient
-
-BEGIN;
-
--- Drop views that are dependent on mv_agent_run_counts
-DROP VIEW IF EXISTS "StoreAgent";
-DROP VIEW IF EXISTS "Creator";
-
--- Update materialized view for agent run counts to exclude runs by the agent's creator
-DROP INDEX IF EXISTS "idx_mv_agent_run_counts";
-DROP MATERIALIZED VIEW IF EXISTS "mv_agent_run_counts";
-CREATE MATERIALIZED VIEW "mv_agent_run_counts" AS
-SELECT
-    run."agentGraphId" AS graph_id,
-    COUNT(*)           AS run_count
-FROM "AgentGraphExecution" run
-JOIN "AgentGraph"          graph ON graph.id = run."agentGraphId"
--- Exclude runs by the agent's creator to avoid inflating run counts
-WHERE graph."userId" != run."userId"
-GROUP BY run."agentGraphId";
-
--- Recreate index
-CREATE UNIQUE INDEX IF NOT EXISTS "idx_mv_agent_run_counts" ON "mv_agent_run_counts"("graph_id");
-
--- Re-populate the materialized view
-REFRESH MATERIALIZED VIEW "mv_agent_run_counts";
-
-
--- Recreate the StoreAgent view with the following changes
--- (compared to 20260115210000_remove_storelistingversion_search):
--- - Narrow to *explicitly active* version (sl.activeVersionId) instead of MAX(version)
--- - Add `recommended_schedule_cron` column
--- - Rename `"storeListingVersionId"` -> `listing_version_id`
--- - Rename `"agentGraphVersions"`    -> `graph_versions`
--- - Rename `"agentGraphId"`          -> `graph_id`
--- - Rename `"useForOnboarding"`      -> `use_for_onboarding`
-CREATE OR REPLACE VIEW "StoreAgent" AS
-WITH store_agent_versions AS (
-    SELECT
-        "storeListingId",
-        array_agg(DISTINCT version::text ORDER BY version::text) AS versions
-    FROM "StoreListingVersion"
-    WHERE "submissionStatus" = 'APPROVED'
-    GROUP BY "storeListingId"
-),
-agent_graph_versions AS (
-    SELECT
-        "storeListingId",
-        array_agg(DISTINCT "agentGraphVersion"::text ORDER BY "agentGraphVersion"::text) AS graph_versions
-    FROM "StoreListingVersion"
-    WHERE "submissionStatus" = 'APPROVED'
-    GROUP BY "storeListingId"
-)
-SELECT
-     sl.id                                               AS listing_id,
-     slv.id                                              AS listing_version_id,
-     slv."createdAt"                                     AS updated_at,
-     sl.slug,
-     COALESCE(slv.name, '')                              AS agent_name,
-     slv."videoUrl"                                      AS agent_video,
-     slv."agentOutputDemoUrl"                            AS agent_output_demo,
-     COALESCE(slv."imageUrls", ARRAY[]::text[])          AS agent_image,
-     slv."isFeatured"                                    AS featured,
-     cp.username                                         AS creator_username,
-     cp."avatarUrl"                                      AS creator_avatar,
-     slv."subHeading"                                    AS sub_heading,
-     slv.description,
-     slv.categories,
-     COALESCE(arc.run_count, 0::bigint)                  AS runs,
-     COALESCE(reviews.avg_rating, 0.0)::double precision AS rating,
-     COALESCE(sav.versions, ARRAY[slv.version::text])    AS versions,
-     slv."agentGraphId"                                  AS graph_id,
-     COALESCE(
-        agv.graph_versions,
-        ARRAY[slv."agentGraphVersion"::text]
-     )                                                   AS graph_versions,
-     slv."isAvailable"                                   AS is_available,
-     COALESCE(sl."useForOnboarding", false)              AS use_for_onboarding,
-     slv."recommendedScheduleCron"                       AS recommended_schedule_cron
-FROM "StoreListing"             AS sl
-JOIN "StoreListingVersion"      AS slv
-  ON slv."storeListingId" = sl.id
- AND slv.id = sl."activeVersionId"
- AND slv."submissionStatus" = 'APPROVED'
-JOIN "AgentGraph"               AS ag
-  ON slv."agentGraphId" = ag.id
- AND slv."agentGraphVersion" = ag.version
-LEFT JOIN "Profile"             AS cp
-  ON sl."owningUserId" = cp."userId"
-LEFT JOIN "mv_review_stats"     AS reviews
-  ON sl.id = reviews."storeListingId"
-LEFT JOIN "mv_agent_run_counts" AS arc
-  ON ag.id = arc.graph_id
-LEFT JOIN store_agent_versions  AS sav
-  ON sl.id = sav."storeListingId"
-LEFT JOIN agent_graph_versions  AS agv
-  ON sl.id = agv."storeListingId"
-WHERE sl."isDeleted" = false
-  AND sl."hasApprovedVersion" = true;
-
-
--- Restore Creator view as last updated in 20250604130249_optimise_store_agent_and_creator_views,
--- with minor changes:
--- - Ensure top_categories always TEXT[]
--- - Filter out empty ('') categories
-CREATE OR REPLACE VIEW "Creator" AS
-WITH creator_listings AS (
-    SELECT
-        sl."owningUserId",
-        sl.id AS listing_id,
-        slv."agentGraphId",
-        slv.categories,
-        sr.score,
-        ar.run_count
-    FROM "StoreListing" sl
-    JOIN "StoreListingVersion" slv
-      ON slv."storeListingId" = sl.id
-     AND slv."submissionStatus" = 'APPROVED'
-    LEFT JOIN "StoreListingReview" sr
-           ON sr."storeListingVersionId" = slv.id
-    LEFT JOIN "mv_agent_run_counts" ar
-           ON ar.graph_id = slv."agentGraphId"
-    WHERE sl."isDeleted" = false
-      AND sl."hasApprovedVersion" = true
-),
-creator_stats AS (
-    SELECT
-        cl."owningUserId",
-        COUNT(DISTINCT cl.listing_id)                  AS num_agents,
-        AVG(COALESCE(cl.score, 0)::numeric)            AS agent_rating,
-        SUM(COALESCE(cl.run_count, 0))                 AS agent_runs,
-        array_agg(DISTINCT cat ORDER BY cat)
-          FILTER (WHERE cat IS NOT NULL AND cat != '') AS all_categories
-    FROM creator_listings cl
-    LEFT JOIN LATERAL unnest(COALESCE(cl.categories, ARRAY[]::text[])) AS cat ON true
-    GROUP BY cl."owningUserId"
-)
-SELECT
-    p.username,
-    p.name,
-    p."avatarUrl"                                AS avatar_url,
-    p.description,
-    COALESCE(cs.all_categories, ARRAY[]::text[]) AS top_categories,
-    p.links,
-    p."isFeatured"                               AS is_featured,
-    COALESCE(cs.num_agents, 0::bigint)           AS num_agents,
-    COALESCE(cs.agent_rating, 0.0)               AS agent_rating,
-    COALESCE(cs.agent_runs, 0::numeric)          AS agent_runs
-FROM "Profile" p
-LEFT JOIN creator_stats cs ON cs."owningUserId" = p."userId";
-
-
--- Recreate the StoreSubmission view with updated fields & query strategy:
--- - Uses mv_agent_run_counts instead of full AgentGraphExecution table scan + aggregation
--- - Renamed agent_id, agent_version -> graph_id, graph_version
--- - Renamed store_listing_version_id -> listing_version_id
--- - Renamed date_submitted -> submitted_at
--- - Renamed runs, rating -> run_count, review_avg_rating
--- - Added fields: instructions, agent_output_demo_url, review_count, is_deleted
-DROP VIEW IF EXISTS "StoreSubmission";
-CREATE OR REPLACE VIEW "StoreSubmission" AS
-WITH review_stats AS (
-    SELECT
-        "storeListingVersionId" AS version_id, -- more specific than mv_review_stats
-        avg(score)              AS avg_rating,
-        count(*)                AS review_count
-    FROM "StoreListingReview"
-    GROUP BY "storeListingVersionId"
-)
-SELECT
-    sl.id              AS listing_id,
-    sl."owningUserId"  AS user_id,
-    sl.slug            AS slug,
-
-    slv.id                   AS listing_version_id,
-    slv.version              AS listing_version,
-    slv."agentGraphId"       AS graph_id,
-    slv."agentGraphVersion"  AS graph_version,
-    slv.name                 AS name,
-    slv."subHeading"         AS sub_heading,
-    slv.description          AS description,
-    slv.instructions         AS instructions,
-    slv.categories           AS categories,
-    slv."imageUrls"          AS image_urls,
-    slv."videoUrl"           AS video_url,
-    slv."agentOutputDemoUrl" AS agent_output_demo_url,
-    slv."submittedAt"        AS submitted_at,
-    slv."changesSummary"     AS changes_summary,
-    slv."submissionStatus"   AS status,
-    slv."reviewedAt"         AS reviewed_at,
-    slv."reviewerId"         AS reviewer_id,
-    slv."reviewComments"     AS review_comments,
-    slv."internalComments"   AS internal_comments,
-    slv."isDeleted"          AS is_deleted,
-
-    COALESCE(run_stats.run_count, 0::bigint) AS run_count,
-    COALESCE(review_stats.review_count, 0::bigint) AS review_count,
-    COALESCE(review_stats.avg_rating, 0.0)::double precision AS review_avg_rating
-FROM      "StoreListing"        sl
-JOIN      "StoreListingVersion" slv     ON slv."storeListingId" = sl.id
-LEFT JOIN review_stats                  ON review_stats.version_id = slv.id
-LEFT JOIN mv_agent_run_counts run_stats ON run_stats.graph_id = slv."agentGraphId"
-WHERE     sl."isDeleted" = false;
-
-
--- Drop unused index on StoreListingReview.reviewByUserId
-DROP INDEX IF EXISTS "StoreListingReview_reviewByUserId_idx";
--- Add index on storeListingVersionId to make StoreSubmission query faster
-CREATE INDEX "StoreListingReview_storeListingVersionId_idx" ON "StoreListingReview"("storeListingVersionId");
-
-COMMIT;

autogpt_platform/backend/schema.prisma

@@ -281,6 +281,7 @@ model AgentGraph {
 
   Presets              AgentPreset[]
   LibraryAgents        LibraryAgent[]
+  StoreListings        StoreListing[]
   StoreListingVersions StoreListingVersion[]
 
   @@id(name: "graphVersionId", [id, version])
@@ -813,8 +814,10 @@ model Profile {
   createdAt DateTime @default(now())
   updatedAt DateTime @default(now()) @updatedAt
 
-  userId String @unique
-  User   User   @relation(fields: [userId], references: [id], onDelete: Cascade)
+  // Only 1 of user or group can be set.
+  // The user this profile belongs to, if any.
+  userId String?
+  User   User?   @relation(fields: [userId], references: [id], onDelete: Cascade)
 
   name        String
   username    String @unique
@@ -827,7 +830,6 @@ model Profile {
   isFeatured Boolean @default(false)
 
   LibraryAgents LibraryAgent[]
-  StoreListings StoreListing[]
 
   @@index([userId])
 }
@@ -858,9 +860,9 @@ view Creator {
 }
 
 view StoreAgent {
-  listing_id         String   @id
-  listing_version_id String
-  updated_at         DateTime
+  listing_id            String   @id
+  storeListingVersionId String
+  updated_at            DateTime
 
   slug              String
   agent_name        String
@@ -877,12 +879,10 @@ view StoreAgent {
   runs               Int
   rating             Float
   versions           String[]
-  graph_id           String
-  graph_versions     String[]
+  agentGraphVersions String[]
+  agentGraphId       String
   is_available       Boolean  @default(true)
-  use_for_onboarding Boolean  @default(false)
-
-  recommended_schedule_cron String?
+  useForOnboarding   Boolean  @default(false)
 
   // Materialized views used (refreshed every 15 minutes via pg_cron):
   // - mv_agent_run_counts - Pre-aggregated agent execution counts by agentGraphId
@@ -896,52 +896,41 @@ view StoreAgent {
 }
 
 view StoreSubmission {
-  // From StoreListing:
-  listing_id String
-  user_id    String
-  slug       String
+  listing_id               String           @id
+  user_id                  String
+  slug                     String
+  name                     String
+  sub_heading              String
+  description              String
+  image_urls               String[]
+  date_submitted           DateTime
+  status                   SubmissionStatus
+  runs                     Int
+  rating                   Float
+  agent_id                 String
+  agent_version            Int
+  store_listing_version_id String
+  reviewer_id              String?
+  review_comments          String?
+  internal_comments        String?
+  reviewed_at              DateTime?
+  changes_summary          String?
+  video_url                String?
+  categories               String[]
 
-  // From StoreListingVersion:
-  listing_version_id String @id
-  listing_version    Int
-  graph_id           String
-  graph_version      Int
-
-  name                  String
-  sub_heading           String
-  description           String
-  instructions          String?
-  categories            String[]
-  image_urls            String[]
-  video_url             String?
-  agent_output_demo_url String?
-
-  submitted_at      DateTime?
-  changes_summary   String?
-  status            SubmissionStatus
-  reviewed_at       DateTime?
-  reviewer_id       String?
-  review_comments   String?
-  internal_comments String?
-
-  is_deleted Boolean
-
-  // Aggregated from AgentGraphExecutions and StoreListingReviews:
-  run_count         Int
-  review_count      Int
-  review_avg_rating Float
+  // Index or unique are not applied to views
 }
 
 // Note: This is actually a MATERIALIZED VIEW in the database
 // Refreshed automatically every 15 minutes via pg_cron (with fallback to manual refresh)
 view mv_agent_run_counts {
-  graph_id  String @unique
-  run_count Int // excluding runs by the graph's creator
+  agentGraphId String @unique
+  run_count    Int
 
-  // Pre-aggregated count of AgentGraphExecution records by agentGraphId.
-  // Used by StoreAgent, Creator, and StoreSubmission views for performance optimization.
-  // - Should have a unique index on graph_id for fast lookups
-  // - Refresh should use CONCURRENTLY to avoid blocking reads
+  // Pre-aggregated count of AgentGraphExecution records by agentGraphId
+  // Used by StoreAgent and Creator views for performance optimization
+  // Unique index created automatically on agentGraphId for fast lookups
+  // Refresh uses CONCURRENTLY to avoid blocking reads
 }
 
 // Note: This is actually a MATERIALIZED VIEW in the database
@@ -990,18 +979,22 @@ model StoreListing {
   ActiveVersion   StoreListingVersion? @relation("ActiveVersion", fields: [activeVersionId], references: [id])
 
   // The agent link here is only so we can do lookup on agentId
-  agentGraphId String       @unique
+  agentGraphId      String
+  agentGraphVersion Int
+  AgentGraph        AgentGraph @relation(fields: [agentGraphId, agentGraphVersion], references: [id, version], onDelete: Cascade)
 
-  owningUserId   String
-  OwningUser     User    @relation(fields: [owningUserId], references: [id])
-  CreatorProfile Profile @relation(fields: [owningUserId], references: [userId], map: "StoreListing_owner_Profile_fkey", onDelete: Cascade)
+  owningUserId String
+  OwningUser   User   @relation(fields: [owningUserId], references: [id])
 
   // Relations
   Versions StoreListingVersion[] @relation("ListingVersions")
 
+  // Unique index on agentId to ensure only one listing per agent, regardless of number of versions the agent has.
+  @@unique([agentGraphId])
   @@unique([owningUserId, slug])
   // Used in the view query
   @@index([isDeleted, hasApprovedVersion])
+  @@index([agentGraphId, agentGraphVersion])
 }
 
 model StoreListingVersion {
@@ -1096,16 +1089,16 @@ model UnifiedContentEmbedding {
   // Search data
   embedding      Unsupported("vector(1536)") // pgvector embedding (extension in platform schema)
   searchableText String // Combined text for search and fallback
-  search         Unsupported("tsvector")?    @default(dbgenerated("''::tsvector")) // Full-text search (auto-populated by trigger)
+  search         Unsupported("tsvector")? @default(dbgenerated("''::tsvector")) // Full-text search (auto-populated by trigger)
   metadata       Json                        @default("{}") // Content-specific metadata
-  // NO @@index for search - GIN index "UnifiedContentEmbedding_search_idx" created via SQL migration
-  // Prisma may generate DROP INDEX on migrate dev - that's okay, migration recreates it
 
   @@unique([contentType, contentId, userId], map: "UnifiedContentEmbedding_contentType_contentId_userId_key")
   @@index([contentType])
   @@index([userId])
   @@index([contentType, userId])
   @@index([embedding], map: "UnifiedContentEmbedding_embedding_idx")
+  // NO @@index for search - GIN index "UnifiedContentEmbedding_search_idx" created via SQL migration
+  // Prisma may generate DROP INDEX on migrate dev - that's okay, migration recreates it
 }
 
 model StoreListingReview {
@@ -1122,9 +1115,8 @@ model StoreListingReview {
   score    Int
   comments String?
 
