Always yield files in ClaudeCodeBlock output

Updated the ClaudeCodeBlock to always yield the 'files' key with an empty list if no files are present, ensuring consistent output that matches the Output schema.

.branchlet.json

@@ -0,0 +1,37 @@
+{
+  "worktreeCopyPatterns": [
+    ".env*",
+    ".vscode/**",
+    ".auth/**",
+    ".claude/**",
+    "autogpt_platform/.env*",
+    "autogpt_platform/backend/.env*",
+    "autogpt_platform/frontend/.env*",
+    "autogpt_platform/frontend/.auth/**",
+    "autogpt_platform/db/docker/.env*"
+  ],
+  "worktreeCopyIgnores": [
+    "**/node_modules/**",
+    "**/dist/**",
+    "**/.git/**",
+    "**/Thumbs.db",
+    "**/.DS_Store",
+    "**/.next/**",
+    "**/__pycache__/**",
+    "**/.ruff_cache/**",
+    "**/.pytest_cache/**",
+    "**/*.pyc",
+    "**/playwright-report/**",
+    "**/logs/**",
+    "**/site/**"
+  ],
+  "worktreePathTemplate": "$BASE_PATH.worktree",
+  "postCreateCmd": [
+    "cd autogpt_platform/autogpt_libs && poetry install",
+    "cd autogpt_platform/backend && poetry install && poetry run prisma generate",
+    "cd autogpt_platform/frontend && pnpm install",
+    "cd docs && pip install -r requirements.txt"
+  ],
+  "terminalCommand": "code .",
+  "deleteBranchWithWorktree": false
+}

.dockerignore

@@ -16,6 +16,7 @@
 !autogpt_platform/backend/poetry.lock
 !autogpt_platform/backend/README.md
 !autogpt_platform/backend/.env
+!autogpt_platform/backend/gen_prisma_types_stub.py
 
 # Platform - Market
 !autogpt_platform/market/market/

.github/workflows/claude-dependabot.yml

@@ -74,7 +74,7 @@ jobs:
 
       - name: Generate Prisma Client
         working-directory: autogpt_platform/backend
-        run: poetry run prisma generate
+        run: poetry run prisma generate && poetry run gen-prisma-stub
 
       # Frontend Node.js/pnpm setup (mirrors platform-frontend-ci.yml)
       - name: Set up Node.js

.github/workflows/claude.yml

@@ -90,7 +90,7 @@ jobs:
 
       - name: Generate Prisma Client
         working-directory: autogpt_platform/backend
-        run: poetry run prisma generate
+        run: poetry run prisma generate && poetry run gen-prisma-stub
 
       # Frontend Node.js/pnpm setup (mirrors platform-frontend-ci.yml)
       - name: Set up Node.js

.github/workflows/copilot-setup-steps.yml

@@ -72,7 +72,7 @@ jobs:
 
       - name: Generate Prisma Client
         working-directory: autogpt_platform/backend
-        run: poetry run prisma generate
+        run: poetry run prisma generate && poetry run gen-prisma-stub
 
       # Frontend Node.js/pnpm setup (mirrors platform-frontend-ci.yml)
       - name: Set up Node.js
@@ -108,6 +108,16 @@ jobs:
       #   run: pnpm playwright install --with-deps chromium
 
       # Docker setup for development environment
+      - name: Free up disk space
+        run: |
+          # Remove large unused tools to free disk space for Docker builds
+          sudo rm -rf /usr/share/dotnet
+          sudo rm -rf /usr/local/lib/android
+          sudo rm -rf /opt/ghc
+          sudo rm -rf /opt/hostedtoolcache/CodeQL
+          sudo docker system prune -af
+          df -h
+
       - name: Set up Docker Buildx
         uses: docker/setup-buildx-action@v3
 

.github/workflows/platform-backend-ci.yml

@@ -134,7 +134,7 @@ jobs:
         run: poetry install
 
       - name: Generate Prisma Client
-        run: poetry run prisma generate
+        run: poetry run prisma generate && poetry run gen-prisma-stub
 
       - id: supabase
         name: Start Supabase

autogpt_platform/Makefile

@@ -12,6 +12,7 @@ reset-db:
 	rm -rf db/docker/volumes/db/data
 	cd backend && poetry run prisma migrate deploy
 	cd backend && poetry run prisma generate
+	cd backend && poetry run gen-prisma-stub
 	
 # View logs for core services
 logs-core:
@@ -33,6 +34,7 @@ init-env:
 migrate:
 	cd backend && poetry run prisma migrate deploy
 	cd backend && poetry run prisma generate
+	cd backend && poetry run gen-prisma-stub
 
 run-backend:
 	cd backend && poetry run app

autogpt_platform/backend/Dockerfile

@@ -48,7 +48,8 @@ RUN poetry install --no-ansi --no-root
 # Generate Prisma client
 COPY autogpt_platform/backend/schema.prisma ./
 COPY autogpt_platform/backend/backend/data/partial_types.py ./backend/data/partial_types.py
-RUN poetry run prisma generate
+COPY autogpt_platform/backend/gen_prisma_types_stub.py ./
+RUN poetry run prisma generate && poetry run gen-prisma-stub
 
 FROM debian:13-slim AS server_dependencies
 

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

@@ -489,7 +489,7 @@ async def update_agent_version_in_library(
     agent_graph_version: int,
 ) -> library_model.LibraryAgent:
     """
-    Updates the agent version in the library if useGraphIsActiveVersion is True.
+    Updates the agent version in the library for any agent owned by the user.
 
     Args:
         user_id: Owner of the LibraryAgent.
@@ -498,20 +498,31 @@ async def update_agent_version_in_library(
 
     Raises:
         DatabaseError: If there's an error with the update.
+        NotFoundError: If no library agent is found for this user and agent.
     """
     logger.debug(
         f"Updating agent version in library for user #{user_id}, "
         f"agent #{agent_graph_id} v{agent_graph_version}"
     )
-    try:
-        library_agent = await prisma.models.LibraryAgent.prisma().find_first_or_raise(
+    async with transaction() as tx:
+        library_agent = await prisma.models.LibraryAgent.prisma(tx).find_first_or_raise(
             where={
                 "userId": user_id,
                 "agentGraphId": agent_graph_id,
-                "useGraphIsActiveVersion": True,
             },
         )
-        lib = await prisma.models.LibraryAgent.prisma().update(
+
+        # Delete any conflicting LibraryAgent for the target version
+        await prisma.models.LibraryAgent.prisma(tx).delete_many(
+            where={
+                "userId": user_id,
+                "agentGraphId": agent_graph_id,
+                "agentGraphVersion": agent_graph_version,
+                "id": {"not": library_agent.id},
+            }
+        )
+
+        lib = await prisma.models.LibraryAgent.prisma(tx).update(
             where={"id": library_agent.id},
             data={
                 "AgentGraph": {
@@ -525,13 +536,13 @@ async def update_agent_version_in_library(
             },
             include={"AgentGraph": True},
         )
-        if lib is None:
-            raise NotFoundError(f"Library agent {library_agent.id} not found")
 
-        return library_model.LibraryAgent.from_db(lib)
-    except prisma.errors.PrismaError as e:
-        logger.error(f"Database error updating agent version in library: {e}")
-        raise DatabaseError("Failed to update agent version in library") from e
+    if lib is None:
+        raise NotFoundError(
+            f"Failed to update library agent for {agent_graph_id} v{agent_graph_version}"
+        )
+
+    return library_model.LibraryAgent.from_db(lib)
 
 
 async def update_library_agent(
@@ -825,6 +836,7 @@ async def add_store_agent_to_library(
                     }
                 },
                 "isCreatedByUser": False,
+                "useGraphIsActiveVersion": False,
                 "settings": SafeJson(
                     _initialize_graph_settings(graph_model).model_dump()
                 ),

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

@@ -48,6 +48,7 @@ class LibraryAgent(pydantic.BaseModel):
     id: str
     graph_id: str
     graph_version: int
+    owner_user_id: str  # ID of user who owns/created this agent graph
 
     image_url: str | None
 
@@ -163,6 +164,7 @@ class LibraryAgent(pydantic.BaseModel):
             id=agent.id,
             graph_id=agent.agentGraphId,
             graph_version=agent.agentGraphVersion,
+            owner_user_id=agent.userId,
             image_url=agent.imageUrl,
             creator_name=creator_name,
             creator_image_url=creator_image_url,

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

@@ -42,6 +42,7 @@ async def test_get_library_agents_success(
                 id="test-agent-1",
                 graph_id="test-agent-1",
                 graph_version=1,
+                owner_user_id=test_user_id,
                 name="Test Agent 1",
                 description="Test Description 1",
                 image_url=None,
@@ -64,6 +65,7 @@ async def test_get_library_agents_success(
                 id="test-agent-2",
                 graph_id="test-agent-2",
                 graph_version=1,
+                owner_user_id=test_user_id,
                 name="Test Agent 2",
                 description="Test Description 2",
                 image_url=None,
@@ -138,6 +140,7 @@ async def test_get_favorite_library_agents_success(
                 id="test-agent-1",
                 graph_id="test-agent-1",
                 graph_version=1,
+                owner_user_id=test_user_id,
                 name="Favorite Agent 1",
                 description="Test Favorite Description 1",
                 image_url=None,
@@ -205,6 +208,7 @@ def test_add_agent_to_library_success(
         id="test-library-agent-id",
         graph_id="test-agent-1",
         graph_version=1,
+        owner_user_id=test_user_id,
         name="Test Agent 1",
         description="Test Description 1",
         image_url=None,

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

@@ -614,6 +614,7 @@ async def get_store_submissions(
         submission_models = []
         for sub in submissions:
             submission_model = store_model.StoreSubmission(
+                listing_id=sub.listing_id,
                 agent_id=sub.agent_id,
                 agent_version=sub.agent_version,
                 name=sub.name,
@@ -667,35 +668,48 @@ async def delete_store_submission(
     submission_id: str,
 ) -> bool:
     """
-    Delete a store listing submission as the submitting user.
+    Delete a store submission version as the submitting user.
 
     Args:
         user_id: ID of the authenticated user
-        submission_id: ID of the submission to be deleted
+        submission_id: StoreListingVersion ID to delete
 
     Returns:
-        bool: True if the submission was successfully deleted, False otherwise
+        bool: True if successfully deleted
     """
-    logger.debug(f"Deleting store submission {submission_id} for user {user_id}")
-
     try:
-        # Verify the submission belongs to this user
-        submission = await prisma.models.StoreListing.prisma().find_first(
-            where={"agentGraphId": submission_id, "owningUserId": user_id}
+        # Find the submission version with ownership check
+        version = await prisma.models.StoreListingVersion.prisma().find_first(
+            where={"id": submission_id}, include={"StoreListing": True}
         )
 
-        if not submission:
-            logger.warning(f"Submission not found for user {user_id}: {submission_id}")
-            raise store_exceptions.SubmissionNotFoundError(
-                f"Submission not found for this user. User ID: {user_id}, Submission ID: {submission_id}"
+        if (
+            not version
+            or not version.StoreListing
+            or version.StoreListing.owningUserId != user_id
+        ):
+            raise store_exceptions.SubmissionNotFoundError("Submission not found")
+
+        # Prevent deletion of approved submissions
+        if version.submissionStatus == prisma.enums.SubmissionStatus.APPROVED:
+            raise store_exceptions.InvalidOperationError(
+                "Cannot delete approved submissions"
             )
 
-        # Delete the submission
-        await prisma.models.StoreListing.prisma().delete(where={"id": submission.id})
-
-        logger.debug(
-            f"Successfully deleted submission {submission_id} for user {user_id}"
+        # Delete the version
+        await prisma.models.StoreListingVersion.prisma().delete(
+            where={"id": version.id}
         )
+
+        # Clean up empty listing if this was the last version
+        remaining = await prisma.models.StoreListingVersion.prisma().count(
+            where={"storeListingId": version.storeListingId}
+        )
+        if remaining == 0:
+            await prisma.models.StoreListing.prisma().delete(
+                where={"id": version.storeListingId}
+            )
+
         return True
 
     except Exception as e:
@@ -759,9 +773,15 @@ async def create_store_submission(
             logger.warning(
                 f"Agent not found for user {user_id}: {agent_id} v{agent_version}"
             )
-            raise store_exceptions.AgentNotFoundError(
-                f"Agent not found for this user. User ID: {user_id}, Agent ID: {agent_id}, Version: {agent_version}"
-            )
+            # Provide more user-friendly error message when agent_id is empty
+            if not agent_id or agent_id.strip() == "":
+                raise store_exceptions.AgentNotFoundError(
+                    "No agent selected. Please select an agent before submitting to the store."
+                )
+            else:
+                raise store_exceptions.AgentNotFoundError(
+                    f"Agent not found for this user. User ID: {user_id}, Agent ID: {agent_id}, Version: {agent_version}"
+                )
 
         # Check if listing already exists for this agent
         existing_listing = await prisma.models.StoreListing.prisma().find_first(
@@ -833,6 +853,7 @@ async def create_store_submission(
         logger.debug(f"Created store listing for agent {agent_id}")
         # Return submission details
         return store_model.StoreSubmission(
+            listing_id=listing.id,
             agent_id=agent_id,
             agent_version=agent_version,
             name=name,
@@ -944,81 +965,56 @@ async def edit_store_submission(
         # Currently we are not allowing user to update the agent associated with a submission
         # If we allow it in future, then we need a check here to verify the agent belongs to this user.
 
-        # Check if we can edit this submission
-        if current_version.submissionStatus == prisma.enums.SubmissionStatus.REJECTED:
+        # Only allow editing of PENDING submissions
+        if current_version.submissionStatus != prisma.enums.SubmissionStatus.PENDING:
             raise store_exceptions.InvalidOperationError(
-                "Cannot edit a rejected submission"
-            )
-
-        # For APPROVED submissions, we need to create a new version
-        if current_version.submissionStatus == prisma.enums.SubmissionStatus.APPROVED:
-            # Create a new version for the existing listing
-            return await create_store_version(
-                user_id=user_id,
-                agent_id=current_version.agentGraphId,
-                agent_version=current_version.agentGraphVersion,
-                store_listing_id=current_version.storeListingId,
-                name=name,
-                video_url=video_url,
-                agent_output_demo_url=agent_output_demo_url,
-                image_urls=image_urls,
-                description=description,
-                sub_heading=sub_heading,
-                categories=categories,
-                changes_summary=changes_summary,
-                recommended_schedule_cron=recommended_schedule_cron,
-                instructions=instructions,
+                f"Cannot edit a {current_version.submissionStatus.value.lower()} submission. Only pending submissions can be edited."
             )
 
         # For PENDING submissions, we can update the existing version
-        elif current_version.submissionStatus == prisma.enums.SubmissionStatus.PENDING:
-            # Update the existing version
-            updated_version = await prisma.models.StoreListingVersion.prisma().update(
-                where={"id": store_listing_version_id},
-                data=prisma.types.StoreListingVersionUpdateInput(
-                    name=name,
-                    videoUrl=video_url,
-                    agentOutputDemoUrl=agent_output_demo_url,
-                    imageUrls=image_urls,
-                    description=description,
-                    categories=categories,
-                    subHeading=sub_heading,
-                    changesSummary=changes_summary,
-                    recommendedScheduleCron=recommended_schedule_cron,
-                    instructions=instructions,
-                ),
-            )
-
-            logger.debug(
-                f"Updated existing version {store_listing_version_id} for agent {current_version.agentGraphId}"
-            )
-
-            if not updated_version:
-                raise DatabaseError("Failed to update store listing version")
-            return store_model.StoreSubmission(
-                agent_id=current_version.agentGraphId,
-                agent_version=current_version.agentGraphVersion,
+        # Update the existing version
+        updated_version = await prisma.models.StoreListingVersion.prisma().update(
+            where={"id": store_listing_version_id},
+            data=prisma.types.StoreListingVersionUpdateInput(
                 name=name,
-                sub_heading=sub_heading,
-                slug=current_version.StoreListing.slug,
+                videoUrl=video_url,
+                agentOutputDemoUrl=agent_output_demo_url,
+                imageUrls=image_urls,
                 description=description,
-                instructions=instructions,
-                image_urls=image_urls,
-                date_submitted=updated_version.submittedAt or updated_version.createdAt,
-                status=updated_version.submissionStatus,
-                runs=0,
-                rating=0.0,
-                store_listing_version_id=updated_version.id,
-                changes_summary=changes_summary,
-                video_url=video_url,
                 categories=categories,
-                version=updated_version.version,
-            )
+                subHeading=sub_heading,
+                changesSummary=changes_summary,
+                recommendedScheduleCron=recommended_schedule_cron,
+                instructions=instructions,
+            ),
+        )
 
-        else:
-            raise store_exceptions.InvalidOperationError(
-                f"Cannot edit submission with status: {current_version.submissionStatus}"
-            )
+        logger.debug(
+            f"Updated existing version {store_listing_version_id} for agent {current_version.agentGraphId}"
+        )
+
+        if not updated_version:
+            raise DatabaseError("Failed to update store listing version")
+        return store_model.StoreSubmission(
+            listing_id=current_version.StoreListing.id,
+            agent_id=current_version.agentGraphId,
+            agent_version=current_version.agentGraphVersion,
+            name=name,
+            sub_heading=sub_heading,
+            slug=current_version.StoreListing.slug,
+            description=description,
+            instructions=instructions,
+            image_urls=image_urls,
+            date_submitted=updated_version.submittedAt or updated_version.createdAt,
+            status=updated_version.submissionStatus,
+            runs=0,
+            rating=0.0,
+            store_listing_version_id=updated_version.id,
+            changes_summary=changes_summary,
+            video_url=video_url,
+            categories=categories,
+            version=updated_version.version,
+        )
 
     except (
         store_exceptions.SubmissionNotFoundError,
@@ -1097,38 +1093,78 @@ async def create_store_version(
                 f"Agent not found for this user. User ID: {user_id}, Agent ID: {agent_id}, Version: {agent_version}"
             )
 
-        # Get the latest version number
-        latest_version = listing.Versions[0] if listing.Versions else None
-
-        next_version = (latest_version.version + 1) if latest_version else 1
-
-        # Create a new version for the existing listing
-        new_version = await prisma.models.StoreListingVersion.prisma().create(
-            data=prisma.types.StoreListingVersionCreateInput(
-                version=next_version,
-                agentGraphId=agent_id,
-                agentGraphVersion=agent_version,
-                name=name,
-                videoUrl=video_url,
-                agentOutputDemoUrl=agent_output_demo_url,
-                imageUrls=image_urls,
-                description=description,
-                instructions=instructions,
-                categories=categories,
-                subHeading=sub_heading,
-                submissionStatus=prisma.enums.SubmissionStatus.PENDING,
-                submittedAt=datetime.now(),
-                changesSummary=changes_summary,
-                recommendedScheduleCron=recommended_schedule_cron,
-                storeListingId=store_listing_id,
+        # Check if there's already a PENDING submission for this agent (any version)
+        existing_pending_submission = (
+            await prisma.models.StoreListingVersion.prisma().find_first(
+                where=prisma.types.StoreListingVersionWhereInput(
+                    storeListingId=store_listing_id,
+                    agentGraphId=agent_id,
+                    submissionStatus=prisma.enums.SubmissionStatus.PENDING,
+                    isDeleted=False,
+                )
             )
         )
 
+        # Handle existing pending submission and create new one atomically
+        async with transaction() as tx:
+            # Get the latest version number first
+            latest_listing = await prisma.models.StoreListing.prisma(tx).find_first(
+                where=prisma.types.StoreListingWhereInput(
+                    id=store_listing_id, owningUserId=user_id
+                ),
+                include={"Versions": {"order_by": {"version": "desc"}, "take": 1}},
+            )
+
+            if not latest_listing:
+                raise store_exceptions.ListingNotFoundError(
+                    f"Store listing not found. User ID: {user_id}, Listing ID: {store_listing_id}"
+                )
+
+            latest_version = (
+                latest_listing.Versions[0] if latest_listing.Versions else None
+            )
+            next_version = (latest_version.version + 1) if latest_version else 1
+
+            # If there's an existing pending submission, delete it atomically before creating new one
+            if existing_pending_submission:
+                logger.info(
+                    f"Found existing PENDING submission for agent {agent_id} (was v{existing_pending_submission.agentGraphVersion}, now v{agent_version}), replacing existing submission instead of creating duplicate"
+                )
+                await prisma.models.StoreListingVersion.prisma(tx).delete(
+                    where={"id": existing_pending_submission.id}
+                )
+                logger.debug(
+                    f"Deleted existing pending submission {existing_pending_submission.id}"
+                )
+
+            # Create a new version for the existing listing
+            new_version = await prisma.models.StoreListingVersion.prisma(tx).create(
+                data=prisma.types.StoreListingVersionCreateInput(
+                    version=next_version,
+                    agentGraphId=agent_id,
+                    agentGraphVersion=agent_version,
+                    name=name,
+                    videoUrl=video_url,
+                    agentOutputDemoUrl=agent_output_demo_url,
+                    imageUrls=image_urls,
+                    description=description,
+                    instructions=instructions,
+                    categories=categories,
+                    subHeading=sub_heading,
+                    submissionStatus=prisma.enums.SubmissionStatus.PENDING,
+                    submittedAt=datetime.now(),
+                    changesSummary=changes_summary,
+                    recommendedScheduleCron=recommended_schedule_cron,
+                    storeListingId=store_listing_id,
+                )
+            )
+
         logger.debug(
             f"Created new version for listing {store_listing_id} of agent {agent_id}"
         )
         # Return submission details
         return store_model.StoreSubmission(
+            listing_id=listing.id,
             agent_id=agent_id,
             agent_version=agent_version,
             name=name,
@@ -1708,15 +1744,12 @@ async def review_store_submission(
 
         # Convert to Pydantic model for consistency
         return store_model.StoreSubmission(
+            listing_id=(submission.StoreListing.id if submission.StoreListing else ""),
             agent_id=submission.agentGraphId,
             agent_version=submission.agentGraphVersion,
             name=submission.name,
             sub_heading=submission.subHeading,
-            slug=(
-                submission.StoreListing.slug
-                if hasattr(submission, "storeListing") and submission.StoreListing
-                else ""
-            ),
+            slug=(submission.StoreListing.slug if submission.StoreListing else ""),
             description=submission.description,
             instructions=submission.instructions,
             image_urls=submission.imageUrls or [],
@@ -1818,9 +1851,7 @@ async def get_admin_listings_with_versions(
         where = prisma.types.StoreListingWhereInput(**where_dict)
         include = prisma.types.StoreListingInclude(
             Versions=prisma.types.FindManyStoreListingVersionArgsFromStoreListing(
-                order_by=prisma.types._StoreListingVersion_version_OrderByInput(
-                    version="desc"
-                )
+                order_by={"version": "desc"}
             ),
             OwningUser=True,
         )
@@ -1845,6 +1876,7 @@ async def get_admin_listings_with_versions(
             # If we have versions, turn them into StoreSubmission models
             for version in listing.Versions or []:
                 version_model = store_model.StoreSubmission(
+                    listing_id=listing.id,
                     agent_id=version.agentGraphId,
                     agent_version=version.agentGraphVersion,
                     name=version.name,

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

@@ -110,6 +110,7 @@ class Profile(pydantic.BaseModel):
 
 
 class StoreSubmission(pydantic.BaseModel):
+    listing_id: str
     agent_id: str
     agent_version: int
     name: str
@@ -164,8 +165,12 @@ class StoreListingsWithVersionsResponse(pydantic.BaseModel):
 
 
 class StoreSubmissionRequest(pydantic.BaseModel):
-    agent_id: str
-    agent_version: int
+    agent_id: str = pydantic.Field(
+        ..., min_length=1, description="Agent ID cannot be empty"
+    )
+    agent_version: int = pydantic.Field(
+        ..., gt=0, description="Agent version must be greater than 0"
+    )
     slug: str
     name: str
     sub_heading: str

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

@@ -138,6 +138,7 @@ def test_creator_details():
 
 def test_store_submission():
     submission = store_model.StoreSubmission(
+        listing_id="listing123",
         agent_id="agent123",
         agent_version=1,
         sub_heading="Test subheading",
@@ -159,6 +160,7 @@ 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",

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

@@ -521,6 +521,7 @@ def test_get_submissions_success(
     mocked_value = store_model.StoreSubmissionsResponse(
         submissions=[
             store_model.StoreSubmission(
+                listing_id="test-listing-id",
                 name="Test Agent",
                 description="Test agent description",
                 image_urls=["test.jpg"],

autogpt_platform/backend/backend/api/rest_api.py

@@ -39,7 +39,7 @@ import backend.data.user
 import backend.integrations.webhooks.utils
 import backend.util.service
 import backend.util.settings
-from backend.blocks.llm import LlmModel
+from backend.blocks.llm import DEFAULT_LLM_MODEL
 from backend.data.model import Credentials
 from backend.integrations.providers import ProviderName
 from backend.monitoring.instrumentation import instrument_fastapi
@@ -113,7 +113,7 @@ async def lifespan_context(app: fastapi.FastAPI):
 
     await backend.data.user.migrate_and_encrypt_user_integrations()
     await backend.data.graph.fix_llm_provider_credentials()
-    await backend.data.graph.migrate_llm_models(LlmModel.GPT4O)
+    await backend.data.graph.migrate_llm_models(DEFAULT_LLM_MODEL)
     await backend.integrations.webhooks.utils.migrate_legacy_triggered_graphs()
 
     with launch_darkly_context():

autogpt_platform/backend/backend/blocks/ai_condition.py

@@ -1,6 +1,7 @@
 from typing import Any
 
 from backend.blocks.llm import (
+    DEFAULT_LLM_MODEL,
     TEST_CREDENTIALS,
     TEST_CREDENTIALS_INPUT,
     AIBlockBase,
@@ -49,7 +50,7 @@ class AIConditionBlock(AIBlockBase):
         )
         model: LlmModel = SchemaField(
             title="LLM Model",
-            default=LlmModel.GPT4O,
+            default=DEFAULT_LLM_MODEL,
             description="The language model to use for evaluating the condition.",
             advanced=False,
         )
@@ -81,7 +82,7 @@ class AIConditionBlock(AIBlockBase):
                 "condition": "the input is an email address",
                 "yes_value": "Valid email",
                 "no_value": "Not an email",
-                "model": LlmModel.GPT4O,
+                "model": DEFAULT_LLM_MODEL,
                 "credentials": TEST_CREDENTIALS_INPUT,
             },
             test_credentials=TEST_CREDENTIALS,

autogpt_platform/backend/backend/blocks/airtable/_webhook.py

@@ -6,6 +6,9 @@ import hashlib
 import hmac
 import logging
 from enum import Enum
+from typing import cast
+
+from prisma.types import Serializable
 
 from backend.sdk import (
     BaseWebhooksManager,
@@ -84,7 +87,9 @@ class AirtableWebhookManager(BaseWebhooksManager):
         # update webhook config
         await update_webhook(
             webhook.id,
-            config={"base_id": base_id, "cursor": response.cursor},
+            config=cast(
+                dict[str, Serializable], {"base_id": base_id, "cursor": response.cursor}
+            ),
         )
 
         event_type = "notification"

autogpt_platform/backend/backend/blocks/claude_code.py

@@ -0,0 +1,602 @@
+import shlex
+from typing import Literal
+
+from e2b import AsyncSandbox as BaseAsyncSandbox
+from pydantic import BaseModel, SecretStr
+
+from backend.data.block import (
+    Block,
+    BlockCategory,
+    BlockOutput,
+    BlockSchemaInput,
+    BlockSchemaOutput,
+)
+from backend.data.model import (
+    APIKeyCredentials,
+    CredentialsField,
+    CredentialsMetaInput,
+    SchemaField,
+)
+from backend.integrations.providers import ProviderName
+
+# Test credentials for E2B
+TEST_E2B_CREDENTIALS = APIKeyCredentials(
+    id="01234567-89ab-cdef-0123-456789abcdef",
+    provider="e2b",
+    api_key=SecretStr("mock-e2b-api-key"),
+    title="Mock E2B API key",
+    expires_at=None,
+)
+TEST_E2B_CREDENTIALS_INPUT = {
+    "provider": TEST_E2B_CREDENTIALS.provider,
+    "id": TEST_E2B_CREDENTIALS.id,
+    "type": TEST_E2B_CREDENTIALS.type,
+    "title": TEST_E2B_CREDENTIALS.title,
+}
+
+# Test credentials for Anthropic
+TEST_ANTHROPIC_CREDENTIALS = APIKeyCredentials(
+    id="2e568a2b-b2ea-475a-8564-9a676bf31c56",
+    provider="anthropic",
+    api_key=SecretStr("mock-anthropic-api-key"),
+    title="Mock Anthropic API key",
+    expires_at=None,
+)
+TEST_ANTHROPIC_CREDENTIALS_INPUT = {
+    "provider": TEST_ANTHROPIC_CREDENTIALS.provider,
+    "id": TEST_ANTHROPIC_CREDENTIALS.id,
+    "type": TEST_ANTHROPIC_CREDENTIALS.type,
+    "title": TEST_ANTHROPIC_CREDENTIALS.title,
+}
+
+
+class ClaudeCodeBlock(Block):
+    """
+    Execute tasks using Claude Code (Anthropic's AI coding assistant) in an E2B sandbox.
+
+    Claude Code can create files, install tools, run commands, and perform complex
+    coding tasks autonomously within a secure sandbox environment.
+    """
+
+    # Use base template - we'll install Claude Code ourselves for latest version
+    DEFAULT_TEMPLATE = "base"
+
+    class Input(BlockSchemaInput):
+        e2b_credentials: CredentialsMetaInput[
+            Literal[ProviderName.E2B], Literal["api_key"]
+        ] = CredentialsField(
+            description=(
+                "API key for the E2B platform to create the sandbox. "
+                "Get one at https://e2b.dev/docs"
+            ),
+        )
+
+        anthropic_credentials: CredentialsMetaInput[
+            Literal[ProviderName.ANTHROPIC], Literal["api_key"]
+        ] = CredentialsField(
+            description=(
+                "API key for Anthropic to power Claude Code. "
+                "Get one at https://console.anthropic.com/"
+            ),
+        )
+
+        prompt: str = SchemaField(
+            description=(
+                "The task or instruction for Claude Code to execute. "
+                "Claude Code can create files, install packages, run commands, "
+                "and perform complex coding tasks."
+            ),
+            placeholder="Create a hello world index.html file",
+            default="",
+            advanced=False,
+        )
+
+        timeout: int = SchemaField(
+            description=(
+                "Sandbox timeout in seconds. Claude Code tasks can take "
+                "a while, so set this appropriately for your task complexity. "
+                "Note: This only applies when creating a new sandbox. "
+                "When reconnecting to an existing sandbox via sandbox_id, "
+                "the original timeout is retained."
+            ),
+            default=300,  # 5 minutes default
+            advanced=True,
+        )
+
+        setup_commands: list[str] = SchemaField(
+            description=(
+                "Optional shell commands to run before executing Claude Code. "
+                "Useful for installing dependencies or setting up the environment."
+            ),
+            default_factory=list,
+            advanced=True,
+        )
+
+        working_directory: str = SchemaField(
+            description="Working directory for Claude Code to operate in.",
+            default="/home/user",
+            advanced=True,
+        )
+
+        # Session/continuation support
+        session_id: str = SchemaField(
+            description=(
+                "Session ID to resume a previous conversation. "
+                "Leave empty for a new conversation. "
+                "Use the session_id from a previous run to continue that conversation."
+            ),
+            default="",
+            advanced=True,
+        )
+
+        sandbox_id: str = SchemaField(
+            description=(
+                "Sandbox ID to reconnect to an existing sandbox. "
+                "Required when resuming a session (along with session_id). "
+                "Use the sandbox_id from a previous run where dispose_sandbox was False."
+            ),
+            default="",
+            advanced=True,
+        )
+
+        conversation_history: str = SchemaField(
+            description=(
+                "Previous conversation history to continue from. "
+                "Use this to restore context on a fresh sandbox if the previous one timed out. "
+                "Pass the conversation_history output from a previous run."
+            ),
+            default="",
+            advanced=True,
+        )
+
+        dispose_sandbox: bool = SchemaField(
+            description=(
+                "Whether to dispose of the sandbox immediately after execution. "
+                "Set to False if you want to continue the conversation later "
+                "(you'll need both sandbox_id and session_id from the output)."
+            ),
+            default=True,
+            advanced=True,
+        )
+
+    class FileOutput(BaseModel):
+        """A file extracted from the sandbox."""
+
+        path: str
+        relative_path: str  # Path relative to working directory (for GitHub, etc.)
+        name: str
+        content: str
+
+    class Output(BlockSchemaOutput):
+        response: str = SchemaField(
+            description="The output/response from Claude Code execution"
+        )
+        files: list["ClaudeCodeBlock.FileOutput"] = SchemaField(
+            description=(
+                "List of files created/modified by Claude Code. "
+                "Each file has 'path', 'name', and 'content' fields."
+            )
+        )
+        conversation_history: str = SchemaField(
+            description=(
+                "Full conversation history including this turn. "
+                "Pass this to conversation_history input to continue on a fresh sandbox "
+                "if the previous sandbox timed out."
+            )
+        )
+        session_id: str = SchemaField(
+            description=(
+                "Session ID for this conversation. "
+                "Pass this back along with sandbox_id to continue the conversation."
+            )
+        )
+        sandbox_id: str = SchemaField(
+            description=(
+                "ID of the sandbox instance. "
+                "Pass this back along with session_id to continue the conversation "
+                "(only available if dispose_sandbox was False)."
+            )
+        )
+
+    def __init__(self):
+        super().__init__(
+            id="4e34f4a5-9b89-4326-ba77-2dd6750b7194",
+            description=(
+                "Execute tasks using Claude Code in an E2B sandbox. "
+                "Claude Code can create files, install tools, run commands, "
+                "and perform complex coding tasks autonomously."
+            ),
+            categories={BlockCategory.DEVELOPER_TOOLS, BlockCategory.AI},
+            input_schema=ClaudeCodeBlock.Input,
+            output_schema=ClaudeCodeBlock.Output,
+            test_credentials={
+                "e2b_credentials": TEST_E2B_CREDENTIALS,
+                "anthropic_credentials": TEST_ANTHROPIC_CREDENTIALS,
+            },
+            test_input={
+                "e2b_credentials": TEST_E2B_CREDENTIALS_INPUT,
+                "anthropic_credentials": TEST_ANTHROPIC_CREDENTIALS_INPUT,
+                "prompt": "Create a hello world HTML file",
+                "timeout": 300,
+                "setup_commands": [],
+                "working_directory": "/home/user",
+                "session_id": "",
+                "sandbox_id": "",
+                "conversation_history": "",
+                "dispose_sandbox": True,
+            },
+            test_output=[
+                ("response", "Created index.html with hello world content"),
+                (
+                    "files",
+                    [
+                        {
+                            "path": "/home/user/index.html",
+                            "relative_path": "index.html",
+                            "name": "index.html",
+                            "content": "<html>Hello World</html>",
+                        }
+                    ],
+                ),
+                (
+                    "conversation_history",
+                    "User: Create a hello world HTML file\n"
+                    "Claude: Created index.html with hello world content",
+                ),
+                ("session_id", str),
+            ],
+            test_mock={
+                "execute_claude_code": lambda *args, **kwargs: (
+                    "Created index.html with hello world content",  # response
+                    [
+                        ClaudeCodeBlock.FileOutput(
+                            path="/home/user/index.html",
+                            relative_path="index.html",
+                            name="index.html",
+                            content="<html>Hello World</html>",
+                        )
+                    ],  # files
+                    "User: Create a hello world HTML file\n"
+                    "Claude: Created index.html with hello world content",  # conversation_history
+                    "test-session-id",  # session_id
+                    "sandbox_id",  # sandbox_id
+                ),
+            },
+        )
+
+    async def execute_claude_code(
+        self,
+        e2b_api_key: str,
+        anthropic_api_key: str,
+        prompt: str,
+        timeout: int,
+        setup_commands: list[str],
+        working_directory: str,
+        session_id: str,
+        existing_sandbox_id: str,
+        conversation_history: str,
+        dispose_sandbox: bool,
+    ) -> tuple[str, list["ClaudeCodeBlock.FileOutput"], str, str, str]:
+        """
+        Execute Claude Code in an E2B sandbox.
+
+        Returns:
+            Tuple of (response, files, conversation_history, session_id, sandbox_id)
+        """
+        import json
+        import uuid
+
+        # Validate that sandbox_id is provided when resuming a session
+        if session_id and not existing_sandbox_id:
+            raise ValueError(
+                "sandbox_id is required when resuming a session with session_id. "
+                "The session state is stored in the original sandbox. "
+                "If the sandbox has timed out, use conversation_history instead "
+                "to restore context on a fresh sandbox."
+            )
+
+        sandbox = None
+
+        try:
+            # Either reconnect to existing sandbox or create a new one
+            if existing_sandbox_id:
+                # Reconnect to existing sandbox for conversation continuation
+                sandbox = await BaseAsyncSandbox.connect(
+                    sandbox_id=existing_sandbox_id,
+                    api_key=e2b_api_key,
+                )
+            else:
+                # Create new sandbox
+                sandbox = await BaseAsyncSandbox.create(
+                    template=self.DEFAULT_TEMPLATE,
+                    api_key=e2b_api_key,
+                    timeout=timeout,
+                    envs={"ANTHROPIC_API_KEY": anthropic_api_key},
+                )
+
+                # Install Claude Code from npm (ensures we get the latest version)
+                install_result = await sandbox.commands.run(
+                    "npm install -g @anthropic-ai/claude-code@latest",
+                    timeout=120,  # 2 min timeout for install
+                )
+                if install_result.exit_code != 0:
+                    raise Exception(
+                        f"Failed to install Claude Code: {install_result.stderr}"
+                    )
+
+                # Run any user-provided setup commands
+                for cmd in setup_commands:
+                    setup_result = await sandbox.commands.run(cmd)
+                    if setup_result.exit_code != 0:
+                        raise Exception(
+                            f"Setup command failed: {cmd}\n"
+                            f"Exit code: {setup_result.exit_code}\n"
+                            f"Stdout: {setup_result.stdout}\n"
+                            f"Stderr: {setup_result.stderr}"
+                        )
+
+            # Generate or use provided session ID
+            current_session_id = session_id if session_id else str(uuid.uuid4())
+
+            # Build base Claude flags
+            base_flags = "-p --dangerously-skip-permissions --output-format json"
+
+            # Add conversation history context if provided (for fresh sandbox continuation)
+            history_flag = ""
+            if conversation_history and not session_id:
+                # Inject previous conversation as context via system prompt
+                # Use consistent escaping via _escape_prompt helper
+                escaped_history = self._escape_prompt(
+                    f"Previous conversation context: {conversation_history}"
+                )
+                history_flag = f" --append-system-prompt {escaped_history}"
+
+            # Build Claude command based on whether we're resuming or starting new
+            # Use shlex.quote for working_directory and session IDs to prevent injection
+            safe_working_dir = shlex.quote(working_directory)
+            if session_id:
+                # Resuming existing session (sandbox still alive)
+                safe_session_id = shlex.quote(session_id)
+                claude_command = (
+                    f"cd {safe_working_dir} && "
+                    f"echo {self._escape_prompt(prompt)} | "
+                    f"claude --resume {safe_session_id} {base_flags}"
+                )
+            else:
+                # New session with specific ID
+                safe_current_session_id = shlex.quote(current_session_id)
+                claude_command = (
+                    f"cd {safe_working_dir} && "
+                    f"echo {self._escape_prompt(prompt)} | "
+                    f"claude --session-id {safe_current_session_id} {base_flags}{history_flag}"
+                )
+
+            result = await sandbox.commands.run(
+                claude_command,
+                timeout=0,  # No command timeout - let sandbox timeout handle it
+            )
+
+            # Check for command failure
+            if result.exit_code != 0:
+                error_msg = result.stderr or result.stdout or "Unknown error"
+                raise Exception(
+                    f"Claude Code command failed with exit code {result.exit_code}:\n"
+                    f"{error_msg}"
+                )
+
+            raw_output = result.stdout or ""
+            sandbox_id = sandbox.sandbox_id
+
+            # Parse JSON output to extract response and build conversation history
+            response = ""
+            new_conversation_history = conversation_history or ""
+
+            try:
+                # The JSON output contains the result
+                output_data = json.loads(raw_output)
+                response = output_data.get("result", raw_output)
+
+                # Build conversation history entry
+                turn_entry = f"User: {prompt}\nClaude: {response}"
+                if new_conversation_history:
+                    new_conversation_history = (
+                        f"{new_conversation_history}\n\n{turn_entry}"
+                    )
+                else:
+                    new_conversation_history = turn_entry
+
+            except json.JSONDecodeError:
+                # If not valid JSON, use raw output
+                response = raw_output
+                turn_entry = f"User: {prompt}\nClaude: {response}"
+                if new_conversation_history:
+                    new_conversation_history = (
+                        f"{new_conversation_history}\n\n{turn_entry}"
+                    )
+                else:
+                    new_conversation_history = turn_entry
+
+            # Extract files from the working directory
+            files = await self._extract_files(sandbox, working_directory)
+
+            return (
+                response,
+                files,
+                new_conversation_history,
+                current_session_id,
+                sandbox_id,
+            )
+
+        finally:
+            if dispose_sandbox and sandbox:
+                await sandbox.kill()
+
+    async def _extract_files(
+        self,
+        sandbox: BaseAsyncSandbox,
+        working_directory: str,
+    ) -> list["ClaudeCodeBlock.FileOutput"]:
+        """
+        Extract files from the sandbox working directory.
+
+        Returns:
+            List of FileOutput objects with path, name, and content
+        """
+        files: list[ClaudeCodeBlock.FileOutput] = []
+
+        # Text file extensions we can safely read
+        text_extensions = {
+            ".txt",
+            ".md",
+            ".html",
+            ".htm",
+            ".css",
+            ".js",
+            ".ts",
+            ".jsx",
+            ".tsx",
+            ".json",
+            ".xml",
+            ".yaml",
+            ".yml",
+            ".toml",
+            ".ini",
+            ".cfg",
+            ".conf",
+            ".py",
+            ".rb",
+            ".php",
+            ".java",
+            ".c",
+            ".cpp",
+            ".h",
+            ".hpp",
+            ".cs",
+            ".go",
+            ".rs",
+            ".swift",
+            ".kt",
+            ".scala",
+            ".sh",
+            ".bash",
+            ".zsh",
+            ".sql",
+            ".graphql",
+            ".env",
+            ".gitignore",
+            ".dockerfile",
+            "Dockerfile",
+            ".vue",
+            ".svelte",
+            ".astro",
+            ".mdx",
+            ".rst",
+            ".tex",
+            ".csv",
+            ".log",
+        }
+
+        try:
+            # List files recursively using find command
+            # Exclude node_modules and .git directories, but allow hidden files
+            # like .env and .gitignore (they're filtered by text_extensions later)
+            safe_working_dir = shlex.quote(working_directory)
+            find_result = await sandbox.commands.run(
+                f"find {safe_working_dir} -type f "
+                f"-not -path '*/node_modules/*' "
+                f"-not -path '*/.git/*' "
+                f"2>/dev/null | head -100"
+            )
+
+            if find_result.stdout:
+                for file_path in find_result.stdout.strip().split("\n"):
+                    if not file_path:
+                        continue
+
+                    # Check if it's a text file we can read
+                    is_text = any(
+                        file_path.endswith(ext) for ext in text_extensions
+                    ) or file_path.endswith("Dockerfile")
+
+                    if is_text:
+                        try:
+                            content = await sandbox.files.read(file_path)
+                            # Handle bytes or string
+                            if isinstance(content, bytes):
+                                content = content.decode("utf-8", errors="replace")
+
+                            # Extract filename from path
+                            file_name = file_path.split("/")[-1]
+
+                            # Calculate relative path by stripping working directory
+                            relative_path = file_path
+                            if file_path.startswith(working_directory):
+                                relative_path = file_path[len(working_directory) :]
+                                # Remove leading slash if present
+                                if relative_path.startswith("/"):
+                                    relative_path = relative_path[1:]
+
+                            files.append(
+                                ClaudeCodeBlock.FileOutput(
+                                    path=file_path,
+                                    relative_path=relative_path,
+                                    name=file_name,
+                                    content=content,
+                                )
+                            )
+                        except Exception:
+                            # Skip files that can't be read
+                            pass
+
+        except Exception:
+            # If file extraction fails, return empty results
+            pass
+
+        return files
+
+    def _escape_prompt(self, prompt: str) -> str:
+        """Escape the prompt for safe shell execution."""
+        # Use single quotes and escape any single quotes in the prompt
+        escaped = prompt.replace("'", "'\"'\"'")
+        return f"'{escaped}'"
+
+    async def run(
+        self,
+        input_data: Input,
+        *,
+        e2b_credentials: APIKeyCredentials,
+        anthropic_credentials: APIKeyCredentials,
+        **kwargs,
+    ) -> BlockOutput:
+        try:
+            (
+                response,
+                files,
+                conversation_history,
+                session_id,
+                sandbox_id,
+            ) = await self.execute_claude_code(
+                e2b_api_key=e2b_credentials.api_key.get_secret_value(),
+                anthropic_api_key=anthropic_credentials.api_key.get_secret_value(),
+                prompt=input_data.prompt,
+                timeout=input_data.timeout,
+                setup_commands=input_data.setup_commands,
+                working_directory=input_data.working_directory,
+                session_id=input_data.session_id,
+                existing_sandbox_id=input_data.sandbox_id,
+                conversation_history=input_data.conversation_history,
+                dispose_sandbox=input_data.dispose_sandbox,
+            )
+
+            yield "response", response
+            # Always yield files (empty list if none) to match Output schema
+            yield "files", [f.model_dump() for f in files]
+            # Always yield conversation_history so user can restore context on fresh sandbox
+            yield "conversation_history", conversation_history
+            # Always yield session_id so user can continue conversation
+            yield "session_id", session_id
+            if not input_data.dispose_sandbox and sandbox_id:
+                yield "sandbox_id", sandbox_id
+
+        except Exception as e:
+            yield "error", str(e)

autogpt_platform/backend/backend/blocks/dataforseo/related_keywords.py

@@ -182,13 +182,10 @@ class DataForSeoRelatedKeywordsBlock(Block):
             if results and len(results) > 0:
                 # results is a list, get the first element
                 first_result = results[0] if isinstance(results, list) else results
-                items = (
-                    first_result.get("items", [])
-                    if isinstance(first_result, dict)
-                    else []
-                )
-                # Ensure items is never None
-                if items is None:
+                # Handle missing key, null value, or valid list value
+                if isinstance(first_result, dict):
+                    items = first_result.get("items") or []
+                else:
                     items = []
                 for item in items:
                     # Extract keyword_data from the item

autogpt_platform/backend/backend/blocks/helpers/review.py

@@ -0,0 +1,184 @@
+"""
+Shared helpers for Human-In-The-Loop (HITL) review functionality.
+Used by both the dedicated HumanInTheLoopBlock and blocks that require human review.
+"""
+
+import logging
+from typing import Any, Optional
+
+from prisma.enums import ReviewStatus
+from pydantic import BaseModel
+
+from backend.data.execution import ExecutionContext, ExecutionStatus
+from backend.data.human_review import ReviewResult
+from backend.executor.manager import async_update_node_execution_status
+from backend.util.clients import get_database_manager_async_client
+
+logger = logging.getLogger(__name__)
+
+
+class ReviewDecision(BaseModel):
+    """Result of a review decision."""
+
+    should_proceed: bool
+    message: str
+    review_result: ReviewResult
+
+
+class HITLReviewHelper:
+    """Helper class for Human-In-The-Loop review operations."""
+
+    @staticmethod
+    async def get_or_create_human_review(**kwargs) -> Optional[ReviewResult]:
+        """Create or retrieve a human review from the database."""
+        return await get_database_manager_async_client().get_or_create_human_review(
+            **kwargs
+        )
+
+    @staticmethod
+    async def update_node_execution_status(**kwargs) -> None:
+        """Update the execution status of a node."""
+        await async_update_node_execution_status(
+            db_client=get_database_manager_async_client(), **kwargs
+        )
+
+    @staticmethod
+    async def update_review_processed_status(
+        node_exec_id: str, processed: bool
+    ) -> None:
+        """Update the processed status of a review."""
+        return await get_database_manager_async_client().update_review_processed_status(
+            node_exec_id, processed
+        )
+
+    @staticmethod
+    async def _handle_review_request(
+        input_data: Any,
+        user_id: str,
+        node_exec_id: str,
+        graph_exec_id: str,
+        graph_id: str,
+        graph_version: int,
+        execution_context: ExecutionContext,
+        block_name: str = "Block",
+        editable: bool = False,
+    ) -> Optional[ReviewResult]:
+        """
+        Handle a review request for a block that requires human review.
+
+        Args:
+            input_data: The input data to be reviewed
+            user_id: ID of the user requesting the review
+            node_exec_id: ID of the node execution
+            graph_exec_id: ID of the graph execution
+            graph_id: ID of the graph
+            graph_version: Version of the graph
+            execution_context: Current execution context
+            block_name: Name of the block requesting review
+            editable: Whether the reviewer can edit the data
+
+        Returns:
+            ReviewResult if review is complete, None if waiting for human input
+
+        Raises:
+            Exception: If review creation or status update fails
+        """
+        # Skip review if safe mode is disabled - return auto-approved result
+        if not execution_context.safe_mode:
+            logger.info(
+                f"Block {block_name} skipping review for node {node_exec_id} - safe mode disabled"
+            )
+            return ReviewResult(
+                data=input_data,
+                status=ReviewStatus.APPROVED,
+                message="Auto-approved (safe mode disabled)",
+                processed=True,
+                node_exec_id=node_exec_id,
+            )
+
+        result = await HITLReviewHelper.get_or_create_human_review(
+            user_id=user_id,
+            node_exec_id=node_exec_id,
+            graph_exec_id=graph_exec_id,
+            graph_id=graph_id,
+            graph_version=graph_version,
+            input_data=input_data,
+            message=f"Review required for {block_name} execution",
+            editable=editable,
+        )
+
+        if result is None:
+            logger.info(
+                f"Block {block_name} pausing execution for node {node_exec_id} - awaiting human review"
+            )
+            await HITLReviewHelper.update_node_execution_status(
+                exec_id=node_exec_id,
+                status=ExecutionStatus.REVIEW,
+            )
+            return None  # Signal that execution should pause
+
+        # Mark review as processed if not already done
+        if not result.processed:
+            await HITLReviewHelper.update_review_processed_status(
+                node_exec_id=node_exec_id, processed=True
+            )
+
+        return result
+
+    @staticmethod
+    async def handle_review_decision(
+        input_data: Any,
+        user_id: str,
+        node_exec_id: str,
+        graph_exec_id: str,
+        graph_id: str,
+        graph_version: int,
+        execution_context: ExecutionContext,
+        block_name: str = "Block",
+        editable: bool = False,
+    ) -> Optional[ReviewDecision]:
+        """
+        Handle a review request and return the decision in a single call.
+
+        Args:
+            input_data: The input data to be reviewed
+            user_id: ID of the user requesting the review
+            node_exec_id: ID of the node execution
+            graph_exec_id: ID of the graph execution
+            graph_id: ID of the graph
+            graph_version: Version of the graph
+            execution_context: Current execution context
+            block_name: Name of the block requesting review
+            editable: Whether the reviewer can edit the data
+
+        Returns:
+            ReviewDecision if review is complete (approved/rejected),
+            None if execution should pause (awaiting review)
+        """
+        review_result = await HITLReviewHelper._handle_review_request(
+            input_data=input_data,
+            user_id=user_id,
+            node_exec_id=node_exec_id,
+            graph_exec_id=graph_exec_id,
+            graph_id=graph_id,
+            graph_version=graph_version,
+            execution_context=execution_context,
+            block_name=block_name,
+            editable=editable,
+        )
+
+        if review_result is None:
+            # Still awaiting review - return None to pause execution
+            return None
+
+        # Review is complete, determine outcome
+        should_proceed = review_result.status == ReviewStatus.APPROVED
+        message = review_result.message or (
+            "Execution approved by reviewer"
+            if should_proceed
+            else "Execution rejected by reviewer"
+        )
+
+        return ReviewDecision(
+            should_proceed=should_proceed, message=message, review_result=review_result
+        )

autogpt_platform/backend/backend/blocks/human_in_the_loop.py

@@ -3,6 +3,7 @@ from typing import Any
 
 from prisma.enums import ReviewStatus
 
+from backend.blocks.helpers.review import HITLReviewHelper
 from backend.data.block import (
     Block,
     BlockCategory,
@@ -11,11 +12,9 @@ from backend.data.block import (
     BlockSchemaOutput,
     BlockType,
 )
-from backend.data.execution import ExecutionContext, ExecutionStatus
+from backend.data.execution import ExecutionContext
 from backend.data.human_review import ReviewResult
 from backend.data.model import SchemaField
-from backend.executor.manager import async_update_node_execution_status
-from backend.util.clients import get_database_manager_async_client
 
 logger = logging.getLogger(__name__)
 
@@ -72,32 +71,26 @@ class HumanInTheLoopBlock(Block):
                 ("approved_data", {"name": "John Doe", "age": 30}),
             ],
             test_mock={
-                "get_or_create_human_review": lambda *_args, **_kwargs: ReviewResult(
-                    data={"name": "John Doe", "age": 30},
-                    status=ReviewStatus.APPROVED,
-                    message="",
-                    processed=False,
-                    node_exec_id="test-node-exec-id",
-                ),
-                "update_node_execution_status": lambda *_args, **_kwargs: None,
-                "update_review_processed_status": lambda *_args, **_kwargs: None,
+                "handle_review_decision": lambda **kwargs: type(
+                    "ReviewDecision",
+                    (),
+                    {
+                        "should_proceed": True,
+                        "message": "Test approval message",
+                        "review_result": ReviewResult(
+                            data={"name": "John Doe", "age": 30},
+                            status=ReviewStatus.APPROVED,
+                            message="",
+                            processed=False,
+                            node_exec_id="test-node-exec-id",
+                        ),
+                    },
+                )(),
             },
         )
 
-    async def get_or_create_human_review(self, **kwargs):
-        return await get_database_manager_async_client().get_or_create_human_review(
-            **kwargs
-        )
-
-    async def update_node_execution_status(self, **kwargs):
-        return await async_update_node_execution_status(
-            db_client=get_database_manager_async_client(), **kwargs
-        )
-
-    async def update_review_processed_status(self, node_exec_id: str, processed: bool):
-        return await get_database_manager_async_client().update_review_processed_status(
-            node_exec_id, processed
-        )
+    async def handle_review_decision(self, **kwargs):
+        return await HITLReviewHelper.handle_review_decision(**kwargs)
 
     async def run(
         self,
@@ -109,7 +102,7 @@ class HumanInTheLoopBlock(Block):
         graph_id: str,
         graph_version: int,
         execution_context: ExecutionContext,
-        **kwargs,
+        **_kwargs,
     ) -> BlockOutput:
         if not execution_context.safe_mode:
             logger.info(
@@ -119,48 +112,28 @@ class HumanInTheLoopBlock(Block):
             yield "review_message", "Auto-approved (safe mode disabled)"
             return
 
-        try:
-            result = await self.get_or_create_human_review(
-                user_id=user_id,
-                node_exec_id=node_exec_id,
-                graph_exec_id=graph_exec_id,
-                graph_id=graph_id,
-                graph_version=graph_version,
-                input_data=input_data.data,
-                message=input_data.name,
-                editable=input_data.editable,
-            )
-        except Exception as e:
-            logger.error(f"Error in HITL block for node {node_exec_id}: {str(e)}")
-            raise
+        decision = await self.handle_review_decision(
+            input_data=input_data.data,
+            user_id=user_id,
+            node_exec_id=node_exec_id,
+            graph_exec_id=graph_exec_id,
+            graph_id=graph_id,
+            graph_version=graph_version,
+            execution_context=execution_context,
+            block_name=self.name,
+            editable=input_data.editable,
+        )
 
-        if result is None:
-            logger.info(
-                f"HITL block pausing execution for node {node_exec_id} - awaiting human review"
-            )
-            try:
-                await self.update_node_execution_status(
-                    exec_id=node_exec_id,
-                    status=ExecutionStatus.REVIEW,
-                )
-                return
-            except Exception as e:
-                logger.error(
-                    f"Failed to update node status for HITL block {node_exec_id}: {str(e)}"
-                )
-                raise
+        if decision is None:
+            return
 
-        if not result.processed:
-            await self.update_review_processed_status(
-                node_exec_id=node_exec_id, processed=True
-            )
+        status = decision.review_result.status
+        if status == ReviewStatus.APPROVED:
+            yield "approved_data", decision.review_result.data
+        elif status == ReviewStatus.REJECTED:
+            yield "rejected_data", decision.review_result.data
+        else:
+            raise RuntimeError(f"Unexpected review status: {status}")
 
-            if result.status == ReviewStatus.APPROVED:
-                yield "approved_data", result.data
-                if result.message:
-                    yield "review_message", result.message
-
-            elif result.status == ReviewStatus.REJECTED:
-                yield "rejected_data", result.data
-                if result.message:
-                    yield "review_message", result.message
+        if decision.message:
+            yield "review_message", decision.message

autogpt_platform/backend/backend/blocks/llm.py

@@ -92,8 +92,9 @@ class LlmModel(str, Enum, metaclass=LlmModelMeta):
     O1 = "o1"
     O1_MINI = "o1-mini"
     # GPT-5 models
-    GPT5 = "gpt-5-2025-08-07"
+    GPT5_2 = "gpt-5.2-2025-12-11"
     GPT5_1 = "gpt-5.1-2025-11-13"
+    GPT5 = "gpt-5-2025-08-07"
     GPT5_MINI = "gpt-5-mini-2025-08-07"
     GPT5_NANO = "gpt-5-nano-2025-08-07"
     GPT5_CHAT = "gpt-5-chat-latest"
@@ -194,8 +195,9 @@ MODEL_METADATA = {
     LlmModel.O1: ModelMetadata("openai", 200000, 100000),  # o1-2024-12-17
     LlmModel.O1_MINI: ModelMetadata("openai", 128000, 65536),  # o1-mini-2024-09-12
     # GPT-5 models
-    LlmModel.GPT5: ModelMetadata("openai", 400000, 128000),
+    LlmModel.GPT5_2: ModelMetadata("openai", 400000, 128000),
     LlmModel.GPT5_1: ModelMetadata("openai", 400000, 128000),
+    LlmModel.GPT5: ModelMetadata("openai", 400000, 128000),
     LlmModel.GPT5_MINI: ModelMetadata("openai", 400000, 128000),
     LlmModel.GPT5_NANO: ModelMetadata("openai", 400000, 128000),
     LlmModel.GPT5_CHAT: ModelMetadata("openai", 400000, 16384),
@@ -303,6 +305,8 @@ MODEL_METADATA = {
     LlmModel.V0_1_0_MD: ModelMetadata("v0", 128000, 64000),
 }
 
+DEFAULT_LLM_MODEL = LlmModel.GPT5_2
+
 for model in LlmModel:
     if model not in MODEL_METADATA:
         raise ValueError(f"Missing MODEL_METADATA metadata for model: {model}")
@@ -790,7 +794,7 @@ class AIStructuredResponseGeneratorBlock(AIBlockBase):
         )
         model: LlmModel = SchemaField(
             title="LLM Model",
-            default=LlmModel.GPT4O,
+            default=DEFAULT_LLM_MODEL,
             description="The language model to use for answering the prompt.",
             advanced=False,
         )
@@ -855,7 +859,7 @@ class AIStructuredResponseGeneratorBlock(AIBlockBase):
             input_schema=AIStructuredResponseGeneratorBlock.Input,
             output_schema=AIStructuredResponseGeneratorBlock.Output,
             test_input={
-                "model": LlmModel.GPT4O,
+                "model": DEFAULT_LLM_MODEL,
                 "credentials": TEST_CREDENTIALS_INPUT,
                 "expected_format": {
                     "key1": "value1",
@@ -1221,7 +1225,7 @@ class AITextGeneratorBlock(AIBlockBase):
         )
         model: LlmModel = SchemaField(
             title="LLM Model",
-            default=LlmModel.GPT4O,
+            default=DEFAULT_LLM_MODEL,
             description="The language model to use for answering the prompt.",
             advanced=False,
         )
@@ -1317,7 +1321,7 @@ class AITextSummarizerBlock(AIBlockBase):
         )
         model: LlmModel = SchemaField(
             title="LLM Model",
-            default=LlmModel.GPT4O,
+            default=DEFAULT_LLM_MODEL,
             description="The language model to use for summarizing the text.",
         )
         focus: str = SchemaField(
@@ -1534,7 +1538,7 @@ class AIConversationBlock(AIBlockBase):
         )
         model: LlmModel = SchemaField(
             title="LLM Model",
-            default=LlmModel.GPT4O,
+            default=DEFAULT_LLM_MODEL,
             description="The language model to use for the conversation.",
         )
         credentials: AICredentials = AICredentialsField()
@@ -1572,7 +1576,7 @@ class AIConversationBlock(AIBlockBase):
                     },
                     {"role": "user", "content": "Where was it played?"},
                 ],
-                "model": LlmModel.GPT4O,
+                "model": DEFAULT_LLM_MODEL,
                 "credentials": TEST_CREDENTIALS_INPUT,
             },
             test_credentials=TEST_CREDENTIALS,
@@ -1635,7 +1639,7 @@ class AIListGeneratorBlock(AIBlockBase):
         )
         model: LlmModel = SchemaField(
             title="LLM Model",
-            default=LlmModel.GPT4O,
+            default=DEFAULT_LLM_MODEL,
             description="The language model to use for generating the list.",
             advanced=True,
         )
@@ -1692,7 +1696,7 @@ class AIListGeneratorBlock(AIBlockBase):
                     "drawing explorers to uncover its mysteries. Each planet showcases the limitless possibilities of "
                     "fictional worlds."
                 ),
-                "model": LlmModel.GPT4O,
+                "model": DEFAULT_LLM_MODEL,
                 "credentials": TEST_CREDENTIALS_INPUT,
                 "max_retries": 3,
                 "force_json_output": False,

autogpt_platform/backend/backend/blocks/search.py

@@ -18,6 +18,7 @@ from backend.data.model import (
     SchemaField,
 )
 from backend.integrations.providers import ProviderName
+from backend.util.request import DEFAULT_USER_AGENT
 
 
 class GetWikipediaSummaryBlock(Block, GetRequest):
@@ -39,17 +40,27 @@ class GetWikipediaSummaryBlock(Block, GetRequest):
             output_schema=GetWikipediaSummaryBlock.Output,
             test_input={"topic": "Artificial Intelligence"},
             test_output=("summary", "summary content"),
-            test_mock={"get_request": lambda url, json: {"extract": "summary content"}},
+            test_mock={
+                "get_request": lambda url, headers, json: {"extract": "summary content"}
+            },
         )
 
     async def run(self, input_data: Input, **kwargs) -> BlockOutput:
         topic = input_data.topic
-        url = f"https://en.wikipedia.org/api/rest_v1/page/summary/{topic}"
+        # URL-encode the topic to handle spaces and special characters
+        encoded_topic = quote(topic, safe="")
+        url = f"https://en.wikipedia.org/api/rest_v1/page/summary/{encoded_topic}"
+
+        # Set headers per Wikimedia robot policy (https://w.wiki/4wJS)
+        # - User-Agent: Required, must identify the bot
+        # - Accept-Encoding: gzip recommended to reduce bandwidth
+        headers = {
+            "User-Agent": DEFAULT_USER_AGENT,
+            "Accept-Encoding": "gzip, deflate",
+        }
 
-        # Note: User-Agent is now automatically set by the request library
-        # to comply with Wikimedia's robot policy (https://w.wiki/4wJS)
         try:
-            response = await self.get_request(url, json=True)
+            response = await self.get_request(url, headers=headers, json=True)
             if "extract" not in response:
                 raise ValueError(f"Unable to parse Wikipedia response: {response}")
             yield "summary", response["extract"]

autogpt_platform/backend/backend/blocks/smart_decision_maker.py

@@ -226,7 +226,7 @@ class SmartDecisionMakerBlock(Block):
         )
         model: llm.LlmModel = SchemaField(
             title="LLM Model",
-            default=llm.LlmModel.GPT4O,
+            default=llm.DEFAULT_LLM_MODEL,
             description="The language model to use for answering the prompt.",
             advanced=False,
         )
@@ -391,8 +391,12 @@ class SmartDecisionMakerBlock(Block):
         """
         block = sink_node.block
 
+        # Use custom name from node metadata if set, otherwise fall back to block.name
+        custom_name = sink_node.metadata.get("customized_name")
+        tool_name = custom_name if custom_name else block.name
+
         tool_function: dict[str, Any] = {
-            "name": SmartDecisionMakerBlock.cleanup(block.name),
+            "name": SmartDecisionMakerBlock.cleanup(tool_name),
             "description": block.description,
         }
         sink_block_input_schema = block.input_schema
@@ -489,14 +493,24 @@ class SmartDecisionMakerBlock(Block):
                 f"Sink graph metadata not found: {graph_id} {graph_version}"
             )
 