-  // Enforce one review per user per listing version
   @@unique([storeListingVersionId, reviewByUserId])
-  @@index([storeListingVersionId])
+  @@index([reviewByUserId])
 }
 
 enum SubmissionStatus {

autogpt_platform/backend/snapshots/agt_details

@@ -23,14 +23,14 @@
     "1.0.0",
     "1.1.0"
   ],
-  "graph_id": "test-graph-id",
-  "graph_versions": [
+  "agentGraphVersions": [
     "1",
     "2"
   ],
+  "agentGraphId": "test-graph-id",
   "last_updated": "2023-01-01T00:00:00",
   "recommended_schedule_cron": null,
-  "active_version_id": "test-version-id",
-  "has_approved_version": true,
+  "active_version_id": null,
+  "has_approved_version": false,
   "changelog": null
 }

autogpt_platform/backend/snapshots/creator_details

@@ -1,16 +1,14 @@
 {
-  "username": "creator1",
   "name": "Test User",
+  "username": "creator1",
   "description": "Test creator description",
-  "avatar_url": "avatar.jpg",
   "links": [
     "link1.com",
     "link2.com"
   ],
-  "is_featured": true,
-  "num_agents": 5,
-  "agent_runs": 1000,
+  "avatar_url": "avatar.jpg",
   "agent_rating": 4.8,
+  "agent_runs": 1000,
   "top_categories": [
     "category1",
     "category2"

autogpt_platform/backend/snapshots/creators_pagination

@@ -1,94 +1,54 @@
 {
   "creators": [
     {
-      "username": "creator0",
       "name": "Creator 0",
+      "username": "creator0",
       "description": "Creator 0 description",
       "avatar_url": "avatar0.jpg",
-      "links": [
-        "user0.link.com"
-      ],
-      "is_featured": false,
       "num_agents": 1,
-      "agent_runs": 100,
       "agent_rating": 4.5,
-      "top_categories": [
-        "cat1",
-        "cat2",
-        "cat3"
-      ]
+      "agent_runs": 100,
+      "is_featured": false
     },
     {
-      "username": "creator1",
       "name": "Creator 1",
+      "username": "creator1",
       "description": "Creator 1 description",
       "avatar_url": "avatar1.jpg",
-      "links": [
-        "user1.link.com"
-      ],
-      "is_featured": false,
       "num_agents": 1,
-      "agent_runs": 100,
       "agent_rating": 4.5,
-      "top_categories": [
-        "cat1",
-        "cat2",
-        "cat3"
-      ]
+      "agent_runs": 100,
+      "is_featured": false
     },
     {
-      "username": "creator2",
       "name": "Creator 2",
+      "username": "creator2",
       "description": "Creator 2 description",
       "avatar_url": "avatar2.jpg",
-      "links": [
-        "user2.link.com"
-      ],
-      "is_featured": false,
       "num_agents": 1,
-      "agent_runs": 100,
       "agent_rating": 4.5,
-      "top_categories": [
-        "cat1",
-        "cat2",
-        "cat3"
-      ]
+      "agent_runs": 100,
+      "is_featured": false
     },
     {
-      "username": "creator3",
       "name": "Creator 3",
+      "username": "creator3",
       "description": "Creator 3 description",
       "avatar_url": "avatar3.jpg",
-      "links": [
-        "user3.link.com"
-      ],
-      "is_featured": false,
       "num_agents": 1,
-      "agent_runs": 100,
       "agent_rating": 4.5,
-      "top_categories": [
-        "cat1",
-        "cat2",
-        "cat3"
-      ]
+      "agent_runs": 100,
+      "is_featured": false
     },
     {
-      "username": "creator4",
       "name": "Creator 4",
+      "username": "creator4",
       "description": "Creator 4 description",
       "avatar_url": "avatar4.jpg",
-      "links": [
-        "user4.link.com"
-      ],
-      "is_featured": false,
       "num_agents": 1,
-      "agent_runs": 100,
       "agent_rating": 4.5,
-      "top_categories": [
-        "cat1",
-        "cat2",
-        "cat3"
-      ]
+      "agent_runs": 100,
+      "is_featured": false
     }
   ],
   "pagination": {

autogpt_platform/backend/snapshots/sub_success

@@ -2,33 +2,32 @@
   "submissions": [
     {
       "listing_id": "test-listing-id",
-      "user_id": "test-user-id",
-      "slug": "test-agent",
-      "listing_version_id": "test-version-id",
-      "listing_version": 1,
-      "graph_id": "test-agent-id",
-      "graph_version": 1,
+      "agent_id": "test-agent-id",
+      "agent_version": 1,
       "name": "Test Agent",
       "sub_heading": "Test agent subheading",
+      "slug": "test-agent",
       "description": "Test agent description",
-      "instructions": "Click the button!",
-      "categories": [
-        "test-category"
-      ],
+      "instructions": null,
       "image_urls": [
         "test.jpg"
       ],
-      "video_url": "test.mp4",
-      "agent_output_demo_url": "demo_video.mp4",
-      "submitted_at": "2023-01-01T00:00:00",
-      "changes_summary": "Initial Submission",
+      "date_submitted": "2023-01-01T00:00:00",
       "status": "APPROVED",
-      "reviewed_at": null,
+      "runs": 50,
+      "rating": 4.2,
+      "store_listing_version_id": null,
+      "version": null,
       "reviewer_id": null,
       "review_comments": null,
-      "run_count": 50,
-      "review_count": 5,
-      "review_avg_rating": 4.2
+      "internal_comments": null,
+      "reviewed_at": null,
+      "changes_summary": null,
+      "video_url": "test.mp4",
+      "agent_output_demo_url": null,
+      "categories": [
+        "test-category"
+      ]
     }
   ],
   "pagination": {

autogpt_platform/backend/test/e2e_test_data.py

@@ -128,7 +128,7 @@ class TestDataCreator:
                     email = "test123@gmail.com"
                 else:
                     email = faker.unique.email()
-                password = "testpassword123"  # Standard test password # pragma: allowlist secret # noqa
+                password = "testpassword123"  # Standard test password
                 user_id = f"test-user-{i}-{faker.uuid4()}"
 
                 # Create user in Supabase Auth (if needed)
@@ -571,8 +571,8 @@ class TestDataCreator:
         if test_user and self.agent_graphs:
             test_submission_data = {
                 "user_id": test_user["id"],
-                "graph_id": self.agent_graphs[0]["id"],
-                "graph_version": 1,
+                "agent_id": self.agent_graphs[0]["id"],
+                "agent_version": 1,
                 "slug": "test-agent-submission",
                 "name": "Test Agent Submission",
                 "sub_heading": "A test agent for frontend testing",
@@ -593,9 +593,9 @@ class TestDataCreator:
                 print("✅ Created special test store submission for test123@gmail.com")
 
                 # ALWAYS approve and feature the test submission
-                if test_submission.listing_version_id:
+                if test_submission.store_listing_version_id:
                     approved_submission = await review_store_submission(
-                        store_listing_version_id=test_submission.listing_version_id,
+                        store_listing_version_id=test_submission.store_listing_version_id,
                         is_approved=True,
                         external_comments="Test submission approved",
                         internal_comments="Auto-approved test submission",
@@ -605,7 +605,7 @@ class TestDataCreator:
                     print("✅ Approved test store submission")
 
                     await prisma.storelistingversion.update(
-                        where={"id": test_submission.listing_version_id},
+                        where={"id": test_submission.store_listing_version_id},
                         data={"isFeatured": True},
                     )
                     featured_count += 1
@@ -640,8 +640,8 @@ class TestDataCreator:
 
                     submission = await create_store_submission(
                         user_id=user["id"],
-                        graph_id=graph["id"],
-                        graph_version=graph.get("version", 1),
+                        agent_id=graph["id"],
+                        agent_version=graph.get("version", 1),
                         slug=faker.slug(),
                         name=graph.get("name", faker.sentence(nb_words=3)),
                         sub_heading=faker.sentence(),
@@ -654,7 +654,7 @@ class TestDataCreator:
                     submissions.append(submission.model_dump())
                     print(f"✅ Created store submission: {submission.name}")
 
-                    if submission.listing_version_id:
+                    if submission.store_listing_version_id:
                         # DETERMINISTIC: First N submissions are always approved
                         # First GUARANTEED_FEATURED_AGENTS of those are always featured
                         should_approve = (
@@ -667,7 +667,7 @@ class TestDataCreator:
                             try:
                                 reviewer_id = random.choice(self.users)["id"]
                                 approved_submission = await review_store_submission(
-                                    store_listing_version_id=submission.listing_version_id,
+                                    store_listing_version_id=submission.store_listing_version_id,
                                     is_approved=True,
                                     external_comments="Auto-approved for E2E testing",
                                     internal_comments="Automatically approved by E2E test data script",
@@ -683,7 +683,9 @@ class TestDataCreator:
                                 if should_feature:
                                     try:
                                         await prisma.storelistingversion.update(
-                                            where={"id": submission.listing_version_id},
+                                            where={
+                                                "id": submission.store_listing_version_id
+                                            },
                                             data={"isFeatured": True},
                                         )
                                         featured_count += 1
@@ -697,7 +699,9 @@ class TestDataCreator:
                                 elif random.random() < 0.2:
                                     try:
                                         await prisma.storelistingversion.update(
-                                            where={"id": submission.listing_version_id},
+                                            where={
+                                                "id": submission.store_listing_version_id
+                                            },
                                             data={"isFeatured": True},
                                         )
                                         featured_count += 1
@@ -717,7 +721,7 @@ class TestDataCreator:
                             try:
                                 reviewer_id = random.choice(self.users)["id"]
                                 await review_store_submission(
-                                    store_listing_version_id=submission.listing_version_id,
+                                    store_listing_version_id=submission.store_listing_version_id,
                                     is_approved=False,
                                     external_comments="Submission rejected - needs improvements",
                                     internal_comments="Automatically rejected by E2E test data script",

autogpt_platform/backend/test/test_data_creator.py

@@ -394,6 +394,7 @@ async def main():
         listing = await db.storelisting.create(
             data={
                 "agentGraphId": graph.id,
+                "agentGraphVersion": graph.version,
                 "owningUserId": user.id,
                 "hasApprovedVersion": random.choice([True, False]),
                 "slug": slug,

autogpt_platform/frontend/components.json

@@ -10,7 +10,6 @@
     "cssVariables": false,
     "prefix": ""
   },
-  "iconLibrary": "radix",
   "aliases": {
     "components": "@/components",
     "utils": "@/lib/utils"

autogpt_platform/frontend/src/app/(platform)/admin/marketplace/actions.ts

@@ -1,39 +1,33 @@
 "use server";
 
 import { revalidatePath } from "next/cache";
+import BackendApi from "@/lib/autogpt-server-api";
 import {
-  getV2GetAdminListingsHistory,
-  postV2ReviewStoreSubmission,
-  getV2AdminDownloadAgentFile,
-} from "@/app/api/__generated__/endpoints/admin/admin";
-import { okData } from "@/app/api/helpers";
-import { SubmissionStatus } from "@/app/api/__generated__/models/submissionStatus";
+  StoreListingsWithVersionsResponse,
+  SubmissionStatus,
+} from "@/lib/autogpt-server-api/types";
 
 export async function approveAgent(formData: FormData) {
-  const storeListingVersionId = formData.get("id") as string;
-  const comments = formData.get("comments") as string;
-
-  await postV2ReviewStoreSubmission(storeListingVersionId, {
-    store_listing_version_id: storeListingVersionId,
+  const data = {
+    store_listing_version_id: formData.get("id") as string,
     is_approved: true,
-    comments,
-  });
+    comments: formData.get("comments") as string,
+  };
+  const api = new BackendApi();
+  await api.reviewSubmissionAdmin(data.store_listing_version_id, data);
 
   revalidatePath("/admin/marketplace");
 }
 
 export async function rejectAgent(formData: FormData) {
-  const storeListingVersionId = formData.get("id") as string;
-  const comments = formData.get("comments") as string;
-  const internal_comments =
-    (formData.get("internal_comments") as string) || undefined;
-
-  await postV2ReviewStoreSubmission(storeListingVersionId, {
-    store_listing_version_id: storeListingVersionId,
+  const data = {
+    store_listing_version_id: formData.get("id") as string,
     is_approved: false,
-    comments,
-    internal_comments,
-  });
+    comments: formData.get("comments") as string,
+    internal_comments: formData.get("internal_comments") as string,
+  };
+  const api = new BackendApi();
+  await api.reviewSubmissionAdmin(data.store_listing_version_id, data);
 
   revalidatePath("/admin/marketplace");
 }
@@ -43,18 +37,26 @@ export async function getAdminListingsWithVersions(
   search?: string,
   page: number = 1,
   pageSize: number = 20,
-) {
-  const response = await getV2GetAdminListingsHistory({
-    status,
-    search,
+): Promise<StoreListingsWithVersionsResponse> {
+  const data: Record<string, any> = {
     page,
     page_size: pageSize,
-  });
+  };
 
-  return okData(response);
+  if (status) {
+    data.status = status;
+  }
+
+  if (search) {
+    data.search = search;
+  }
+  const api = new BackendApi();
+  const response = await api.getAdminListingsWithVersions(data);
+  return response;
 }
 
 export async function downloadAsAdmin(storeListingVersion: string) {
-  const response = await getV2AdminDownloadAgentFile(storeListingVersion);
-  return okData(response);
+  const api = new BackendApi();
+  const file = await api.downloadStoreAgentAdmin(storeListingVersion);
+  return file;
 }

autogpt_platform/frontend/src/app/(platform)/admin/marketplace/components/AdminAgentsDataTable.tsx