+        # Use custom name from node metadata if set, otherwise fall back to graph name
+        custom_name = sink_node.metadata.get("customized_name")
+        tool_name = custom_name if custom_name else sink_graph_meta.name
+
         tool_function: dict[str, Any] = {
-            "name": SmartDecisionMakerBlock.cleanup(sink_graph_meta.name),
+            "name": SmartDecisionMakerBlock.cleanup(tool_name),
             "description": sink_graph_meta.description,
         }
 
         properties = {}
+        field_mapping = {}
 
         for link in links:
+            field_name = link.sink_name
+
+            clean_field_name = SmartDecisionMakerBlock.cleanup(field_name)
+            field_mapping[clean_field_name] = field_name
+
             sink_block_input_schema = sink_node.input_default["input_schema"]
             sink_block_properties = sink_block_input_schema.get("properties", {}).get(
                 link.sink_name, {}
@@ -506,7 +520,7 @@ class SmartDecisionMakerBlock(Block):
                 if "description" in sink_block_properties
                 else f"The {link.sink_name} of the tool"
             )
-            properties[link.sink_name] = {
+            properties[clean_field_name] = {
                 "type": "string",
                 "description": description,
                 "default": json.dumps(sink_block_properties.get("default", None)),
@@ -519,7 +533,7 @@ class SmartDecisionMakerBlock(Block):
             "strict": True,
         }
 
-        # Store node info for later use in output processing
+        tool_function["_field_mapping"] = field_mapping
         tool_function["_sink_node_id"] = sink_node.id
 
         return {"type": "function", "function": tool_function}
@@ -975,10 +989,28 @@ class SmartDecisionMakerBlock(Block):
         graph_version: int,
         execution_context: ExecutionContext,
         execution_processor: "ExecutionProcessor",
+        nodes_to_skip: set[str] | None = None,
         **kwargs,
     ) -> BlockOutput:
 
         tool_functions = await self._create_tool_node_signatures(node_id)
+        original_tool_count = len(tool_functions)
+
+        # Filter out tools for nodes that should be skipped (e.g., missing optional credentials)
+        if nodes_to_skip:
+            tool_functions = [
+                tf
+                for tf in tool_functions
+                if tf.get("function", {}).get("_sink_node_id") not in nodes_to_skip
+            ]
+
+            # Only raise error if we had tools but they were all filtered out
+            if original_tool_count > 0 and not tool_functions:
+                raise ValueError(
+                    "No available tools to execute - all downstream nodes are unavailable "
+                    "(possibly due to missing optional credentials)"
+                )
+
         yield "tool_functions", json.dumps(tool_functions)
 
         conversation_history = input_data.conversation_history or []
@@ -1129,8 +1161,9 @@ class SmartDecisionMakerBlock(Block):
                 original_field_name = field_mapping.get(clean_arg_name, clean_arg_name)
                 arg_value = tool_args.get(clean_arg_name)
 
-                sanitized_arg_name = self.cleanup(original_field_name)
-                emit_key = f"tools_^_{sink_node_id}_~_{sanitized_arg_name}"
+                # Use original_field_name directly (not sanitized) to match link sink_name
+                # The field_mapping already translates from LLM's cleaned names to original names
+                emit_key = f"tools_^_{sink_node_id}_~_{original_field_name}"
 
                 logger.debug(
                     "[SmartDecisionMakerBlock|geid:%s|neid:%s] emit %s",

autogpt_platform/backend/backend/blocks/test/test_blocks_dos_vulnerability.py

@@ -196,6 +196,15 @@ class TestXMLParserBlockSecurity:
             async for _ in block.run(XMLParserBlock.Input(input_xml=large_xml)):
                 pass
 
+    async def test_rejects_text_outside_root(self):
+        """Ensure parser surfaces readable errors for invalid root text."""
+        block = XMLParserBlock()
+        invalid_xml = "<root><child>value</child></root> trailing"
+
+        with pytest.raises(ValueError, match="text outside the root element"):
+            async for _ in block.run(XMLParserBlock.Input(input_xml=invalid_xml)):
+                pass
+
 
 class TestStoreMediaFileSecurity:
     """Test file storage security limits."""

autogpt_platform/backend/backend/blocks/test/test_llm.py

@@ -28,7 +28,7 @@ class TestLLMStatsTracking:
 
             response = await llm.llm_call(
                 credentials=llm.TEST_CREDENTIALS,
-                llm_model=llm.LlmModel.GPT4O,
+                llm_model=llm.DEFAULT_LLM_MODEL,
                 prompt=[{"role": "user", "content": "Hello"}],
                 max_tokens=100,
             )
@@ -65,7 +65,7 @@ class TestLLMStatsTracking:
         input_data = llm.AIStructuredResponseGeneratorBlock.Input(
             prompt="Test prompt",
             expected_format={"key1": "desc1", "key2": "desc2"},
-            model=llm.LlmModel.GPT4O,
+            model=llm.DEFAULT_LLM_MODEL,
             credentials=llm.TEST_CREDENTIALS_INPUT,  # type: ignore  # type: ignore
         )
 
@@ -109,7 +109,7 @@ class TestLLMStatsTracking:
         # Run the block
         input_data = llm.AITextGeneratorBlock.Input(
             prompt="Generate text",
-            model=llm.LlmModel.GPT4O,
+            model=llm.DEFAULT_LLM_MODEL,
             credentials=llm.TEST_CREDENTIALS_INPUT,  # type: ignore
         )
 
@@ -170,7 +170,7 @@ class TestLLMStatsTracking:
         input_data = llm.AIStructuredResponseGeneratorBlock.Input(
             prompt="Test prompt",
             expected_format={"key1": "desc1", "key2": "desc2"},
-            model=llm.LlmModel.GPT4O,
+            model=llm.DEFAULT_LLM_MODEL,
             credentials=llm.TEST_CREDENTIALS_INPUT,  # type: ignore
             retry=2,
         )
@@ -228,7 +228,7 @@ class TestLLMStatsTracking:
 
         input_data = llm.AITextSummarizerBlock.Input(
             text=long_text,
-            model=llm.LlmModel.GPT4O,
+            model=llm.DEFAULT_LLM_MODEL,
             credentials=llm.TEST_CREDENTIALS_INPUT,  # type: ignore
             max_tokens=100,  # Small chunks
             chunk_overlap=10,
@@ -299,7 +299,7 @@ class TestLLMStatsTracking:
             # Test with very short text (should only need 1 chunk + 1 final summary)
             input_data = llm.AITextSummarizerBlock.Input(
                 text="This is a short text.",
-                model=llm.LlmModel.GPT4O,
+                model=llm.DEFAULT_LLM_MODEL,
                 credentials=llm.TEST_CREDENTIALS_INPUT,  # type: ignore
                 max_tokens=1000,  # Large enough to avoid chunking
             )
@@ -346,7 +346,7 @@ class TestLLMStatsTracking:
                 {"role": "assistant", "content": "Hi there!"},
                 {"role": "user", "content": "How are you?"},
             ],
-            model=llm.LlmModel.GPT4O,
+            model=llm.DEFAULT_LLM_MODEL,
             credentials=llm.TEST_CREDENTIALS_INPUT,  # type: ignore
         )
 
@@ -387,7 +387,7 @@ class TestLLMStatsTracking:
         # Run the block
         input_data = llm.AIListGeneratorBlock.Input(
             focus="test items",
-            model=llm.LlmModel.GPT4O,
+            model=llm.DEFAULT_LLM_MODEL,
             credentials=llm.TEST_CREDENTIALS_INPUT,  # type: ignore
             max_retries=3,
         )
@@ -469,7 +469,7 @@ class TestLLMStatsTracking:
         input_data = llm.AIStructuredResponseGeneratorBlock.Input(
             prompt="Test",
             expected_format={"result": "desc"},
-            model=llm.LlmModel.GPT4O,
+            model=llm.DEFAULT_LLM_MODEL,
             credentials=llm.TEST_CREDENTIALS_INPUT,  # type: ignore
         )
 
@@ -513,7 +513,7 @@ class TestAITextSummarizerValidation:
         # Create input data
         input_data = llm.AITextSummarizerBlock.Input(
             text="Some text to summarize",
-            model=llm.LlmModel.GPT4O,
+            model=llm.DEFAULT_LLM_MODEL,
             credentials=llm.TEST_CREDENTIALS_INPUT,  # type: ignore
             style=llm.SummaryStyle.BULLET_POINTS,
         )
@@ -558,7 +558,7 @@ class TestAITextSummarizerValidation:
         # Create input data
         input_data = llm.AITextSummarizerBlock.Input(
             text="Some text to summarize",
-            model=llm.LlmModel.GPT4O,
+            model=llm.DEFAULT_LLM_MODEL,
             credentials=llm.TEST_CREDENTIALS_INPUT,  # type: ignore
             style=llm.SummaryStyle.BULLET_POINTS,
             max_tokens=1000,
@@ -593,7 +593,7 @@ class TestAITextSummarizerValidation:
         # Create input data
         input_data = llm.AITextSummarizerBlock.Input(
             text="Some text to summarize",
-            model=llm.LlmModel.GPT4O,
+            model=llm.DEFAULT_LLM_MODEL,
             credentials=llm.TEST_CREDENTIALS_INPUT,  # type: ignore
         )
 
@@ -623,7 +623,7 @@ class TestAITextSummarizerValidation:
         # Create input data
         input_data = llm.AITextSummarizerBlock.Input(
             text="Some text to summarize",
-            model=llm.LlmModel.GPT4O,
+            model=llm.DEFAULT_LLM_MODEL,
             credentials=llm.TEST_CREDENTIALS_INPUT,  # type: ignore
             max_tokens=1000,
         )
@@ -654,7 +654,7 @@ class TestAITextSummarizerValidation:
         # Create input data
         input_data = llm.AITextSummarizerBlock.Input(
             text="Some text to summarize",
-            model=llm.LlmModel.GPT4O,
+            model=llm.DEFAULT_LLM_MODEL,
             credentials=llm.TEST_CREDENTIALS_INPUT,  # type: ignore
         )
 

autogpt_platform/backend/backend/blocks/test/test_smart_decision_maker.py

@@ -233,7 +233,7 @@ async def test_smart_decision_maker_tracks_llm_stats():
         # Create test input
         input_data = SmartDecisionMakerBlock.Input(
             prompt="Should I continue with this task?",
-            model=llm_module.LlmModel.GPT4O,
+            model=llm_module.DEFAULT_LLM_MODEL,
             credentials=llm_module.TEST_CREDENTIALS_INPUT,  # type: ignore
             agent_mode_max_iterations=0,
         )
@@ -335,7 +335,7 @@ async def test_smart_decision_maker_parameter_validation():
 
         input_data = SmartDecisionMakerBlock.Input(
             prompt="Search for keywords",
-            model=llm_module.LlmModel.GPT4O,
+            model=llm_module.DEFAULT_LLM_MODEL,
             credentials=llm_module.TEST_CREDENTIALS_INPUT,  # type: ignore
             retry=2,  # Set retry to 2 for testing
             agent_mode_max_iterations=0,
@@ -402,7 +402,7 @@ async def test_smart_decision_maker_parameter_validation():
 
         input_data = SmartDecisionMakerBlock.Input(
             prompt="Search for keywords",
-            model=llm_module.LlmModel.GPT4O,
+            model=llm_module.DEFAULT_LLM_MODEL,
             credentials=llm_module.TEST_CREDENTIALS_INPUT,  # type: ignore
             agent_mode_max_iterations=0,
         )
@@ -462,7 +462,7 @@ async def test_smart_decision_maker_parameter_validation():
 
         input_data = SmartDecisionMakerBlock.Input(
             prompt="Search for keywords",
-            model=llm_module.LlmModel.GPT4O,
+            model=llm_module.DEFAULT_LLM_MODEL,
             credentials=llm_module.TEST_CREDENTIALS_INPUT,  # type: ignore
             agent_mode_max_iterations=0,
         )
@@ -526,7 +526,7 @@ async def test_smart_decision_maker_parameter_validation():
 
         input_data = SmartDecisionMakerBlock.Input(
             prompt="Search for keywords",
-            model=llm_module.LlmModel.GPT4O,
+            model=llm_module.DEFAULT_LLM_MODEL,
             credentials=llm_module.TEST_CREDENTIALS_INPUT,  # type: ignore
             agent_mode_max_iterations=0,
         )
@@ -648,7 +648,7 @@ async def test_smart_decision_maker_raw_response_conversion():
 
         input_data = SmartDecisionMakerBlock.Input(
             prompt="Test prompt",
-            model=llm_module.LlmModel.GPT4O,
+            model=llm_module.DEFAULT_LLM_MODEL,
             credentials=llm_module.TEST_CREDENTIALS_INPUT,  # type: ignore
             retry=2,
             agent_mode_max_iterations=0,
@@ -722,7 +722,7 @@ async def test_smart_decision_maker_raw_response_conversion():
     ):
         input_data = SmartDecisionMakerBlock.Input(
             prompt="Simple prompt",
-            model=llm_module.LlmModel.GPT4O,
+            model=llm_module.DEFAULT_LLM_MODEL,
             credentials=llm_module.TEST_CREDENTIALS_INPUT,  # type: ignore
             agent_mode_max_iterations=0,
         )
@@ -778,7 +778,7 @@ async def test_smart_decision_maker_raw_response_conversion():
     ):
         input_data = SmartDecisionMakerBlock.Input(
             prompt="Another test",
-            model=llm_module.LlmModel.GPT4O,
+            model=llm_module.DEFAULT_LLM_MODEL,
             credentials=llm_module.TEST_CREDENTIALS_INPUT,  # type: ignore
             agent_mode_max_iterations=0,
         )
@@ -931,7 +931,7 @@ async def test_smart_decision_maker_agent_mode():
         # Test agent mode with max_iterations = 3
         input_data = SmartDecisionMakerBlock.Input(
             prompt="Complete this task using tools",
-            model=llm_module.LlmModel.GPT4O,
+            model=llm_module.DEFAULT_LLM_MODEL,
             credentials=llm_module.TEST_CREDENTIALS_INPUT,  # type: ignore
             agent_mode_max_iterations=3,  # Enable agent mode with 3 max iterations
         )
@@ -1020,7 +1020,7 @@ async def test_smart_decision_maker_traditional_mode_default():
         # Test default behavior (traditional mode)
         input_data = SmartDecisionMakerBlock.Input(
             prompt="Test prompt",
-            model=llm_module.LlmModel.GPT4O,
+            model=llm_module.DEFAULT_LLM_MODEL,
             credentials=llm_module.TEST_CREDENTIALS_INPUT,  # type: ignore
             agent_mode_max_iterations=0,  # Traditional mode
         )
@@ -1057,3 +1057,153 @@ async def test_smart_decision_maker_traditional_mode_default():
         )  # Should yield individual tool parameters
         assert "tools_^_test-sink-node-id_~_max_keyword_difficulty" in outputs
         assert "conversations" in outputs
+
+
+@pytest.mark.asyncio
+async def test_smart_decision_maker_uses_customized_name_for_blocks():
+    """Test that SmartDecisionMakerBlock uses customized_name from node metadata for tool names."""
+    from unittest.mock import MagicMock
+
+    from backend.blocks.basic import StoreValueBlock
+    from backend.blocks.smart_decision_maker import SmartDecisionMakerBlock
+    from backend.data.graph import Link, Node
+
+    # Create a mock node with customized_name in metadata
+    mock_node = MagicMock(spec=Node)
+    mock_node.id = "test-node-id"
+    mock_node.block_id = StoreValueBlock().id
+    mock_node.metadata = {"customized_name": "My Custom Tool Name"}
+    mock_node.block = StoreValueBlock()
+
+    # Create a mock link
+    mock_link = MagicMock(spec=Link)
+    mock_link.sink_name = "input"
+
+    # Call the function directly
+    result = await SmartDecisionMakerBlock._create_block_function_signature(
+        mock_node, [mock_link]
+    )
+
+    # Verify the tool name uses the customized name (cleaned up)
+    assert result["type"] == "function"
+    assert result["function"]["name"] == "my_custom_tool_name"  # Cleaned version
+    assert result["function"]["_sink_node_id"] == "test-node-id"
+
+
+@pytest.mark.asyncio
+async def test_smart_decision_maker_falls_back_to_block_name():
+    """Test that SmartDecisionMakerBlock falls back to block.name when no customized_name."""
+    from unittest.mock import MagicMock
+
+    from backend.blocks.basic import StoreValueBlock
+    from backend.blocks.smart_decision_maker import SmartDecisionMakerBlock
+    from backend.data.graph import Link, Node
+
+    # Create a mock node without customized_name
+    mock_node = MagicMock(spec=Node)
+    mock_node.id = "test-node-id"
+    mock_node.block_id = StoreValueBlock().id
+    mock_node.metadata = {}  # No customized_name
+    mock_node.block = StoreValueBlock()
+
+    # Create a mock link
+    mock_link = MagicMock(spec=Link)
+    mock_link.sink_name = "input"
+
+    # Call the function directly
+    result = await SmartDecisionMakerBlock._create_block_function_signature(
+        mock_node, [mock_link]
+    )
+
+    # Verify the tool name uses the block's default name
+    assert result["type"] == "function"
+    assert result["function"]["name"] == "storevalueblock"  # Default block name cleaned
+    assert result["function"]["_sink_node_id"] == "test-node-id"
+
+
+@pytest.mark.asyncio
+async def test_smart_decision_maker_uses_customized_name_for_agents():
+    """Test that SmartDecisionMakerBlock uses customized_name from metadata for agent nodes."""
+    from unittest.mock import AsyncMock, MagicMock, patch
+
+    from backend.blocks.smart_decision_maker import SmartDecisionMakerBlock
+    from backend.data.graph import Link, Node
+
+    # Create a mock node with customized_name in metadata
+    mock_node = MagicMock(spec=Node)
+    mock_node.id = "test-agent-node-id"
+    mock_node.metadata = {"customized_name": "My Custom Agent"}
+    mock_node.input_default = {
+        "graph_id": "test-graph-id",
+        "graph_version": 1,
+        "input_schema": {"properties": {"test_input": {"description": "Test input"}}},
+    }
+
+    # Create a mock link
+    mock_link = MagicMock(spec=Link)
+    mock_link.sink_name = "test_input"
+
+    # Mock the database client
+    mock_graph_meta = MagicMock()
+    mock_graph_meta.name = "Original Agent Name"
+    mock_graph_meta.description = "Agent description"
+
+    mock_db_client = AsyncMock()
+    mock_db_client.get_graph_metadata.return_value = mock_graph_meta
+
+    with patch(
+        "backend.blocks.smart_decision_maker.get_database_manager_async_client",
+        return_value=mock_db_client,
+    ):
+        result = await SmartDecisionMakerBlock._create_agent_function_signature(
+            mock_node, [mock_link]
+        )
+
+    # Verify the tool name uses the customized name (cleaned up)
+    assert result["type"] == "function"
+    assert result["function"]["name"] == "my_custom_agent"  # Cleaned version
+    assert result["function"]["_sink_node_id"] == "test-agent-node-id"
+
+
+@pytest.mark.asyncio
+async def test_smart_decision_maker_agent_falls_back_to_graph_name():
+    """Test that agent node falls back to graph name when no customized_name."""
+    from unittest.mock import AsyncMock, MagicMock, patch
+
+    from backend.blocks.smart_decision_maker import SmartDecisionMakerBlock
+    from backend.data.graph import Link, Node
+
+    # Create a mock node without customized_name
+    mock_node = MagicMock(spec=Node)
+    mock_node.id = "test-agent-node-id"
+    mock_node.metadata = {}  # No customized_name
+    mock_node.input_default = {
+        "graph_id": "test-graph-id",
+        "graph_version": 1,
+        "input_schema": {"properties": {"test_input": {"description": "Test input"}}},
+    }
+
+    # Create a mock link
+    mock_link = MagicMock(spec=Link)
+    mock_link.sink_name = "test_input"
+
+    # Mock the database client
+    mock_graph_meta = MagicMock()
+    mock_graph_meta.name = "Original Agent Name"
+    mock_graph_meta.description = "Agent description"
+
+    mock_db_client = AsyncMock()
+    mock_db_client.get_graph_metadata.return_value = mock_graph_meta
+
+    with patch(
+        "backend.blocks.smart_decision_maker.get_database_manager_async_client",
+        return_value=mock_db_client,
+    ):
+        result = await SmartDecisionMakerBlock._create_agent_function_signature(
+            mock_node, [mock_link]
+        )
+
+    # Verify the tool name uses the graph's default name
+    assert result["type"] == "function"
+    assert result["function"]["name"] == "original_agent_name"  # Graph name cleaned
+    assert result["function"]["_sink_node_id"] == "test-agent-node-id"

autogpt_platform/backend/backend/blocks/test/test_smart_decision_maker_dict.py

@@ -15,6 +15,7 @@ async def test_smart_decision_maker_handles_dynamic_dict_fields():
     mock_node.block = CreateDictionaryBlock()
     mock_node.block_id = CreateDictionaryBlock().id
     mock_node.input_default = {}
+    mock_node.metadata = {}
 
     # Create mock links with dynamic dictionary fields
     mock_links = [
@@ -77,6 +78,7 @@ async def test_smart_decision_maker_handles_dynamic_list_fields():
     mock_node.block = AddToListBlock()
     mock_node.block_id = AddToListBlock().id
     mock_node.input_default = {}
+    mock_node.metadata = {}
 
     # Create mock links with dynamic list fields
     mock_links = [

autogpt_platform/backend/backend/blocks/test/test_smart_decision_maker_dynamic_fields.py

@@ -44,6 +44,7 @@ async def test_create_block_function_signature_with_dict_fields():
     mock_node.block = CreateDictionaryBlock()
     mock_node.block_id = CreateDictionaryBlock().id
     mock_node.input_default = {}
+    mock_node.metadata = {}
 
     # Create mock links with dynamic dictionary fields (source sanitized, sink original)
     mock_links = [
@@ -106,6 +107,7 @@ async def test_create_block_function_signature_with_list_fields():
     mock_node.block = AddToListBlock()
     mock_node.block_id = AddToListBlock().id
     mock_node.input_default = {}
+    mock_node.metadata = {}
 
     # Create mock links with dynamic list fields
     mock_links = [
@@ -159,6 +161,7 @@ async def test_create_block_function_signature_with_object_fields():
     mock_node.block = MatchTextPatternBlock()
     mock_node.block_id = MatchTextPatternBlock().id
     mock_node.input_default = {}
+    mock_node.metadata = {}
 
     # Create mock links with dynamic object fields
     mock_links = [
@@ -208,11 +211,13 @@ async def test_create_tool_node_signatures():
         mock_dict_node.block = CreateDictionaryBlock()
         mock_dict_node.block_id = CreateDictionaryBlock().id
         mock_dict_node.input_default = {}
+        mock_dict_node.metadata = {}
 
         mock_list_node = Mock()
         mock_list_node.block = AddToListBlock()
         mock_list_node.block_id = AddToListBlock().id
         mock_list_node.input_default = {}
+        mock_list_node.metadata = {}
 
         # Mock links with dynamic fields
         dict_link1 = Mock(
@@ -373,7 +378,7 @@ async def test_output_yielding_with_dynamic_fields():
             input_data = block.input_schema(
                 prompt="Create a user dictionary",
                 credentials=llm.TEST_CREDENTIALS_INPUT,
-                model=llm.LlmModel.GPT4O,
+                model=llm.DEFAULT_LLM_MODEL,
                 agent_mode_max_iterations=0,  # Use traditional mode to test output yielding
             )
 
@@ -423,6 +428,7 @@ async def test_mixed_regular_and_dynamic_fields():
     mock_node.block.name = "TestBlock"
     mock_node.block.description = "A test block"
     mock_node.block.input_schema = Mock()
+    mock_node.metadata = {}
 
     # Mock the get_field_schema to return a proper schema for regular fields
     def get_field_schema(field_name):
@@ -594,7 +600,7 @@ async def test_validation_errors_dont_pollute_conversation():
                 input_data = block.input_schema(
                     prompt="Test prompt",
                     credentials=llm.TEST_CREDENTIALS_INPUT,
-                    model=llm.LlmModel.GPT4O,
+                    model=llm.DEFAULT_LLM_MODEL,
                     retry=3,  # Allow retries
                     agent_mode_max_iterations=1,
                 )

autogpt_platform/backend/backend/blocks/wordpress/__init__.py

@@ -1,3 +1,3 @@
-from .blog import WordPressCreatePostBlock
+from .blog import WordPressCreatePostBlock, WordPressGetAllPostsBlock
 
-__all__ = ["WordPressCreatePostBlock"]
+__all__ = ["WordPressCreatePostBlock", "WordPressGetAllPostsBlock"]

autogpt_platform/backend/backend/blocks/wordpress/_api.py

@@ -161,7 +161,7 @@ async def oauth_exchange_code_for_tokens(
         grant_type="authorization_code",
     ).model_dump(exclude_none=True)
 
-    response = await Requests().post(
+    response = await Requests(raise_for_status=False).post(
         f"{WORDPRESS_BASE_URL}oauth2/token",
         headers=headers,
         data=data,
@@ -205,7 +205,7 @@ async def oauth_refresh_tokens(
         grant_type="refresh_token",
     ).model_dump(exclude_none=True)
 
-    response = await Requests().post(
+    response = await Requests(raise_for_status=False).post(
         f"{WORDPRESS_BASE_URL}oauth2/token",
         headers=headers,
         data=data,
@@ -252,7 +252,7 @@ async def validate_token(
         "token": token,
     }
 
-    response = await Requests().get(
+    response = await Requests(raise_for_status=False).get(
         f"{WORDPRESS_BASE_URL}oauth2/token-info",
         params=params,
     )
@@ -296,7 +296,7 @@ async def make_api_request(
 
     url = f"{WORDPRESS_BASE_URL.rstrip('/')}{endpoint}"
 
-    request_method = getattr(Requests(), method.lower())
+    request_method = getattr(Requests(raise_for_status=False), method.lower())
     response = await request_method(
         url,
         headers=headers,
@@ -476,6 +476,7 @@ async def create_post(
         data["tags"] = ",".join(str(t) for t in data["tags"])
 
     # Make the API request
+    site = normalize_site(site)
     endpoint = f"/rest/v1.1/sites/{site}/posts/new"
 
     headers = {
@@ -483,7 +484,7 @@ async def create_post(
         "Content-Type": "application/x-www-form-urlencoded",
     }
 
-    response = await Requests().post(
+    response = await Requests(raise_for_status=False).post(
         f"{WORDPRESS_BASE_URL.rstrip('/')}{endpoint}",
         headers=headers,
         data=data,
@@ -499,3 +500,132 @@ async def create_post(
     )
     error_message = error_data.get("message", response.text)
     raise ValueError(f"Failed to create post: {response.status} - {error_message}")
+
+
+class Post(BaseModel):
+    """Response model for individual posts in a posts list response.
+
+    This is a simplified version compared to PostResponse, as the list endpoint
+    returns less detailed information than the create/get single post endpoints.
+    """
+
+    ID: int
+    site_ID: int
+    author: PostAuthor
+    date: datetime
+    modified: datetime
+    title: str
+    URL: str
+    short_URL: str
+    content: str | None = None
+    excerpt: str | None = None
+    slug: str
+    guid: str
+    status: str
+    sticky: bool
+    password: str | None = ""
+    parent: Union[Dict[str, Any], bool, None] = None
+    type: str
+    discussion: Dict[str, Union[str, bool, int]] | None = None
+    likes_enabled: bool | None = None
+    sharing_enabled: bool | None = None
+    like_count: int | None = None
+    i_like: bool | None = None
+    is_reblogged: bool | None = None
+    is_following: bool | None = None
+    global_ID: str | None = None
+    featured_image: str | None = None
+    post_thumbnail: Dict[str, Any] | None = None
+    format: str | None = None
+    geo: Union[Dict[str, Any], bool, None] = None
+    menu_order: int | None = None
+    page_template: str | None = None
+    publicize_URLs: List[str] | None = None
+    terms: Dict[str, Dict[str, Any]] | None = None
+    tags: Dict[str, Dict[str, Any]] | None = None
+    categories: Dict[str, Dict[str, Any]] | None = None
+    attachments: Dict[str, Dict[str, Any]] | None = None
+    attachment_count: int | None = None
+    metadata: List[Dict[str, Any]] | None = None
+    meta: Dict[str, Any] | None = None
+    capabilities: Dict[str, bool] | None = None
+    revisions: List[int] | None = None
+    other_URLs: Dict[str, Any] | None = None
+
+
+class PostsResponse(BaseModel):
+    """Response model for WordPress posts list."""
+
+    found: int
+    posts: List[Post]
+    meta: Dict[str, Any]
+
+
+def normalize_site(site: str) -> str:
+    """
+    Normalize a site identifier by stripping protocol and trailing slashes.
+
+    Args:
+        site: Site URL, domain, or ID (e.g., "https://myblog.wordpress.com/", "myblog.wordpress.com", "123456789")
+
+    Returns:
+        Normalized site identifier (domain or ID only)
+    """
+    site = site.strip()
+    if site.startswith("https://"):
+        site = site[8:]
+    elif site.startswith("http://"):
+        site = site[7:]
+    return site.rstrip("/")
+
+
+async def get_posts(
+    credentials: Credentials,
+    site: str,
+    status: PostStatus | None = None,
+    number: int = 100,
+    offset: int = 0,
+) -> PostsResponse:
+    """
+    Get posts from a WordPress site.
+
+    Args:
+        credentials: OAuth credentials
+        site: Site ID or domain (e.g., "myblog.wordpress.com" or "123456789")
+        status: Filter by post status using PostStatus enum, or None for all
+        number: Number of posts to retrieve (max 100)
+        offset: Number of posts to skip (for pagination)
+
+    Returns:
+        PostsResponse with the list of posts
+    """
+    site = normalize_site(site)
+    endpoint = f"/rest/v1.1/sites/{site}/posts"
+
+    headers = {
+        "Authorization": credentials.auth_header(),
+    }
+
+    params: Dict[str, Any] = {
+        "number": max(1, min(number, 100)),  # 1–100 posts per request
+        "offset": offset,
+    }
+
+    if status:
+        params["status"] = status.value
+    response = await Requests(raise_for_status=False).get(
+        f"{WORDPRESS_BASE_URL.rstrip('/')}{endpoint}",
+        headers=headers,
+        params=params,
+    )
+
+    if response.ok:
+        return PostsResponse.model_validate(response.json())
+
+    error_data = (
+        response.json()
+        if response.headers.get("content-type", "").startswith("application/json")
+        else {}
+    )
+    error_message = error_data.get("message", response.text)
+    raise ValueError(f"Failed to get posts: {response.status} - {error_message}")

autogpt_platform/backend/backend/blocks/wordpress/blog.py

@@ -9,7 +9,15 @@ from backend.sdk import (
     SchemaField,
 )
 
-from ._api import CreatePostRequest, PostResponse, PostStatus, create_post
+from ._api import (
+    CreatePostRequest,
+    Post,
+    PostResponse,
+    PostsResponse,
+    PostStatus,
+    create_post,
+    get_posts,
+)
 from ._config import wordpress
 
 
@@ -49,8 +57,15 @@ class WordPressCreatePostBlock(Block):
         media_urls: list[str] = SchemaField(
             description="URLs of images to sideload and attach to the post", default=[]
         )
+        publish_as_draft: bool = SchemaField(
+            description="If True, publishes the post as a draft. If False, publishes it publicly.",
+            default=False,
+        )
 
     class Output(BlockSchemaOutput):
+        site: str = SchemaField(
+            description="The site ID or domain (pass-through for chaining with other blocks)"
+        )
         post_id: int = SchemaField(description="The ID of the created post")
         post_url: str = SchemaField(description="The full URL of the created post")
         short_url: str = SchemaField(description="The shortened wp.me URL")
@@ -78,7 +93,9 @@ class WordPressCreatePostBlock(Block):
             tags=input_data.tags,
             featured_image=input_data.featured_image,
             media_urls=input_data.media_urls,
-            status=PostStatus.PUBLISH,
+            status=(
+                PostStatus.DRAFT if input_data.publish_as_draft else PostStatus.PUBLISH
+            ),
         )
 
         post_response: PostResponse = await create_post(
@@ -87,7 +104,69 @@ class WordPressCreatePostBlock(Block):
             post_data=post_request,
         )
 