@@ -6,8 +6,10 @@ import {
   TableHeader,
   TableRow,
 } from "@/components/__legacy__/ui/table";
-import type { StoreSubmissionAdminView } from "@/app/api/__generated__/models/storeSubmissionAdminView";
-import type { SubmissionStatus } from "@/app/api/__generated__/models/submissionStatus";
+import {
+  StoreSubmission,
+  SubmissionStatus,
+} from "@/lib/autogpt-server-api/types";
 import { PaginationControls } from "../../../../../components/__legacy__/ui/pagination-controls";
 import { getAdminListingsWithVersions } from "@/app/(platform)/admin/marketplace/actions";
 import { ExpandableRow } from "./ExpandleRow";
@@ -15,14 +17,12 @@ import { SearchAndFilterAdminMarketplace } from "./SearchFilterForm";
 
 // Helper function to get the latest version by version number
 const getLatestVersionByNumber = (
-  versions: StoreSubmissionAdminView[] | undefined,
-): StoreSubmissionAdminView | null => {
+  versions: StoreSubmission[],
+): StoreSubmission | null => {
   if (!versions || versions.length === 0) return null;
   return versions.reduce(
     (latest, current) =>
-      (current.listing_version ?? 0) > (latest.listing_version ?? 1)
-        ? current
-        : latest,
+      (current.version ?? 0) > (latest.version ?? 1) ? current : latest,
     versions[0],
   );
 };
@@ -37,14 +37,12 @@ export async function AdminAgentsDataTable({
   initialSearch?: string;
 }) {
   // Server-side data fetching
-  const data = await getAdminListingsWithVersions(
+  const { listings, pagination } = await getAdminListingsWithVersions(
     initialStatus,
     initialSearch,
     initialPage,
     10,
   );
-  const listings = data?.listings ?? [];
-  const pagination = data?.pagination;
 
   return (
     <div className="space-y-4">
@@ -94,7 +92,7 @@ export async function AdminAgentsDataTable({
 
       <PaginationControls
         currentPage={initialPage}
-        totalPages={pagination?.total_pages ?? 1}
+        totalPages={pagination.total_pages}
       />
     </div>
   );

autogpt_platform/frontend/src/app/(platform)/admin/marketplace/components/ApproveRejectButton.tsx

@@ -13,7 +13,7 @@ import {
 } from "@/components/__legacy__/ui/dialog";
 import { Label } from "@/components/__legacy__/ui/label";
 import { Textarea } from "@/components/__legacy__/ui/textarea";
-import type { StoreSubmissionAdminView } from "@/app/api/__generated__/models/storeSubmissionAdminView";
+import type { StoreSubmission } from "@/lib/autogpt-server-api/types";
 import { useRouter } from "next/navigation";
 import {
   approveAgent,
@@ -23,7 +23,7 @@ import {
 export function ApproveRejectButtons({
   version,
 }: {
-  version: StoreSubmissionAdminView;
+  version: StoreSubmission;
 }) {
   const router = useRouter();
   const [isApproveDialogOpen, setIsApproveDialogOpen] = useState(false);
@@ -95,7 +95,7 @@ export function ApproveRejectButtons({
             <input
               type="hidden"
               name="id"
-              value={version.listing_version_id || ""}
+              value={version.store_listing_version_id || ""}
             />
 
             <div className="grid gap-4 py-4">
@@ -142,7 +142,7 @@ export function ApproveRejectButtons({
             <input
               type="hidden"
               name="id"
-              value={version.listing_version_id || ""}
+              value={version.store_listing_version_id || ""}
             />
 
             <div className="grid gap-4 py-4">

autogpt_platform/frontend/src/app/(platform)/admin/marketplace/components/ExpandleRow.tsx

@@ -12,9 +12,11 @@ import {
 import { Badge } from "@/components/__legacy__/ui/badge";
 import { ChevronDown, ChevronRight } from "lucide-react";
 import { formatDistanceToNow } from "date-fns";
-import type { StoreListingWithVersionsAdminView } from "@/app/api/__generated__/models/storeListingWithVersionsAdminView";
-import type { StoreSubmissionAdminView } from "@/app/api/__generated__/models/storeSubmissionAdminView";
-import { SubmissionStatus } from "@/app/api/__generated__/models/submissionStatus";
+import {
+  type StoreListingWithVersions,
+  type StoreSubmission,
+  SubmissionStatus,
+} from "@/lib/autogpt-server-api/types";
 import { ApproveRejectButtons } from "./ApproveRejectButton";
 import { DownloadAgentAdminButton } from "./DownloadAgentButton";
 
@@ -36,8 +38,8 @@ export function ExpandableRow({
   listing,
   latestVersion,
 }: {
-  listing: StoreListingWithVersionsAdminView;
-  latestVersion: StoreSubmissionAdminView | null;
+  listing: StoreListingWithVersions;
+  latestVersion: StoreSubmission | null;
 }) {
   const [expanded, setExpanded] = useState(false);
 
@@ -67,17 +69,17 @@ export function ExpandableRow({
           {latestVersion?.status && getStatusBadge(latestVersion.status)}
         </TableCell>
         <TableCell onClick={() => setExpanded(!expanded)}>
-          {latestVersion?.submitted_at
-            ? formatDistanceToNow(new Date(latestVersion.submitted_at), {
+          {latestVersion?.date_submitted
+            ? formatDistanceToNow(new Date(latestVersion.date_submitted), {
                 addSuffix: true,
               })
             : "Unknown"}
         </TableCell>
         <TableCell className="text-right">
           <div className="flex justify-end gap-2">
-            {latestVersion?.listing_version_id && (
+            {latestVersion?.store_listing_version_id && (
               <DownloadAgentAdminButton
-                storeListingVersionId={latestVersion.listing_version_id}
+                storeListingVersionId={latestVersion.store_listing_version_id}
               />
             )}
 
@@ -113,17 +115,14 @@ export function ExpandableRow({
                   </TableRow>
                 </TableHeader>
                 <TableBody>
-                  {(listing.versions ?? [])
-                    .sort(
-                      (a, b) =>
-                        (b.listing_version ?? 1) - (a.listing_version ?? 0),
-                    )
+                  {listing.versions
+                    .sort((a, b) => (b.version ?? 1) - (a.version ?? 0))
                     .map((version) => (
-                      <TableRow key={version.listing_version_id}>
+                      <TableRow key={version.store_listing_version_id}>
                         <TableCell>
-                          v{version.listing_version || "?"}
-                          {version.listing_version_id ===
-                            listing.active_listing_version_id && (
+                          v{version.version || "?"}
+                          {version.store_listing_version_id ===
+                            listing.active_version_id && (
                             <Badge className="ml-2 bg-blue-500">Active</Badge>
                           )}
                         </TableCell>
@@ -132,9 +131,9 @@ export function ExpandableRow({
                           {version.changes_summary || "No summary"}
                         </TableCell>
                         <TableCell>
-                          {version.submitted_at
+                          {version.date_submitted
                             ? formatDistanceToNow(
-                                new Date(version.submitted_at),
+                                new Date(version.date_submitted),
                                 { addSuffix: true },
                               )
                             : "Unknown"}
@@ -183,10 +182,10 @@ export function ExpandableRow({
                         {/* <TableCell>{version.categories.join(", ")}</TableCell> */}
                         <TableCell className="text-right">
                           <div className="flex justify-end gap-2">
-                            {version.listing_version_id && (
+                            {version.store_listing_version_id && (
                               <DownloadAgentAdminButton
                                 storeListingVersionId={
-                                  version.listing_version_id
+                                  version.store_listing_version_id
                                 }
                               />
                             )}

autogpt_platform/frontend/src/app/(platform)/admin/marketplace/components/SearchFilterForm.tsx

@@ -12,7 +12,7 @@ import {
   SelectTrigger,
   SelectValue,
 } from "@/components/__legacy__/ui/select";
-import { SubmissionStatus } from "@/app/api/__generated__/models/submissionStatus";
+import { SubmissionStatus } from "@/lib/autogpt-server-api/types";
 
 export function SearchAndFilterAdminMarketplace({
   initialSearch,

autogpt_platform/frontend/src/app/(platform)/admin/marketplace/page.tsx

@@ -1,11 +1,11 @@
 import { withRoleAccess } from "@/lib/withRoleAccess";
 import { Suspense } from "react";
-import type { SubmissionStatus } from "@/app/api/__generated__/models/submissionStatus";
+import type { SubmissionStatus } from "@/lib/autogpt-server-api/types";
 import { AdminAgentsDataTable } from "./components/AdminAgentsDataTable";
 
 type MarketplaceAdminPageSearchParams = {
   page?: string;
-  status?: SubmissionStatus;
+  status?: string;
   search?: string;
 };
 
@@ -15,7 +15,7 @@ async function AdminMarketplaceDashboard({
   searchParams: MarketplaceAdminPageSearchParams;
 }) {
   const page = searchParams.page ? Number.parseInt(searchParams.page) : 1;
-  const status = searchParams.status;
+  const status = searchParams.status as SubmissionStatus | undefined;
   const search = searchParams.search;
 
   return (

autogpt_platform/frontend/src/app/(platform)/copilot/components/ChatMessagesContainer/ChatMessagesContainer.tsx

@@ -5,19 +5,15 @@ import {
 } from "@/components/ai-elements/conversation";
 import { Message, MessageContent } from "@/components/ai-elements/message";
 import { LoadingSpinner } from "@/components/atoms/LoadingSpinner/LoadingSpinner";
-import { FileUIPart, ToolUIPart, UIDataTypes, UIMessage, UITools } from "ai";
+import { FileUIPart, UIDataTypes, UIMessage, UITools } from "ai";
 import { TOOL_PART_PREFIX } from "../JobStatsBar/constants";
 import { TurnStatsBar } from "../JobStatsBar/TurnStatsBar";
 import { parseSpecialMarkers } from "./helpers";
 import { AssistantMessageActions } from "./components/AssistantMessageActions";
-import { CollapsedToolGroup } from "./components/CollapsedToolGroup";
 import { MessageAttachments } from "./components/MessageAttachments";
 import { MessagePartRenderer } from "./components/MessagePartRenderer";
-import { ReasoningCollapse } from "./components/ReasoningCollapse";
 import { ThinkingIndicator } from "./components/ThinkingIndicator";
 
-type MessagePart = UIMessage<unknown, UIDataTypes, UITools>["parts"][number];
-
 interface Props {
   messages: UIMessage<unknown, UIDataTypes, UITools>[];
   status: string;
@@ -27,132 +23,6 @@ interface Props {
   sessionID?: string | null;
 }
 
-function isCompletedToolPart(part: MessagePart): part is ToolUIPart {
-  return (
-    part.type.startsWith("tool-") &&
-    "state" in part &&
-    (part.state === "output-available" || part.state === "output-error")
-  );
-}
-
-type RenderSegment =
-  | { kind: "part"; part: MessagePart; index: number }
-  | { kind: "collapsed-group"; parts: ToolUIPart[] };
-
-// Tool types that have custom renderers and should NOT be collapsed
-const CUSTOM_TOOL_TYPES = new Set([
-  "tool-find_block",
-  "tool-find_agent",
-  "tool-find_library_agent",
-  "tool-search_docs",
-  "tool-get_doc_page",
-  "tool-run_block",
-  "tool-run_mcp_tool",
-  "tool-run_agent",
-  "tool-schedule_agent",
-  "tool-create_agent",
-  "tool-edit_agent",
-  "tool-view_agent_output",
-  "tool-search_feature_requests",
-  "tool-create_feature_request",
-]);
-
-/**
- * Groups consecutive completed generic tool parts into collapsed segments.
- * Non-generic tools (those with custom renderers) and active/streaming tools
- * are left as individual parts.
- */
-function buildRenderSegments(
-  parts: MessagePart[],
-  baseIndex = 0,
-): RenderSegment[] {
-  const segments: RenderSegment[] = [];
-  let pendingGroup: Array<{ part: ToolUIPart; index: number }> | null = null;
-
-  function flushGroup() {
-    if (!pendingGroup) return;
-    if (pendingGroup.length >= 2) {
-      segments.push({
-        kind: "collapsed-group",
-        parts: pendingGroup.map((p) => p.part),
-      });
-    } else {
-      for (const p of pendingGroup) {
-        segments.push({ kind: "part", part: p.part, index: p.index });
-      }
-    }
-    pendingGroup = null;
-  }
-
-  parts.forEach((part, i) => {
-    const absoluteIndex = baseIndex + i;
-    const isGenericCompletedTool =
-      isCompletedToolPart(part) && !CUSTOM_TOOL_TYPES.has(part.type);
-
-    if (isGenericCompletedTool) {
-      if (!pendingGroup) pendingGroup = [];
-      pendingGroup.push({ part: part as ToolUIPart, index: absoluteIndex });
-    } else {
-      flushGroup();
-      segments.push({ kind: "part", part, index: absoluteIndex });
-    }
-  });
-
-  flushGroup();
-  return segments;
-}
-
-/**
- * For finalized assistant messages, split parts into "reasoning" (intermediate
- * text + tools before the final response) and "response" (final text after the
- * last tool). If there are no tools, everything is response.
- */
-function splitReasoningAndResponse(parts: MessagePart[]): {
-  reasoning: MessagePart[];
-  response: MessagePart[];
-} {
-  const lastToolIndex = parts.findLastIndex((p) => p.type.startsWith("tool-"));
-
-  // No tools → everything is response
-  if (lastToolIndex === -1) {
-    return { reasoning: [], response: parts };
-  }
-
-  // Check if there's any text after the last tool
-  const hasResponseAfterTools = parts
-    .slice(lastToolIndex + 1)
-    .some((p) => p.type === "text");
-
-  if (!hasResponseAfterTools) {
-    // No final text response → don't collapse anything
-    return { reasoning: [], response: parts };
-  }
-
-  return {
-    reasoning: parts.slice(0, lastToolIndex + 1),
-    response: parts.slice(lastToolIndex + 1),
-  };
-}
-
-function renderSegments(
-  segments: RenderSegment[],
-  messageID: string,
-): React.ReactNode[] {
-  return segments.map((seg, segIdx) => {
-    if (seg.kind === "collapsed-group") {
-      return <CollapsedToolGroup key={`group-${segIdx}`} parts={seg.parts} />;
-    }
-    return (
-      <MessagePartRenderer
-        key={`${messageID}-${seg.index}`}
-        part={seg.part}
-        messageID={messageID}
-        partIndex={seg.index}
-      />
-    );
-  });
-}
-
 /** Collect all messages belonging to a turn: the user message + every
  *  assistant message up to (but not including) the next user message. */
 function getTurnMessages(
@@ -249,24 +119,6 @@ export function ChatMessagesContainer({
             (p): p is FileUIPart => p.type === "file",
           );
 