+        yield "site", input_data.site
         yield "post_id", post_response.ID
         yield "post_url", post_response.URL
         yield "short_url", post_response.short_URL
         yield "post_data", post_response.model_dump()
+
+
+class WordPressGetAllPostsBlock(Block):
+    """
+    Fetches all posts from a WordPress.com site or Jetpack-enabled site.
+    Supports filtering by status and pagination.
+    """
+
+    class Input(BlockSchemaInput):
+        credentials: CredentialsMetaInput = wordpress.credentials_field()
+        site: str = SchemaField(
+            description="Site ID or domain (e.g., 'myblog.wordpress.com' or '123456789')"
+        )
+        status: PostStatus | None = SchemaField(
+            description="Filter by post status, or None for all",
+            default=None,
+        )
+        number: int = SchemaField(
+            description="Number of posts to retrieve (max 100 per request)", default=20
+        )
+        offset: int = SchemaField(
+            description="Number of posts to skip (for pagination)", default=0
+        )
+
+    class Output(BlockSchemaOutput):
+        site: str = SchemaField(
+            description="The site ID or domain (pass-through for chaining with other blocks)"
+        )
+        found: int = SchemaField(description="Total number of posts found")
+        posts: list[Post] = SchemaField(
+            description="List of post objects with their details"
+        )
+        post: Post = SchemaField(
+            description="Individual post object (yielded for each post)"
+        )
+
+    def __init__(self):
+        super().__init__(
+            id="97728fa7-7f6f-4789-ba0c-f2c114119536",
+            description="Fetch all posts from WordPress.com or Jetpack sites",
+            categories={BlockCategory.SOCIAL},
+            input_schema=self.Input,
+            output_schema=self.Output,
+        )
+
+    async def run(
+        self, input_data: Input, *, credentials: Credentials, **kwargs
+    ) -> BlockOutput:
+        posts_response: PostsResponse = await get_posts(
+            credentials=credentials,
+            site=input_data.site,
+            status=input_data.status,
+            number=input_data.number,
+            offset=input_data.offset,
+        )
+
+        yield "site", input_data.site
+        yield "found", posts_response.found
+        yield "posts", posts_response.posts
+        for post in posts_response.posts:
+            yield "post", post

autogpt_platform/backend/backend/blocks/xml_parser.py

@@ -1,5 +1,5 @@
 from gravitasml.parser import Parser
-from gravitasml.token import tokenize
+from gravitasml.token import Token, tokenize
 
 from backend.data.block import Block, BlockOutput, BlockSchemaInput, BlockSchemaOutput
 from backend.data.model import SchemaField
@@ -25,6 +25,38 @@ class XMLParserBlock(Block):
             ],
         )
 
+    @staticmethod
+    def _validate_tokens(tokens: list[Token]) -> None:
+        """Ensure the XML has a single root element and no stray text."""
+        if not tokens:
+            raise ValueError("XML input is empty.")
+
+        depth = 0
+        root_seen = False
+
+        for token in tokens:
+            if token.type == "TAG_OPEN":
+                if depth == 0 and root_seen:
+                    raise ValueError("XML must have a single root element.")
+                depth += 1
+                if depth == 1:
+                    root_seen = True
+            elif token.type == "TAG_CLOSE":
+                depth -= 1
+                if depth < 0:
+                    raise SyntaxError("Unexpected closing tag in XML input.")
+            elif token.type in {"TEXT", "ESCAPE"}:
+                if depth == 0 and token.value:
+                    raise ValueError(
+                        "XML contains text outside the root element; "
+                        "wrap content in a single root tag."
+                    )
+
+        if depth != 0:
+            raise SyntaxError("Unclosed tag detected in XML input.")
+        if not root_seen:
+            raise ValueError("XML must include a root element.")
+
     async def run(self, input_data: Input, **kwargs) -> BlockOutput:
         # Security fix: Add size limits to prevent XML bomb attacks
         MAX_XML_SIZE = 10 * 1024 * 1024  # 10MB limit for XML input
@@ -35,16 +67,12 @@ class XMLParserBlock(Block):
             )
 
         try:
-            tokens = tokenize(input_data.input_xml)
+            tokens = list(tokenize(input_data.input_xml))
+            self._validate_tokens(tokens)
+
             parser = Parser(tokens)
             parsed_result = parser.parse()
             yield "parsed_xml", parsed_result
-        except AttributeError as attr_e:
-            raise ValueError(
-                f"XML parsing error: The gravitasml library encountered an incompatible structure. "
-                f"This may occur with certain XML formats that create List objects with text content. "
-                f"Details: {attr_e}"
-            ) from attr_e
         except ValueError as val_e:
             raise ValueError(f"Validation error for dict:{val_e}") from val_e
         except SyntaxError as syn_e:

autogpt_platform/backend/backend/blocks/youtube.py

@@ -111,6 +111,8 @@ class TranscribeYoutubeVideoBlock(Block):
                 return parsed_url.path.split("/")[2]
             if parsed_url.path[:3] == "/v/":
                 return parsed_url.path.split("/")[2]
+            if parsed_url.path.startswith("/shorts/"):
+                return parsed_url.path.split("/")[2]
         raise ValueError(f"Invalid YouTube URL: {url}")
 
     def get_transcript(

autogpt_platform/backend/backend/data/block.py

@@ -50,6 +50,8 @@ from .model import (
 logger = logging.getLogger(__name__)
 
 if TYPE_CHECKING:
+    from backend.data.execution import ExecutionContext
+
     from .graph import Link
 
 app_config = Config()
@@ -472,6 +474,7 @@ class Block(ABC, Generic[BlockSchemaInputType, BlockSchemaOutputType]):
         self.block_type = block_type
         self.webhook_config = webhook_config
         self.execution_stats: NodeExecutionStats = NodeExecutionStats()
+        self.requires_human_review: bool = False
 
         if self.webhook_config:
             if isinstance(self.webhook_config, BlockWebhookConfig):
@@ -614,7 +617,77 @@ class Block(ABC, Generic[BlockSchemaInputType, BlockSchemaOutputType]):
                     block_id=self.id,
                 ) from ex
 
+    async def is_block_exec_need_review(
+        self,
+        input_data: BlockInput,
+        *,
+        user_id: str,
+        node_exec_id: str,
+        graph_exec_id: str,
+        graph_id: str,
+        graph_version: int,
+        execution_context: "ExecutionContext",
+        **kwargs,
+    ) -> tuple[bool, BlockInput]:
+        """
+        Check if this block execution needs human review and handle the review process.
+
+        Returns:
+            Tuple of (should_pause, input_data_to_use)
+            - should_pause: True if execution should be paused for review
+            - input_data_to_use: The input data to use (may be modified by reviewer)
+        """
+        # Skip review if not required or safe mode is disabled
+        if not self.requires_human_review or not execution_context.safe_mode:
+            return False, input_data
+
+        from backend.blocks.helpers.review import HITLReviewHelper
+
+        # Handle the review request and get decision
+        decision = await HITLReviewHelper.handle_review_decision(
+            input_data=input_data,
+            user_id=user_id,
+            node_exec_id=node_exec_id,
+            graph_exec_id=graph_exec_id,
+            graph_id=graph_id,
+            graph_version=graph_version,
+            execution_context=execution_context,
+            block_name=self.name,
+            editable=True,
+        )
+
+        if decision is None:
+            # We're awaiting review - pause execution
+            return True, input_data
+
+        if not decision.should_proceed:
+            # Review was rejected, raise an error to stop execution
+            raise BlockExecutionError(
+                message=f"Block execution rejected by reviewer: {decision.message}",
+                block_name=self.name,
+                block_id=self.id,
+            )
+
+        # Review was approved - use the potentially modified data
+        # ReviewResult.data must be a dict for block inputs
+        reviewed_data = decision.review_result.data
+        if not isinstance(reviewed_data, dict):
+            raise BlockExecutionError(
+                message=f"Review data must be a dict for block input, got {type(reviewed_data).__name__}",
+                block_name=self.name,
+                block_id=self.id,
+            )
+        return False, reviewed_data
+
     async def _execute(self, input_data: BlockInput, **kwargs) -> BlockOutput:
+        # Check for review requirement and get potentially modified input data
+        should_pause, input_data = await self.is_block_exec_need_review(
+            input_data, **kwargs
+        )
+        if should_pause:
+            return
+
+        # Validate the input data (original or reviewer-modified) once
         if error := self.input_schema.validate_data(input_data):
             raise BlockInputError(
                 message=f"Unable to execute block with invalid input data: {error}",
@@ -622,6 +695,7 @@ class Block(ABC, Generic[BlockSchemaInputType, BlockSchemaOutputType]):
                 block_id=self.id,
             )
 
+        # Use the validated input data
         async for output_name, output_data in self.run(
             self.input_schema(**{k: v for k, v in input_data.items() if v is not None}),
             **kwargs,

autogpt_platform/backend/backend/data/block_cost_config.py

@@ -59,12 +59,13 @@ from backend.integrations.credentials_store import (
 
 MODEL_COST: dict[LlmModel, int] = {
     LlmModel.O3: 4,
-    LlmModel.O3_MINI: 2,  # $1.10 / $4.40
-    LlmModel.O1: 16,  # $15 / $60
+    LlmModel.O3_MINI: 2,
+    LlmModel.O1: 16,
     LlmModel.O1_MINI: 4,
     # GPT-5 models
-    LlmModel.GPT5: 2,
+    LlmModel.GPT5_2: 6,
     LlmModel.GPT5_1: 5,
+    LlmModel.GPT5: 2,
     LlmModel.GPT5_MINI: 1,
     LlmModel.GPT5_NANO: 1,
     LlmModel.GPT5_CHAT: 5,
@@ -87,7 +88,7 @@ MODEL_COST: dict[LlmModel, int] = {
     LlmModel.AIML_API_LLAMA3_3_70B: 1,
     LlmModel.AIML_API_META_LLAMA_3_1_70B: 1,
     LlmModel.AIML_API_LLAMA_3_2_3B: 1,
-    LlmModel.LLAMA3_3_70B: 1,  # $0.59 / $0.79
+    LlmModel.LLAMA3_3_70B: 1,
     LlmModel.LLAMA3_1_8B: 1,
     LlmModel.OLLAMA_LLAMA3_3: 1,
     LlmModel.OLLAMA_LLAMA3_2: 1,

autogpt_platform/backend/backend/data/credit.py

@@ -341,6 +341,19 @@ class UserCreditBase(ABC):
 
         if result:
             # UserBalance is already updated by the CTE
+
+            # Clear insufficient funds notification flags when credits are added
+            # so user can receive alerts again if they run out in the future.
+            if transaction.amount > 0 and transaction.type in [
+                CreditTransactionType.GRANT,
+                CreditTransactionType.TOP_UP,
+            ]:
+                from backend.executor.manager import (
+                    clear_insufficient_funds_notifications,
+                )
+
+                await clear_insufficient_funds_notifications(user_id)
+
             return result[0]["balance"]
 
     async def _add_transaction(
@@ -530,6 +543,22 @@ class UserCreditBase(ABC):
         if result:
             new_balance, tx_key = result[0]["balance"], result[0]["transactionKey"]
             # UserBalance is already updated by the CTE
+
+            # Clear insufficient funds notification flags when credits are added
+            # so user can receive alerts again if they run out in the future.
+            if (
+                amount > 0
+                and is_active
+                and transaction_type
+                in [CreditTransactionType.GRANT, CreditTransactionType.TOP_UP]
+            ):
+                # Lazy import to avoid circular dependency with executor.manager
+                from backend.executor.manager import (
+                    clear_insufficient_funds_notifications,
+                )
+
+                await clear_insufficient_funds_notifications(user_id)
+
             return new_balance, tx_key
 
         # If no result, either user doesn't exist or insufficient balance

autogpt_platform/backend/backend/data/execution.py

@@ -383,6 +383,7 @@ class GraphExecutionWithNodes(GraphExecution):
         self,
         execution_context: ExecutionContext,
         compiled_nodes_input_masks: Optional[NodesInputMasks] = None,
+        nodes_to_skip: Optional[set[str]] = None,
     ):
         return GraphExecutionEntry(
             user_id=self.user_id,
@@ -390,6 +391,7 @@ class GraphExecutionWithNodes(GraphExecution):
             graph_version=self.graph_version or 0,
             graph_exec_id=self.id,
             nodes_input_masks=compiled_nodes_input_masks,
+            nodes_to_skip=nodes_to_skip or set(),
             execution_context=execution_context,
         )
 
@@ -1145,6 +1147,8 @@ class GraphExecutionEntry(BaseModel):
     graph_id: str
     graph_version: int
     nodes_input_masks: Optional[NodesInputMasks] = None
+    nodes_to_skip: set[str] = Field(default_factory=set)
+    """Node IDs that should be skipped due to optional credentials not being configured."""
     execution_context: ExecutionContext = Field(default_factory=ExecutionContext)
 
 

autogpt_platform/backend/backend/data/graph.py

@@ -94,6 +94,15 @@ class Node(BaseDbModel):
     input_links: list[Link] = []
     output_links: list[Link] = []
 
+    @property
+    def credentials_optional(self) -> bool:
+        """
+        Whether credentials are optional for this node.
+        When True and credentials are not configured, the node will be skipped
+        during execution rather than causing a validation error.
+        """
+        return self.metadata.get("credentials_optional", False)
+
     @property
     def block(self) -> AnyBlockSchema | "_UnknownBlockBase":
         """Get the block for this node. Returns UnknownBlock if block is deleted/missing."""
@@ -235,7 +244,10 @@ class BaseGraph(BaseDbModel):
         return any(
             node.block_id
             for node in self.nodes
-            if node.block.block_type == BlockType.HUMAN_IN_THE_LOOP
+            if (
+                node.block.block_type == BlockType.HUMAN_IN_THE_LOOP
+                or node.block.requires_human_review
+            )
         )
 
     @property
@@ -326,7 +338,35 @@ class Graph(BaseGraph):
     @computed_field
     @property
     def credentials_input_schema(self) -> dict[str, Any]:
-        return self._credentials_input_schema.jsonschema()
+        schema = self._credentials_input_schema.jsonschema()
+
+        # Determine which credential fields are required based on credentials_optional metadata
+        graph_credentials_inputs = self.aggregate_credentials_inputs()
+        required_fields = []
+
+        # Build a map of node_id -> node for quick lookup
+        all_nodes = {node.id: node for node in self.nodes}
+        for sub_graph in self.sub_graphs:
+            for node in sub_graph.nodes:
+                all_nodes[node.id] = node
+
+        for field_key, (
+            _field_info,
+            node_field_pairs,
+        ) in graph_credentials_inputs.items():
+            # A field is required if ANY node using it has credentials_optional=False
+            is_required = False
+            for node_id, _field_name in node_field_pairs:
+                node = all_nodes.get(node_id)
+                if node and not node.credentials_optional:
+                    is_required = True
+                    break
+
+            if is_required:
+                required_fields.append(field_key)
+
+        schema["required"] = required_fields
+        return schema
 
     @property
     def _credentials_input_schema(self) -> type[BlockSchema]:

autogpt_platform/backend/backend/data/graph_test.py

@@ -396,3 +396,58 @@ async def test_access_store_listing_graph(server: SpinTestServer):
         created_graph.id, created_graph.version, "3e53486c-cf57-477e-ba2a-cb02dc828e1b"
     )
     assert got_graph is not None
+
+
+# ============================================================================
+# Tests for Optional Credentials Feature
+# ============================================================================
+
+
+def test_node_credentials_optional_default():
+    """Test that credentials_optional defaults to False when not set in metadata."""
+    node = Node(
+        id="test_node",
+        block_id=StoreValueBlock().id,
+        input_default={},
+        metadata={},
+    )
+    assert node.credentials_optional is False
+
+
+def test_node_credentials_optional_true():
+    """Test that credentials_optional returns True when explicitly set."""
+    node = Node(
+        id="test_node",
+        block_id=StoreValueBlock().id,
+        input_default={},
+        metadata={"credentials_optional": True},
+    )
+    assert node.credentials_optional is True
+
+
+def test_node_credentials_optional_false():
+    """Test that credentials_optional returns False when explicitly set to False."""
+    node = Node(
+        id="test_node",
+        block_id=StoreValueBlock().id,
+        input_default={},
+        metadata={"credentials_optional": False},
+    )
+    assert node.credentials_optional is False
+
+
+def test_node_credentials_optional_with_other_metadata():
+    """Test that credentials_optional works correctly with other metadata present."""
+    node = Node(
+        id="test_node",
+        block_id=StoreValueBlock().id,
+        input_default={},
+        metadata={
+            "position": {"x": 100, "y": 200},
+            "customized_name": "My Custom Node",
+            "credentials_optional": True,
+        },
+    )
+    assert node.credentials_optional is True
+    assert node.metadata["position"] == {"x": 100, "y": 200}
+    assert node.metadata["customized_name"] == "My Custom Node"

autogpt_platform/backend/backend/executor/manager.py

@@ -114,6 +114,40 @@ utilization_gauge = Gauge(
     "Ratio of active graph runs to max graph workers",
 )
 
+# Redis key prefix for tracking insufficient funds Discord notifications.
+# We only send one notification per user per agent until they top up credits.
+INSUFFICIENT_FUNDS_NOTIFIED_PREFIX = "insufficient_funds_discord_notified"
+# TTL for the notification flag (30 days) - acts as a fallback cleanup
+INSUFFICIENT_FUNDS_NOTIFIED_TTL_SECONDS = 30 * 24 * 60 * 60
+
+
+async def clear_insufficient_funds_notifications(user_id: str) -> int:
+    """
+    Clear all insufficient funds notification flags for a user.
+
+    This should be called when a user tops up their credits, allowing
+    Discord notifications to be sent again if they run out of funds.
+
+    Args:
+        user_id: The user ID to clear notifications for.
+
+    Returns:
+        The number of keys that were deleted.
+    """
+    try:
+        redis_client = await redis.get_redis_async()
+        pattern = f"{INSUFFICIENT_FUNDS_NOTIFIED_PREFIX}:{user_id}:*"
+        keys = [key async for key in redis_client.scan_iter(match=pattern)]
+        if keys:
+            return await redis_client.delete(*keys)
+        return 0
+    except Exception as e:
+        logger.warning(
+            f"Failed to clear insufficient funds notification flags for user "
+            f"{user_id}: {e}"
+        )
+        return 0
+
 
 # Thread-local storage for ExecutionProcessor instances
 _tls = threading.local()
@@ -144,6 +178,7 @@ async def execute_node(
     execution_processor: "ExecutionProcessor",
     execution_stats: NodeExecutionStats | None = None,
     nodes_input_masks: Optional[NodesInputMasks] = None,
+    nodes_to_skip: Optional[set[str]] = None,
 ) -> BlockOutput:
     """
     Execute a node in the graph. This will trigger a block execution on a node,
@@ -211,6 +246,7 @@ async def execute_node(
         "user_id": user_id,
         "execution_context": execution_context,
         "execution_processor": execution_processor,
+        "nodes_to_skip": nodes_to_skip or set(),
     }
 
     # Last-minute fetch credentials + acquire a system-wide read-write lock to prevent
@@ -508,6 +544,7 @@ class ExecutionProcessor:
         node_exec_progress: NodeExecutionProgress,
         nodes_input_masks: Optional[NodesInputMasks],
         graph_stats_pair: tuple[GraphExecutionStats, threading.Lock],
+        nodes_to_skip: Optional[set[str]] = None,
     ) -> NodeExecutionStats:
         log_metadata = LogMetadata(
             logger=_logger,
@@ -530,6 +567,7 @@ class ExecutionProcessor:
             db_client=db_client,
             log_metadata=log_metadata,
             nodes_input_masks=nodes_input_masks,
+            nodes_to_skip=nodes_to_skip,
         )
         if isinstance(status, BaseException):
             raise status
@@ -575,6 +613,7 @@ class ExecutionProcessor:
         db_client: "DatabaseManagerAsyncClient",
         log_metadata: LogMetadata,
         nodes_input_masks: Optional[NodesInputMasks] = None,
+        nodes_to_skip: Optional[set[str]] = None,
     ) -> ExecutionStatus:
         status = ExecutionStatus.RUNNING
 
@@ -611,6 +650,7 @@ class ExecutionProcessor:
                 execution_processor=self,
                 execution_stats=stats,
                 nodes_input_masks=nodes_input_masks,
+                nodes_to_skip=nodes_to_skip,
             ):
                 await persist_output(output_name, output_data)
 
@@ -922,6 +962,21 @@ class ExecutionProcessor:
 
                 queued_node_exec = execution_queue.get()
 
+                # Check if this node should be skipped due to optional credentials
+                if queued_node_exec.node_id in graph_exec.nodes_to_skip:
+                    log_metadata.info(
+                        f"Skipping node execution {queued_node_exec.node_exec_id} "
+                        f"for node {queued_node_exec.node_id} - optional credentials not configured"
+                    )
+                    # Mark the node as completed without executing
+                    # No outputs will be produced, so downstream nodes won't trigger
+                    update_node_execution_status(
+                        db_client=db_client,
+                        exec_id=queued_node_exec.node_exec_id,
+                        status=ExecutionStatus.COMPLETED,
+                    )
+                    continue
+
                 log_metadata.debug(
                     f"Dispatching node execution {queued_node_exec.node_exec_id} "
                     f"for node {queued_node_exec.node_id}",
@@ -982,6 +1037,7 @@ class ExecutionProcessor:
                             execution_stats,
                             execution_stats_lock,
                         ),
+                        nodes_to_skip=graph_exec.nodes_to_skip,
                     ),
                     self.node_execution_loop,
                 )
@@ -1261,12 +1317,40 @@ class ExecutionProcessor:
         graph_id: str,
         e: InsufficientBalanceError,
     ):
+        # Check if we've already sent a notification for this user+agent combo.
+        # We only send one notification per user per agent until they top up credits.
+        redis_key = f"{INSUFFICIENT_FUNDS_NOTIFIED_PREFIX}:{user_id}:{graph_id}"
+        try:
+            redis_client = redis.get_redis()
+            # SET NX returns True only if the key was newly set (didn't exist)
+            is_new_notification = redis_client.set(
+                redis_key,
+                "1",
+                nx=True,
+                ex=INSUFFICIENT_FUNDS_NOTIFIED_TTL_SECONDS,
+            )
+            if not is_new_notification:
+                # Already notified for this user+agent, skip all notifications
+                logger.debug(
+                    f"Skipping duplicate insufficient funds notification for "
+                    f"user={user_id}, graph={graph_id}"
+                )
+                return
+        except Exception as redis_error:
+            # If Redis fails, log and continue to send the notification
+            # (better to occasionally duplicate than to never notify)
+            logger.warning(
+                f"Failed to check/set insufficient funds notification flag in Redis: "
+                f"{redis_error}"
+            )
+
         shortfall = abs(e.amount) - e.balance
         metadata = db_client.get_graph_metadata(graph_id)
         base_url = (
             settings.config.frontend_base_url or settings.config.platform_base_url
         )
 
+        # Queue user email notification
         queue_notification(
             NotificationEventModel(
                 user_id=user_id,
@@ -1280,6 +1364,7 @@ class ExecutionProcessor:
             )
         )
 
+        # Send Discord system alert
         try:
             user_email = db_client.get_user_email_by_id(user_id)
 