-          // For finalized assistant messages, split into reasoning + response.
-          // During streaming, show everything normally with tool collapsing.
-          const isFinalized =
-            message.role === "assistant" && !isCurrentlyStreaming;
-          const { reasoning, response } = isFinalized
-            ? splitReasoningAndResponse(message.parts)
-            : { reasoning: [] as MessagePart[], response: message.parts };
-          const hasReasoning = reasoning.length > 0;
-
-          const responseStartIndex = message.parts.length - response.length;
-          const responseSegments =
-            message.role === "assistant"
-              ? buildRenderSegments(response, responseStartIndex)
-              : null;
-          const reasoningSegments = hasReasoning
-            ? buildRenderSegments(reasoning, 0)
-            : null;
-
           return (
             <Message from={message.role} key={message.id}>
               <MessageContent
@@ -276,21 +128,14 @@ export function ChatMessagesContainer({
                   "group-[.is-assistant]:bg-transparent group-[.is-assistant]:text-slate-900"
                 }
               >
-                {hasReasoning && reasoningSegments && (
-                  <ReasoningCollapse>
-                    {renderSegments(reasoningSegments, message.id)}
-                  </ReasoningCollapse>
-                )}
-                {responseSegments
-                  ? renderSegments(responseSegments, message.id)
-                  : message.parts.map((part, i) => (
-                      <MessagePartRenderer
-                        key={`${message.id}-${i}`}
-                        part={part}
-                        messageID={message.id}
-                        partIndex={i}
-                      />
-                    ))}
+                {message.parts.map((part, i) => (
+                  <MessagePartRenderer
+                    key={`${message.id}-${i}`}
+                    part={part}
+                    messageID={message.id}
+                    partIndex={i}
+                  />
+                ))}
                 {isLastInTurn && !isCurrentlyStreaming && (
                   <TurnStatsBar
                     turnMessages={getTurnMessages(messages, messageIndex)}

autogpt_platform/frontend/src/app/(platform)/copilot/components/ChatMessagesContainer/components/CollapsedToolGroup.tsx

@@ -1,152 +0,0 @@
-"use client";
-
-import { useId, useState } from "react";
-import {
-  ArrowsClockwiseIcon,
-  CaretRightIcon,
-  CheckCircleIcon,
-  FileIcon,
-  FilesIcon,
-  GearIcon,
-  GlobeIcon,
-  ListChecksIcon,
-  MagnifyingGlassIcon,
-  MonitorIcon,
-  PencilSimpleIcon,
-  TerminalIcon,
-  TrashIcon,
-  WarningDiamondIcon,
-} from "@phosphor-icons/react";
-import type { ToolUIPart } from "ai";
-import {
-  type ToolCategory,
-  extractToolName,
-  getAnimationText,
-  getToolCategory,
-} from "../../../tools/GenericTool/helpers";
-
-interface Props {
-  parts: ToolUIPart[];
-}
-
-/** Category icon matching GenericTool's ToolIcon for completed states. */
-function EntryIcon({
-  category,
-  isError,
-}: {
-  category: ToolCategory;
-  isError: boolean;
-}) {
-  if (isError) {
-    return (
-      <WarningDiamondIcon size={14} weight="regular" className="text-red-500" />
-    );
-  }
-
-  const iconClass = "text-green-500";
-  switch (category) {
-    case "bash":
-      return <TerminalIcon size={14} weight="regular" className={iconClass} />;
-    case "web":
-      return <GlobeIcon size={14} weight="regular" className={iconClass} />;
-    case "browser":
-      return <MonitorIcon size={14} weight="regular" className={iconClass} />;
-    case "file-read":
-    case "file-write":
-      return <FileIcon size={14} weight="regular" className={iconClass} />;
-    case "file-delete":
-      return <TrashIcon size={14} weight="regular" className={iconClass} />;
-    case "file-list":
-      return <FilesIcon size={14} weight="regular" className={iconClass} />;
-    case "search":
-      return (
-        <MagnifyingGlassIcon size={14} weight="regular" className={iconClass} />
-      );
-    case "edit":
-      return (
-        <PencilSimpleIcon size={14} weight="regular" className={iconClass} />
-      );
-    case "todo":
-      return (
-        <ListChecksIcon size={14} weight="regular" className={iconClass} />
-      );
-    case "compaction":
-      return (
-        <ArrowsClockwiseIcon size={14} weight="regular" className={iconClass} />
-      );
-    default:
-      return <GearIcon size={14} weight="regular" className={iconClass} />;
-  }
-}
-
-export function CollapsedToolGroup({ parts }: Props) {
-  const [expanded, setExpanded] = useState(false);
-  const panelId = useId();
-
-  const errorCount = parts.filter((p) => p.state === "output-error").length;
-  const label =
-    errorCount > 0
-      ? `${parts.length} tool calls (${errorCount} failed)`
-      : `${parts.length} tool calls completed`;
-
-  return (
-    <div className="py-1">
-      <button
-        type="button"
-        onClick={() => setExpanded(!expanded)}
-        aria-expanded={expanded}
-        aria-controls={panelId}
-        className="flex items-center gap-1.5 text-sm text-muted-foreground transition-colors hover:text-foreground"
-      >
-        <CaretRightIcon
-          size={12}
-          weight="bold"
-          className={
-            "transition-transform duration-150 " + (expanded ? "rotate-90" : "")
-          }
-        />
-        {errorCount > 0 ? (
-          <WarningDiamondIcon
-            size={14}
-            weight="regular"
-            className="text-red-500"
-          />
-        ) : (
-          <CheckCircleIcon
-            size={14}
-            weight="regular"
-            className="text-green-500"
-          />
-        )}
-        <span>{label}</span>
-      </button>
-
-      {expanded && (
-        <div
-          id={panelId}
-          className="ml-5 mt-1 space-y-0.5 border-l border-neutral-200 pl-3"
-        >
-          {parts.map((part) => {
-            const toolName = extractToolName(part);
-            const category = getToolCategory(toolName);
-            const text = getAnimationText(part, category);
-            const isError = part.state === "output-error";
-
-            return (
-              <div
-                key={part.toolCallId}
-                className={
-                  "flex items-center gap-1.5 text-xs " +
-                  (isError ? "text-red-500" : "text-muted-foreground")
-                }
-              >
-                <EntryIcon category={category} isError={isError} />
-                <span>{text}</span>
-              </div>
-            );
-          })}
-        </div>
-      )}
-    </div>
-  );
-}

autogpt_platform/frontend/src/app/(platform)/copilot/components/ChatMessagesContainer/components/FeedbackModal.tsx

@@ -15,7 +15,6 @@ export function FeedbackModal({ isOpen, onSubmit, onCancel }: Props) {
   const [comment, setComment] = useState("");
 
   function handleSubmit() {
-    if (!comment.trim()) return;
     onSubmit(comment);
     setComment("");
   }
@@ -37,7 +36,7 @@ export function FeedbackModal({ isOpen, onSubmit, onCancel }: Props) {
     >
       <Dialog.Content>
         <div className="mx-auto w-[95%] space-y-4">
-          <p className="text-sm text-muted-foreground">
+          <p className="text-sm text-slate-600">
             Your feedback helps us improve. Share details below.
           </p>
           <Textarea
@@ -49,18 +48,12 @@ export function FeedbackModal({ isOpen, onSubmit, onCancel }: Props) {
             className="resize-none"
           />
           <div className="flex items-center justify-between">
-            <p className="text-xs text-muted-foreground">
-              {comment.length}/2000
-            </p>
+            <p className="text-xs text-slate-400">{comment.length}/2000</p>
             <div className="flex gap-2">
               <Button variant="outline" size="sm" onClick={handleClose}>
                 Cancel
               </Button>
-              <Button
-                size="sm"
-                onClick={handleSubmit}
-                disabled={!comment.trim()}
-              >
+              <Button size="sm" onClick={handleSubmit}>
                 Submit feedback
               </Button>
             </div>

autogpt_platform/frontend/src/app/(platform)/copilot/components/ChatMessagesContainer/components/MessagePartRenderer.tsx

@@ -10,7 +10,6 @@ import {
   SearchFeatureRequestsTool,
 } from "../../../tools/FeatureRequests/FeatureRequests";
 import { FindAgentsTool } from "../../../tools/FindAgents/FindAgents";
-import { FolderTool } from "../../../tools/FolderTool/FolderTool";
 import { FindBlocksTool } from "../../../tools/FindBlocks/FindBlocks";
 import { GenericTool } from "../../../tools/GenericTool/GenericTool";
 import { RunAgentTool } from "../../../tools/RunAgent/RunAgent";
@@ -146,13 +145,6 @@ export function MessagePartRenderer({ part, messageID, partIndex }: Props) {
       return <SearchFeatureRequestsTool key={key} part={part as ToolUIPart} />;
     case "tool-create_feature_request":
       return <CreateFeatureRequestTool key={key} part={part as ToolUIPart} />;
-    case "tool-create_folder":
-    case "tool-list_folders":
-    case "tool-update_folder":
-    case "tool-move_folder":
-    case "tool-delete_folder":
-    case "tool-move_agents_to_folder":
-      return <FolderTool key={key} part={part as ToolUIPart} />;
     default:
       // Render a generic tool indicator for SDK built-in
       // tools (Read, Glob, Grep, etc.) or any unrecognized tool

autogpt_platform/frontend/src/app/(platform)/copilot/components/ChatMessagesContainer/components/ReasoningCollapse.tsx

@@ -1,27 +0,0 @@
-"use client";
-
-import { LightbulbIcon } from "@phosphor-icons/react";
-import { Dialog } from "@/components/molecules/Dialog/Dialog";
-
-interface Props {
-  children: React.ReactNode;
-}
-
-export function ReasoningCollapse({ children }: Props) {
-  return (
-    <Dialog title="Reasoning">
-      <Dialog.Trigger>
-        <button
-          type="button"
-          className="flex items-center gap-1 text-xs text-zinc-500 transition-colors hover:text-zinc-700"
-        >
-          <LightbulbIcon size={12} weight="bold" />
-          <span>Show reasoning</span>
-        </button>
-      </Dialog.Trigger>
-      <Dialog.Content>
-        <div className="space-y-1">{children}</div>
-      </Dialog.Content>
-    </Dialog>
-  );
-}

autogpt_platform/frontend/src/app/(platform)/copilot/helpers/convertChatSessionToUiMessages.ts

@@ -181,14 +181,6 @@ export function convertChatSessionMessagesToUiMessages(
 
     if (parts.length === 0) return;
 
-    // Merge consecutive assistant messages into a single UIMessage
-    // to avoid split bubbles on page reload.
-    const prevUI = uiMessages[uiMessages.length - 1];
-    if (msg.role === "assistant" && prevUI && prevUI.role === "assistant") {
-      prevUI.parts.push(...parts);
-      return;
-    }
-
     uiMessages.push({
       id: `${sessionId}-${index}`,
       role: msg.role,

autogpt_platform/frontend/src/app/(platform)/copilot/tools/CreateAgent/helpers.tsx

@@ -10,7 +10,7 @@ import {
   WarningDiamondIcon,
 } from "@phosphor-icons/react";
 import type { ToolUIPart } from "ai";
-import { ScaleLoader } from "../../components/ScaleLoader/ScaleLoader";
+import { OrbitLoader } from "../../components/OrbitLoader/OrbitLoader";
 
 export type CreateAgentToolOutput =
   | AgentPreviewResponse
@@ -134,7 +134,7 @@ export function ToolIcon({
     );
   }
   if (isStreaming) {
-    return <ScaleLoader size={14} />;
+    return <OrbitLoader size={24} />;
   }
   return <PlusIcon size={14} weight="regular" className="text-neutral-400" />;
 }

autogpt_platform/frontend/src/app/(platform)/copilot/tools/EditAgent/helpers.tsx

@@ -9,7 +9,7 @@ import {
   WarningDiamondIcon,
 } from "@phosphor-icons/react";
 import type { ToolUIPart } from "ai";
-import { ScaleLoader } from "../../components/ScaleLoader/ScaleLoader";
+import { OrbitLoader } from "../../components/OrbitLoader/OrbitLoader";
 
 export type EditAgentToolOutput =
   | AgentPreviewResponse
@@ -121,7 +121,7 @@ export function ToolIcon({
     );
   }
   if (isStreaming) {
-    return <ScaleLoader size={14} />;
+    return <OrbitLoader size={24} />;
   }
   return (
     <PencilLineIcon size={14} weight="regular" className="text-neutral-400" />

autogpt_platform/frontend/src/app/(platform)/copilot/tools/FolderTool/FolderTool.tsx