autogpt_platform/backend/backend/executor/manager_insufficient_funds_test.py

@@ -0,0 +1,560 @@
+from unittest.mock import AsyncMock, MagicMock, patch
+
+import pytest
+from prisma.enums import NotificationType
+
+from backend.data.notifications import ZeroBalanceData
+from backend.executor.manager import (
+    INSUFFICIENT_FUNDS_NOTIFIED_PREFIX,
+    ExecutionProcessor,
+    clear_insufficient_funds_notifications,
+)
+from backend.util.exceptions import InsufficientBalanceError
+from backend.util.test import SpinTestServer
+
+
+async def async_iter(items):
+    """Helper to create an async iterator from a list."""
+    for item in items:
+        yield item
+
+
+@pytest.mark.asyncio(loop_scope="session")
+async def test_handle_insufficient_funds_sends_discord_alert_first_time(
+    server: SpinTestServer,
+):
+    """Test that the first insufficient funds notification sends a Discord alert."""
+
+    execution_processor = ExecutionProcessor()
+    user_id = "test-user-123"
+    graph_id = "test-graph-456"
+    error = InsufficientBalanceError(
+        message="Insufficient balance",
+        user_id=user_id,
+        balance=72,  # $0.72
+        amount=-714,  # Attempting to spend $7.14
+    )
+
+    with patch(
+        "backend.executor.manager.queue_notification"
+    ) as mock_queue_notif, patch(
+        "backend.executor.manager.get_notification_manager_client"
+    ) as mock_get_client, patch(
+        "backend.executor.manager.settings"
+    ) as mock_settings, patch(
+        "backend.executor.manager.redis"
+    ) as mock_redis_module:
+
+        # Setup mocks
+        mock_client = MagicMock()
+        mock_get_client.return_value = mock_client
+        mock_settings.config.frontend_base_url = "https://test.com"
+
+        # Mock Redis to simulate first-time notification (set returns True)
+        mock_redis_client = MagicMock()
+        mock_redis_module.get_redis.return_value = mock_redis_client
+        mock_redis_client.set.return_value = True  # Key was newly set
+
+        # Create mock database client
+        mock_db_client = MagicMock()
+        mock_graph_metadata = MagicMock()
+        mock_graph_metadata.name = "Test Agent"
+        mock_db_client.get_graph_metadata.return_value = mock_graph_metadata
+        mock_db_client.get_user_email_by_id.return_value = "test@example.com"
+
+        # Test the insufficient funds handler
+        execution_processor._handle_insufficient_funds_notif(
+            db_client=mock_db_client,
+            user_id=user_id,
+            graph_id=graph_id,
+            e=error,
+        )
+
+        # Verify notification was queued
+        mock_queue_notif.assert_called_once()
+        notification_call = mock_queue_notif.call_args[0][0]
+        assert notification_call.type == NotificationType.ZERO_BALANCE
+        assert notification_call.user_id == user_id
+        assert isinstance(notification_call.data, ZeroBalanceData)
+        assert notification_call.data.current_balance == 72
+
+        # Verify Redis was checked with correct key pattern
+        expected_key = f"{INSUFFICIENT_FUNDS_NOTIFIED_PREFIX}:{user_id}:{graph_id}"
+        mock_redis_client.set.assert_called_once()
+        call_args = mock_redis_client.set.call_args
+        assert call_args[0][0] == expected_key
+        assert call_args[1]["nx"] is True
+
+        # Verify Discord alert was sent
+        mock_client.discord_system_alert.assert_called_once()
+        discord_message = mock_client.discord_system_alert.call_args[0][0]
+        assert "Insufficient Funds Alert" in discord_message
+        assert "test@example.com" in discord_message
+        assert "Test Agent" in discord_message
+
+
+@pytest.mark.asyncio(loop_scope="session")
+async def test_handle_insufficient_funds_skips_duplicate_notifications(
+    server: SpinTestServer,
+):
+    """Test that duplicate insufficient funds notifications skip both email and Discord."""
+
+    execution_processor = ExecutionProcessor()
+    user_id = "test-user-123"
+    graph_id = "test-graph-456"
+    error = InsufficientBalanceError(
+        message="Insufficient balance",
+        user_id=user_id,
+        balance=72,
+        amount=-714,
+    )
+
+    with patch(
+        "backend.executor.manager.queue_notification"
+    ) as mock_queue_notif, patch(
+        "backend.executor.manager.get_notification_manager_client"
+    ) as mock_get_client, patch(
+        "backend.executor.manager.settings"
+    ) as mock_settings, patch(
+        "backend.executor.manager.redis"
+    ) as mock_redis_module:
+
+        # Setup mocks
+        mock_client = MagicMock()
+        mock_get_client.return_value = mock_client
+        mock_settings.config.frontend_base_url = "https://test.com"
+
+        # Mock Redis to simulate duplicate notification (set returns False/None)
+        mock_redis_client = MagicMock()
+        mock_redis_module.get_redis.return_value = mock_redis_client
+        mock_redis_client.set.return_value = None  # Key already existed
+
+        # Create mock database client
+        mock_db_client = MagicMock()
+        mock_db_client.get_graph_metadata.return_value = MagicMock(name="Test Agent")
+
+        # Test the insufficient funds handler
+        execution_processor._handle_insufficient_funds_notif(
+            db_client=mock_db_client,
+            user_id=user_id,
+            graph_id=graph_id,
+            e=error,
+        )
+
+        # Verify email notification was NOT queued (deduplication worked)
+        mock_queue_notif.assert_not_called()
+
+        # Verify Discord alert was NOT sent (deduplication worked)
+        mock_client.discord_system_alert.assert_not_called()
+
+
+@pytest.mark.asyncio(loop_scope="session")
+async def test_handle_insufficient_funds_different_agents_get_separate_alerts(
+    server: SpinTestServer,
+):
+    """Test that different agents for the same user get separate Discord alerts."""
+
+    execution_processor = ExecutionProcessor()
+    user_id = "test-user-123"
+    graph_id_1 = "test-graph-111"
+    graph_id_2 = "test-graph-222"
+
+    error = InsufficientBalanceError(
+        message="Insufficient balance",
+        user_id=user_id,
+        balance=72,
+        amount=-714,
+    )
+
+    with patch("backend.executor.manager.queue_notification"), patch(
+        "backend.executor.manager.get_notification_manager_client"
+    ) as mock_get_client, patch(
+        "backend.executor.manager.settings"
+    ) as mock_settings, patch(
+        "backend.executor.manager.redis"
+    ) as mock_redis_module:
+
+        mock_client = MagicMock()
+        mock_get_client.return_value = mock_client
+        mock_settings.config.frontend_base_url = "https://test.com"
+
+        mock_redis_client = MagicMock()
+        mock_redis_module.get_redis.return_value = mock_redis_client
+        # Both calls return True (first time for each agent)
+        mock_redis_client.set.return_value = True
+
+        mock_db_client = MagicMock()
+        mock_graph_metadata = MagicMock()
+        mock_graph_metadata.name = "Test Agent"
+        mock_db_client.get_graph_metadata.return_value = mock_graph_metadata
+        mock_db_client.get_user_email_by_id.return_value = "test@example.com"
+
+        # First agent notification
+        execution_processor._handle_insufficient_funds_notif(
+            db_client=mock_db_client,
+            user_id=user_id,
+            graph_id=graph_id_1,
+            e=error,
+        )
+
+        # Second agent notification
+        execution_processor._handle_insufficient_funds_notif(
+            db_client=mock_db_client,
+            user_id=user_id,
+            graph_id=graph_id_2,
+            e=error,
+        )
+
+        # Verify Discord alerts were sent for both agents
+        assert mock_client.discord_system_alert.call_count == 2
+
+        # Verify Redis was called with different keys
+        assert mock_redis_client.set.call_count == 2
+        calls = mock_redis_client.set.call_args_list
+        assert (
+            calls[0][0][0]
+            == f"{INSUFFICIENT_FUNDS_NOTIFIED_PREFIX}:{user_id}:{graph_id_1}"
+        )
+        assert (
+            calls[1][0][0]
+            == f"{INSUFFICIENT_FUNDS_NOTIFIED_PREFIX}:{user_id}:{graph_id_2}"
+        )
+
+
+@pytest.mark.asyncio(loop_scope="session")
+async def test_clear_insufficient_funds_notifications(server: SpinTestServer):
+    """Test that clearing notifications removes all keys for a user."""
+
+    user_id = "test-user-123"
+
+    with patch("backend.executor.manager.redis") as mock_redis_module:
+
+        mock_redis_client = MagicMock()
+        # get_redis_async is an async function, so we need AsyncMock for it
+        mock_redis_module.get_redis_async = AsyncMock(return_value=mock_redis_client)
+
+        # Mock scan_iter to return some keys as an async iterator
+        mock_keys = [
+            f"{INSUFFICIENT_FUNDS_NOTIFIED_PREFIX}:{user_id}:graph-1",
+            f"{INSUFFICIENT_FUNDS_NOTIFIED_PREFIX}:{user_id}:graph-2",
+            f"{INSUFFICIENT_FUNDS_NOTIFIED_PREFIX}:{user_id}:graph-3",
+        ]
+        mock_redis_client.scan_iter.return_value = async_iter(mock_keys)
+        # delete is awaited, so use AsyncMock
+        mock_redis_client.delete = AsyncMock(return_value=3)
+
+        # Clear notifications
+        result = await clear_insufficient_funds_notifications(user_id)
+
+        # Verify correct pattern was used
+        expected_pattern = f"{INSUFFICIENT_FUNDS_NOTIFIED_PREFIX}:{user_id}:*"
+        mock_redis_client.scan_iter.assert_called_once_with(match=expected_pattern)
+
+        # Verify delete was called with all keys
+        mock_redis_client.delete.assert_called_once_with(*mock_keys)
+
+        # Verify return value
+        assert result == 3
+
+
+@pytest.mark.asyncio(loop_scope="session")
+async def test_clear_insufficient_funds_notifications_no_keys(server: SpinTestServer):
+    """Test clearing notifications when there are no keys to clear."""
+
+    user_id = "test-user-no-notifications"
+
+    with patch("backend.executor.manager.redis") as mock_redis_module:
+
+        mock_redis_client = MagicMock()
+        # get_redis_async is an async function, so we need AsyncMock for it
+        mock_redis_module.get_redis_async = AsyncMock(return_value=mock_redis_client)
+
+        # Mock scan_iter to return no keys as an async iterator
+        mock_redis_client.scan_iter.return_value = async_iter([])
+
+        # Clear notifications
+        result = await clear_insufficient_funds_notifications(user_id)
+
+        # Verify delete was not called
+        mock_redis_client.delete.assert_not_called()
+
+        # Verify return value
+        assert result == 0
+
+
+@pytest.mark.asyncio(loop_scope="session")
+async def test_clear_insufficient_funds_notifications_handles_redis_error(
+    server: SpinTestServer,
+):
+    """Test that clearing notifications handles Redis errors gracefully."""
+
+    user_id = "test-user-redis-error"
+
+    with patch("backend.executor.manager.redis") as mock_redis_module:
+
+        # Mock get_redis_async to raise an error
+        mock_redis_module.get_redis_async = AsyncMock(
+            side_effect=Exception("Redis connection failed")
+        )
+
+        # Clear notifications should not raise, just return 0
+        result = await clear_insufficient_funds_notifications(user_id)
+
+        # Verify it returned 0 (graceful failure)
+        assert result == 0
+
+
+@pytest.mark.asyncio(loop_scope="session")
+async def test_handle_insufficient_funds_continues_on_redis_error(
+    server: SpinTestServer,
+):
+    """Test that both email and Discord notifications are still sent when Redis fails."""
+
+    execution_processor = ExecutionProcessor()
+    user_id = "test-user-123"
+    graph_id = "test-graph-456"
+    error = InsufficientBalanceError(
+        message="Insufficient balance",
+        user_id=user_id,
+        balance=72,
+        amount=-714,
+    )
+
+    with patch(
+        "backend.executor.manager.queue_notification"
+    ) as mock_queue_notif, patch(
+        "backend.executor.manager.get_notification_manager_client"
+    ) as mock_get_client, patch(
+        "backend.executor.manager.settings"
+    ) as mock_settings, patch(
+        "backend.executor.manager.redis"
+    ) as mock_redis_module:
+
+        mock_client = MagicMock()
+        mock_get_client.return_value = mock_client
+        mock_settings.config.frontend_base_url = "https://test.com"
+
+        # Mock Redis to raise an error
+        mock_redis_client = MagicMock()
+        mock_redis_module.get_redis.return_value = mock_redis_client
+        mock_redis_client.set.side_effect = Exception("Redis connection error")
+
+        mock_db_client = MagicMock()
+        mock_graph_metadata = MagicMock()
+        mock_graph_metadata.name = "Test Agent"
+        mock_db_client.get_graph_metadata.return_value = mock_graph_metadata
+        mock_db_client.get_user_email_by_id.return_value = "test@example.com"
+
+        # Test the insufficient funds handler
+        execution_processor._handle_insufficient_funds_notif(
+            db_client=mock_db_client,
+            user_id=user_id,
+            graph_id=graph_id,
+            e=error,
+        )
+
+        # Verify email notification was still queued despite Redis error
+        mock_queue_notif.assert_called_once()
+
+        # Verify Discord alert was still sent despite Redis error
+        mock_client.discord_system_alert.assert_called_once()
+
+
+@pytest.mark.asyncio(loop_scope="session")
+async def test_add_transaction_clears_notifications_on_grant(server: SpinTestServer):
+    """Test that _add_transaction clears notification flags when adding GRANT credits."""
+    from prisma.enums import CreditTransactionType
+
+    from backend.data.credit import UserCredit
+
+    user_id = "test-user-grant-clear"
+
+    with patch("backend.data.credit.query_raw_with_schema") as mock_query, patch(
+        "backend.executor.manager.redis"
+    ) as mock_redis_module:
+
+        # Mock the query to return a successful transaction
+        mock_query.return_value = [{"balance": 1000, "transactionKey": "test-tx-key"}]
+
+        # Mock async Redis for notification clearing
+        mock_redis_client = MagicMock()
+        mock_redis_module.get_redis_async = AsyncMock(return_value=mock_redis_client)
+        mock_redis_client.scan_iter.return_value = async_iter(
+            [f"{INSUFFICIENT_FUNDS_NOTIFIED_PREFIX}:{user_id}:graph-1"]
+        )
+        mock_redis_client.delete = AsyncMock(return_value=1)
+
+        # Create a concrete instance
+        credit_model = UserCredit()
+
+        # Call _add_transaction with GRANT type (should clear notifications)
+        await credit_model._add_transaction(
+            user_id=user_id,
+            amount=500,  # Positive amount
+            transaction_type=CreditTransactionType.GRANT,
+            is_active=True,  # Active transaction
+        )
+
+        # Verify notification clearing was called
+        mock_redis_module.get_redis_async.assert_called_once()
+        mock_redis_client.scan_iter.assert_called_once_with(
+            match=f"{INSUFFICIENT_FUNDS_NOTIFIED_PREFIX}:{user_id}:*"
+        )
+
+
+@pytest.mark.asyncio(loop_scope="session")
+async def test_add_transaction_clears_notifications_on_top_up(server: SpinTestServer):
+    """Test that _add_transaction clears notification flags when adding TOP_UP credits."""
+    from prisma.enums import CreditTransactionType
+
+    from backend.data.credit import UserCredit
+
+    user_id = "test-user-topup-clear"
+
+    with patch("backend.data.credit.query_raw_with_schema") as mock_query, patch(
+        "backend.executor.manager.redis"
+    ) as mock_redis_module:
+
+        # Mock the query to return a successful transaction
+        mock_query.return_value = [{"balance": 2000, "transactionKey": "test-tx-key-2"}]
+
+        # Mock async Redis for notification clearing
+        mock_redis_client = MagicMock()
+        mock_redis_module.get_redis_async = AsyncMock(return_value=mock_redis_client)
+        mock_redis_client.scan_iter.return_value = async_iter([])
+        mock_redis_client.delete = AsyncMock(return_value=0)
+
+        credit_model = UserCredit()
+
+        # Call _add_transaction with TOP_UP type (should clear notifications)
+        await credit_model._add_transaction(
+            user_id=user_id,
+            amount=1000,  # Positive amount
+            transaction_type=CreditTransactionType.TOP_UP,
+            is_active=True,
+        )
+
+        # Verify notification clearing was attempted
+        mock_redis_module.get_redis_async.assert_called_once()
+
+
+@pytest.mark.asyncio(loop_scope="session")
+async def test_add_transaction_skips_clearing_for_inactive_transaction(
+    server: SpinTestServer,
+):
+    """Test that _add_transaction does NOT clear notifications for inactive transactions."""
+    from prisma.enums import CreditTransactionType
+
+    from backend.data.credit import UserCredit
+
+    user_id = "test-user-inactive"
+
+    with patch("backend.data.credit.query_raw_with_schema") as mock_query, patch(
+        "backend.executor.manager.redis"
+    ) as mock_redis_module:
+
+        # Mock the query to return a successful transaction
+        mock_query.return_value = [{"balance": 500, "transactionKey": "test-tx-key-3"}]
+
+        # Mock async Redis
+        mock_redis_client = MagicMock()
+        mock_redis_module.get_redis_async = AsyncMock(return_value=mock_redis_client)
+
+        credit_model = UserCredit()
+
+        # Call _add_transaction with is_active=False (should NOT clear notifications)
+        await credit_model._add_transaction(
+            user_id=user_id,
+            amount=500,
+            transaction_type=CreditTransactionType.TOP_UP,
+            is_active=False,  # Inactive - pending Stripe payment
+        )
+
+        # Verify notification clearing was NOT called
+        mock_redis_module.get_redis_async.assert_not_called()
+
+
+@pytest.mark.asyncio(loop_scope="session")
+async def test_add_transaction_skips_clearing_for_usage_transaction(
+    server: SpinTestServer,
+):
+    """Test that _add_transaction does NOT clear notifications for USAGE transactions."""
+    from prisma.enums import CreditTransactionType
+
+    from backend.data.credit import UserCredit
+
+    user_id = "test-user-usage"
+
+    with patch("backend.data.credit.query_raw_with_schema") as mock_query, patch(
+        "backend.executor.manager.redis"
+    ) as mock_redis_module:
+
+        # Mock the query to return a successful transaction
+        mock_query.return_value = [{"balance": 400, "transactionKey": "test-tx-key-4"}]
+
+        # Mock async Redis
+        mock_redis_client = MagicMock()
+        mock_redis_module.get_redis_async = AsyncMock(return_value=mock_redis_client)
+
+        credit_model = UserCredit()
+
+        # Call _add_transaction with USAGE type (spending, should NOT clear)
+        await credit_model._add_transaction(
+            user_id=user_id,
+            amount=-100,  # Negative - spending credits
+            transaction_type=CreditTransactionType.USAGE,
+            is_active=True,
+        )
+
+        # Verify notification clearing was NOT called
+        mock_redis_module.get_redis_async.assert_not_called()
+
+
+@pytest.mark.asyncio(loop_scope="session")
+async def test_enable_transaction_clears_notifications(server: SpinTestServer):
+    """Test that _enable_transaction clears notification flags when enabling a TOP_UP."""
+    from prisma.enums import CreditTransactionType
+
+    from backend.data.credit import UserCredit
+
+    user_id = "test-user-enable"
+
+    with patch("backend.data.credit.CreditTransaction") as mock_credit_tx, patch(
+        "backend.data.credit.query_raw_with_schema"
+    ) as mock_query, patch("backend.executor.manager.redis") as mock_redis_module:
+
+        # Mock finding the pending transaction
+        mock_transaction = MagicMock()
+        mock_transaction.amount = 1000
+        mock_transaction.type = CreditTransactionType.TOP_UP
+        mock_credit_tx.prisma.return_value.find_first = AsyncMock(
+            return_value=mock_transaction
+        )
+
+        # Mock the query to return updated balance
+        mock_query.return_value = [{"balance": 1500}]
+
+        # Mock async Redis for notification clearing
+        mock_redis_client = MagicMock()
+        mock_redis_module.get_redis_async = AsyncMock(return_value=mock_redis_client)
+        mock_redis_client.scan_iter.return_value = async_iter(
+            [f"{INSUFFICIENT_FUNDS_NOTIFIED_PREFIX}:{user_id}:graph-1"]
+        )
+        mock_redis_client.delete = AsyncMock(return_value=1)
+
+        credit_model = UserCredit()
+
+        # Call _enable_transaction (simulates Stripe checkout completion)
+        from backend.util.json import SafeJson
+
+        await credit_model._enable_transaction(
+            transaction_key="cs_test_123",
+            user_id=user_id,
+            metadata=SafeJson({"payment": "completed"}),
+        )
+
+        # Verify notification clearing was called
+        mock_redis_module.get_redis_async.assert_called_once()
+        mock_redis_client.scan_iter.assert_called_once_with(
+            match=f"{INSUFFICIENT_FUNDS_NOTIFIED_PREFIX}:{user_id}:*"
+        )

autogpt_platform/backend/backend/executor/utils.py

@@ -239,14 +239,19 @@ async def _validate_node_input_credentials(
     graph: GraphModel,
     user_id: str,
     nodes_input_masks: Optional[NodesInputMasks] = None,
-) -> dict[str, dict[str, str]]:
+) -> tuple[dict[str, dict[str, str]], set[str]]:
     """
-    Checks all credentials for all nodes of the graph and returns structured errors.
+    Checks all credentials for all nodes of the graph and returns structured errors
+    and a set of nodes that should be skipped due to optional missing credentials.
 
     Returns:
-        dict[node_id, dict[field_name, error_message]]: Credential validation errors per node
+        tuple[
+            dict[node_id, dict[field_name, error_message]]: Credential validation errors per node,
+            set[node_id]: Nodes that should be skipped (optional credentials not configured)
+        ]
     """
     credential_errors: dict[str, dict[str, str]] = defaultdict(dict)
+    nodes_to_skip: set[str] = set()
 
     for node in graph.nodes:
         block = node.block
@@ -256,27 +261,46 @@ async def _validate_node_input_credentials(
         if not credentials_fields:
             continue
 
+        # Track if any credential field is missing for this node
+        has_missing_credentials = False
+
         for field_name, credentials_meta_type in credentials_fields.items():
             try:
+                # Check nodes_input_masks first, then input_default
+                field_value = None
                 if (
                     nodes_input_masks
                     and (node_input_mask := nodes_input_masks.get(node.id))
                     and field_name in node_input_mask
                 ):
-                    credentials_meta = credentials_meta_type.model_validate(
-                        node_input_mask[field_name]
-                    )
+                    field_value = node_input_mask[field_name]
                 elif field_name in node.input_default:
-                    credentials_meta = credentials_meta_type.model_validate(
-                        node.input_default[field_name]
-                    )
-                else:
-                    # Missing credentials
-                    credential_errors[node.id][
-                        field_name
-                    ] = "These credentials are required"
-                    continue
+                    # For optional credentials, don't use input_default - treat as missing
+                    # This prevents stale credential IDs from failing validation
+                    if node.credentials_optional:
+                        field_value = None
+                    else:
+                        field_value = node.input_default[field_name]
+
+                # Check if credentials are missing (None, empty, or not present)
+                if field_value is None or (
+                    isinstance(field_value, dict) and not field_value.get("id")
+                ):
+                    has_missing_credentials = True
+                    # If node has credentials_optional flag, mark for skipping instead of error
+                    if node.credentials_optional:
+                        continue  # Don't add error, will be marked for skip after loop
+                    else:
+                        credential_errors[node.id][
+                            field_name
+                        ] = "These credentials are required"
+                        continue
+
+                credentials_meta = credentials_meta_type.model_validate(field_value)
+
             except ValidationError as e:
+                # Validation error means credentials were provided but invalid
+                # This should always be an error, even if optional
                 credential_errors[node.id][field_name] = f"Invalid credentials: {e}"
                 continue
 
@@ -287,6 +311,7 @@ async def _validate_node_input_credentials(
                 )
             except Exception as e:
                 # Handle any errors fetching credentials
+                # If credentials were explicitly configured but unavailable, it's an error
                 credential_errors[node.id][
                     field_name
                 ] = f"Credentials not available: {e}"
@@ -313,7 +338,19 @@ async def _validate_node_input_credentials(
                 ] = "Invalid credentials: type/provider mismatch"
                 continue
 
-    return credential_errors
+        # If node has optional credentials and any are missing, mark for skipping
+        # But only if there are no other errors for this node
+        if (
+            has_missing_credentials
+            and node.credentials_optional
+            and node.id not in credential_errors
+        ):
+            nodes_to_skip.add(node.id)
+            logger.info(
+                f"Node #{node.id} will be skipped: optional credentials not configured"
+            )
+
+    return credential_errors, nodes_to_skip
 
 
 def make_node_credentials_input_map(
@@ -355,21 +392,25 @@ async def validate_graph_with_credentials(
     graph: GraphModel,
     user_id: str,
     nodes_input_masks: Optional[NodesInputMasks] = None,
-) -> Mapping[str, Mapping[str, str]]:
+) -> tuple[Mapping[str, Mapping[str, str]], set[str]]:
     """
-    Validate graph including credentials and return structured errors per node.
+    Validate graph including credentials and return structured errors per node,
+    along with a set of nodes that should be skipped due to optional missing credentials.
 
     Returns:
-        dict[node_id, dict[field_name, error_message]]: Validation errors per node
+        tuple[
+            dict[node_id, dict[field_name, error_message]]: Validation errors per node,
+            set[node_id]: Nodes that should be skipped (optional credentials not configured)
+        ]
     """
     # Get input validation errors
     node_input_errors = GraphModel.validate_graph_get_errors(
         graph, for_run=True, nodes_input_masks=nodes_input_masks
     )
 
-    # Get credential input/availability/validation errors
-    node_credential_input_errors = await _validate_node_input_credentials(
-        graph, user_id, nodes_input_masks
+    # Get credential input/availability/validation errors and nodes to skip
+    node_credential_input_errors, nodes_to_skip = (
+        await _validate_node_input_credentials(graph, user_id, nodes_input_masks)
     )
 
     # Merge credential errors with structural errors
@@ -378,7 +419,7 @@ async def validate_graph_with_credentials(
             node_input_errors[node_id] = {}
         node_input_errors[node_id].update(field_errors)
 
-    return node_input_errors
+    return node_input_errors, nodes_to_skip
 
 
 async def _construct_starting_node_execution_input(
@@ -386,7 +427,7 @@ async def _construct_starting_node_execution_input(
     user_id: str,
     graph_inputs: BlockInput,
     nodes_input_masks: Optional[NodesInputMasks] = None,
-) -> list[tuple[str, BlockInput]]:
+) -> tuple[list[tuple[str, BlockInput]], set[str]]:
     """
     Validates and prepares the input data for executing a graph.
     This function checks the graph for starting nodes, validates the input data
@@ -400,11 +441,14 @@ async def _construct_starting_node_execution_input(
         node_credentials_map: `dict[node_id, dict[input_name, CredentialsMetaInput]]`
 
     Returns:
-        list[tuple[str, BlockInput]]: A list of tuples, each containing the node ID and
-            the corresponding input data for that node.
+        tuple[
+            list[tuple[str, BlockInput]]: A list of tuples, each containing the node ID
+                and the corresponding input data for that node.
+            set[str]: Node IDs that should be skipped (optional credentials not configured)
+        ]
     """
     # Use new validation function that includes credentials
-    validation_errors = await validate_graph_with_credentials(
+    validation_errors, nodes_to_skip = await validate_graph_with_credentials(
         graph, user_id, nodes_input_masks
     )
     n_error_nodes = len(validation_errors)
@@ -445,7 +489,7 @@ async def _construct_starting_node_execution_input(
             "No starting nodes found for the graph, make sure an AgentInput or blocks with no inbound links are present as starting nodes."
         )
 
-    return nodes_input
+    return nodes_input, nodes_to_skip
 
 
 async def validate_and_construct_node_execution_input(
@@ -456,7 +500,7 @@ async def validate_and_construct_node_execution_input(
     graph_credentials_inputs: Optional[Mapping[str, CredentialsMetaInput]] = None,
     nodes_input_masks: Optional[NodesInputMasks] = None,
     is_sub_graph: bool = False,
-) -> tuple[GraphModel, list[tuple[str, BlockInput]], NodesInputMasks]:
+) -> tuple[GraphModel, list[tuple[str, BlockInput]], NodesInputMasks, set[str]]:
     """
     Public wrapper that handles graph fetching, credential mapping, and validation+construction.
     This centralizes the logic used by both scheduler validation and actual execution.
@@ -473,6 +517,7 @@ async def validate_and_construct_node_execution_input(
         GraphModel: Full graph object for the given `graph_id`.
         list[tuple[node_id, BlockInput]]: Starting node IDs with corresponding inputs.
         dict[str, BlockInput]: Node input masks including all passed-in credentials.
+        set[str]: Node IDs that should be skipped (optional credentials not configured).
 
     Raises:
         NotFoundError: If the graph is not found.
@@ -514,14 +559,16 @@ async def validate_and_construct_node_execution_input(
         nodes_input_masks or {},
     )
 
-    starting_nodes_input = await _construct_starting_node_execution_input(
-        graph=graph,
-        user_id=user_id,
-        graph_inputs=graph_inputs,
-        nodes_input_masks=nodes_input_masks,
+    starting_nodes_input, nodes_to_skip = (
+        await _construct_starting_node_execution_input(
+            graph=graph,
+            user_id=user_id,
+            graph_inputs=graph_inputs,
+            nodes_input_masks=nodes_input_masks,
+        )
     )
 
-    return graph, starting_nodes_input, nodes_input_masks
+    return graph, starting_nodes_input, nodes_input_masks, nodes_to_skip
 
 
 def _merge_nodes_input_masks(
@@ -779,6 +826,9 @@ async def add_graph_execution(
 
         # Use existing execution's compiled input masks
         compiled_nodes_input_masks = graph_exec.nodes_input_masks or {}
+        # For resumed executions, nodes_to_skip was already determined at creation time
+        # TODO: Consider storing nodes_to_skip in DB if we need to preserve it across resumes
+        nodes_to_skip: set[str] = set()
 
         logger.info(f"Resuming graph execution #{graph_exec.id} for graph #{graph_id}")
     else:
@@ -787,7 +837,7 @@ async def add_graph_execution(
         )
 
         # Create new execution
-        graph, starting_nodes_input, compiled_nodes_input_masks = (
+        graph, starting_nodes_input, compiled_nodes_input_masks, nodes_to_skip = (
             await validate_and_construct_node_execution_input(
                 graph_id=graph_id,
                 user_id=user_id,
@@ -836,6 +886,7 @@ async def add_graph_execution(
     try:
         graph_exec_entry = graph_exec.to_graph_execution_entry(
             compiled_nodes_input_masks=compiled_nodes_input_masks,
+            nodes_to_skip=nodes_to_skip,
             execution_context=execution_context,
         )
         logger.info(f"Publishing execution {graph_exec.id} to execution queue")

autogpt_platform/backend/backend/executor/utils_test.py

@@ -367,10 +367,13 @@ async def test_add_graph_execution_is_repeatable(mocker: MockerFixture):
     )
 
     # Setup mock returns
+    # The function returns (graph, starting_nodes_input, compiled_nodes_input_masks, nodes_to_skip)
+    nodes_to_skip: set[str] = set()
     mock_validate.return_value = (
         mock_graph,
         starting_nodes_input,
         compiled_nodes_input_masks,
+        nodes_to_skip,
     )
     mock_prisma.is_connected.return_value = True
     mock_edb.create_graph_execution = mocker.AsyncMock(return_value=mock_graph_exec)
@@ -456,3 +459,212 @@ async def test_add_graph_execution_is_repeatable(mocker: MockerFixture):
     # Both executions should succeed (though they create different objects)
     assert result1 == mock_graph_exec
     assert result2 == mock_graph_exec_2
+
+
+# ============================================================================
+# Tests for Optional Credentials Feature
+# ============================================================================
+
+
+@pytest.mark.asyncio
+async def test_validate_node_input_credentials_returns_nodes_to_skip(
+    mocker: MockerFixture,
+):
+    """
+    Test that _validate_node_input_credentials returns nodes_to_skip set
+    for nodes with credentials_optional=True and missing credentials.
+    """
+    from backend.executor.utils import _validate_node_input_credentials
+
+    # Create a mock node with credentials_optional=True
+    mock_node = mocker.MagicMock()
+    mock_node.id = "node-with-optional-creds"
+    mock_node.credentials_optional = True
+    mock_node.input_default = {}  # No credentials configured
+
+    # Create a mock block with credentials field
+    mock_block = mocker.MagicMock()
+    mock_credentials_field_type = mocker.MagicMock()
+    mock_block.input_schema.get_credentials_fields.return_value = {
+        "credentials": mock_credentials_field_type
+    }
+    mock_node.block = mock_block
+
+    # Create mock graph
+    mock_graph = mocker.MagicMock()
+    mock_graph.nodes = [mock_node]
+
+    # Call the function
+    errors, nodes_to_skip = await _validate_node_input_credentials(
+        graph=mock_graph,
+        user_id="test-user-id",
+        nodes_input_masks=None,
+    )
+
+    # Node should be in nodes_to_skip, not in errors
+    assert mock_node.id in nodes_to_skip
+    assert mock_node.id not in errors
+
+
+@pytest.mark.asyncio
+async def test_validate_node_input_credentials_required_missing_creds_error(
+    mocker: MockerFixture,
+):
+    """
+    Test that _validate_node_input_credentials returns errors
+    for nodes with credentials_optional=False and missing credentials.
+    """
+    from backend.executor.utils import _validate_node_input_credentials
+
+    # Create a mock node with credentials_optional=False (required)
+    mock_node = mocker.MagicMock()
+    mock_node.id = "node-with-required-creds"
+    mock_node.credentials_optional = False
+    mock_node.input_default = {}  # No credentials configured
+
+    # Create a mock block with credentials field
+    mock_block = mocker.MagicMock()
+    mock_credentials_field_type = mocker.MagicMock()
+    mock_block.input_schema.get_credentials_fields.return_value = {
+        "credentials": mock_credentials_field_type
+    }
+    mock_node.block = mock_block
+
+    # Create mock graph
+    mock_graph = mocker.MagicMock()
+    mock_graph.nodes = [mock_node]
+
+    # Call the function
+    errors, nodes_to_skip = await _validate_node_input_credentials(
+        graph=mock_graph,
+        user_id="test-user-id",
+        nodes_input_masks=None,
+    )
+
+    # Node should be in errors, not in nodes_to_skip
+    assert mock_node.id in errors
+    assert "credentials" in errors[mock_node.id]
+    assert "required" in errors[mock_node.id]["credentials"].lower()
+    assert mock_node.id not in nodes_to_skip
+
+
+@pytest.mark.asyncio
+async def test_validate_graph_with_credentials_returns_nodes_to_skip(
+    mocker: MockerFixture,
+):
+    """
+    Test that validate_graph_with_credentials returns nodes_to_skip set
+    from _validate_node_input_credentials.
+    """
+    from backend.executor.utils import validate_graph_with_credentials
+
+    # Mock _validate_node_input_credentials to return specific values
+    mock_validate = mocker.patch(
+        "backend.executor.utils._validate_node_input_credentials"
+    )
+    expected_errors = {"node1": {"field": "error"}}
+    expected_nodes_to_skip = {"node2", "node3"}
+    mock_validate.return_value = (expected_errors, expected_nodes_to_skip)
+
+    # Mock GraphModel with validate_graph_get_errors method
+    mock_graph = mocker.MagicMock()
+    mock_graph.validate_graph_get_errors.return_value = {}
+
+    # Call the function
+    errors, nodes_to_skip = await validate_graph_with_credentials(
+        graph=mock_graph,
+        user_id="test-user-id",
+        nodes_input_masks=None,
+    )
+
+    # Verify nodes_to_skip is passed through
+    assert nodes_to_skip == expected_nodes_to_skip
+    assert "node1" in errors
+
+
+@pytest.mark.asyncio
+async def test_add_graph_execution_with_nodes_to_skip(mocker: MockerFixture):
+    """
+    Test that add_graph_execution properly passes nodes_to_skip
+    to the graph execution entry.
+    """
+    from backend.data.execution import GraphExecutionWithNodes
+    from backend.executor.utils import add_graph_execution
+
+    # Mock data
+    graph_id = "test-graph-id"
+    user_id = "test-user-id"
+    inputs = {"test_input": "test_value"}
+    graph_version = 1
+
+    # Mock the graph object
+    mock_graph = mocker.MagicMock()
+    mock_graph.version = graph_version
+
+    # Starting nodes and masks
+    starting_nodes_input = [("node1", {"input1": "value1"})]
+    compiled_nodes_input_masks = {}
+    nodes_to_skip = {"skipped-node-1", "skipped-node-2"}
+
+    # Mock the graph execution object
+    mock_graph_exec = mocker.MagicMock(spec=GraphExecutionWithNodes)
+    mock_graph_exec.id = "execution-id-123"
+    mock_graph_exec.node_executions = []
+
+    # Track what's passed to to_graph_execution_entry
+    captured_kwargs = {}
+
+    def capture_to_entry(**kwargs):
+        captured_kwargs.update(kwargs)
+        return mocker.MagicMock()
+
+    mock_graph_exec.to_graph_execution_entry.side_effect = capture_to_entry
+
+    # Setup mocks
+    mock_validate = mocker.patch(
+        "backend.executor.utils.validate_and_construct_node_execution_input"
+    )
+    mock_edb = mocker.patch("backend.executor.utils.execution_db")
+    mock_prisma = mocker.patch("backend.executor.utils.prisma")
+    mock_udb = mocker.patch("backend.executor.utils.user_db")
+    mock_gdb = mocker.patch("backend.executor.utils.graph_db")
+    mock_get_queue = mocker.patch("backend.executor.utils.get_async_execution_queue")
+    mock_get_event_bus = mocker.patch(
+        "backend.executor.utils.get_async_execution_event_bus"
+    )
+
+    # Setup returns - include nodes_to_skip in the tuple
+    mock_validate.return_value = (
+        mock_graph,
+        starting_nodes_input,
+        compiled_nodes_input_masks,
+        nodes_to_skip,  # This should be passed through
+    )
+    mock_prisma.is_connected.return_value = True
+    mock_edb.create_graph_execution = mocker.AsyncMock(return_value=mock_graph_exec)
+    mock_edb.update_graph_execution_stats = mocker.AsyncMock(
+        return_value=mock_graph_exec
+    )
+    mock_edb.update_node_execution_status_batch = mocker.AsyncMock()
+
+    mock_user = mocker.MagicMock()
+    mock_user.timezone = "UTC"
+    mock_settings = mocker.MagicMock()
+    mock_settings.human_in_the_loop_safe_mode = True
+
+    mock_udb.get_user_by_id = mocker.AsyncMock(return_value=mock_user)
+    mock_gdb.get_graph_settings = mocker.AsyncMock(return_value=mock_settings)
+    mock_get_queue.return_value = mocker.AsyncMock()
+    mock_get_event_bus.return_value = mocker.MagicMock(publish=mocker.AsyncMock())
+
+    # Call the function
+    await add_graph_execution(
+        graph_id=graph_id,
+        user_id=user_id,
+        inputs=inputs,
+        graph_version=graph_version,
+    )
+
+    # Verify nodes_to_skip was passed to to_graph_execution_entry
+    assert "nodes_to_skip" in captured_kwargs
+    assert captured_kwargs["nodes_to_skip"] == nodes_to_skip

autogpt_platform/backend/backend/integrations/oauth/__init__.py

@@ -8,6 +8,7 @@ from .discord import DiscordOAuthHandler
 from .github import GitHubOAuthHandler
 from .google import GoogleOAuthHandler
 from .notion import NotionOAuthHandler
+from .reddit import RedditOAuthHandler
 from .twitter import TwitterOAuthHandler
 
 if TYPE_CHECKING:
@@ -20,6 +21,7 @@ _ORIGINAL_HANDLERS = [
     GitHubOAuthHandler,
     GoogleOAuthHandler,
     NotionOAuthHandler,
+    RedditOAuthHandler,
     TwitterOAuthHandler,
     TodoistOAuthHandler,
 ]