@@ -1,296 +0,0 @@
-"use client";
-
-import type { ToolUIPart } from "ai";
-import {
-  FileIcon,
-  FolderIcon,
-  FolderPlusIcon,
-  FoldersIcon,
-  TrashIcon,
-  WarningDiamondIcon,
-} from "@phosphor-icons/react";
-import {
-  File as TreeFile,
-  Folder as TreeFolder,
-  Tree,
-  type TreeViewElement,
-} from "@/components/molecules/file-tree";
-import { MorphingTextAnimation } from "../../components/MorphingTextAnimation/MorphingTextAnimation";
-import { ToolAccordion } from "../../components/ToolAccordion/ToolAccordion";
-import {
-  ContentCard,
-  ContentCardHeader,
-  ContentCardTitle,
-  ContentGrid,
-  ContentHint,
-  ContentMessage,
-} from "../../components/ToolAccordion/AccordionContent";
-import { OrbitLoader } from "../../components/OrbitLoader/OrbitLoader";
-import {
-  getAnimationText,
-  getFolderToolOutput,
-  isAgentsMoved,
-  isErrorOutput,
-  isFolderCreated,
-  isFolderDeleted,
-  isFolderList,
-  isFolderMoved,
-  isFolderUpdated,
-  type FolderInfo,
-  type FolderToolOutput,
-  type FolderTreeInfo,
-} from "./helpers";
-
-interface Props {
-  part: ToolUIPart;
-}
-
-/* ------------------------------------------------------------------ */
-/*  Icons                                                              */
-/* ------------------------------------------------------------------ */
-
-function ToolStatusIcon({
-  isStreaming,
-  isError,
-}: {
-  isStreaming: boolean;
-  isError: boolean;
-}) {
-  if (isError) {
-    return (
-      <WarningDiamondIcon size={14} weight="regular" className="text-red-500" />
-    );
-  }
-  if (isStreaming) {
-    return <OrbitLoader size={14} />;
-  }
-  return <FolderIcon size={14} weight="regular" className="text-neutral-400" />;
-}
-
-/* ------------------------------------------------------------------ */
-/*  Folder card                                                        */
-/* ------------------------------------------------------------------ */
-
-function FolderCard({ folder }: { folder: FolderInfo }) {
-  return (
-    <ContentCard>
-      <ContentCardHeader>
-        <div className="flex items-center gap-2">
-          {folder.color ? (
-            <span
-              className="inline-block h-3 w-3 rounded-full"
-              style={{ backgroundColor: folder.color }}
-            />
-          ) : (
-            <FolderIcon size={14} weight="fill" className="text-neutral-600" />
-          )}
-          <ContentCardTitle>{folder.name}</ContentCardTitle>
-        </div>
-      </ContentCardHeader>
-      <ContentHint>
-        {folder.agent_count} agent{folder.agent_count !== 1 ? "s" : ""}
-        {folder.subfolder_count > 0 &&
-          ` · ${folder.subfolder_count} subfolder${folder.subfolder_count !== 1 ? "s" : ""}`}
-      </ContentHint>
-      {folder.agents && folder.agents.length > 0 && (
-        <div className="mt-2 space-y-1 border-t border-neutral-200 pt-2">
-          {folder.agents.map((a) => (
-            <div key={a.id} className="flex items-center gap-1.5">
-              <FileIcon
-                size={12}
-                weight="duotone"
-                className="text-neutral-600"
-              />
-              <span className="text-xs text-zinc-600">{a.name}</span>
-            </div>
-          ))}
-        </div>
-      )}
-    </ContentCard>
-  );
-}
-
-/* ------------------------------------------------------------------ */
-/*  Tree renderer using file-tree component                            */
-/* ------------------------------------------------------------------ */
-
-type TreeNode = TreeViewElement & { isAgent?: boolean };
-
-function folderTreeToElements(nodes: FolderTreeInfo[]): TreeNode[] {
-  return nodes.map((node) => {
-    const children: TreeNode[] = [
-      ...folderTreeToElements(node.children),
-      ...(node.agents ?? []).map((a) => ({
-        id: a.id,
-        name: a.name,
-        isAgent: true,
-      })),
-    ];
-    return {
-      id: node.id,
-      name: `${node.name} (${node.agent_count} agent${node.agent_count !== 1 ? "s" : ""})`,
-      children: children.length > 0 ? children : undefined,
-    };
-  });
-}
-
-function collectAllIDs(nodes: FolderTreeInfo[]): string[] {
-  return nodes.flatMap((n) => [n.id, ...collectAllIDs(n.children)]);
-}
-
-function FolderTreeView({ tree }: { tree: FolderTreeInfo[] }) {
-  const elements = folderTreeToElements(tree);
-  const allIDs = collectAllIDs(tree);
-
-  return (
-    <Tree
-      initialExpandedItems={allIDs}
-      elements={elements}
-      openIcon={
-        <FolderIcon size={16} weight="fill" className="text-neutral-600" />
-      }
-      closeIcon={
-        <FolderIcon size={16} weight="duotone" className="text-neutral-600" />
-      }
-      className="max-h-64"
-    >
-      {elements.map((el) => (
-        <FolderTreeNodes key={el.id} element={el} />
-      ))}
-    </Tree>
-  );
-}
-
-function FolderTreeNodes({ element }: { element: TreeNode }) {
-  if (element.isAgent) {
-    return (
-      <TreeFile
-        value={element.id}
-        fileIcon={
-          <FileIcon size={14} weight="duotone" className="text-neutral-600" />
-        }
-      >
-        <span className="text-sm text-zinc-700">{element.name}</span>
-      </TreeFile>
-    );
-  }
-
-  if (element.children && element.children.length > 0) {
-    return (
-      <TreeFolder value={element.id} element={element.name} isSelectable>
-        {element.children.map((child) => (
-          <FolderTreeNodes key={child.id} element={child as TreeNode} />
-        ))}
-      </TreeFolder>
-    );
-  }
-
-  return <TreeFolder value={element.id} element={element.name} isSelectable />;
-}
-
-/* ------------------------------------------------------------------ */
-/*  Accordion content per output type                                  */
-/* ------------------------------------------------------------------ */
-
-function AccordionContent({ output }: { output: FolderToolOutput }) {
-  if (isFolderCreated(output)) {
-    return (
-      <ContentGrid>
-        <FolderCard folder={output.folder} />
-      </ContentGrid>
-    );
-  }
-
-  if (isFolderList(output)) {
-    if (output.tree && output.tree.length > 0) {
-      return <FolderTreeView tree={output.tree} />;
-    }
-    if (output.folders && output.folders.length > 0) {
-      return (
-        <ContentGrid className="sm:grid-cols-2">
-          {output.folders.map((folder) => (
-            <FolderCard key={folder.id} folder={folder} />
-          ))}
-        </ContentGrid>
-      );
-    }
-    return <ContentMessage>No folders found.</ContentMessage>;
-  }
-
-  if (isFolderUpdated(output) || isFolderMoved(output)) {
-    return (
-      <ContentGrid>
-        <FolderCard folder={output.folder} />
-      </ContentGrid>
-    );
-  }
-
-  if (isFolderDeleted(output)) {
-    return <ContentMessage>{output.message}</ContentMessage>;
-  }
-
-  if (isAgentsMoved(output)) {
-    return <ContentMessage>{output.message}</ContentMessage>;
-  }
-
-  return null;
-}
-
-/* ------------------------------------------------------------------ */
-/*  Main component                                                     */
-/* ------------------------------------------------------------------ */
-
-function getAccordionTitle(output: FolderToolOutput): string {
-  if (isFolderCreated(output)) return `Created "${output.folder.name}"`;
-  if (isFolderList(output))
-    return `${output.count} folder${output.count !== 1 ? "s" : ""}`;
-  if (isFolderUpdated(output)) return `Updated "${output.folder.name}"`;
-  if (isFolderMoved(output)) return `Moved "${output.folder.name}"`;
-  if (isFolderDeleted(output)) return "Folder deleted";
-  if (isAgentsMoved(output))
-    return `Moved ${output.count} agent${output.count !== 1 ? "s" : ""}`;
-  return "Folder operation";
-}
-
-function getAccordionIcon(output: FolderToolOutput) {
-  if (isFolderCreated(output))
-    return <FolderPlusIcon size={32} weight="light" />;
-  if (isFolderList(output)) return <FoldersIcon size={32} weight="light" />;
-  if (isFolderDeleted(output)) return <TrashIcon size={32} weight="light" />;
-  return <FolderIcon size={32} weight="light" />;
-}
-
-export function FolderTool({ part }: Props) {
-  const text = getAnimationText(part);
-  const output = getFolderToolOutput(part);
-
-  const isStreaming =
-    part.state === "input-streaming" || part.state === "input-available";
-  const isError =
-    part.state === "output-error" || (!!output && isErrorOutput(output));
-
-  const hasContent =
-    part.state === "output-available" && !!output && !isErrorOutput(output);
-
-  return (
-    <div className="py-2">
-      <div className="flex items-center gap-2 text-sm text-muted-foreground">
-        <ToolStatusIcon isStreaming={isStreaming} isError={isError} />
-        <MorphingTextAnimation
-          text={text}
-          className={isError ? "text-red-500" : undefined}
-        />
-      </div>
-
-      {hasContent && output && (
-        <ToolAccordion
-          icon={getAccordionIcon(output)}
-          title={getAccordionTitle(output)}
-          defaultExpanded={isFolderList(output)}
-        >
-          <AccordionContent output={output} />
-        </ToolAccordion>
-      )}
-    </div>
-  );
-}

autogpt_platform/frontend/src/app/(platform)/copilot/tools/FolderTool/helpers.ts

@@ -1,174 +0,0 @@
-import type { ToolUIPart } from "ai";
-
-interface FolderAgentSummary {
-  id: string;
-  name: string;
-  description?: string;
-}
-
-interface FolderInfo {
-  id: string;
-  name: string;
-  parent_id?: string | null;
-  icon?: string | null;
-  color?: string | null;
-  agent_count: number;
-  subfolder_count: number;
-  agents?: FolderAgentSummary[] | null;
-}
-
-interface FolderTreeInfo extends FolderInfo {
-  children: FolderTreeInfo[];
-}
-
-interface FolderCreatedOutput {
-  type: "folder_created";
-  message: string;
-  folder: FolderInfo;
-}
-
-interface FolderListOutput {
-  type: "folder_list";
-  message: string;
-  folders?: FolderInfo[];
-  tree?: FolderTreeInfo[];
-  count: number;
-}
-
-interface FolderUpdatedOutput {
-  type: "folder_updated";
-  message: string;
-  folder: FolderInfo;
-}
-
-interface FolderMovedOutput {
-  type: "folder_moved";
-  message: string;
-  folder: FolderInfo;
-  target_parent_id?: string | null;
-}
-
-interface FolderDeletedOutput {
-  type: "folder_deleted";
-  message: string;
-  folder_id: string;
-}
-
-interface AgentsMovedOutput {
-  type: "agents_moved_to_folder";
-  message: string;
-  agent_ids: string[];
-  folder_id?: string | null;
-  count: number;
-}
-
-interface ErrorOutput {
-  type: "error";
-  message: string;
-  error?: string;
-}
-
-export type FolderToolOutput =
-  | FolderCreatedOutput
-  | FolderListOutput
-  | FolderUpdatedOutput
-  | FolderMovedOutput
-  | FolderDeletedOutput
-  | AgentsMovedOutput
-  | ErrorOutput;
-
-export type { FolderAgentSummary, FolderInfo, FolderTreeInfo };
-
-function parseOutput(output: unknown): FolderToolOutput | null {
-  if (!output) return null;
-  if (typeof output === "string") {
-    const trimmed = output.trim();
-    if (!trimmed) return null;
-    try {
-      return parseOutput(JSON.parse(trimmed) as unknown);
-    } catch {
-      return null;
-    }
-  }
-  if (typeof output === "object") {
-    const obj = output as Record<string, unknown>;
-    if (typeof obj.type === "string") {
-      return output as FolderToolOutput;
-    }
-  }
-  return null;
-}
-
-export function getFolderToolOutput(part: {
-  output?: unknown;
-}): FolderToolOutput | null {
-  return parseOutput(part.output);
-}
-
-export function isFolderCreated(o: FolderToolOutput): o is FolderCreatedOutput {
-  return o.type === "folder_created";
-}
-
-export function isFolderList(o: FolderToolOutput): o is FolderListOutput {
-  return o.type === "folder_list";
-}
-
-export function isFolderUpdated(o: FolderToolOutput): o is FolderUpdatedOutput {
-  return o.type === "folder_updated";
-}
-
-export function isFolderMoved(o: FolderToolOutput): o is FolderMovedOutput {
-  return o.type === "folder_moved";
-}
-
-export function isFolderDeleted(o: FolderToolOutput): o is FolderDeletedOutput {
-  return o.type === "folder_deleted";
-}
-
-export function isAgentsMoved(o: FolderToolOutput): o is AgentsMovedOutput {
-  return o.type === "agents_moved_to_folder";
-}
-
-export function isErrorOutput(o: FolderToolOutput): o is ErrorOutput {
-  return o.type === "error";
-}
-
-export function getAnimationText(part: {
-  type: string;
-  state: ToolUIPart["state"];
-  output?: unknown;
-}): string {
-  const toolName = part.type.replace(/^tool-/, "");
-
-  switch (part.state) {
-    case "input-streaming":
-    case "input-available": {
-      switch (toolName) {
-        case "create_folder":
-          return "Creating folder…";
-        case "list_folders":
-          return "Loading folders…";
-        case "update_folder":
-          return "Updating folder…";
-        case "move_folder":
-          return "Moving folder…";
-        case "delete_folder":
-          return "Deleting folder…";
-        case "move_agents_to_folder":
-          return "Moving agents…";
-        default:
-          return "Managing folders…";
-      }
-    }
-    case "output-available": {
-      const output = getFolderToolOutput(part);
-      if (!output) return "Done";
-      if (isErrorOutput(output)) return "Folder operation failed";
-      return output.message;
-    }
-    case "output-error":
-      return "Folder operation failed";
-    default:
-      return "Managing folders…";
-  }
-}

autogpt_platform/frontend/src/app/(platform)/copilot/tools/GenericTool/GenericTool.tsx

@@ -31,13 +31,6 @@ import {
   OutputItem,
 } from "@/components/contextual/OutputRenderers";
 import type { OutputMetadata } from "@/components/contextual/OutputRenderers";
-import {
-  type ToolCategory,
-  extractToolName,
-  getAnimationText,
-  getToolCategory,
-  truncate,
-} from "./helpers";
 
 interface Props {
   part: ToolUIPart;
@@ -55,6 +48,77 @@ function RenderMedia({
   return <OutputItem value={value} metadata={metadata} renderer={renderer} />;
 }
 
+/* ------------------------------------------------------------------ */
+/*  Tool name helpers                                                  */
+/* ------------------------------------------------------------------ */
+
+function extractToolName(part: ToolUIPart): string {
+  return part.type.replace(/^tool-/, "");
+}
+
+function formatToolName(name: string): string {
+  return name.replace(/_/g, " ").replace(/^\w/, (c) => c.toUpperCase());
+}
+
+/* ------------------------------------------------------------------ */
+/*  Tool categorization                                                */
+/* ------------------------------------------------------------------ */
+
+type ToolCategory =
+  | "bash"
+  | "web"
+  | "browser"
+  | "file-read"
+  | "file-write"
+  | "file-delete"
+  | "file-list"
+  | "search"
+  | "edit"
+  | "todo"
+  | "compaction"
+  | "other";
+
+function getToolCategory(toolName: string): ToolCategory {
+  switch (toolName) {
+    case "bash_exec":
+      return "bash";
+    case "web_fetch":
+    case "WebSearch":
+    case "WebFetch":
+      return "web";
+    case "browser_navigate":
+    case "browser_act":
+    case "browser_screenshot":
+      return "browser";
+    case "read_workspace_file":
+    case "read_file":
+    case "Read":
+      return "file-read";
+    case "write_workspace_file":
+    case "write_file":
+    case "Write":
+      return "file-write";
+    case "delete_workspace_file":
+      return "file-delete";
+    case "list_workspace_files":
+    case "glob":
+    case "Glob":
+      return "file-list";
+    case "grep":
+    case "Grep":
+      return "search";
+    case "edit_file":
+    case "Edit":
+      return "edit";
+    case "TodoWrite":
+      return "todo";
+    case "context_compaction":
+      return "compaction";
+    default:
+      return "other";
+  }
+}
+
 /* ------------------------------------------------------------------ */
 /*  Tool icon                                                          */
 /* ------------------------------------------------------------------ */
@@ -77,7 +141,7 @@ function ToolIcon({
     return <OrbitLoader size={14} />;
   }
 
-  const iconClass = "text-green-500";
+  const iconClass = "text-neutral-400";
   switch (category) {
     case "bash":
       return <TerminalIcon size={14} weight="regular" className={iconClass} />;
@@ -146,6 +210,191 @@ function AccordionIcon({ category }: { category: ToolCategory }) {
   }
 }
 