autogpt_platform/backend/backend/integrations/oauth/reddit.py

@@ -0,0 +1,208 @@
+import time
+import urllib.parse
+from typing import ClassVar, Optional
+
+from pydantic import SecretStr
+
+from backend.data.model import OAuth2Credentials
+from backend.integrations.oauth.base import BaseOAuthHandler
+from backend.integrations.providers import ProviderName
+from backend.util.request import Requests
+from backend.util.settings import Settings
+
+settings = Settings()
+
+
+class RedditOAuthHandler(BaseOAuthHandler):
+    """
+    Reddit OAuth 2.0 handler.
+
+    Based on the documentation at:
+    - https://github.com/reddit-archive/reddit/wiki/OAuth2
+
+    Notes:
+    - Reddit requires `duration=permanent` to get refresh tokens
+    - Access tokens expire after 1 hour (3600 seconds)
+    - Reddit requires HTTP Basic Auth for token requests
+    - Reddit requires a unique User-Agent header
+    """
+
+    PROVIDER_NAME = ProviderName.REDDIT
+    DEFAULT_SCOPES: ClassVar[list[str]] = [
+        "identity",  # Get username, verify auth
+        "read",  # Access posts and comments
+        "submit",  # Submit new posts and comments
+        "edit",  # Edit own posts and comments
+        "history",  # Access user's post history
+        "privatemessages",  # Access inbox and send private messages
+        "flair",  # Access and set flair on posts/subreddits
+    ]
+
+    AUTHORIZE_URL = "https://www.reddit.com/api/v1/authorize"
+    TOKEN_URL = "https://www.reddit.com/api/v1/access_token"
+    USERNAME_URL = "https://oauth.reddit.com/api/v1/me"
+    REVOKE_URL = "https://www.reddit.com/api/v1/revoke_token"
+
+    def __init__(self, client_id: str, client_secret: str, redirect_uri: str):
+        self.client_id = client_id
+        self.client_secret = client_secret
+        self.redirect_uri = redirect_uri
+
+    def get_login_url(
+        self, scopes: list[str], state: str, code_challenge: Optional[str]
+    ) -> str:
+        """Generate Reddit OAuth 2.0 authorization URL"""
+        scopes = self.handle_default_scopes(scopes)
+
+        params = {
+            "response_type": "code",
+            "client_id": self.client_id,
+            "redirect_uri": self.redirect_uri,
+            "scope": " ".join(scopes),
+            "state": state,
+            "duration": "permanent",  # Required for refresh tokens
+        }
+
+        return f"{self.AUTHORIZE_URL}?{urllib.parse.urlencode(params)}"
+
+    async def exchange_code_for_tokens(
+        self, code: str, scopes: list[str], code_verifier: Optional[str]
+    ) -> OAuth2Credentials:
+        """Exchange authorization code for access tokens"""
+        scopes = self.handle_default_scopes(scopes)
+
+        headers = {
+            "Content-Type": "application/x-www-form-urlencoded",
+            "User-Agent": settings.config.reddit_user_agent,
+        }
+
+        data = {
+            "grant_type": "authorization_code",
+            "code": code,
+            "redirect_uri": self.redirect_uri,
+        }
+
+        # Reddit requires HTTP Basic Auth for token requests
+        auth = (self.client_id, self.client_secret)
+
+        response = await Requests().post(
+            self.TOKEN_URL, headers=headers, data=data, auth=auth
+        )
+
+        if not response.ok:
+            error_text = response.text()
+            raise ValueError(
+                f"Reddit token exchange failed: {response.status} - {error_text}"
+            )
+
+        tokens = response.json()
+
+        if "error" in tokens:
+            raise ValueError(f"Reddit OAuth error: {tokens.get('error')}")
+
+        username = await self._get_username(tokens["access_token"])
+
+        return OAuth2Credentials(
+            provider=self.PROVIDER_NAME,
+            title=None,
+            username=username,
+            access_token=tokens["access_token"],
+            refresh_token=tokens.get("refresh_token"),
+            access_token_expires_at=int(time.time()) + tokens.get("expires_in", 3600),
+            refresh_token_expires_at=None,  # Reddit refresh tokens don't expire
+            scopes=scopes,
+        )
+
+    async def _get_username(self, access_token: str) -> str:
+        """Get the username from the access token"""
+        headers = {
+            "Authorization": f"Bearer {access_token}",
+            "User-Agent": settings.config.reddit_user_agent,
+        }
+
+        response = await Requests().get(self.USERNAME_URL, headers=headers)
+
+        if not response.ok:
+            raise ValueError(f"Failed to get Reddit username: {response.status}")
+
+        data = response.json()
+        return data.get("name", "unknown")
+
+    async def _refresh_tokens(
+        self, credentials: OAuth2Credentials
+    ) -> OAuth2Credentials:
+        """Refresh access tokens using refresh token"""
+        if not credentials.refresh_token:
+            raise ValueError("No refresh token available")
+
+        headers = {
+            "Content-Type": "application/x-www-form-urlencoded",
+            "User-Agent": settings.config.reddit_user_agent,
+        }
+
+        data = {
+            "grant_type": "refresh_token",
+            "refresh_token": credentials.refresh_token.get_secret_value(),
+        }
+
+        auth = (self.client_id, self.client_secret)
+
+        response = await Requests().post(
+            self.TOKEN_URL, headers=headers, data=data, auth=auth
+        )
+
+        if not response.ok:
+            error_text = response.text()
+            raise ValueError(
+                f"Reddit token refresh failed: {response.status} - {error_text}"
+            )
+
+        tokens = response.json()
+
+        if "error" in tokens:
+            raise ValueError(f"Reddit OAuth error: {tokens.get('error')}")
+
+        username = await self._get_username(tokens["access_token"])
+
+        # Reddit may or may not return a new refresh token
+        new_refresh_token = tokens.get("refresh_token")
+        if new_refresh_token:
+            refresh_token: SecretStr | None = SecretStr(new_refresh_token)
+        elif credentials.refresh_token:
+            # Keep the existing refresh token
+            refresh_token = credentials.refresh_token
+        else:
+            refresh_token = None
+
+        return OAuth2Credentials(
+            id=credentials.id,
+            provider=self.PROVIDER_NAME,
+            title=credentials.title,
+            username=username,
+            access_token=tokens["access_token"],
+            refresh_token=refresh_token,
+            access_token_expires_at=int(time.time()) + tokens.get("expires_in", 3600),
+            refresh_token_expires_at=None,
+            scopes=credentials.scopes,
+        )
+
+    async def revoke_tokens(self, credentials: OAuth2Credentials) -> bool:
+        """Revoke the access token"""
+        headers = {
+            "Content-Type": "application/x-www-form-urlencoded",
+            "User-Agent": settings.config.reddit_user_agent,
+        }
+
+        data = {
+            "token": credentials.access_token.get_secret_value(),
+            "token_type_hint": "access_token",
+        }
+
+        auth = (self.client_id, self.client_secret)
+
+        response = await Requests().post(
+            self.REVOKE_URL, headers=headers, data=data, auth=auth
+        )
+
+        # Reddit returns 204 No Content on successful revocation
+        return response.ok

autogpt_platform/backend/backend/util/settings.py

@@ -264,7 +264,7 @@ class Config(UpdateTrackingModel["Config"], BaseSettings):
     )
 
     reddit_user_agent: str = Field(
-        default="AutoGPT:1.0 (by /u/autogpt)",
+        default="web:AutoGPT:v0.6.0 (by /u/autogpt)",
         description="The user agent for the Reddit API",
     )
 

autogpt_platform/backend/gen_prisma_types_stub.py

@@ -0,0 +1,227 @@
+#!/usr/bin/env python3
+"""
+Generate a lightweight stub for prisma/types.py that collapses all exported
+symbols to Any. This prevents Pyright from spending time/budget on Prisma's
+query DSL types while keeping runtime behavior unchanged.
+
+Usage:
+    poetry run gen-prisma-stub
+
+This script automatically finds the prisma package location and generates
+the types.pyi stub file in the same directory as types.py.
+"""
+
+from __future__ import annotations
+
+import ast
+import importlib.util
+import sys
+from pathlib import Path
+from typing import Iterable, Set
+
+
+def _iter_assigned_names(target: ast.expr) -> Iterable[str]:
+    """Extract names from assignment targets (handles tuple unpacking)."""
+    if isinstance(target, ast.Name):
+        yield target.id
+    elif isinstance(target, (ast.Tuple, ast.List)):
+        for elt in target.elts:
+            yield from _iter_assigned_names(elt)
+
+
+def _is_private(name: str) -> bool:
+    """Check if a name is private (starts with _ but not __)."""
+    return name.startswith("_") and not name.startswith("__")
+
+
+def _is_safe_type_alias(node: ast.Assign) -> bool:
+    """Check if an assignment is a safe type alias that shouldn't be stubbed.
+
+    Safe types are:
+    - Literal types (don't cause type budget issues)
+    - Simple type references (SortMode, SortOrder, etc.)
+    - TypeVar definitions
+    """
+    if not node.value:
+        return False
+
+    # Check if it's a Subscript (like Literal[...], Union[...], TypeVar[...])
+    if isinstance(node.value, ast.Subscript):
+        # Get the base type name
+        if isinstance(node.value.value, ast.Name):
+            base_name = node.value.value.id
+            # Literal types are safe
+            if base_name == "Literal":
+                return True
+            # TypeVar is safe
+            if base_name == "TypeVar":
+                return True
+        elif isinstance(node.value.value, ast.Attribute):
+            # Handle typing_extensions.Literal etc.
+            if node.value.value.attr == "Literal":
+                return True
+
+    # Check if it's a simple Name reference (like SortMode = _types.SortMode)
+    if isinstance(node.value, ast.Attribute):
+        return True
+
+    # Check if it's a Call (like TypeVar(...))
+    if isinstance(node.value, ast.Call):
+        if isinstance(node.value.func, ast.Name):
+            if node.value.func.id == "TypeVar":
+                return True
+
+    return False
+
+
+def collect_top_level_symbols(
+    tree: ast.Module, source_lines: list[str]
+) -> tuple[Set[str], Set[str], list[str], Set[str]]:
+    """Collect all top-level symbols from an AST module.
+
+    Returns:
+        Tuple of (class_names, function_names, safe_variable_sources, unsafe_variable_names)
+        safe_variable_sources contains the actual source code lines for safe variables
+    """
+    classes: Set[str] = set()
+    functions: Set[str] = set()
+    safe_variable_sources: list[str] = []
+    unsafe_variables: Set[str] = set()
+
+    for node in tree.body:
+        if isinstance(node, ast.ClassDef):
+            if not _is_private(node.name):
+                classes.add(node.name)
+        elif isinstance(node, (ast.FunctionDef, ast.AsyncFunctionDef)):
+            if not _is_private(node.name):
+                functions.add(node.name)
+        elif isinstance(node, ast.Assign):
+            is_safe = _is_safe_type_alias(node)
+            names = []
+            for t in node.targets:
+                for n in _iter_assigned_names(t):
+                    if not _is_private(n):
+                        names.append(n)
+            if names:
+                if is_safe:
+                    # Extract the source code for this assignment
+                    start_line = node.lineno - 1  # 0-indexed
+                    end_line = node.end_lineno if node.end_lineno else node.lineno
+                    source = "\n".join(source_lines[start_line:end_line])
+                    safe_variable_sources.append(source)
+                else:
+                    unsafe_variables.update(names)
+        elif isinstance(node, ast.AnnAssign) and node.target:
+            # Annotated assignments are always stubbed
+            for n in _iter_assigned_names(node.target):
+                if not _is_private(n):
+                    unsafe_variables.add(n)
+
+    return classes, functions, safe_variable_sources, unsafe_variables
+
+
+def find_prisma_types_path() -> Path:
+    """Find the prisma types.py file in the installed package."""
+    spec = importlib.util.find_spec("prisma")
+    if spec is None or spec.origin is None:
+        raise RuntimeError("Could not find prisma package. Is it installed?")
+
+    prisma_dir = Path(spec.origin).parent
+    types_path = prisma_dir / "types.py"
+
+    if not types_path.exists():
+        raise RuntimeError(f"prisma/types.py not found at {types_path}")
+
+    return types_path
+
+
+def generate_stub(src_path: Path, stub_path: Path) -> int:
+    """Generate the .pyi stub file from the source types.py."""
+    code = src_path.read_text(encoding="utf-8", errors="ignore")
+    source_lines = code.splitlines()
+    tree = ast.parse(code, filename=str(src_path))
+    classes, functions, safe_variable_sources, unsafe_variables = (
+        collect_top_level_symbols(tree, source_lines)
+    )
+
+    header = """\
+# -*- coding: utf-8 -*-
+# Auto-generated stub file - DO NOT EDIT
+# Generated by gen_prisma_types_stub.py
+#
+# This stub intentionally collapses complex Prisma query DSL types to Any.
+# Prisma's generated types can explode Pyright's type inference budgets
+# on large schemas. We collapse them to Any so the rest of the codebase
+# can remain strongly typed while keeping runtime behavior unchanged.
+#
+# Safe types (Literal, TypeVar, simple references) are preserved from the
+# original types.py to maintain proper type checking where possible.
+
+from __future__ import annotations
+from typing import Any
+from typing_extensions import Literal
+
+# Re-export commonly used typing constructs that may be imported from this module
+from typing import TYPE_CHECKING, TypeVar, Generic, Union, Optional, List, Dict
+
+# Base type alias for stubbed Prisma types - allows any dict structure
+_PrismaDict = dict[str, Any]
+
+"""
+
+    lines = [header]
+
+    # Include safe variable definitions (Literal types, TypeVars, etc.)
+    lines.append("# Safe type definitions preserved from original types.py")
+    for source in safe_variable_sources:
+        lines.append(source)
+    lines.append("")
+
+    # Stub all classes and unsafe variables uniformly as dict[str, Any] aliases
+    # This allows:
+    # 1. Use in type annotations: x: SomeType
+    # 2. Constructor calls: SomeType(...)
+    # 3. Dict literal assignments: x: SomeType = {...}
+    lines.append(
+        "# Stubbed types (collapsed to dict[str, Any] to prevent type budget exhaustion)"
+    )
+    all_stubbed = sorted(classes | unsafe_variables)
+    for name in all_stubbed:
+        lines.append(f"{name} = _PrismaDict")
+
+    lines.append("")
+
+    # Stub functions
+    for name in sorted(functions):
+        lines.append(f"def {name}(*args: Any, **kwargs: Any) -> Any: ...")
+
+    lines.append("")
+
+    stub_path.write_text("\n".join(lines), encoding="utf-8")
+    return (
+        len(classes)
+        + len(functions)
+        + len(safe_variable_sources)
+        + len(unsafe_variables)
+    )
+
+
+def main() -> None:
+    """Main entry point."""
+    try:
+        types_path = find_prisma_types_path()
+        stub_path = types_path.with_suffix(".pyi")
+
+        print(f"Found prisma types.py at: {types_path}")
+        print(f"Generating stub at: {stub_path}")
+
+        num_symbols = generate_stub(types_path, stub_path)
+        print(f"Generated {stub_path.name} with {num_symbols} Any-typed symbols")
+
+    except Exception as e:
+        print(f"Error: {e}", file=sys.stderr)
+        sys.exit(1)
+
+
+if __name__ == "__main__":
+    main()

autogpt_platform/backend/linter.py

@@ -25,6 +25,9 @@ def run(*command: str) -> None:
 
 
 def lint():
+    # Generate Prisma types stub before running pyright to prevent type budget exhaustion
+    run("gen-prisma-stub")
+
     lint_step_args: list[list[str]] = [
         ["ruff", "check", *TARGET_DIRS, "--exit-zero"],
         ["ruff", "format", "--diff", "--check", LIBS_DIR],
@@ -49,4 +52,6 @@ def format():
     run("ruff", "format", LIBS_DIR)
     run("isort", "--profile", "black", BACKEND_DIR)
     run("black", BACKEND_DIR)
+    # Generate Prisma types stub before running pyright to prevent type budget exhaustion
+    run("gen-prisma-stub")
     run("pyright", *TARGET_DIRS)

autogpt_platform/backend/poetry.lock

@@ -1906,6 +1906,22 @@ httpx = {version = ">=0.26,<0.29", extras = ["http2"]}
 pydantic = ">=1.10,<3"
 pyjwt = ">=2.10.1,<3.0.0"
 
+[[package]]
+name = "gravitas-md2gdocs"
+version = "0.1.0"
+description = "Convert Markdown to Google Docs API requests"
+optional = false
+python-versions = ">=3.10"
+groups = ["main"]
+files = [
+    {file = "gravitas_md2gdocs-0.1.0-py3-none-any.whl", hash = "sha256:0cb0627779fdd65c1604818af4142eea1b25d055060183363de1bae4d9e46508"},
+    {file = "gravitas_md2gdocs-0.1.0.tar.gz", hash = "sha256:bb3122fe9fa35c528f3f00b785d3f1398d350082d5d03f60f56c895bdcc68033"},
+]
+
+[package.extras]
+dev = ["google-auth-oauthlib (>=1.0.0)", "pytest (>=7.0.0)", "pytest-cov (>=4.0.0)", "python-dotenv (>=1.0.0)", "ruff (>=0.1.0)"]
+google = ["google-api-python-client (>=2.0.0)", "google-auth (>=2.0.0)"]
+
 [[package]]
 name = "gravitasml"
 version = "0.1.4"
@@ -7279,4 +7295,4 @@ cffi = ["cffi (>=1.11)"]
 [metadata]
 lock-version = "2.1"
 python-versions = ">=3.10,<3.14"
-content-hash = "13b191b2a1989d3321ff713c66ff6f5f4f3b82d15df4d407e0e5dbf87d7522c4"
+content-hash = "a93ba0cea3b465cb6ec3e3f258b383b09f84ea352ccfdbfa112902cde5653fc6"

autogpt_platform/backend/pyproject.toml

@@ -82,6 +82,7 @@ firecrawl-py = "^4.3.6"
 exa-py = "^1.14.20"
 croniter = "^6.0.0"
 stagehand = "^0.5.1"
+gravitas-md2gdocs = "^0.1.0"
 
 [tool.poetry.group.dev.dependencies]
 aiohappyeyeballs = "^2.6.1"
@@ -116,6 +117,7 @@ lint = "linter:lint"
 test = "run_tests:test"
 load-store-agents = "test.load_store_agents:run"
 export-api-schema = "backend.cli.generate_openapi_json:main"
+gen-prisma-stub = "gen_prisma_types_stub:main"
 oauth-tool = "backend.cli.oauth_tool:cli"
 
 [tool.isort]
@@ -133,6 +135,9 @@ ignore_patterns = []
 [tool.pytest.ini_options]
 asyncio_mode = "auto"
 asyncio_default_fixture_loop_scope = "session"
+# Disable syrupy plugin to avoid conflict with pytest-snapshot
+# Both provide --snapshot-update argument causing ArgumentError
+addopts = "-p no:syrupy"
 filterwarnings = [
     "ignore:'audioop' is deprecated:DeprecationWarning:discord.player",
     "ignore:invalid escape sequence:DeprecationWarning:tweepy.api",

autogpt_platform/backend/snapshots/grph_single

@@ -2,6 +2,7 @@
   "created_at": "2025-09-04T13:37:00",
   "credentials_input_schema": {
     "properties": {},
+    "required": [],
     "title": "TestGraphCredentialsInputSchema",
     "type": "object"
   },

autogpt_platform/backend/snapshots/grphs_all

@@ -2,6 +2,7 @@
   {
     "credentials_input_schema": {
       "properties": {},
+      "required": [],
       "title": "TestGraphCredentialsInputSchema",
       "type": "object"
     },

autogpt_platform/backend/snapshots/lib_agts_search

@@ -4,6 +4,7 @@
       "id": "test-agent-1",
       "graph_id": "test-agent-1",
       "graph_version": 1,
+      "owner_user_id": "3e53486c-cf57-477e-ba2a-cb02dc828e1a",
       "image_url": null,
       "creator_name": "Test Creator",
       "creator_image_url": "",
@@ -41,6 +42,7 @@
       "id": "test-agent-2",
       "graph_id": "test-agent-2",
       "graph_version": 1,
+      "owner_user_id": "3e53486c-cf57-477e-ba2a-cb02dc828e1a",
       "image_url": null,
       "creator_name": "Test Creator",
       "creator_image_url": "",

autogpt_platform/backend/snapshots/sub_success

@@ -1,6 +1,7 @@
 {
   "submissions": [
     {
+      "listing_id": "test-listing-id",
       "agent_id": "test-agent-id",
       "agent_version": 1,
       "name": "Test Agent",

autogpt_platform/backend/test/blocks/test_google_docs_format_text_color.py

@@ -0,0 +1,113 @@
+from unittest.mock import Mock
+
+from backend.blocks.google.docs import GoogleDocsFormatTextBlock
+
+
+def _make_mock_docs_service() -> Mock:
+    service = Mock()
+    # Ensure chained call exists: service.documents().batchUpdate(...).execute()
+    service.documents.return_value.batchUpdate.return_value.execute.return_value = {}
+    return service
+
+
+def test_format_text_parses_shorthand_hex_color():
+    block = GoogleDocsFormatTextBlock()
+    service = _make_mock_docs_service()
+
+    result = block._format_text(
+        service,
+        document_id="doc_1",
+        start_index=1,
+        end_index=2,
+        bold=False,
+        italic=False,
+        underline=False,
+        font_size=0,
+        foreground_color="#FFF",
+    )
+
+    assert result["success"] is True
+
+    # Verify request body contains correct rgbColor for white.
+    _, kwargs = service.documents.return_value.batchUpdate.call_args
+    requests = kwargs["body"]["requests"]
+    rgb = requests[0]["updateTextStyle"]["textStyle"]["foregroundColor"]["color"][
+        "rgbColor"
+    ]
+    assert rgb == {"red": 1.0, "green": 1.0, "blue": 1.0}
+
+
+def test_format_text_parses_full_hex_color():
+    block = GoogleDocsFormatTextBlock()
+    service = _make_mock_docs_service()
+
+    result = block._format_text(
+        service,
+        document_id="doc_1",
+        start_index=1,
+        end_index=2,
+        bold=False,
+        italic=False,
+        underline=False,
+        font_size=0,
+        foreground_color="#FF0000",
+    )
+
+    assert result["success"] is True
+
+    _, kwargs = service.documents.return_value.batchUpdate.call_args
+    requests = kwargs["body"]["requests"]
+    rgb = requests[0]["updateTextStyle"]["textStyle"]["foregroundColor"]["color"][
+        "rgbColor"
+    ]
+    assert rgb == {"red": 1.0, "green": 0.0, "blue": 0.0}
+
+
+def test_format_text_ignores_invalid_color_when_other_fields_present():
+    block = GoogleDocsFormatTextBlock()
+    service = _make_mock_docs_service()
+
+    result = block._format_text(
+        service,
+        document_id="doc_1",
+        start_index=1,
+        end_index=2,
+        bold=True,
+        italic=False,
+        underline=False,
+        font_size=0,
+        foreground_color="#GGG",
+    )
+
+    assert result["success"] is True
+    assert "warning" in result
+
+    # Should still apply bold, but should NOT include foregroundColor in textStyle.
+    _, kwargs = service.documents.return_value.batchUpdate.call_args
+    requests = kwargs["body"]["requests"]
+    text_style = requests[0]["updateTextStyle"]["textStyle"]
+    fields = requests[0]["updateTextStyle"]["fields"]
+
+    assert text_style == {"bold": True}
+    assert fields == "bold"
+
+
+def test_format_text_invalid_color_only_does_not_call_api():
+    block = GoogleDocsFormatTextBlock()
+    service = _make_mock_docs_service()
+
+    result = block._format_text(
+        service,
+        document_id="doc_1",
+        start_index=1,
+        end_index=2,
+        bold=False,
+        italic=False,
+        underline=False,
+        font_size=0,
+        foreground_color="#F",
+    )
+
+    assert result["success"] is False
+    assert "Invalid foreground_color" in result["message"]
+    service.documents.return_value.batchUpdate.assert_not_called()

autogpt_platform/backend/test/blocks/test_youtube.py

@@ -37,6 +37,18 @@ class TestTranscribeYoutubeVideoBlock:
         video_id = self.youtube_block.extract_video_id(url)
         assert video_id == "dQw4w9WgXcQ"
 
+    def test_extract_video_id_shorts_url(self):
+        """Test extracting video ID from YouTube Shorts URL."""
+        url = "https://www.youtube.com/shorts/dtUqwMu3e-g"
+        video_id = self.youtube_block.extract_video_id(url)
+        assert video_id == "dtUqwMu3e-g"
+
+    def test_extract_video_id_shorts_url_with_params(self):
+        """Test extracting video ID from YouTube Shorts URL with query parameters."""
+        url = "https://www.youtube.com/shorts/dtUqwMu3e-g?feature=share"
+        video_id = self.youtube_block.extract_video_id(url)
+        assert video_id == "dtUqwMu3e-g"
+
     @patch("backend.blocks.youtube.YouTubeTranscriptApi")
     def test_get_transcript_english_available(self, mock_api_class):
         """Test getting transcript when English is available."""

autogpt_platform/cloudflare_worker.js

@@ -0,0 +1,146 @@
+/**
+ * Cloudflare Workers Script for docs.agpt.co → agpt.co/docs migration
+ * 
+ * Deploy this script to handle all redirects with a single JavaScript file.
+ * No rule limits, easy to maintain, handles all edge cases.
+ */
+
+// URL mapping for special cases that don't follow patterns
+const SPECIAL_MAPPINGS = {
+  // Root page
+  '/': '/docs/platform',
+  
+  // Special cases that don't follow standard patterns
+  '/platform/d_id/': '/docs/integrations/block-integrations/d-id',
+  '/platform/blocks/blocks/': '/docs/integrations',
+  '/platform/blocks/decoder_block/': '/docs/integrations/block-integrations/text-decoder',
+  '/platform/blocks/http': '/docs/integrations/block-integrations/send-web-request',
+  '/platform/blocks/llm/': '/docs/integrations/block-integrations/ai-and-llm',
+  '/platform/blocks/time_blocks': '/docs/integrations/block-integrations/time-and-date',
+  '/platform/blocks/text_to_speech_block': '/docs/integrations/block-integrations/text-to-speech',
+  '/platform/blocks/ai_shortform_video_block': '/docs/integrations/block-integrations/ai-shortform-video',
+  '/platform/blocks/replicate_flux_advanced': '/docs/integrations/block-integrations/replicate-flux-advanced',
+  '/platform/blocks/flux_kontext': '/docs/integrations/block-integrations/flux-kontext',
+  '/platform/blocks/ai_condition/': '/docs/integrations/block-integrations/ai-condition',
+  '/platform/blocks/email_block': '/docs/integrations/block-integrations/email',
+  '/platform/blocks/google_maps': '/docs/integrations/block-integrations/google-maps',
+  '/platform/blocks/google/gmail': '/docs/integrations/block-integrations/gmail',
+  '/platform/blocks/github/issues/': '/docs/integrations/block-integrations/github-issues',
+  '/platform/blocks/github/repo/': '/docs/integrations/block-integrations/github-repo',
+  '/platform/blocks/github/pull_requests': '/docs/integrations/block-integrations/github-pull-requests',
+  '/platform/blocks/twitter/twitter': '/docs/integrations/block-integrations/twitter',
+  '/classic/setup/': '/docs/classic/setup/setting-up-autogpt-classic',
+  '/code-of-conduct/': '/docs/classic/help-us-improve-autogpt/code-of-conduct',
+  '/contributing/': '/docs/classic/contributing',
+  '/contribute/': '/docs/contribute',
+  '/forge/components/introduction/': '/docs/classic/forge/introduction'
+};
+
+/**
+ * Transform path by replacing underscores with hyphens and removing trailing slashes
+ */
+function transformPath(path) {
+  return path.replace(/_/g, '-').replace(/\/$/, '');
+}
+
+/**
+ * Handle docs.agpt.co redirects
+ */
+function handleDocsRedirect(url) {
+  const pathname = url.pathname;
+  
+  // Check special mappings first
+  if (SPECIAL_MAPPINGS[pathname]) {
+    return `https://agpt.co${SPECIAL_MAPPINGS[pathname]}`;
+  }
+  
+  // Pattern-based redirects
+  
+  // Platform blocks: /platform/blocks/* → /docs/integrations/block-integrations/*
+  if (pathname.startsWith('/platform/blocks/')) {
+    const blockName = pathname.substring('/platform/blocks/'.length);
+    const transformedName = transformPath(blockName);
+    return `https://agpt.co/docs/integrations/block-integrations/${transformedName}`;
+  }
+  
+  // Platform contributing: /platform/contributing/* → /docs/platform/contributing/*
+  if (pathname.startsWith('/platform/contributing/')) {
+    const subPath = pathname.substring('/platform/contributing/'.length);
+    return `https://agpt.co/docs/platform/contributing/${subPath}`;
+  }
+  
+  // Platform general: /platform/* → /docs/platform/* (with underscore→hyphen)
+  if (pathname.startsWith('/platform/')) {
+    const subPath = pathname.substring('/platform/'.length);
+    const transformedPath = transformPath(subPath);
+    return `https://agpt.co/docs/platform/${transformedPath}`;
+  }
+  
+  // Forge components: /forge/components/* → /docs/classic/forge/introduction/*
+  if (pathname.startsWith('/forge/components/')) {
+    const subPath = pathname.substring('/forge/components/'.length);
+    return `https://agpt.co/docs/classic/forge/introduction/${subPath}`;
+  }
+  
+  // Forge general: /forge/* → /docs/classic/forge/*
+  if (pathname.startsWith('/forge/')) {
+    const subPath = pathname.substring('/forge/'.length);
+    return `https://agpt.co/docs/classic/forge/${subPath}`;
+  }
+  
+  // Classic: /classic/* → /docs/classic/*
+  if (pathname.startsWith('/classic/')) {
+    const subPath = pathname.substring('/classic/'.length);
+    return `https://agpt.co/docs/classic/${subPath}`;
+  }
+  
+  // Default fallback
+  return 'https://agpt.co/docs/';
+}
+
+/**
+ * Main Worker function
+ */
+export default {
+  async fetch(request, env, ctx) {
+    const url = new URL(request.url);
+    
+    // Only handle docs.agpt.co requests
+    if (url.hostname === 'docs.agpt.co') {
+      const redirectUrl = handleDocsRedirect(url);
+      
+      return new Response(null, {
+        status: 301,
+        headers: {
+          'Location': redirectUrl,
+          'Cache-Control': 'max-age=300' // Cache redirects for 5 minutes
+        }
+      });
+    }
+    
+    // For non-docs requests, pass through or return 404
+    return new Response('Not Found', { status: 404 });
+  }
+};
+
+// Test function for local development
+export function testRedirects() {
+  const testCases = [
+    'https://docs.agpt.co/',
+    'https://docs.agpt.co/platform/getting-started/',
+    'https://docs.agpt.co/platform/advanced_setup/',
+    'https://docs.agpt.co/platform/blocks/basic/',
+    'https://docs.agpt.co/platform/blocks/ai_condition/',
+    'https://docs.agpt.co/classic/setup/',
+    'https://docs.agpt.co/forge/components/agents/',
+    'https://docs.agpt.co/contributing/',
+    'https://docs.agpt.co/unknown-page'
+  ];
+  
+  console.log('Testing redirects:');
+  testCases.forEach(testUrl => {
+    const url = new URL(testUrl);
+    const result = handleDocsRedirect(url);
+    console.log(`${testUrl} → ${result}`);
+  });
+}

autogpt_platform/docker-compose.platform.yml

@@ -37,7 +37,7 @@ services:
       context: ../
       dockerfile: autogpt_platform/backend/Dockerfile
       target: migrate
-    command: ["sh", "-c", "poetry run prisma generate && poetry run prisma migrate deploy"]
+    command: ["sh", "-c", "poetry run prisma generate && poetry run gen-prisma-stub && poetry run prisma migrate deploy"]
     develop:
       watch:
         - path: ./

autogpt_platform/frontend/package.json

@@ -46,14 +46,15 @@
     "@radix-ui/react-scroll-area": "1.2.10",
     "@radix-ui/react-select": "2.2.6",
     "@radix-ui/react-separator": "1.1.7",
+    "@radix-ui/react-slider": "1.3.6",
     "@radix-ui/react-slot": "1.2.3",
     "@radix-ui/react-switch": "1.2.6",
     "@radix-ui/react-tabs": "1.1.13",
     "@radix-ui/react-toast": "1.2.15",
     "@radix-ui/react-tooltip": "1.2.8",
-    "@rjsf/core": "5.24.13",
-    "@rjsf/utils": "5.24.13",
-    "@rjsf/validator-ajv8": "5.24.13",
+    "@rjsf/core": "6.1.2",
+    "@rjsf/utils": "6.1.2",
+    "@rjsf/validator-ajv8": "6.1.2",
     "@sentry/nextjs": "10.27.0",
     "@supabase/ssr": "0.7.0",
     "@supabase/supabase-js": "2.78.0",
@@ -69,6 +70,7 @@
     "cmdk": "1.1.1",
     "cookie": "1.0.2",
     "date-fns": "4.1.0",
+    "dexie": "4.2.1",
     "dotenv": "17.2.3",
     "elliptic": "6.6.1",
     "embla-carousel-react": "8.6.0",
@@ -90,7 +92,6 @@
     "react-currency-input-field": "4.0.3",
     "react-day-picker": "9.11.1",
     "react-dom": "18.3.1",
-    "react-drag-drop-files": "2.4.0",
     "react-hook-form": "7.66.0",
     "react-icons": "5.5.0",
     "react-markdown": "9.0.3",

autogpt_platform/frontend/src/app/(platform)/auth/integrations/oauth_callback/route.ts

@@ -1,4 +1,4 @@
-import { OAuthPopupResultMessage } from "@/components/renderers/input-renderer/fields/CredentialField/models/OAuthCredentialModal/useOAuthCredentialModal";
+import { OAuthPopupResultMessage } from "./types";
 import { NextResponse } from "next/server";
 
 // This route is intended to be used as the callback for integration OAuth flows,

autogpt_platform/frontend/src/app/(platform)/auth/integrations/oauth_callback/types.ts

@@ -0,0 +1,11 @@
+export type OAuthPopupResultMessage = { message_type: "oauth_popup_result" } & (
+  | {
+      success: true;
+      code: string;
+      state: string;
+    }
+  | {
+      success: false;
+      message: string;
+    }
+);

autogpt_platform/frontend/src/app/(platform)/build/components/BuilderActions/components/AgentOutputs/AgentOutputs.tsx