+/* ------------------------------------------------------------------ */
+/*  Input extraction                                                   */
+/* ------------------------------------------------------------------ */
+
+function getInputSummary(toolName: string, input: unknown): string | null {
+  if (!input || typeof input !== "object") return null;
+  const inp = input as Record<string, unknown>;
+
+  switch (toolName) {
+    case "bash_exec":
+      return typeof inp.command === "string" ? inp.command : null;
+    case "web_fetch":
+    case "WebFetch":
+      return typeof inp.url === "string" ? inp.url : null;
+    case "WebSearch":
+      return typeof inp.query === "string" ? inp.query : null;
+    case "browser_navigate":
+      return typeof inp.url === "string" ? inp.url : null;
+    case "browser_act":
+      return typeof inp.action === "string"
+        ? inp.target
+          ? `${inp.action} ${inp.target}`
+          : (inp.action as string)
+        : null;
+    case "browser_screenshot":
+      return null;
+    case "read_workspace_file":
+    case "read_file":
+    case "Read":
+      return (
+        (typeof inp.file_path === "string" ? inp.file_path : null) ??
+        (typeof inp.path === "string" ? inp.path : null)
+      );
+    case "write_workspace_file":
+    case "write_file":
+    case "Write":
+      return (
+        (typeof inp.file_path === "string" ? inp.file_path : null) ??
+        (typeof inp.path === "string" ? inp.path : null)
+      );
+    case "delete_workspace_file":
+      return typeof inp.file_path === "string" ? inp.file_path : null;
+    case "glob":
+    case "Glob":
+      return typeof inp.pattern === "string" ? inp.pattern : null;
+    case "grep":
+    case "Grep":
+      return typeof inp.pattern === "string" ? inp.pattern : null;
+    case "edit_file":
+    case "Edit":
+      return typeof inp.file_path === "string" ? inp.file_path : null;
+    case "TodoWrite": {
+      // Extract the in-progress task name for the status line
+      const todos = Array.isArray(inp.todos) ? inp.todos : [];
+      const active = todos.find(
+        (t: Record<string, unknown>) => t.status === "in_progress",
+      );
+      if (active && typeof active.activeForm === "string")
+        return active.activeForm;
+      if (active && typeof active.content === "string") return active.content;
+      return null;
+    }
+    default:
+      return null;
+  }
+}
+
+function truncate(text: string, maxLen: number): string {
+  if (text.length <= maxLen) return text;
+  return text.slice(0, maxLen).trimEnd() + "…";
+}
+
+/* ------------------------------------------------------------------ */
+/*  Animation text                                                     */
+/* ------------------------------------------------------------------ */
+
+function getAnimationText(part: ToolUIPart, category: ToolCategory): string {
+  const toolName = extractToolName(part);
+  const summary = getInputSummary(toolName, part.input);
+  const shortSummary = summary ? truncate(summary, 60) : null;
+
+  switch (part.state) {
+    case "input-streaming":
+    case "input-available": {
+      switch (category) {
+        case "bash":
+          return shortSummary ? `Running: ${shortSummary}` : "Running command…";
+        case "web":
+          if (toolName === "WebSearch") {
+            return shortSummary
+              ? `Searching "${shortSummary}"`
+              : "Searching the web…";
+          }
+          return shortSummary
+            ? `Fetching ${shortSummary}`
+            : "Fetching web content…";
+        case "browser":
+          if (toolName === "browser_screenshot") return "Taking screenshot…";
+          return shortSummary
+            ? `Browsing ${shortSummary}`
+            : "Interacting with browser…";
+        case "file-read":
+          return shortSummary ? `Reading ${shortSummary}` : "Reading file…";
+        case "file-write":
+          return shortSummary ? `Writing ${shortSummary}` : "Writing file…";
+        case "file-delete":
+          return shortSummary ? `Deleting ${shortSummary}` : "Deleting file…";
+        case "file-list":
+          return shortSummary ? `Listing ${shortSummary}` : "Listing files…";
+        case "search":
+          return shortSummary
+            ? `Searching for "${shortSummary}"`
+            : "Searching…";
+        case "edit":
+          return shortSummary ? `Editing ${shortSummary}` : "Editing file…";
+        case "todo":
+          return shortSummary ? `${shortSummary}` : "Updating task list…";
+        case "compaction":
+          return "Summarizing earlier messages…";
+        default:
+          return `Running ${formatToolName(toolName)}…`;
+      }
+    }
+    case "output-available": {
+      switch (category) {
+        case "bash": {
+          const exitCode = getExitCode(part.output);
+          if (exitCode !== null && exitCode !== 0) {
+            return `Command exited with code ${exitCode}`;
+          }
+          return shortSummary ? `Ran: ${shortSummary}` : "Command completed";
+        }
+        case "web":
+          if (toolName === "WebSearch") {
+            return shortSummary
+              ? `Searched "${shortSummary}"`
+              : "Web search completed";
+          }
+          return shortSummary
+            ? `Fetched ${shortSummary}`
+            : "Fetched web content";
+        case "browser":
+          if (toolName === "browser_screenshot") return "Screenshot captured";
+          return shortSummary
+            ? `Browsed ${shortSummary}`
+            : "Browser action completed";
+        case "file-read":
+          return shortSummary ? `Read ${shortSummary}` : "File read completed";
+        case "file-write":
+          return shortSummary ? `Wrote ${shortSummary}` : "File written";
+        case "file-delete":
+          return shortSummary ? `Deleted ${shortSummary}` : "File deleted";
+        case "file-list":
+          return "Listed files";
+        case "search":
+          return shortSummary
+            ? `Searched for "${shortSummary}"`
+            : "Search completed";
+        case "edit":
+          return shortSummary ? `Edited ${shortSummary}` : "Edit completed";
+        case "todo":
+          return "Updated task list";
+        case "compaction":
+          return "Earlier messages were summarized";
+        default:
+          return `${formatToolName(toolName)} completed`;
+      }
+    }
+    case "output-error": {
+      switch (category) {
+        case "bash":
+          return "Command failed";
+        case "web":
+          return toolName === "WebSearch" ? "Search failed" : "Fetch failed";
+        case "browser":
+          return "Browser action failed";
+        default:
+          return `${formatToolName(toolName)} failed`;
+      }
+    }
+    default:
+      return `Running ${formatToolName(toolName)}…`;
+  }
+}
+
 /* ------------------------------------------------------------------ */
 /*  Output parsing helpers                                             */
 /* ------------------------------------------------------------------ */
@@ -186,6 +435,13 @@ function extractMcpText(output: Record<string, unknown>): string | null {
   return null;
 }
 
+function getExitCode(output: unknown): number | null {
+  const parsed = parseOutput(output);
+  if (!parsed) return null;
+  if (typeof parsed.exit_code === "number") return parsed.exit_code;
+  return null;
+}
+
 function getStringField(
   obj: Record<string, unknown>,
   ...keys: string[]

autogpt_platform/frontend/src/app/(platform)/copilot/tools/GenericTool/helpers.ts

@@ -1,285 +0,0 @@
-import type { ToolUIPart } from "ai";
-
-/* ------------------------------------------------------------------ */
-/*  Tool name helpers                                                  */
-/* ------------------------------------------------------------------ */
-
-export function extractToolName(part: ToolUIPart): string {
-  return part.type.replace(/^tool-/, "");
-}
-
-export function formatToolName(name: string): string {
-  return name.replace(/_/g, " ").replace(/^\w/, (c) => c.toUpperCase());
-}
-
-/* ------------------------------------------------------------------ */
-/*  Tool categorization                                                */
-/* ------------------------------------------------------------------ */
-
-export type ToolCategory =
-  | "bash"
-  | "web"
-  | "browser"
-  | "file-read"
-  | "file-write"
-  | "file-delete"
-  | "file-list"
-  | "search"
-  | "edit"
-  | "todo"
-  | "compaction"
-  | "other";
-
-export function getToolCategory(toolName: string): ToolCategory {
-  switch (toolName) {
-    case "bash_exec":
-      return "bash";
-    case "web_fetch":
-    case "WebSearch":
-    case "WebFetch":
-      return "web";
-    case "browser_navigate":
-    case "browser_act":
-    case "browser_screenshot":
-      return "browser";
-    case "read_workspace_file":
-    case "read_file":
-    case "Read":
-      return "file-read";
-    case "write_workspace_file":
-    case "write_file":
-    case "Write":
-      return "file-write";
-    case "delete_workspace_file":
-      return "file-delete";
-    case "list_workspace_files":
-    case "glob":
-    case "Glob":
-      return "file-list";
-    case "grep":
-    case "Grep":
-      return "search";
-    case "edit_file":
-    case "Edit":
-      return "edit";
-    case "TodoWrite":
-      return "todo";
-    case "context_compaction":
-      return "compaction";
-    default:
-      return "other";
-  }
-}
-
-/* ------------------------------------------------------------------ */
-/*  Input summary                                                      */
-/* ------------------------------------------------------------------ */
-
-function getInputSummary(toolName: string, input: unknown): string | null {
-  if (!input || typeof input !== "object") return null;
-  const inp = input as Record<string, unknown>;
-
-  switch (toolName) {
-    case "bash_exec":
-      return typeof inp.command === "string" ? inp.command : null;
-    case "web_fetch":
-    case "WebFetch":
-      return typeof inp.url === "string" ? inp.url : null;
-    case "WebSearch":
-      return typeof inp.query === "string" ? inp.query : null;
-    case "browser_navigate":
-      return typeof inp.url === "string" ? inp.url : null;
-    case "browser_act":
-      if (typeof inp.action !== "string") return null;
-      return typeof inp.target === "string"
-        ? `${inp.action} ${inp.target}`
-        : inp.action;
-    case "browser_screenshot":
-      return null;
-    case "read_workspace_file":
-    case "read_file":
-    case "Read":
-      return (
-        (typeof inp.file_path === "string" ? inp.file_path : null) ??
-        (typeof inp.path === "string" ? inp.path : null)
-      );
-    case "write_workspace_file":
-    case "write_file":
-    case "Write":
-      return (
-        (typeof inp.file_path === "string" ? inp.file_path : null) ??
-        (typeof inp.path === "string" ? inp.path : null)
-      );
-    case "delete_workspace_file":
-      return typeof inp.file_path === "string" ? inp.file_path : null;
-    case "glob":
-    case "Glob":
-      return typeof inp.pattern === "string" ? inp.pattern : null;
-    case "grep":
-    case "Grep":
-      return typeof inp.pattern === "string" ? inp.pattern : null;
-    case "edit_file":
-    case "Edit":
-      return typeof inp.file_path === "string" ? inp.file_path : null;
-    case "TodoWrite": {
-      const todos = Array.isArray(inp.todos) ? inp.todos : [];
-      const active = todos.find(
-        (t: unknown) =>
-          t !== null &&
-          typeof t === "object" &&
-          (t as Record<string, unknown>).status === "in_progress",
-      ) as Record<string, unknown> | undefined;
-      if (active && typeof active.activeForm === "string")
-        return active.activeForm;
-      if (active && typeof active.content === "string") return active.content;
-      return null;
-    }
-    default:
-      return null;
-  }
-}
-
-export function truncate(text: string, maxLen: number): string {
-  if (text.length <= maxLen) return text;
-  return text.slice(0, maxLen).trimEnd() + "\u2026";
-}
-
-/* ------------------------------------------------------------------ */
-/*  Exit code helper                                                   */
-/* ------------------------------------------------------------------ */
-
-function getExitCode(output: unknown): number | null {
-  if (!output || typeof output !== "object") return null;
-  const parsed = output as Record<string, unknown>;
-  if (typeof parsed.exit_code === "number") return parsed.exit_code;
-  return null;
-}
-
-/* ------------------------------------------------------------------ */
-/*  Animation text                                                     */
-/* ------------------------------------------------------------------ */
-
-export function getAnimationText(
-  part: ToolUIPart,
-  category: ToolCategory,
-): string {
-  const toolName = extractToolName(part);
-  const summary = getInputSummary(toolName, part.input);
-  const shortSummary = summary ? truncate(summary, 60) : null;
-
-  switch (part.state) {
-    case "input-streaming":
-    case "input-available": {
-      switch (category) {
-        case "bash":
-          return shortSummary
-            ? `Running: ${shortSummary}`
-            : "Running command\u2026";
-        case "web":
-          if (toolName === "WebSearch") {
-            return shortSummary
-              ? `Searching "${shortSummary}"`
-              : "Searching the web\u2026";
-          }
-          return shortSummary
-            ? `Fetching ${shortSummary}`
-            : "Fetching web content\u2026";
-        case "browser":
-          if (toolName === "browser_screenshot")
-            return "Taking screenshot\u2026";
-          return shortSummary
-            ? `Browsing ${shortSummary}`
-            : "Interacting with browser\u2026";
-        case "file-read":
-          return shortSummary
-            ? `Reading ${shortSummary}`
-            : "Reading file\u2026";
-        case "file-write":
-          return shortSummary
-            ? `Writing ${shortSummary}`
-            : "Writing file\u2026";
-        case "file-delete":
-          return shortSummary
-            ? `Deleting ${shortSummary}`
-            : "Deleting file\u2026";
-        case "file-list":
-          return shortSummary
-            ? `Listing ${shortSummary}`
-            : "Listing files\u2026";
-        case "search":
-          return shortSummary
-            ? `Searching for "${shortSummary}"`
-            : "Searching\u2026";
-        case "edit":
-          return shortSummary
-            ? `Editing ${shortSummary}`
-            : "Editing file\u2026";
-        case "todo":
-          return shortSummary ? `${shortSummary}` : "Updating task list\u2026";
-        case "compaction":
-          return "Summarizing earlier messages\u2026";
-        default:
-          return `Running ${formatToolName(toolName)}\u2026`;
-      }
-    }
-    case "output-available": {
-      switch (category) {
-        case "bash": {
-          const exitCode = getExitCode(part.output);
-          if (exitCode !== null && exitCode !== 0) {
-            return `Command exited with code ${exitCode}`;
-          }
-          return shortSummary ? `Ran: ${shortSummary}` : "Command completed";
-        }
-        case "web":
-          if (toolName === "WebSearch") {
-            return shortSummary
-              ? `Searched "${shortSummary}"`
-              : "Web search completed";
-          }
-          return shortSummary
-            ? `Fetched ${shortSummary}`
-            : "Fetched web content";
-        case "browser":
-          if (toolName === "browser_screenshot") return "Screenshot captured";
-          return shortSummary
-            ? `Browsed ${shortSummary}`
-            : "Browser action completed";
-        case "file-read":
-          return shortSummary ? `Read ${shortSummary}` : "File read completed";
-        case "file-write":
-          return shortSummary ? `Wrote ${shortSummary}` : "File written";
-        case "file-delete":
-          return shortSummary ? `Deleted ${shortSummary}` : "File deleted";
-        case "file-list":
-          return "Listed files";
-        case "search":
-          return shortSummary
-            ? `Searched for "${shortSummary}"`
-            : "Search completed";
-        case "edit":
-          return shortSummary ? `Edited ${shortSummary}` : "Edit completed";
-        case "todo":
-          return "Updated task list";
-        case "compaction":
-          return "Earlier messages were summarized";
-        default:
-          return `${formatToolName(toolName)} completed`;
-      }
-    }
-    case "output-error": {
-      switch (category) {
-        case "bash":
-          return "Command failed";
-        case "web":
-          return toolName === "WebSearch" ? "Search failed" : "Fetch failed";
-        case "browser":
-          return "Browser action failed";
-        default:
-          return `${formatToolName(toolName)} failed`;
-      }
-    }
-    default:
-      return `Running ${formatToolName(toolName)}\u2026`;
-  }
-}

autogpt_platform/frontend/src/app/(platform)/copilot/tools/RunAgent/RunAgent.tsx

@@ -2,7 +2,7 @@
 
 import type { ToolUIPart } from "ai";
 import { MorphingTextAnimation } from "../../components/MorphingTextAnimation/MorphingTextAnimation";
-import { ScaleLoader } from "../../components/ScaleLoader/ScaleLoader";
+import { OrbitLoader } from "../../components/OrbitLoader/OrbitLoader";
 import { ToolAccordion } from "../../components/ToolAccordion/ToolAccordion";
 import {
   ContentGrid,
@@ -86,7 +86,7 @@ export function RunAgentTool({ part }: Props) {
 
       {isStreaming && !output && (
         <ToolAccordion
-          icon={<ScaleLoader size={14} />}
+          icon={<OrbitLoader size={32} />}
           title="Running agent, this may take a few minutes. Play while you wait."
           expanded={true}
         >

autogpt_platform/frontend/src/app/(platform)/copilot/tools/RunAgent/helpers.tsx

@@ -10,7 +10,7 @@ import {
   WarningDiamondIcon,
 } from "@phosphor-icons/react";
 import type { ToolUIPart } from "ai";
-import { ScaleLoader } from "../../components/ScaleLoader/ScaleLoader";
+import { OrbitLoader } from "../../components/OrbitLoader/OrbitLoader";
 
 export interface RunAgentInput {
   username_agent_slug?: string;
@@ -171,7 +171,7 @@ export function ToolIcon({
     );
   }
   if (isStreaming) {
-    return <ScaleLoader size={14} />;
+    return <OrbitLoader size={24} />;
   }
   return <PlayIcon size={14} weight="regular" className="text-neutral-400" />;
 }

autogpt_platform/frontend/src/app/(platform)/copilot/tools/RunBlock/helpers.tsx

@@ -8,7 +8,7 @@ import {
   WarningDiamondIcon,
 } from "@phosphor-icons/react";
 import type { ToolUIPart } from "ai";
-import { ScaleLoader } from "../../components/ScaleLoader/ScaleLoader";
+import { OrbitLoader } from "../../components/OrbitLoader/OrbitLoader";
 
 /** Block details returned on first run_block attempt (before input_data provided). */
 export interface BlockDetailsResponse {
@@ -157,7 +157,7 @@ export function ToolIcon({
     );
   }
   if (isStreaming) {
-    return <ScaleLoader size={14} />;
+    return <OrbitLoader size={24} />;
   }
   return <PlayIcon size={14} weight="regular" className="text-neutral-400" />;
 }

autogpt_platform/frontend/src/app/(platform)/copilot/tools/RunMCPTool/helpers.tsx

@@ -6,7 +6,7 @@ import { ResponseType } from "@/app/api/__generated__/models/responseType";
 import type { SetupRequirementsResponse } from "@/app/api/__generated__/models/setupRequirementsResponse";
 import { WarningDiamondIcon, PlugsConnectedIcon } from "@phosphor-icons/react";
 import type { ToolUIPart } from "ai";
-import { ScaleLoader } from "../../components/ScaleLoader/ScaleLoader";
+import { OrbitLoader } from "../../components/OrbitLoader/OrbitLoader";
 
 // ------------------------------------------------------------------ //
 //  Re-export generated types for use by RunMCPTool components
@@ -212,7 +212,7 @@ export function ToolIcon({
     );
   }
   if (isStreaming) {
-    return <ScaleLoader size={14} />;
+    return <OrbitLoader size={24} />;
   }
   return (
     <PlugsConnectedIcon

autogpt_platform/frontend/src/app/(platform)/copilot/useCopilotPage.ts

@@ -5,9 +5,10 @@ import {
   type getV2ListSessionsResponse,
 } from "@/app/api/__generated__/endpoints/chat/chat";
 import { toast } from "@/components/molecules/Toast/use-toast";
-import { uploadFileDirect } from "@/lib/direct-upload";
 import { useBreakpoint } from "@/lib/hooks/useBreakpoint";
+import { getWebSocketToken } from "@/lib/supabase/actions";
 import { useSupabase } from "@/lib/supabase/hooks/useSupabase";
+import { environment } from "@/services/environment";
 import { useQueryClient } from "@tanstack/react-query";
 import type { FileUIPart } from "ai";
 import { useEffect, useRef, useState } from "react";
@@ -128,25 +129,49 @@ export function useCopilotPage() {
     files: File[],
     sid: string,
   ): Promise<UploadedFile[]> {
+    // Upload directly to the Python backend, bypassing the Next.js serverless
+    // proxy.  Vercel's 4.5 MB function payload limit would reject larger files
+    // when routed through /api/workspace/files/upload.
+    const { token, error: tokenError } = await getWebSocketToken();
+    if (tokenError || !token) {
+      toast({
+        title: "Authentication error",
+        description: "Please sign in again.",
+        variant: "destructive",
+      });
+      return [];
+    }
+
+    const backendBase = environment.getAGPTServerBaseUrl();
+
     const results = await Promise.allSettled(
       files.map(async (file) => {
-        try {
-          const data = await uploadFileDirect(file, sid);
-          if (!data.file_id) throw new Error("No file_id returned");
-          return {
-            file_id: data.file_id,
-            name: data.name || file.name,
-            mime_type: data.mime_type || "application/octet-stream",
-          } as UploadedFile;
-        } catch (err) {
+        const formData = new FormData();
+        formData.append("file", file);
+        const url = new URL("/api/workspace/files/upload", backendBase);
+        url.searchParams.set("session_id", sid);
+        const res = await fetch(url.toString(), {
+          method: "POST",
+          headers: { Authorization: `Bearer ${token}` },
+          body: formData,
+        });
+        if (!res.ok) {
+          const err = await res.text();
           console.error("File upload failed:", err);
           toast({
             title: "File upload failed",
             description: file.name,
             variant: "destructive",
           });
-          throw err;
+          throw new Error(err);
         }
+        const data = await res.json();
+        if (!data.file_id) throw new Error("No file_id returned");
+        return {
+          file_id: data.file_id,
+          name: data.name || file.name,
+          mime_type: data.mime_type || "application/octet-stream",
+        } as UploadedFile;
       }),
     );
     return results

autogpt_platform/frontend/src/app/(platform)/copilot/useCopilotStream.ts

@@ -92,18 +92,12 @@ export function useCopilotStream({
   // Set when the user explicitly clicks stop — prevents onError from
   // triggering a reconnect cycle for the resulting AbortError.
   const isUserStoppingRef = useRef(false);
-  // Set when all reconnect attempts are exhausted — prevents hasActiveStream
-  // from keeping the UI blocked forever when the backend is slow to clear it.
-  // Must be state (not ref) so that setting it triggers a re-render and
-  // recomputes `isReconnecting`.
-  const [reconnectExhausted, setReconnectExhausted] = useState(false);
 
   function handleReconnect(sid: string) {
     if (isReconnectScheduledRef.current || !sid) return;
 
     const nextAttempt = reconnectAttemptsRef.current + 1;
     if (nextAttempt > RECONNECT_MAX_ATTEMPTS) {
-      setReconnectExhausted(true);
       toast({
         title: "Connection lost",
         description: "Unable to reconnect. Please refresh the page.",
@@ -152,11 +146,7 @@ export function useCopilotStream({
         return;
       }
 
-      // Check if backend executor is still running after clean close.
-      // Brief delay to let the backend clear active_stream — without this,
-      // the refetch often races and sees stale active_stream=true, triggering
-      // unnecessary reconnect cycles.
-      await new Promise((r) => setTimeout(r, 500));
+      // Check if backend executor is still running after clean close
       const result = await refetchSession();
       const d = result.data;
       const backendActive =
@@ -286,7 +276,6 @@ export function useCopilotStream({
     setIsReconnectScheduled(false);
     hasShownDisconnectToast.current = false;
     isUserStoppingRef.current = false;
-    setReconnectExhausted(false);
     hasResumedRef.current.clear();
     return () => {
       clearTimeout(reconnectTimerRef.current);
@@ -310,7 +299,6 @@ export function useCopilotStream({
       if (status === "ready") {
         reconnectAttemptsRef.current = 0;
         hasShownDisconnectToast.current = false;
-        setReconnectExhausted(false);
       }
     }
   }, [status, sessionId, queryClient, isReconnectScheduled]);
@@ -370,12 +358,10 @@ export function useCopilotStream({
   }, [hasActiveStream]);
 
   // True while reconnecting or backend has active stream but we haven't connected yet.
-  // Suppressed when the user explicitly stopped or when all reconnect attempts
-  // are exhausted — the backend may be slow to clear active_stream but the UI
-  // should remain responsive.
+  // Suppressed when the user explicitly stopped — the backend may take a moment
+  // to clear active_stream but the UI should be responsive immediately.
   const isReconnecting =
     !isUserStoppingRef.current &&
-    !reconnectExhausted &&
     (isReconnectScheduled ||
       (hasActiveStream && status !== "streaming" && status !== "submitted"));
 

autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/NewAgentLibraryView/components/AgentVersionChangelog.tsx

@@ -42,8 +42,8 @@ export function AgentVersionChangelog({
 
   // Create version info from available graph versions
   const storeData = okData(storeAgentData) as StoreAgentDetails | undefined;
-  const agentVersions: VersionInfo[] = storeData?.graph_versions
-    ? storeData.graph_versions
+  const agentVersions: VersionInfo[] = storeData?.agentGraphVersions
+    ? storeData.agentGraphVersions
         .map((versionStr: string) => parseInt(versionStr, 10))
         .sort((a: number, b: number) => b - a) // Sort descending (newest first)
         .map((version: number) => ({

autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/NewAgentLibraryView/components/modals/RunAgentInputs/useRunAgentInputs.ts

@@ -1,16 +1,14 @@
-import { postV1UploadFileToCloudStorage } from "@/app/api/__generated__/endpoints/files/files";
-import { resolveResponse } from "@/app/api/helpers";
+import BackendAPI from "@/lib/autogpt-server-api";
 import { useState } from "react";
 
 export function useRunAgentInputs() {
+  const api = new BackendAPI();
   const [uploadProgress, setUploadProgress] = useState(0);
 
   async function handleUploadFile(file: File) {
-    setUploadProgress(0);
-    const result = await resolveResponse(
-      postV1UploadFileToCloudStorage({ file }, { expiration_hours: 24 }),
+    const result = await api.uploadFile(file, "gcs", 24, (progress) =>
+      setUploadProgress(progress),
     );
-    setUploadProgress(100);
     return result;
   }
 

autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/NewAgentLibraryView/hooks/useMarketplaceUpdate.ts

@@ -95,14 +95,14 @@ export function useMarketplaceUpdate({ agent }: UseMarketplaceUpdateProps) {
     const submissionsResponse = okData(submissionsData) as any;
     const agentSubmissions =
       submissionsResponse?.submissions?.filter(
-        (submission: StoreSubmission) => submission.graph_id === agent.graph_id,
+        (submission: StoreSubmission) => submission.agent_id === agent.graph_id,
       ) || [];
 
     const highestSubmittedVersion =
       agentSubmissions.length > 0
         ? Math.max(
             ...agentSubmissions.map(
-              (submission: StoreSubmission) => submission.graph_version,
+              (submission: StoreSubmission) => submission.agent_version,
             ),
           )
         : 0;

autogpt_platform/frontend/src/app/(platform)/marketplace/components/CreatorCard/CreatorCard.tsx

@@ -3,7 +3,7 @@ import { backgroundColor } from "./helper";
 
 interface CreatorCardProps {
   creatorName: string;
-  creatorImage: string | null;
+  creatorImage: string;
   bio: string;
   agentsUploaded: number;
   onClick: () => void;

autogpt_platform/frontend/src/app/(platform)/marketplace/components/CreatorInfoCard/CreatorInfoCard.tsx

@@ -7,7 +7,7 @@ import { StarRatingIcons } from "@/components/__legacy__/ui/icons";
 interface CreatorInfoCardProps {
   username: string;
   handle: string;
-  avatarSrc: string | null;
+  avatarSrc: string;
   categories: string[];
   averageRating: number;
   totalRuns: number;
@@ -29,14 +29,12 @@ export const CreatorInfoCard = ({
     >
       <div className="flex w-full flex-col items-start justify-start gap-3.5 sm:h-[218px]">
         <Avatar className="h-[100px] w-[100px] sm:h-[130px] sm:w-[130px]">
-          {avatarSrc && (
-            <AvatarImage
-              width={130}
-              height={130}
-              src={avatarSrc}
-              alt={`${username}'s avatar`}
-            />
-          )}
+          <AvatarImage
+            width={130}
+            height={130}
+            src={avatarSrc}
+            alt={`${username}'s avatar`}
+          />
           <AvatarFallback
             size={130}
             className="h-[100px] w-[100px] sm:h-[130px] sm:w-[130px]"

autogpt_platform/frontend/src/app/(platform)/marketplace/components/FeaturedCreators/FeaturedCreators.tsx

@@ -2,11 +2,11 @@
 
 import { CreatorCard } from "../CreatorCard/CreatorCard";
 import { useFeaturedCreators } from "./useFeaturedCreators";
-import { CreatorDetails } from "@/app/api/__generated__/models/creatorDetails";
+import { Creator } from "@/app/api/__generated__/models/creator";
 
 interface FeaturedCreatorsProps {
   title?: string;
-  featuredCreators: CreatorDetails[];
+  featuredCreators: Creator[];
 }
 
 export const FeaturedCreators = ({

autogpt_platform/frontend/src/app/(platform)/marketplace/components/FeaturedCreators/useFeaturedCreators.ts

@@ -1,8 +1,8 @@
-import { CreatorDetails } from "@/app/api/__generated__/models/creatorDetails";
+import { Creator } from "@/app/api/__generated__/models/creator";
 import { useRouter } from "next/navigation";
 
 interface useFeaturedCreatorsProps {
-  featuredCreators: CreatorDetails[];
+  featuredCreators: Creator[];
 }
 
 export const useFeaturedCreators = ({

autogpt_platform/frontend/src/app/(platform)/profile/(user)/dashboard/components/AgentTable/AgentTable.tsx

@@ -3,23 +3,33 @@
 import * as React from "react";
 import { AgentTableCard } from "../AgentTableCard/AgentTableCard";
 import { StoreSubmission } from "@/app/api/__generated__/models/storeSubmission";
-import { AgentTableRow } from "../AgentTableRow/AgentTableRow";
+import {
+  AgentTableRow,
+  AgentTableRowProps,
+} from "../AgentTableRow/AgentTableRow";
 import { StoreSubmissionEditRequest } from "@/app/api/__generated__/models/storeSubmissionEditRequest";
 
 export interface AgentTableProps {
-  storeAgentSubmissions: StoreSubmission[];
+  agents: Omit<
+    AgentTableRowProps,
+    | "setSelectedAgents"
+    | "selectedAgents"
+    | "onViewSubmission"
+    | "onDeleteSubmission"
+    | "onEditSubmission"
+  >[];
   onViewSubmission: (submission: StoreSubmission) => void;
   onDeleteSubmission: (submission_id: string) => void;
   onEditSubmission: (
     submission: StoreSubmissionEditRequest & {
       store_listing_version_id: string | undefined;
-      graph_id: string;
+      agent_id: string;
     },
   ) => void;
 }
 
 export const AgentTable: React.FC<AgentTableProps> = ({
-  storeAgentSubmissions,
+  agents,
   onViewSubmission,
   onDeleteSubmission,
   onEditSubmission,
@@ -53,19 +63,19 @@ export const AgentTable: React.FC<AgentTableProps> = ({
       </div>
 