@@ -16,6 +16,7 @@ import {
   SheetTitle,
   SheetTrigger,
 } from "@/components/__legacy__/ui/sheet";
+import { Button } from "@/components/atoms/Button/Button";
 import {
   Tooltip,
   TooltipContent,
@@ -25,7 +26,6 @@ import {
 import { BookOpenIcon } from "@phosphor-icons/react";
 import { useMemo } from "react";
 import { useShallow } from "zustand/react/shallow";
-import { BuilderActionButton } from "../BuilderActionButton";
 
 export const AgentOutputs = ({ flowID }: { flowID: string | null }) => {
   const hasOutputs = useGraphStore(useShallow((state) => state.hasOutputs));
@@ -76,9 +76,13 @@ export const AgentOutputs = ({ flowID }: { flowID: string | null }) => {
         <Tooltip>
           <TooltipTrigger asChild>
             <SheetTrigger asChild>
-              <BuilderActionButton disabled={!flowID || !hasOutputs()}>
-                <BookOpenIcon className="size-6" />
-              </BuilderActionButton>
+              <Button
+                variant="outline"
+                size="icon"
+                disabled={!flowID || !hasOutputs()}
+              >
+                <BookOpenIcon className="size-4" />
+              </Button>
             </SheetTrigger>
           </TooltipTrigger>
           <TooltipContent>

autogpt_platform/frontend/src/app/(platform)/build/components/BuilderActions/components/BuilderActionButton.tsx

@@ -1,37 +0,0 @@
-import { Button } from "@/components/atoms/Button/Button";
-import { ButtonProps } from "@/components/atoms/Button/helpers";
-import { cn } from "@/lib/utils";
-import { CircleNotchIcon } from "@phosphor-icons/react";
-
-export const BuilderActionButton = ({
-  children,
-  className,
-  isLoading,
-  ...props
-}: ButtonProps & { isLoading?: boolean }) => {
-  return (
-    <Button
-      variant="icon"
-      size={"small"}
-      className={cn(
-        "relative h-12 w-12 min-w-0 text-lg",
-        "bg-gradient-to-br from-zinc-50 to-zinc-200",
-        "border border-zinc-200",
-        "shadow-[inset_0_3px_0_0_rgba(255,255,255,0.5),0_2px_4px_0_rgba(0,0,0,0.2)]",
-        "dark:shadow-[inset_0_1px_0_0_rgba(255,255,255,0.1),0_2px_4px_0_rgba(0,0,0,0.4)]",
-        "hover:shadow-[inset_0_1px_0_0_rgba(255,255,255,0.5),0_1px_2px_0_rgba(0,0,0,0.2)]",
-        "active:shadow-[inset_0_2px_4px_0_rgba(0,0,0,0.2)]",
-        "transition-all duration-150",
-        "disabled:cursor-not-allowed disabled:opacity-50",
-        className,
-      )}
-      {...props}
-    >
-      {!isLoading ? (
-        children
-      ) : (
-        <CircleNotchIcon className="size-6 animate-spin" />
-      )}
-    </Button>
-  );
-};

autogpt_platform/frontend/src/app/(platform)/build/components/BuilderActions/components/PublishToMarketplace/PublishToMarketplace.tsx

@@ -1,12 +1,12 @@
-import { ShareIcon } from "@phosphor-icons/react";
-import { BuilderActionButton } from "../BuilderActionButton";
+import { Button } from "@/components/atoms/Button/Button";
 import {
   Tooltip,
   TooltipContent,
   TooltipTrigger,
 } from "@/components/atoms/Tooltip/BaseTooltip";
-import { usePublishToMarketplace } from "./usePublishToMarketplace";
 import { PublishAgentModal } from "@/components/contextual/PublishAgentModal/PublishAgentModal";
+import { ShareIcon } from "@phosphor-icons/react";
+import { usePublishToMarketplace } from "./usePublishToMarketplace";
 
 export const PublishToMarketplace = ({ flowID }: { flowID: string | null }) => {
   const { handlePublishToMarketplace, publishState, handleStateChange } =
@@ -16,12 +16,14 @@ export const PublishToMarketplace = ({ flowID }: { flowID: string | null }) => {
     <>
       <Tooltip>
         <TooltipTrigger asChild>
-          <BuilderActionButton
+          <Button
+            variant="outline"
+            size="icon"
             onClick={handlePublishToMarketplace}
             disabled={!flowID}
           >
-            <ShareIcon className="size-6 drop-shadow-sm" />
-          </BuilderActionButton>
+            <ShareIcon className="size-4" />
+          </Button>
         </TooltipTrigger>
         <TooltipContent>Publish to Marketplace</TooltipContent>
       </Tooltip>
@@ -30,6 +32,7 @@ export const PublishToMarketplace = ({ flowID }: { flowID: string | null }) => {
         targetState={publishState}
         onStateChange={handleStateChange}
         preSelectedAgentId={flowID || undefined}
+        showTrigger={false}
       />
     </>
   );

autogpt_platform/frontend/src/app/(platform)/build/components/BuilderActions/components/RunGraph/RunGraph.tsx

@@ -1,15 +1,14 @@
-import { useRunGraph } from "./useRunGraph";
 import { useGraphStore } from "@/app/(platform)/build/stores/graphStore";
-import { useShallow } from "zustand/react/shallow";
-import { PlayIcon, StopIcon } from "@phosphor-icons/react";
-import { cn } from "@/lib/utils";
-import { RunInputDialog } from "../RunInputDialog/RunInputDialog";
+import { Button } from "@/components/atoms/Button/Button";
 import {
   Tooltip,
   TooltipContent,
   TooltipTrigger,
 } from "@/components/atoms/Tooltip/BaseTooltip";
-import { BuilderActionButton } from "../BuilderActionButton";
+import { PlayIcon, StopIcon } from "@phosphor-icons/react";
+import { useShallow } from "zustand/react/shallow";
+import { RunInputDialog } from "../RunInputDialog/RunInputDialog";
+import { useRunGraph } from "./useRunGraph";
 
 export const RunGraph = ({ flowID }: { flowID: string | null }) => {
   const {
@@ -29,21 +28,19 @@ export const RunGraph = ({ flowID }: { flowID: string | null }) => {
     <>
       <Tooltip>
         <TooltipTrigger asChild>
-          <BuilderActionButton
-            className={cn(
-              isGraphRunning &&
-                "border-red-500 bg-gradient-to-br from-red-400 to-red-500 shadow-[inset_0_2px_0_0_rgba(255,255,255,0.5),0_2px_4px_0_rgba(0,0,0,0.2)]",
-            )}
+          <Button
+            size="icon"
+            variant={isGraphRunning ? "destructive" : "primary"}
             onClick={isGraphRunning ? handleStopGraph : handleRunGraph}
             disabled={!flowID || isExecutingGraph || isTerminatingGraph}
-            isLoading={isExecutingGraph || isTerminatingGraph || isSaving}
+            loading={isExecutingGraph || isTerminatingGraph || isSaving}
           >
             {!isGraphRunning ? (
-              <PlayIcon className="size-6 drop-shadow-sm" />
+              <PlayIcon className="size-4" />
             ) : (
-              <StopIcon className="size-6 drop-shadow-sm" />
+              <StopIcon className="size-4" />
             )}
-          </BuilderActionButton>
+          </Button>
         </TooltipTrigger>
         <TooltipContent>
           {isGraphRunning ? "Stop agent" : "Run agent"}

autogpt_platform/frontend/src/app/(platform)/build/components/BuilderActions/components/RunInputDialog/RunInputDialog.tsx

@@ -5,7 +5,7 @@ import { useGraphStore } from "@/app/(platform)/build/stores/graphStore";
 import { Button } from "@/components/atoms/Button/Button";
 import { ClockIcon, PlayIcon } from "@phosphor-icons/react";
 import { Text } from "@/components/atoms/Text/Text";
-import { FormRenderer } from "@/components/renderers/input-renderer/FormRenderer";
+import { FormRenderer } from "@/components/renderers/InputRenderer/FormRenderer";
 import { useRunInputDialog } from "./useRunInputDialog";
 import { CronSchedulerDialog } from "../CronSchedulerDialog/CronSchedulerDialog";
 
@@ -66,6 +66,7 @@ export const RunInputDialog = ({
                     formContext={{
                       showHandles: false,
                       size: "large",
+                      showOptionalToggle: false,
                     }}
                   />
                 </div>

autogpt_platform/frontend/src/app/(platform)/build/components/BuilderActions/components/RunInputDialog/useRunInputDialog.ts

@@ -8,7 +8,7 @@ import {
 import { parseAsInteger, parseAsString, useQueryStates } from "nuqs";
 import { useMemo, useState } from "react";
 import { uiSchema } from "../../../FlowEditor/nodes/uiSchema";
-import { isCredentialFieldSchema } from "@/components/renderers/input-renderer/fields/CredentialField/helpers";
+import { isCredentialFieldSchema } from "@/components/renderers/InputRenderer/custom/CredentialField/helpers";
 
 export const useRunInputDialog = ({
   setIsOpen,
@@ -66,7 +66,7 @@ export const useRunInputDialog = ({
         if (isCredentialFieldSchema(fieldSchema)) {
           dynamicUiSchema[fieldName] = {
             ...dynamicUiSchema[fieldName],
-            "ui:field": "credentials",
+            "ui:field": "custom/credential_field",
           };
         }
       });
@@ -76,12 +76,18 @@ export const useRunInputDialog = ({
   }, [credentialsSchema]);
 
   const handleManualRun = async () => {
+    // Filter out incomplete credentials (those without a valid id)
+    // RJSF auto-populates const values (provider, type) but not id field
+    const validCredentials = Object.fromEntries(
+      Object.entries(credentialValues).filter(([_, cred]) => cred && cred.id),
+    );
+
     await executeGraph({
       graphId: flowID ?? "",
       graphVersion: flowVersion || null,
       data: {
         inputs: inputValues,
-        credentials_inputs: credentialValues,
+        credentials_inputs: validCredentials,
         source: "builder",
       },
     });

autogpt_platform/frontend/src/app/(platform)/build/components/BuilderActions/components/ScheduleGraph/ScheduleGraph.tsx

@@ -1,14 +1,14 @@
-import { ClockIcon } from "@phosphor-icons/react";
-import { RunInputDialog } from "../RunInputDialog/RunInputDialog";
-import { useScheduleGraph } from "./useScheduleGraph";
+import { Button } from "@/components/atoms/Button/Button";
 import {
   Tooltip,
   TooltipContent,
   TooltipProvider,
   TooltipTrigger,
 } from "@/components/atoms/Tooltip/BaseTooltip";
+import { ClockIcon } from "@phosphor-icons/react";
 import { CronSchedulerDialog } from "../CronSchedulerDialog/CronSchedulerDialog";
-import { BuilderActionButton } from "../BuilderActionButton";
+import { RunInputDialog } from "../RunInputDialog/RunInputDialog";
+import { useScheduleGraph } from "./useScheduleGraph";
 
 export const ScheduleGraph = ({ flowID }: { flowID: string | null }) => {
   const {
@@ -23,12 +23,14 @@ export const ScheduleGraph = ({ flowID }: { flowID: string | null }) => {
       <TooltipProvider>
         <Tooltip>
           <TooltipTrigger asChild>
-            <BuilderActionButton
+            <Button
+              variant="outline"
+              size="icon"
               onClick={handleScheduleGraph}
               disabled={!flowID}
             >
-              <ClockIcon className="size-6" />
-            </BuilderActionButton>
+              <ClockIcon className="size-4" />
+            </Button>
           </TooltipTrigger>
           <TooltipContent>
             <p>Schedule Graph</p>

autogpt_platform/frontend/src/app/(platform)/build/components/DraftRecoveryDialog/DraftRecoveryPopup.tsx

@@ -0,0 +1,160 @@
+"use client";
+
+import { Button } from "@/components/atoms/Button/Button";
+import { ClockCounterClockwiseIcon, XIcon } from "@phosphor-icons/react";
+import { cn } from "@/lib/utils";
+import { formatTimeAgo } from "@/lib/utils/time";
+import {
+  Tooltip,
+  TooltipContent,
+  TooltipTrigger,
+} from "@/components/atoms/Tooltip/BaseTooltip";
+import { useDraftRecoveryPopup } from "./useDraftRecoveryPopup";
+import { Text } from "@/components/atoms/Text/Text";
+import { AnimatePresence, motion } from "framer-motion";
+import { DraftDiff } from "@/lib/dexie/draft-utils";
+
+interface DraftRecoveryPopupProps {
+  isInitialLoadComplete: boolean;
+}
+
+function formatDiffSummary(diff: DraftDiff | null): string {
+  if (!diff) return "";
+
+  const parts: string[] = [];
+
+  // Node changes
+  const nodeChanges: string[] = [];
+  if (diff.nodes.added > 0) nodeChanges.push(`+${diff.nodes.added}`);
+  if (diff.nodes.removed > 0) nodeChanges.push(`-${diff.nodes.removed}`);
+  if (diff.nodes.modified > 0) nodeChanges.push(`~${diff.nodes.modified}`);
+
+  if (nodeChanges.length > 0) {
+    parts.push(
+      `${nodeChanges.join("/")} block${diff.nodes.added + diff.nodes.removed + diff.nodes.modified !== 1 ? "s" : ""}`,
+    );
+  }
+
+  // Edge changes
+  const edgeChanges: string[] = [];
+  if (diff.edges.added > 0) edgeChanges.push(`+${diff.edges.added}`);
+  if (diff.edges.removed > 0) edgeChanges.push(`-${diff.edges.removed}`);
+  if (diff.edges.modified > 0) edgeChanges.push(`~${diff.edges.modified}`);
+
+  if (edgeChanges.length > 0) {
+    parts.push(
+      `${edgeChanges.join("/")} connection${diff.edges.added + diff.edges.removed + diff.edges.modified !== 1 ? "s" : ""}`,
+    );
+  }
+
+  return parts.join(", ");
+}
+
+export function DraftRecoveryPopup({
+  isInitialLoadComplete,
+}: DraftRecoveryPopupProps) {
+  const {
+    isOpen,
+    popupRef,
+    nodeCount,
+    edgeCount,
+    diff,
+    savedAt,
+    onLoad,
+    onDiscard,
+  } = useDraftRecoveryPopup(isInitialLoadComplete);
+
+  const diffSummary = formatDiffSummary(diff);
+
+  return (
+    <AnimatePresence>
+      {isOpen && (
+        <motion.div
+          ref={popupRef}
+          className={cn("absolute left-1/2 top-4 z-50")}
+          initial={{
+            opacity: 0,
+            x: "-50%",
+            y: "-150%",
+            scale: 0.5,
+            filter: "blur(20px)",
+          }}
+          animate={{
+            opacity: 1,
+            x: "-50%",
+            y: "0%",
+            scale: 1,
+            filter: "blur(0px)",
+          }}
+          exit={{
+            opacity: 0,
+            y: "-150%",
+            scale: 0.5,
+            filter: "blur(20px)",
+            transition: { duration: 0.4, type: "spring", bounce: 0.2 },
+          }}
+          transition={{ duration: 0.2, type: "spring", bounce: 0.2 }}
+        >
+          <div
+            className={cn(
+              "flex items-center gap-3 rounded-xlarge border border-amber-200 bg-amber-50 px-4 py-3 shadow-lg",
+            )}
+          >
+            <div className="flex items-center gap-2 text-amber-700 dark:text-amber-300">
+              <ClockCounterClockwiseIcon className="h-5 w-5" weight="fill" />
+            </div>
+
+            <div className="flex flex-col">
+              <Text
+                variant="small-medium"
+                className="text-amber-900 dark:text-amber-100"
+              >
+                Unsaved changes found
+              </Text>
+              <Text
+                variant="small"
+                className="text-amber-700 dark:text-amber-400"
+              >
+                {diffSummary ||
+                  `${nodeCount} block${nodeCount !== 1 ? "s" : ""}, ${edgeCount} connection${edgeCount !== 1 ? "s" : ""}`}{" "}
+                • {formatTimeAgo(new Date(savedAt).toISOString())}
+              </Text>
+            </div>
+
+            <div className="ml-2 flex items-center gap-2">
+              <Tooltip delayDuration={10}>
+                <TooltipTrigger asChild>
+                  <Button
+                    variant="primary"
+                    size="small"
+                    onClick={onLoad}
+                    className="aspect-square min-w-0 p-1.5"
+                  >
+                    <ClockCounterClockwiseIcon size={20} weight="fill" />
+                    <span className="sr-only">Restore changes</span>
+                  </Button>
+                </TooltipTrigger>
+                <TooltipContent>Restore changes</TooltipContent>
+              </Tooltip>
+              <Tooltip delayDuration={10}>
+                <TooltipTrigger asChild>
+                  <Button
+                    variant="destructive"
+                    size="icon"
+                    onClick={onDiscard}
+                    aria-label="Discard changes"
+                    className="aspect-square min-w-0 p-1.5"
+                  >
+                    <XIcon size={20} />
+                    <span className="sr-only">Discard changes</span>
+                  </Button>
+                </TooltipTrigger>
+                <TooltipContent>Discard changes</TooltipContent>
+              </Tooltip>
+            </div>
+          </div>
+        </motion.div>
+      )}
+    </AnimatePresence>
+  );
+}

autogpt_platform/frontend/src/app/(platform)/build/components/DraftRecoveryDialog/useDraftRecoveryPopup.tsx

@@ -0,0 +1,63 @@
+import { useEffect, useRef } from "react";
+import { useDraftManager } from "../FlowEditor/Flow/useDraftManager";
+
+export const useDraftRecoveryPopup = (isInitialLoadComplete: boolean) => {
+  const popupRef = useRef<HTMLDivElement>(null);
+
+  const {
+    isRecoveryOpen: isOpen,
+    savedAt,
+    nodeCount,
+    edgeCount,
+    diff,
+    loadDraft: onLoad,
+    discardDraft: onDiscard,
+  } = useDraftManager(isInitialLoadComplete);
+
+  useEffect(() => {
+    if (!isOpen) return;
+
+    const handleClickOutside = (event: MouseEvent) => {
+      if (
+        popupRef.current &&
+        !popupRef.current.contains(event.target as Node)
+      ) {
+        onDiscard();
+      }
+    };
+
+    const timeoutId = setTimeout(() => {
+      document.addEventListener("mousedown", handleClickOutside);
+    }, 100);
+
+    return () => {
+      clearTimeout(timeoutId);
+      document.removeEventListener("mousedown", handleClickOutside);
+    };
+  }, [isOpen, onDiscard]);
+
+  useEffect(() => {
+    if (!isOpen) return;
+
+    const handleKeyDown = (event: KeyboardEvent) => {
+      if (event.key === "Escape") {
+        onDiscard();
+      }
+    };
+
+    document.addEventListener("keydown", handleKeyDown);
+    return () => {
+      document.removeEventListener("keydown", handleKeyDown);
+    };
+  }, [isOpen, onDiscard]);
+  return {
+    popupRef,
+    isOpen,
+    nodeCount,
+    edgeCount,
+    diff,
+    savedAt,
+    onLoad,
+    onDiscard,
+  };
+};

autogpt_platform/frontend/src/app/(platform)/build/components/FlowEditor/Flow/Flow.tsx

@@ -1,26 +1,27 @@
-import { ReactFlow, Background } from "@xyflow/react";
-import NewControlPanel from "../../NewControlPanel/NewControlPanel";
-import CustomEdge from "../edges/CustomEdge";
-import { useFlow } from "./useFlow";
-import { useShallow } from "zustand/react/shallow";
-import { useNodeStore } from "../../../stores/nodeStore";
-import { useMemo, useEffect, useCallback } from "react";
-import { CustomNode } from "../nodes/CustomNode/CustomNode";
-import { useCustomEdge } from "../edges/useCustomEdge";
-import { useFlowRealtime } from "./useFlowRealtime";
-import { GraphLoadingBox } from "./components/GraphLoadingBox";
-import { BuilderActions } from "../../BuilderActions/BuilderActions";
-import { RunningBackground } from "./components/RunningBackground";
-import { useGraphStore } from "../../../stores/graphStore";
-import { useCopyPaste } from "./useCopyPaste";
-import { FloatingReviewsPanel } from "@/components/organisms/FloatingReviewsPanel/FloatingReviewsPanel";
-import { parseAsString, useQueryStates } from "nuqs";
-import { CustomControls } from "./components/CustomControl";
 import { useGetV1GetSpecificGraph } from "@/app/api/__generated__/endpoints/graphs/graphs";
 import { okData } from "@/app/api/helpers";
+import { FloatingReviewsPanel } from "@/components/organisms/FloatingReviewsPanel/FloatingReviewsPanel";
+import { Background, ReactFlow } from "@xyflow/react";
+import { parseAsString, useQueryStates } from "nuqs";
+import { useCallback, useMemo } from "react";
+import { useShallow } from "zustand/react/shallow";
+import { useGraphStore } from "../../../stores/graphStore";
+import { useNodeStore } from "../../../stores/nodeStore";
+import { BuilderActions } from "../../BuilderActions/BuilderActions";
+import { DraftRecoveryPopup } from "../../DraftRecoveryDialog/DraftRecoveryPopup";
+import { FloatingSafeModeToggle } from "../../FloatingSafeModeToogle";
+import NewControlPanel from "../../NewControlPanel/NewControlPanel";
+import CustomEdge from "../edges/CustomEdge";
+import { useCustomEdge } from "../edges/useCustomEdge";
+import { CustomNode } from "../nodes/CustomNode/CustomNode";
+import { CustomControls } from "./components/CustomControl";
+import { GraphLoadingBox } from "./components/GraphLoadingBox";
+import { RunningBackground } from "./components/RunningBackground";
 import { TriggerAgentBanner } from "./components/TriggerAgentBanner";
 import { resolveCollisions } from "./helpers/resolve-collision";
-import { FloatingSafeModeToggle } from "../../FloatingSafeModeToogle";
+import { useCopyPaste } from "./useCopyPaste";
+import { useFlow } from "./useFlow";
+import { useFlowRealtime } from "./useFlowRealtime";
 
 export const Flow = () => {
   const [{ flowID, flowExecutionID }] = useQueryStates({
@@ -41,14 +42,18 @@ export const Flow = () => {
 
   const nodes = useNodeStore(useShallow((state) => state.nodes));
   const setNodes = useNodeStore(useShallow((state) => state.setNodes));
+
   const onNodesChange = useNodeStore(
     useShallow((state) => state.onNodesChange),
   );
+
   const hasWebhookNodes = useNodeStore(
     useShallow((state) => state.hasWebhookNodes()),
   );
+
   const nodeTypes = useMemo(() => ({ custom: CustomNode }), []);
   const edgeTypes = useMemo(() => ({ custom: CustomEdge }), []);
+
   const onNodeDragStop = useCallback(() => {
     setNodes(
       resolveCollisions(nodes, {
@@ -60,29 +65,26 @@ export const Flow = () => {
   }, [setNodes, nodes]);
   const { edges, onConnect, onEdgesChange } = useCustomEdge();
 
-  // We use this hook to load the graph and convert them into custom nodes and edges.
-  const { onDragOver, onDrop, isFlowContentLoading, isLocked, setIsLocked } =
-    useFlow();
+  // for loading purpose
+  const {
+    onDragOver,
+    onDrop,
+    isFlowContentLoading,
+    isInitialLoadComplete,
+    isLocked,
+    setIsLocked,
+  } = useFlow();
 
   // This hook is used for websocket realtime updates.
   useFlowRealtime();
 
   // Copy/paste functionality
-  const handleCopyPaste = useCopyPaste();
+  useCopyPaste();
 
-  useEffect(() => {
-    const handleKeyDown = (event: KeyboardEvent) => {
-      handleCopyPaste(event);
-    };
-
-    window.addEventListener("keydown", handleKeyDown);
-    return () => {
-      window.removeEventListener("keydown", handleKeyDown);
-    };
-  }, [handleCopyPaste]);
   const isGraphRunning = useGraphStore(
     useShallow((state) => state.isGraphRunning),
   );
+
   return (
     <div className="flex h-full w-full dark:bg-slate-900">
       <div className="relative flex-1">
@@ -95,6 +97,9 @@ export const Flow = () => {
           onConnect={onConnect}
           onEdgesChange={onEdgesChange}
           onNodeDragStop={onNodeDragStop}
+          onNodeContextMenu={(event) => {
+            event.preventDefault();
+          }}
           maxZoom={2}
           minZoom={0.1}
           onDragOver={onDragOver}
@@ -102,6 +107,7 @@ export const Flow = () => {
           nodesDraggable={!isLocked}
           nodesConnectable={!isLocked}
           elementsSelectable={!isLocked}
+          deleteKeyCode={["Backspace", "Delete"]}
         >
           <Background />
           <CustomControls setIsLocked={setIsLocked} isLocked={isLocked} />
@@ -115,6 +121,7 @@ export const Flow = () => {
               className="right-2 top-32 p-2"
             />
           )}
+          <DraftRecoveryPopup isInitialLoadComplete={isInitialLoadComplete} />
         </ReactFlow>
       </div>
       {/* TODO: Need to update it in future - also do not send executionId as prop - rather use useQueryState inside the component */}

autogpt_platform/frontend/src/app/(platform)/build/components/FlowEditor/Flow/helpers/resolve-collision.ts

@@ -48,8 +48,6 @@ export const resolveCollisions: CollisionAlgorithm = (
     const width = (node.width ?? node.measured?.width ?? 0) + margin * 2;
     const height = (node.height ?? node.measured?.height ?? 0) + margin * 2;
 
-    console.log("width", width);
-    console.log("height", height);
     const x = node.position.x - margin;
     const y = node.position.y - margin;
 

autogpt_platform/frontend/src/app/(platform)/build/components/FlowEditor/Flow/useCopyPaste.ts

@@ -1,4 +1,4 @@
-import { useCallback } from "react";
+import { useCallback, useEffect } from "react";
 import { useReactFlow } from "@xyflow/react";
 import { v4 as uuidv4 } from "uuid";
 import { useNodeStore } from "../../../stores/nodeStore";
@@ -151,5 +151,16 @@ export function useCopyPaste() {
     [getViewport, toast],
   );
 
+  useEffect(() => {
+    const handleKeyDown = (event: KeyboardEvent) => {
+      handleCopyPaste(event);
+    };
+
+    window.addEventListener("keydown", handleKeyDown);
+    return () => {
+      window.removeEventListener("keydown", handleKeyDown);
+    };
+  }, [handleCopyPaste]);
+
   return handleCopyPaste;
 }

autogpt_platform/frontend/src/app/(platform)/build/components/FlowEditor/Flow/useDraftManager.ts

@@ -0,0 +1,319 @@
+import { useState, useCallback, useEffect, useRef } from "react";
+import { parseAsString, parseAsInteger, useQueryStates } from "nuqs";
+import {
+  draftService,
+  getTempFlowId,
+  getOrCreateTempFlowId,
+  DraftData,
+} from "@/services/builder-draft/draft-service";
+import { BuilderDraft } from "@/lib/dexie/db";
+import {
+  cleanNodes,
+  cleanEdges,
+  calculateDraftDiff,
+  DraftDiff,
+} from "@/lib/dexie/draft-utils";
+import { useNodeStore } from "../../../stores/nodeStore";
+import { useEdgeStore } from "../../../stores/edgeStore";
+import { useGraphStore } from "../../../stores/graphStore";
+import { useHistoryStore } from "../../../stores/historyStore";
+import isEqual from "lodash/isEqual";
+
+const AUTO_SAVE_INTERVAL_MS = 15000; // 15 seconds
+
+interface DraftRecoveryState {
+  isOpen: boolean;
+  draft: BuilderDraft | null;
+  diff: DraftDiff | null;
+}
+
+/**
+ * Consolidated hook for draft persistence and recovery
+ * - Auto-saves builder state every 15 seconds
+ * - Saves on beforeunload event
+ * - Checks for and manages unsaved drafts on load
+ */
+export function useDraftManager(isInitialLoadComplete: boolean) {
+  const [state, setState] = useState<DraftRecoveryState>({
+    isOpen: false,
+    draft: null,
+    diff: null,
+  });
+
+  const [{ flowID, flowVersion }] = useQueryStates({
+    flowID: parseAsString,
+    flowVersion: parseAsInteger,
+  });
+
+  const lastSavedStateRef = useRef<DraftData | null>(null);
+  const saveTimeoutRef = useRef<NodeJS.Timeout | null>(null);
+  const isDirtyRef = useRef(false);
+  const hasCheckedForDraft = useRef(false);
+
+  const getEffectiveFlowId = useCallback((): string => {
+    return flowID || getOrCreateTempFlowId();
+  }, [flowID]);
+
+  const getCurrentState = useCallback((): DraftData => {
+    const nodes = useNodeStore.getState().nodes;
+    const edges = useEdgeStore.getState().edges;
+    const nodeCounter = useNodeStore.getState().nodeCounter;
+    const graphStore = useGraphStore.getState();
+
+    return {
+      nodes,
+      edges,
+      graphSchemas: {
+        input: graphStore.inputSchema,
+        credentials: graphStore.credentialsInputSchema,
+        output: graphStore.outputSchema,
+      },
+      nodeCounter,
+      flowVersion: flowVersion ?? undefined,
+    };
+  }, [flowVersion]);
+
+  const cleanStateForComparison = useCallback((stateData: DraftData) => {
+    return {
+      nodes: cleanNodes(stateData.nodes),
+      edges: cleanEdges(stateData.edges),
+    };
+  }, []);
+
+  const hasChanges = useCallback((): boolean => {
+    const currentState = getCurrentState();
+
+    if (!lastSavedStateRef.current) {
+      return currentState.nodes.length > 0;
+    }
+
+    const currentClean = cleanStateForComparison(currentState);
+    const lastClean = cleanStateForComparison(lastSavedStateRef.current);
+
+    return !isEqual(currentClean, lastClean);
+  }, [getCurrentState, cleanStateForComparison]);
+
+  const saveDraft = useCallback(async () => {
+    const effectiveFlowId = getEffectiveFlowId();
+    const currentState = getCurrentState();
+
+    if (currentState.nodes.length === 0 && currentState.edges.length === 0) {
+      return;
+    }
+
+    if (!hasChanges()) {
+      return;
+    }
+
+    try {
+      await draftService.saveDraft(effectiveFlowId, currentState);
+      lastSavedStateRef.current = currentState;
+      isDirtyRef.current = false;
+    } catch (error) {
+      console.error("[DraftPersistence] Failed to save draft:", error);
+    }
+  }, [getEffectiveFlowId, getCurrentState, hasChanges]);
+
+  const scheduleSave = useCallback(() => {
+    isDirtyRef.current = true;
+
+    if (saveTimeoutRef.current) {
+      clearTimeout(saveTimeoutRef.current);
+    }
+
+    saveTimeoutRef.current = setTimeout(() => {
+      saveDraft();
+    }, AUTO_SAVE_INTERVAL_MS);
+  }, [saveDraft]);
+
+  useEffect(() => {
+    const unsubscribeNodes = useNodeStore.subscribe((storeState, prevState) => {
+      if (storeState.nodes !== prevState.nodes) {
+        scheduleSave();
+      }
+    });
+
+    const unsubscribeEdges = useEdgeStore.subscribe((storeState, prevState) => {
+      if (storeState.edges !== prevState.edges) {
+        scheduleSave();
+      }
+    });
+
+    return () => {
+      unsubscribeNodes();
+      unsubscribeEdges();
+    };
+  }, [scheduleSave]);
+
+  useEffect(() => {
+    const handleBeforeUnload = () => {
+      if (isDirtyRef.current) {
+        const effectiveFlowId = getEffectiveFlowId();
+        const currentState = getCurrentState();
+
+        if (
+          currentState.nodes.length === 0 &&
+          currentState.edges.length === 0
+        ) {
+          return;
+        }
+
+        draftService.saveDraft(effectiveFlowId, currentState).catch(() => {
+          // Ignore errors on unload
+        });
+      }
+    };
+
+    window.addEventListener("beforeunload", handleBeforeUnload);
+    return () => {
+      window.removeEventListener("beforeunload", handleBeforeUnload);
+    };
+  }, [getEffectiveFlowId, getCurrentState]);
+
+  useEffect(() => {
+    return () => {
+      if (saveTimeoutRef.current) {
+        clearTimeout(saveTimeoutRef.current);
+      }
+      if (isDirtyRef.current) {
+        saveDraft();
+      }
+    };
+  }, [saveDraft]);
+
+  useEffect(() => {
+    draftService.cleanupExpired().catch((error) => {
+      console.error(
+        "[DraftPersistence] Failed to cleanup expired drafts:",
+        error,
+      );
+    });
+  }, []);
+
+  const checkForDraft = useCallback(async () => {
+    const effectiveFlowId = flowID || getTempFlowId();
+
+    if (!effectiveFlowId) {
+      return;
+    }
+
+    try {
+      const draft = await draftService.loadDraft(effectiveFlowId);
+
+      if (!draft) {
+        return;
+      }
+
+      const currentNodes = useNodeStore.getState().nodes;
+      const currentEdges = useEdgeStore.getState().edges;
+
+      const isDifferent = draftService.isDraftDifferent(
+        draft,
+        currentNodes,
+        currentEdges,
+      );
+
+      if (isDifferent && (draft.nodes.length > 0 || draft.edges.length > 0)) {
+        const diff = calculateDraftDiff(
+          draft.nodes,
+          draft.edges,
+          currentNodes,
+          currentEdges,
+        );
+        setState({
+          isOpen: true,
+          draft,
+          diff,
+        });
+      } else {
+        await draftService.deleteDraft(effectiveFlowId);
+      }
+    } catch (error) {
+      console.error("[DraftRecovery] Failed to check for draft:", error);
+    }
+  }, [flowID]);
+
+  useEffect(() => {
+    if (isInitialLoadComplete && !hasCheckedForDraft.current) {
+      hasCheckedForDraft.current = true;
+      checkForDraft();
+    }
+  }, [isInitialLoadComplete, checkForDraft]);
+
+  useEffect(() => {
+    hasCheckedForDraft.current = false;
+    setState({
+      isOpen: false,
+      draft: null,
+      diff: null,
+    });
+  }, [flowID]);
+
+  const loadDraft = useCallback(async () => {
+    if (!state.draft) return;
+
+    const { draft } = state;
+
+    try {
+      useNodeStore.getState().setNodes(draft.nodes);
+      useEdgeStore.getState().setEdges(draft.edges);
+      draft.nodes.forEach((node) => {
+        useNodeStore.getState().syncHardcodedValuesWithHandleIds(node.id);
+      });
+
+      if (draft.nodeCounter !== undefined) {
+        useNodeStore.setState({ nodeCounter: draft.nodeCounter });
+      }
+
+      if (draft.graphSchemas) {
+        useGraphStore
+          .getState()
+          .setGraphSchemas(
+            draft.graphSchemas.input as Record<string, unknown> | null,
+            draft.graphSchemas.credentials as Record<string, unknown> | null,
+            draft.graphSchemas.output as Record<string, unknown> | null,
+          );
+      }
+
+      setTimeout(() => {
+        useHistoryStore.getState().initializeHistory();
+      }, 100);
+
+      await draftService.deleteDraft(draft.id);
+
+      setState({
+        isOpen: false,
+        draft: null,
+        diff: null,
+      });
+    } catch (error) {
+      console.error("[DraftRecovery] Failed to load draft:", error);
+    }
+  }, [state.draft]);
+
+  const discardDraft = useCallback(async () => {
+    if (!state.draft) {
+      setState({ isOpen: false, draft: null, diff: null });
+      return;
+    }
+
+    try {
+      await draftService.deleteDraft(state.draft.id);
+    } catch (error) {
+      console.error("[DraftRecovery] Failed to discard draft:", error);
+    }
+
+    setState({ isOpen: false, draft: null, diff: null });
+  }, [state.draft]);
+
+  return {
+    // Recovery popup props
+    isRecoveryOpen: state.isOpen,
+    savedAt: state.draft?.savedAt ?? 0,
+    nodeCount: state.draft?.nodes.length ?? 0,
+    edgeCount: state.draft?.edges.length ?? 0,
+    diff: state.diff,
+    loadDraft,
+    discardDraft,
+  };
+}

autogpt_platform/frontend/src/app/(platform)/build/components/FlowEditor/Flow/useFlow.ts