       {/* Table body */}
-      {storeAgentSubmissions.length > 0 ? (
+      {agents.length > 0 ? (
         <div className="flex flex-col">
-          {storeAgentSubmissions.map((agentSubmission) => (
-            <div key={agentSubmission.listing_version_id} className="md:block">
+          {agents.map((agent) => (
+            <div key={agent.id} className="md:block">
               <AgentTableRow
-                storeAgentSubmission={agentSubmission}
+                {...agent}
                 onViewSubmission={onViewSubmission}
                 onDeleteSubmission={onDeleteSubmission}
                 onEditSubmission={onEditSubmission}
               />
               <div className="block md:hidden">
                 <AgentTableCard
-                  storeAgentSubmission={agentSubmission}
+                  {...agent}
                   onViewSubmission={onViewSubmission}
                 />
               </div>

autogpt_platform/frontend/src/app/(platform)/profile/(user)/dashboard/components/AgentTableCard/AgentTableCard.tsx

@@ -3,38 +3,62 @@
 import Image from "next/image";
 import { IconStarFilled, IconMore } from "@/components/__legacy__/ui/icons";
 import { StoreSubmission } from "@/app/api/__generated__/models/storeSubmission";
+import { SubmissionStatus } from "@/app/api/__generated__/models/submissionStatus";
 import { Status } from "@/components/__legacy__/Status";
 
 export interface AgentTableCardProps {
-  storeAgentSubmission: StoreSubmission;
+  agent_id: string;
+  agent_version: number;
+  agentName: string;
+  sub_heading: string;
+  description: string;
+  imageSrc: string[];
+  dateSubmitted: Date;
+  status: SubmissionStatus;
+  runs: number;
+  rating: number;
+  id: number;
+  listing_id?: string;
   onViewSubmission: (submission: StoreSubmission) => void;
 }
 
 export const AgentTableCard = ({
-  storeAgentSubmission,
+  agent_id,
+  agent_version,
+  agentName,
+  sub_heading,
+  description,
+  imageSrc,
+  dateSubmitted,
+  status,
+  runs,
+  rating,
+  listing_id,
   onViewSubmission,
 }: AgentTableCardProps) => {
   const onView = () => {
-    onViewSubmission(storeAgentSubmission);
+    onViewSubmission({
+      listing_id: listing_id || "",
+      agent_id,
+      agent_version,
+      slug: "",
+      name: agentName,
+      sub_heading,
+      description,
+      image_urls: imageSrc,
+      date_submitted: dateSubmitted,
+      status: status,
+      runs,
+      rating,
+    });
   };
 
-  const {
-    graph_version,
-    name: agentName,
-    description,
-    image_urls,
-    submitted_at,
-    status,
-    run_count,
-    review_avg_rating: rating,
-  } = storeAgentSubmission;
-
   return (
     <div className="border-b border-neutral-300 p-4 dark:border-neutral-700">
       <div className="flex gap-4">
         <div className="relative aspect-video w-24 shrink-0 overflow-hidden rounded-lg bg-[#d9d9d9] dark:bg-neutral-800">
           <Image
-            src={image_urls?.[0] ?? "/nada.png"}
+            src={imageSrc?.[0] ?? "/nada.png"}
             alt={agentName}
             fill
             style={{ objectFit: "cover" }}
@@ -46,7 +70,7 @@ export const AgentTableCard = ({
               {agentName}
             </h3>
             <span className="text-[13px] text-neutral-500 dark:text-neutral-400">
-              v{graph_version}
+              v{agent_version}
             </span>
           </div>
           <p className="line-clamp-2 text-sm text-neutral-600 dark:text-neutral-400">
@@ -64,14 +88,14 @@ export const AgentTableCard = ({
       <div className="mt-4 flex flex-wrap gap-4">
         <Status status={status} />
         <div className="text-sm text-neutral-600 dark:text-neutral-400">
-          {submitted_at && submitted_at.toLocaleDateString()}
+          {dateSubmitted.toLocaleDateString()}
         </div>
         <div className="text-sm text-neutral-600 dark:text-neutral-400">
-          {(run_count ?? 0).toLocaleString()} runs
+          {runs.toLocaleString()} runs
         </div>
         <div className="flex items-center gap-1">
           <span className="text-sm font-medium text-neutral-800 dark:text-neutral-200">
-            {(rating ?? 0).toFixed(1)}
+            {rating.toFixed(1)}
           </span>
           <IconStarFilled className="h-4 w-4 text-neutral-800 dark:text-neutral-200" />
         </div>

autogpt_platform/frontend/src/app/(platform)/profile/(user)/dashboard/components/AgentTableRow/AgentTableRow.tsx

@@ -18,60 +18,92 @@ import {
 import { SubmissionStatus } from "@/app/api/__generated__/models/submissionStatus";
 import { StoreSubmissionEditRequest } from "@/app/api/__generated__/models/storeSubmissionEditRequest";
 
-export type AgentTableRowProps = {
-  storeAgentSubmission: StoreSubmission;
+export interface AgentTableRowProps {
+  agent_id: string;
+  agent_version: number;
+  agentName: string;
+  sub_heading: string;
+  description: string;
+  imageSrc: string[];
+  dateSubmitted: Date;
+  status: SubmissionStatus;
+  runs: number;
+  rating: number;
+  id: number;
+  video_url?: string;
+  categories?: string[];
+  store_listing_version_id?: string;
+  changes_summary?: string;
+  listing_id?: string;
   onViewSubmission: (submission: StoreSubmission) => void;
   onDeleteSubmission: (submission_id: string) => void;
   onEditSubmission: (
     submission: StoreSubmissionEditRequest & {
       store_listing_version_id: string | undefined;
-      graph_id: string;
+      agent_id: string;
     },
   ) => void;
-};
+}
 
 export const AgentTableRow = ({
-  storeAgentSubmission,
+  agent_id,
+  agent_version,
+  agentName,
+  sub_heading,
+  description,
+  imageSrc,
+  dateSubmitted,
+  status,
+  runs,
+  rating,
+  id,
+  video_url,
+  categories,
+  store_listing_version_id,
+  changes_summary,
+  listing_id,
   onViewSubmission,
   onDeleteSubmission,
   onEditSubmission,
 }: AgentTableRowProps) => {
   const { handleView, handleDelete, handleEdit } = useAgentTableRow({
-    storeAgentSubmission,
+    id,
     onViewSubmission,
     onDeleteSubmission,
     onEditSubmission,
-  });
-
-  const {
-    listing_version_id,
-    graph_id,
-    graph_version,
-    name: agentName,
+    agent_id,
+    agent_version,
+    agentName,
+    sub_heading,
     description,
-    image_urls,
-    submitted_at,
+    imageSrc,
+    dateSubmitted,
     status,
-    run_count,
-    review_avg_rating,
-  } = storeAgentSubmission;
+    runs,
+    rating,
+    video_url,
+    categories,
+    store_listing_version_id,
+    changes_summary,
+    listing_id,
+  });
 
   const canModify = status === SubmissionStatus.PENDING;
 
   return (
     <div
       data-testid="agent-table-row"
-      data-agent-id={graph_id}
-      data-submission-id={listing_version_id}
+      data-agent-id={agent_id}
+      data-submission-id={store_listing_version_id}
       className="hidden items-center border-b border-neutral-300 px-4 py-4 hover:bg-neutral-50 dark:border-neutral-700 dark:hover:bg-neutral-800 md:flex"
     >
       <div className="grid w-full grid-cols-[minmax(400px,1fr),180px,140px,100px,100px,40px] items-center gap-4">
         {/* Agent info column */}
         <div className="flex items-center gap-4">
-          {image_urls?.[0] ? (
+          {imageSrc?.[0] ? (
             <div className="relative aspect-video w-32 shrink-0 overflow-hidden rounded-[10px] bg-zinc-100">
               <Image
-                src={image_urls?.[0] ?? ""}
+                src={imageSrc?.[0] ?? ""}
                 alt={agentName}
                 fill
                 style={{ objectFit: "cover" }}
@@ -96,7 +128,7 @@ export const AgentTableRow = ({
                 size="small"
                 className="text-neutral-500 dark:text-neutral-400"
               >
-                v{graph_version}
+                v{agent_version}
               </Text>
             </div>
             <Text
@@ -110,7 +142,7 @@ export const AgentTableRow = ({
 
         {/* Date column */}
         <div className="text-sm text-neutral-600 dark:text-neutral-400">
-          {submitted_at && submitted_at.toLocaleDateString()}
+          {dateSubmitted.toLocaleDateString()}
         </div>
 
         {/* Status column */}
@@ -120,16 +152,14 @@ export const AgentTableRow = ({
 
         {/* Runs column */}
         <div className="text-right text-sm text-neutral-600 dark:text-neutral-400">
-          {run_count?.toLocaleString() ?? "0"}
+          {runs?.toLocaleString() ?? "0"}
         </div>
 
         {/* Reviews column */}
         <div className="text-right">
-          {review_avg_rating ? (
+          {rating ? (
             <div className="flex items-center justify-end gap-1">
-              <span className="text-sm font-medium">
-                {review_avg_rating.toFixed(1)}
-              </span>
+              <span className="text-sm font-medium">{rating.toFixed(1)}</span>
               <StarIcon weight="fill" className="h-2 w-2" />
             </div>
           ) : (

autogpt_platform/frontend/src/app/(platform)/profile/(user)/dashboard/components/AgentTableRow/useAgentTableRow.ts

@@ -1,45 +1,97 @@
 import { StoreSubmission } from "@/app/api/__generated__/models/storeSubmission";
 import { StoreSubmissionEditRequest } from "@/app/api/__generated__/models/storeSubmissionEditRequest";
+import { SubmissionStatus } from "@/app/api/__generated__/models/submissionStatus";
 
 interface useAgentTableRowProps {
-  storeAgentSubmission: StoreSubmission;
+  id: number;
   onViewSubmission: (submission: StoreSubmission) => void;
   onDeleteSubmission: (submission_id: string) => void;
   onEditSubmission: (
     submission: StoreSubmissionEditRequest & {
       store_listing_version_id: string | undefined;
-      graph_id: string;
+      agent_id: string;
     },
   ) => void;
+  agent_id: string;
+  agent_version: number;
+  agentName: string;
+  sub_heading: string;
+  description: string;
+  imageSrc: string[];
+  dateSubmitted: Date;
+  status: SubmissionStatus;
+  runs: number;
+  rating: number;
+  video_url?: string;
+  categories?: string[];
+  store_listing_version_id?: string;
+  changes_summary?: string;
+  listing_id?: string;
 }
 
 export const useAgentTableRow = ({
-  storeAgentSubmission,
   onViewSubmission,
   onDeleteSubmission,
   onEditSubmission,
+  agent_id,
+  agent_version,
+  agentName,
+  sub_heading,
+  description,
+  imageSrc,
+  dateSubmitted,
+  status,
+  runs,
+  rating,
+  video_url,
+  categories,
+  store_listing_version_id,
+  changes_summary,
+  listing_id,
 }: useAgentTableRowProps) => {
   const handleView = () => {
-    onViewSubmission(storeAgentSubmission);
+    onViewSubmission({
+      listing_id: listing_id || "",
+      agent_id,
+      agent_version,
+      slug: "",
+      name: agentName,
+      sub_heading,
+      description,
+      image_urls: imageSrc,
+      date_submitted: dateSubmitted,
+      status: status,
+      runs,
+      rating,
+      video_url,
+      categories,
+      store_listing_version_id,
+    } satisfies StoreSubmission);
   };
 
   const handleEdit = () => {
     onEditSubmission({
-      name: storeAgentSubmission.name,
-      sub_heading: storeAgentSubmission.sub_heading,
-      description: storeAgentSubmission.description,
-      image_urls: storeAgentSubmission.image_urls,
-      video_url: storeAgentSubmission.video_url,
-      categories: storeAgentSubmission.categories,
-      changes_summary:
-        storeAgentSubmission.changes_summary || "Update Submission",
-      store_listing_version_id: storeAgentSubmission.listing_version_id,
-      graph_id: storeAgentSubmission.graph_id,
+      name: agentName,
+      sub_heading,
+      description,
+      image_urls: imageSrc,
+      video_url,
+      categories,
+      changes_summary: changes_summary || "Update Submission",
+      store_listing_version_id,
+      agent_id,
     });
   };
 
   const handleDelete = () => {
-    onDeleteSubmission(storeAgentSubmission.listing_version_id);
+    // Backend only accepts StoreListingVersion IDs for deletion
+    if (!store_listing_version_id) {
+      console.error(
+        "Cannot delete submission: store_listing_version_id is required",
+      );
+      return;
+    }
+    onDeleteSubmission(store_listing_version_id);
   };
 
   return { handleView, handleDelete, handleEdit };

autogpt_platform/frontend/src/app/(platform)/profile/(user)/dashboard/components/MainDashboardPage/MainDashboardPage.tsx

@@ -81,7 +81,26 @@ export const MainDashboardPage = () => {
           <SubmissionsLoading />
         ) : submissions && submissions.submissions.length > 0 ? (
           <AgentTable
-            storeAgentSubmissions={submissions.submissions}
+            agents={submissions.submissions.map((submission, index) => ({
+              id: index,
+              agent_id: submission.agent_id,
+              agent_version: submission.agent_version,
+              sub_heading: submission.sub_heading,
+              agentName: submission.name,
+              description: submission.description,
+              imageSrc: submission.image_urls || [""],
+              dateSubmitted: submission.date_submitted,
+              status: submission.status,
+              runs: submission.runs,
+              rating: submission.rating,
+              video_url: submission.video_url || undefined,
+              categories: submission.categories,
+              slug: submission.slug,
+              store_listing_version_id:
+                submission.store_listing_version_id || undefined,
+              changes_summary: submission.changes_summary || undefined,
+              listing_id: submission.listing_id,
+            }))}
             onViewSubmission={onViewSubmission}
             onDeleteSubmission={onDeleteSubmission}
             onEditSubmission={onEditSubmission}

autogpt_platform/frontend/src/app/(platform)/profile/(user)/dashboard/components/MainDashboardPage/useMainDashboardPage.ts

@@ -24,7 +24,7 @@ type EditState = {
   submission:
     | (StoreSubmissionEditRequest & {
         store_listing_version_id: string | undefined;
-        graph_id: string;
+        agent_id: string;
       })
     | null;
 };
@@ -79,7 +79,7 @@ export const useMainDashboardPage = () => {
   const onEditSubmission = (
     submission: StoreSubmissionEditRequest & {
       store_listing_version_id: string | undefined;
-      graph_id: string;
+      agent_id: string;
     },
   ) => {
     setEditState({
@@ -90,7 +90,7 @@ export const useMainDashboardPage = () => {
 
   const onEditSuccess = async (submission: StoreSubmission) => {
     try {
-      if (!submission.listing_version_id) {
+      if (!submission.store_listing_version_id) {
         Sentry.captureException(
           new Error("No store listing version ID found for submission"),
         );

autogpt_platform/frontend/src/app/(platform)/profile/(user)/page.tsx

@@ -4,7 +4,7 @@ import { useGetV2GetUserProfile } from "@/app/api/__generated__/endpoints/store/
 import { ProfileInfoForm } from "@/components/__legacy__/ProfileInfoForm";
 import { ErrorCard } from "@/components/molecules/ErrorCard/ErrorCard";
 import { isLogoutInProgress } from "@/lib/autogpt-server-api/helpers";
-import type { ProfileDetails } from "@/app/api/__generated__/models/profileDetails";
+import { ProfileDetails } from "@/lib/autogpt-server-api/types";
 import { useSupabase } from "@/lib/supabase/hooks/useSupabase";
 import { ProfileLoading } from "./ProfileLoading";