@@ -21,6 +21,7 @@ import { AgentExecutionStatus } from "@/app/api/__generated__/models/agentExecut
 export const useFlow = () => {
   const [isLocked, setIsLocked] = useState(false);
   const [hasAutoFramed, setHasAutoFramed] = useState(false);
+  const [isInitialLoadComplete, setIsInitialLoadComplete] = useState(false);
   const addNodes = useNodeStore(useShallow((state) => state.addNodes));
   const addLinks = useEdgeStore(useShallow((state) => state.addLinks));
   const updateNodeStatus = useNodeStore(
@@ -120,6 +121,14 @@ export const useFlow = () => {
     if (customNodes.length > 0) {
       useNodeStore.getState().setNodes([]);
       addNodes(customNodes);
+
+      // Sync hardcoded values with handle IDs.
+      // If a key–value field has a key without a value, the backend omits it from hardcoded values.
+      // But if a handleId exists for that key, it causes inconsistency.
+      // This ensures hardcoded values stay in sync with handle IDs.
+      customNodes.forEach((node) => {
+        useNodeStore.getState().syncHardcodedValuesWithHandleIds(node.id);
+      });
     }
   }, [customNodes, addNodes]);
 
@@ -174,11 +183,23 @@ export const useFlow = () => {
     if (customNodes.length > 0 && graph?.links) {
       const timer = setTimeout(() => {
         useHistoryStore.getState().initializeHistory();
+        // Mark initial load as complete after history is initialized
+        setIsInitialLoadComplete(true);
       }, 100);
       return () => clearTimeout(timer);
     }
   }, [customNodes, graph?.links]);
 
+  // Also mark as complete for new flows (no flowID) after a short delay
+  useEffect(() => {
+    if (!flowID && !isGraphLoading && !isBlocksLoading) {
+      const timer = setTimeout(() => {
+        setIsInitialLoadComplete(true);
+      }, 200);
+      return () => clearTimeout(timer);
+    }
+  }, [flowID, isGraphLoading, isBlocksLoading]);
+
   useEffect(() => {
     return () => {
       useNodeStore.getState().setNodes([]);
@@ -217,6 +238,7 @@ export const useFlow = () => {
 
   useEffect(() => {
     setHasAutoFramed(false);
+    setIsInitialLoadComplete(false);
   }, [flowID, flowVersion]);
 
   // Drag and drop block from block menu
@@ -253,6 +275,7 @@ export const useFlow = () => {
 
   return {
     isFlowContentLoading: isGraphLoading || isBlocksLoading,
+    isInitialLoadComplete,
     onDragOver,
     onDrop,
     isLocked,

autogpt_platform/frontend/src/app/(platform)/build/components/FlowEditor/edges/useCustomEdge.ts

@@ -1,12 +1,17 @@
-import { Connection as RFConnection, EdgeChange } from "@xyflow/react";
+import {
+  Connection as RFConnection,
+  EdgeChange,
+  applyEdgeChanges,
+} from "@xyflow/react";
 import { useEdgeStore } from "@/app/(platform)/build/stores/edgeStore";
 import { useCallback } from "react";
 import { useNodeStore } from "../../../stores/nodeStore";
+import { CustomEdge } from "./CustomEdge";
 
 export const useCustomEdge = () => {
   const edges = useEdgeStore((s) => s.edges);
   const addEdge = useEdgeStore((s) => s.addEdge);
-  const removeEdge = useEdgeStore((s) => s.removeEdge);
+  const setEdges = useEdgeStore((s) => s.setEdges);
 
   const onConnect = useCallback(
     (conn: RFConnection) => {
@@ -45,14 +50,10 @@ export const useCustomEdge = () => {
   );
 
   const onEdgesChange = useCallback(
-    (changes: EdgeChange[]) => {
-      changes.forEach((change) => {
-        if (change.type === "remove") {
-          removeEdge(change.id);
-        }
-      });
+    (changes: EdgeChange<CustomEdge>[]) => {
+      setEdges(applyEdgeChanges(changes, edges));
     },
-    [removeEdge],
+    [edges, setEdges],
   );
 
   return { edges, onConnect, onEdgesChange };

autogpt_platform/frontend/src/app/(platform)/build/components/FlowEditor/handlers/NodeHandle.tsx

@@ -1,26 +1,32 @@
 import { CircleIcon } from "@phosphor-icons/react";
 import { Handle, Position } from "@xyflow/react";
+import { useEdgeStore } from "../../../stores/edgeStore";
+import { cleanUpHandleId } from "@/components/renderers/InputRenderer/helpers";
+import { cn } from "@/lib/utils";
 
-const NodeHandle = ({
+const InputNodeHandle = ({
   handleId,
-  isConnected,
-  side,
+  nodeId,
 }: {
   handleId: string;
-  isConnected: boolean;
-  side: "left" | "right";
+  nodeId: string;
 }) => {
+  const cleanedHandleId = cleanUpHandleId(handleId);
+  const isInputConnected = useEdgeStore((state) =>
+    state.isInputConnected(nodeId ?? "", cleanedHandleId),
+  );
+
   return (
     <Handle
-      type={side === "left" ? "target" : "source"}
-      position={side === "left" ? Position.Left : Position.Right}
-      id={handleId}
-      className={side === "left" ? "-ml-4 mr-2" : "-mr-2 ml-2"}
+      type={"target"}
+      position={Position.Left}
+      id={cleanedHandleId}
+      className={"-ml-6 mr-2"}
     >
       <div className="pointer-events-none">
         <CircleIcon
           size={16}
-          weight={isConnected ? "fill" : "duotone"}
+          weight={isInputConnected ? "fill" : "duotone"}
           className={"text-gray-400 opacity-100"}
         />
       </div>
@@ -28,4 +34,35 @@ const NodeHandle = ({
   );
 };
 
-export default NodeHandle;
+const OutputNodeHandle = ({
+  field_name,
+  nodeId,
+  hexColor,
+}: {
+  field_name: string;
+  nodeId: string;
+  hexColor: string;
+}) => {
+  const isOutputConnected = useEdgeStore((state) =>
+    state.isOutputConnected(nodeId, field_name),
+  );
+  return (
+    <Handle
+      type={"source"}
+      position={Position.Right}
+      id={field_name}
+      className={"-mr-2 ml-2"}
+    >
+      <div className="pointer-events-none">
+        <CircleIcon
+          size={16}
+          weight={"duotone"}
+          color={isOutputConnected ? hexColor : "gray"}
+          className={cn("text-gray-400 opacity-100")}
+        />
+      </div>
+    </Handle>
+  );
+};
+
+export { InputNodeHandle, OutputNodeHandle };

autogpt_platform/frontend/src/app/(platform)/build/components/FlowEditor/handlers/helpers.ts

@@ -1,31 +1,4 @@
-/**
- * Handle ID Types for different input structures
- *
- * Examples:
- * SIMPLE: "message"
- * NESTED: "config.api_key"
- * ARRAY: "items_$_0", "items_$_1"
- * KEY_VALUE: "headers_#_Authorization", "params_#_limit"
- *
- * Note: All handle IDs are sanitized to remove spaces and special characters.
- * Spaces become underscores, and special characters are removed.
- * Example: "user name" becomes "user_name", "email@domain.com" becomes "emaildomaincom"
- */
-export enum HandleIdType {
-  SIMPLE = "SIMPLE",
-  NESTED = "NESTED",
-  ARRAY = "ARRAY",
-  KEY_VALUE = "KEY_VALUE",
-}
-
-const fromRjsfId = (id: string): string => {
-  if (!id) return "";
-  const parts = id.split("_");
-  const filtered = parts.filter(
-    (p) => p !== "root" && p !== "properties" && p.length > 0,
-  );
-  return filtered.join("_") || "";
-};
+// Here we are handling single level of nesting, if need more in future then i will update it
 
 const sanitizeForHandleId = (str: string): string => {
   if (!str) return "";
@@ -38,51 +11,53 @@ const sanitizeForHandleId = (str: string): string => {
     .replace(/^_|_$/g, ""); // Remove leading/trailing underscores
 };
 
-export const generateHandleId = (
+const cleanTitleId = (id: string): string => {
+  if (!id) return "";
+
+  if (id.endsWith("_title")) {
+    id = id.slice(0, -6);
+  }
+  const parts = id.split("_");
+  const filtered = parts.filter(
+    (p) => p !== "root" && p !== "properties" && p.length > 0,
+  );
+  const filtered_id = filtered.join("_") || "";
+  return filtered_id;
+};
+
+export const generateHandleIdFromTitleId = (
   fieldKey: string,
-  nestedValues: string[] = [],
-  type: HandleIdType = HandleIdType.SIMPLE,
+  {
+    isObjectProperty,
+    isAdditionalProperty,
+    isArrayItem,
+  }: {
+    isArrayItem?: boolean;
+    isObjectProperty?: boolean;
+    isAdditionalProperty?: boolean;
+  } = {
+    isArrayItem: false,
+    isObjectProperty: false,
+    isAdditionalProperty: false,
+  },
 ): string => {
   if (!fieldKey) return "";
 
-  fieldKey = fromRjsfId(fieldKey);
-  fieldKey = sanitizeForHandleId(fieldKey);
+  const filteredKey = cleanTitleId(fieldKey);
+  if (isAdditionalProperty || isArrayItem) {
+    return filteredKey;
+  }
+  const cleanedKey = sanitizeForHandleId(filteredKey);
 
-  if (type === HandleIdType.SIMPLE || nestedValues.length === 0) {
-    return fieldKey;
+  if (isObjectProperty) {
+    // "config_api_key" -> "config.api_key"
+    const parts = cleanedKey.split("_");
+    if (parts.length >= 2) {
+      const baseName = parts[0];
+      const propertyName = parts.slice(1).join("_");
+      return `${baseName}.${propertyName}`;
+    }
   }
 
-  const sanitizedNestedValues = nestedValues.map((value) =>
-    sanitizeForHandleId(value),
-  );
-
-  switch (type) {
-    case HandleIdType.NESTED:
-      return [fieldKey, ...sanitizedNestedValues].join(".");
-
-    case HandleIdType.ARRAY:
-      return [fieldKey, ...sanitizedNestedValues].join("_$_");
-
-    case HandleIdType.KEY_VALUE:
-      return [fieldKey, ...sanitizedNestedValues].join("_#_");
-
-    default:
-      return fieldKey;
-  }
-};
-
-export const parseKeyValueHandleId = (
-  handleId: string,
-  type: HandleIdType,
-): string => {
-  if (type === HandleIdType.KEY_VALUE) {
-    return handleId.split("_#_")[1];
-  } else if (type === HandleIdType.ARRAY) {
-    return handleId.split("_$_")[1];
-  } else if (type === HandleIdType.NESTED) {
-    return handleId.split(".")[1];
-  } else if (type === HandleIdType.SIMPLE) {
-    return handleId.split("_")[1];
-  }
-  return "";
+  return cleanedKey;
 };

autogpt_platform/frontend/src/app/(platform)/build/components/FlowEditor/nodes/CustomNode/CustomNode.tsx

@@ -1,24 +1,25 @@
-import React from "react";
-import { Node as XYNode, NodeProps } from "@xyflow/react";
-import { RJSFSchema } from "@rjsf/utils";
-import { BlockUIType } from "../../../types";
-import { StickyNoteBlock } from "./components/StickyNoteBlock";
-import { BlockInfoCategoriesItem } from "@/app/api/__generated__/models/blockInfoCategoriesItem";
-import { BlockCost } from "@/app/api/__generated__/models/blockCost";
 import { AgentExecutionStatus } from "@/app/api/__generated__/models/agentExecutionStatus";
+import { BlockCost } from "@/app/api/__generated__/models/blockCost";
+import { BlockInfoCategoriesItem } from "@/app/api/__generated__/models/blockInfoCategoriesItem";
 import { NodeExecutionResult } from "@/app/api/__generated__/models/nodeExecutionResult";
-import { NodeContainer } from "./components/NodeContainer";
-import { NodeHeader } from "./components/NodeHeader";
-import { FormCreator } from "../FormCreator";
-import { preprocessInputSchema } from "@/components/renderers/input-renderer/utils/input-schema-pre-processor";
-import { OutputHandler } from "../OutputHandler";
-import { NodeAdvancedToggle } from "./components/NodeAdvancedToggle";
-import { NodeDataRenderer } from "./components/NodeOutput/NodeOutput";
-import { NodeExecutionBadge } from "./components/NodeExecutionBadge";
-import { cn } from "@/lib/utils";
-import { WebhookDisclaimer } from "./components/WebhookDisclaimer";
-import { AyrshareConnectButton } from "./components/AyrshareConnectButton";
 import { NodeModelMetadata } from "@/app/api/__generated__/models/nodeModelMetadata";
+import { preprocessInputSchema } from "@/components/renderers/InputRenderer/utils/input-schema-pre-processor";
+import { cn } from "@/lib/utils";
+import { RJSFSchema } from "@rjsf/utils";
+import { NodeProps, Node as XYNode } from "@xyflow/react";
+import React from "react";
+import { BlockUIType } from "../../../types";
+import { FormCreator } from "../FormCreator";
+import { OutputHandler } from "../OutputHandler";
+import { AyrshareConnectButton } from "./components/AyrshareConnectButton";
+import { NodeAdvancedToggle } from "./components/NodeAdvancedToggle";
+import { NodeContainer } from "./components/NodeContainer";
+import { NodeExecutionBadge } from "./components/NodeExecutionBadge";
+import { NodeHeader } from "./components/NodeHeader";
+import { NodeDataRenderer } from "./components/NodeOutput/NodeOutput";
+import { NodeRightClickMenu } from "./components/NodeRightClickMenu";
+import { StickyNoteBlock } from "./components/StickyNoteBlock";
+import { WebhookDisclaimer } from "./components/WebhookDisclaimer";
 
 export type CustomNodeData = {
   hardcodedValues: {
@@ -88,7 +89,7 @@ export const CustomNode: React.FC<NodeProps<CustomNode>> = React.memo(
 
     // Currently all blockTypes design are similar - that's why i am using the same component for all of them
     // If in future - if we need some drastic change in some blockTypes design - we can create separate components for them
-    return (
+    const node = (
       <NodeContainer selected={selected} nodeId={nodeId} hasErrors={hasErrors}>
         <div className="rounded-xlarge bg-white">
           <NodeHeader data={data} nodeId={nodeId} />
@@ -99,7 +100,7 @@ export const CustomNode: React.FC<NodeProps<CustomNode>> = React.memo(
             nodeId={nodeId}
             uiType={data.uiType}
             className={cn(
-              "bg-white pr-6",
+              "bg-white px-4",
               isWebhook && "pointer-events-none opacity-50",
             )}
             showHandles={showHandles}
@@ -117,6 +118,15 @@ export const CustomNode: React.FC<NodeProps<CustomNode>> = React.memo(
         <NodeExecutionBadge nodeId={nodeId} />
       </NodeContainer>
     );
+
+    return (
+      <NodeRightClickMenu
+        nodeId={nodeId}
+        subGraphID={data.hardcodedValues?.graph_id}
+      >
+        {node}
+      </NodeRightClickMenu>
+    );
   },
 );
 

autogpt_platform/frontend/src/app/(platform)/build/components/FlowEditor/nodes/CustomNode/components/NodeAdvancedToggle.tsx

@@ -8,7 +8,7 @@ export const NodeAdvancedToggle = ({ nodeId }: { nodeId: string }) => {
   );
   const setShowAdvanced = useNodeStore((state) => state.setShowAdvanced);
   return (
-    <div className="flex items-center justify-between gap-2 rounded-b-xlarge border-t border-slate-200/50 bg-white px-5 py-3.5">
+    <div className="flex items-center justify-between gap-2 rounded-b-xlarge border-t border-zinc-200 bg-white px-5 py-3.5">
       <Text variant="body" className="font-medium text-slate-700">
         Advanced
       </Text>

autogpt_platform/frontend/src/app/(platform)/build/components/FlowEditor/nodes/CustomNode/components/NodeContainer.tsx

@@ -22,7 +22,7 @@ export const NodeContainer = ({
   return (
     <div
       className={cn(
-        "z-12 max-w-[370px] rounded-xlarge ring-1 ring-slate-200/60",
+        "z-12 w-[350px] rounded-xlarge ring-1 ring-slate-200/60",
         selected && "shadow-lg ring-2 ring-slate-200",
         status && nodeStyleBasedOnStatus[status],
         hasErrors ? nodeStyleBasedOnStatus[AgentExecutionStatus.FAILED] : "",

autogpt_platform/frontend/src/app/(platform)/build/components/FlowEditor/nodes/CustomNode/components/NodeContextMenu.tsx

@@ -1,26 +1,31 @@
-import { Separator } from "@/components/__legacy__/ui/separator";
+import { useCopyPasteStore } from "@/app/(platform)/build/stores/copyPasteStore";
+import { useNodeStore } from "@/app/(platform)/build/stores/nodeStore";
 import {
   DropdownMenu,
-  DropdownMenuContent,
-  DropdownMenuItem,
   DropdownMenuTrigger,
 } from "@/components/molecules/DropdownMenu/DropdownMenu";
-import { DotsThreeOutlineVerticalIcon } from "@phosphor-icons/react";
-import { Copy, Trash2, ExternalLink } from "lucide-react";
-import { useNodeStore } from "@/app/(platform)/build/stores/nodeStore";
-import { useCopyPasteStore } from "@/app/(platform)/build/stores/copyPasteStore";
+import {
+  SecondaryDropdownMenuContent,
+  SecondaryDropdownMenuItem,
+  SecondaryDropdownMenuSeparator,
+} from "@/components/molecules/SecondaryMenu/SecondaryMenu";
+import {
+  ArrowSquareOutIcon,
+  CopyIcon,
+  DotsThreeOutlineVerticalIcon,
+  TrashIcon,
+} from "@phosphor-icons/react";
 import { useReactFlow } from "@xyflow/react";
 
-export const NodeContextMenu = ({
-  nodeId,
-  subGraphID,
-}: {
+type Props = {
   nodeId: string;
   subGraphID?: string;
-}) => {
+};
+
+export const NodeContextMenu = ({ nodeId, subGraphID }: Props) => {
   const { deleteElements } = useReactFlow();
 
-  const handleCopy = () => {
+  function handleCopy() {
     useNodeStore.setState((state) => ({
       nodes: state.nodes.map((node) => ({
         ...node,
@@ -30,47 +35,47 @@ export const NodeContextMenu = ({
 
     useCopyPasteStore.getState().copySelectedNodes();
     useCopyPasteStore.getState().pasteNodes();
-  };
+  }
 
-  const handleDelete = () => {
+  function handleDelete() {
     deleteElements({ nodes: [{ id: nodeId }] });
-  };
+  }
 
   return (
     <DropdownMenu>
       <DropdownMenuTrigger className="py-2">
         <DotsThreeOutlineVerticalIcon size={16} weight="fill" />
       </DropdownMenuTrigger>
-      <DropdownMenuContent
-        side="right"
-        align="start"
-        className="rounded-xlarge"
-      >
-        <DropdownMenuItem onClick={handleCopy} className="hover:rounded-xlarge">
-          <Copy className="mr-2 h-4 w-4" />
-          Copy Node
-        </DropdownMenuItem>
+      <SecondaryDropdownMenuContent side="right" align="start">
+        <SecondaryDropdownMenuItem onClick={handleCopy}>
+          <CopyIcon size={20} className="mr-2 dark:text-gray-100" />
+          <span className="dark:text-gray-100">Copy</span>
+        </SecondaryDropdownMenuItem>
+        <SecondaryDropdownMenuSeparator />
 
         {subGraphID && (
-          <DropdownMenuItem
-            onClick={() => window.open(`/build?flowID=${subGraphID}`)}
-            className="hover:rounded-xlarge"
-          >
-            <ExternalLink className="mr-2 h-4 w-4" />
-            Open Agent
-          </DropdownMenuItem>
+          <>
+            <SecondaryDropdownMenuItem
+              onClick={() => window.open(`/build?flowID=${subGraphID}`)}
+            >
+              <ArrowSquareOutIcon
+                size={20}
+                className="mr-2 dark:text-gray-100"
+              />
+              <span className="dark:text-gray-100">Open agent</span>
+            </SecondaryDropdownMenuItem>
+            <SecondaryDropdownMenuSeparator />
+          </>
         )}
 
-        <Separator className="my-2" />
-
-        <DropdownMenuItem
-          onClick={handleDelete}
-          className="text-red-600 hover:rounded-xlarge"
-        >
-          <Trash2 className="mr-2 h-4 w-4" />
-          Delete
-        </DropdownMenuItem>
-      </DropdownMenuContent>
+        <SecondaryDropdownMenuItem variant="destructive" onClick={handleDelete}>
+          <TrashIcon
+            size={20}
+            className="mr-2 text-red-500 dark:text-red-400"
+          />
+          <span className="dark:text-red-400">Delete</span>
+        </SecondaryDropdownMenuItem>
+      </SecondaryDropdownMenuContent>
     </DropdownMenu>
   );
 };

autogpt_platform/frontend/src/app/(platform)/build/components/FlowEditor/nodes/CustomNode/components/NodeHeader.tsx

@@ -1,29 +1,30 @@
-import { Text } from "@/components/atoms/Text/Text";
-import { beautifyString, cn } from "@/lib/utils";
-import { NodeCost } from "./NodeCost";
-import { NodeBadges } from "./NodeBadges";
-import { NodeContextMenu } from "./NodeContextMenu";
-import { CustomNodeData } from "../CustomNode";
 import { useNodeStore } from "@/app/(platform)/build/stores/nodeStore";
-import { useState } from "react";
+import { Text } from "@/components/atoms/Text/Text";
 import {
   Tooltip,
   TooltipContent,
   TooltipProvider,
   TooltipTrigger,
 } from "@/components/atoms/Tooltip/BaseTooltip";
+import { beautifyString, cn } from "@/lib/utils";
+import { useState } from "react";
+import { CustomNodeData } from "../CustomNode";
+import { NodeBadges } from "./NodeBadges";
+import { NodeContextMenu } from "./NodeContextMenu";
+import { NodeCost } from "./NodeCost";
 
-export const NodeHeader = ({
-  data,
-  nodeId,
-}: {
+type Props = {
   data: CustomNodeData;
   nodeId: string;
-}) => {
+};
+
+export const NodeHeader = ({ data, nodeId }: Props) => {
   const updateNodeData = useNodeStore((state) => state.updateNodeData);
   const title = (data.metadata?.customized_name as string) || data.title;
   const [isEditingTitle, setIsEditingTitle] = useState(false);
-  const [editedTitle, setEditedTitle] = useState(title);
+  const [editedTitle, setEditedTitle] = useState(
+    beautifyString(title).replace("Block", "").trim(),
+  );
 
   const handleTitleEdit = () => {
     updateNodeData(nodeId, {
@@ -41,7 +42,7 @@ export const NodeHeader = ({
   };
 
   return (
-    <div className="flex h-auto flex-col gap-1 rounded-xlarge border-b border-slate-200/50 bg-gradient-to-r from-slate-50/80 to-white/90 px-4 py-4 pt-3">
+    <div className="flex h-auto flex-col gap-1 rounded-xlarge border-b border-zinc-200 bg-gradient-to-r from-slate-50/80 to-white/90 px-4 py-4 pt-3">
       {/* Title row with context menu */}
       <div className="flex items-start justify-between gap-2">
         <div className="flex min-w-0 flex-1 items-center gap-2">
@@ -67,13 +68,16 @@ export const NodeHeader = ({
                 <Tooltip>
                   <TooltipTrigger asChild>
                     <div>
-                      <Text variant="large-semibold" className="line-clamp-1">
-                        {beautifyString(title)}
+                      <Text
+                        variant="large-semibold"
+                        className="line-clamp-1 hover:cursor-text"
+                      >
+                        {beautifyString(title).replace("Block", "").trim()}
                       </Text>
                     </div>
                   </TooltipTrigger>
                   <TooltipContent>
-                    <p>{beautifyString(title)}</p>
+                    <p>{beautifyString(title).replace("Block", "").trim()}</p>
                   </TooltipContent>
                 </Tooltip>
               </TooltipProvider>

autogpt_platform/frontend/src/app/(platform)/build/components/FlowEditor/nodes/CustomNode/components/NodeOutput/NodeOutput.tsx

@@ -23,7 +23,7 @@ export const NodeDataRenderer = ({ nodeId }: { nodeId: string }) => {
   }
 
   return (
-    <div className="flex flex-col gap-3 rounded-b-xl border-t border-slate-200/50 px-4 py-4">
+    <div className="flex flex-col gap-3 rounded-b-xl border-t border-zinc-200 px-4 py-4">
       <div className="flex items-center justify-between">
         <Text variant="body-medium" className="!font-semibold text-slate-700">
           Node Output

autogpt_platform/frontend/src/app/(platform)/build/components/FlowEditor/nodes/CustomNode/components/NodeOutput/components/NodeDataViewer/NodeDataViewer.tsx

@@ -151,7 +151,7 @@ export const NodeDataViewer: FC<NodeDataViewerProps> = ({
         </div>
 
         <div className="flex justify-end pt-4">
-          {outputItems.length > 0 && (
+          {outputItems.length > 1 && (
             <OutputActions
               items={outputItems.map((item) => ({
                 value: item.value,

autogpt_platform/frontend/src/app/(platform)/build/components/FlowEditor/nodes/CustomNode/components/NodeRightClickMenu.tsx

@@ -0,0 +1,104 @@
+import { useCopyPasteStore } from "@/app/(platform)/build/stores/copyPasteStore";
+import { useNodeStore } from "@/app/(platform)/build/stores/nodeStore";
+import {
+  SecondaryMenuContent,
+  SecondaryMenuItem,
+  SecondaryMenuSeparator,
+} from "@/components/molecules/SecondaryMenu/SecondaryMenu";
+import { ArrowSquareOutIcon, CopyIcon, TrashIcon } from "@phosphor-icons/react";
+import * as ContextMenu from "@radix-ui/react-context-menu";
+import { useReactFlow } from "@xyflow/react";
+import { useEffect, useRef } from "react";
+import { CustomNode } from "../CustomNode";
+
+type Props = {
+  nodeId: string;
+  subGraphID?: string;
+  children: React.ReactNode;
+};
+
+const DOUBLE_CLICK_TIMEOUT = 300;
+
+export function NodeRightClickMenu({ nodeId, subGraphID, children }: Props) {
+  const { deleteElements } = useReactFlow<CustomNode>();
+  const lastRightClickTime = useRef<number>(0);
+  const containerRef = useRef<HTMLDivElement>(null);
+
+  function copyNode() {
+    useNodeStore.setState((state) => ({
+      nodes: state.nodes.map((node) => ({
+        ...node,
+        selected: node.id === nodeId,
+      })),
+    }));
+
+    useCopyPasteStore.getState().copySelectedNodes();
+    useCopyPasteStore.getState().pasteNodes();
+  }
+
+  function deleteNode() {
+    deleteElements({ nodes: [{ id: nodeId }] });
+  }
+
+  useEffect(() => {
+    const container = containerRef.current;
+    if (!container) return;
+
+    function handleContextMenu(e: MouseEvent) {
+      const now = Date.now();
+      const timeSinceLastClick = now - lastRightClickTime.current;
+
+      if (timeSinceLastClick < DOUBLE_CLICK_TIMEOUT) {
+        e.stopImmediatePropagation();
+        lastRightClickTime.current = 0;
+        return;
+      }
+
+      lastRightClickTime.current = now;
+    }
+
+    container.addEventListener("contextmenu", handleContextMenu, true);
+
+    return () => {
+      container.removeEventListener("contextmenu", handleContextMenu, true);
+    };
+  }, []);
+
+  return (
+    <ContextMenu.Root>
+      <ContextMenu.Trigger asChild>
+        <div ref={containerRef}>{children}</div>
+      </ContextMenu.Trigger>
+      <SecondaryMenuContent>
+        <SecondaryMenuItem onSelect={copyNode}>
+          <CopyIcon size={20} className="mr-2 dark:text-gray-100" />
+          <span className="dark:text-gray-100">Copy</span>
+        </SecondaryMenuItem>
+        <SecondaryMenuSeparator />
+
+        {subGraphID && (
+          <>
+            <SecondaryMenuItem
+              onClick={() => window.open(`/build?flowID=${subGraphID}`)}
+            >
+              <ArrowSquareOutIcon
+                size={20}
+                className="mr-2 dark:text-gray-100"
+              />
+              <span className="dark:text-gray-100">Open agent</span>
+            </SecondaryMenuItem>
+            <SecondaryMenuSeparator />
+          </>
+        )}
+
+        <SecondaryMenuItem variant="destructive" onSelect={deleteNode}>
+          <TrashIcon
+            size={20}
+            className="mr-2 text-red-500 dark:text-red-400"
+          />
+          <span className="dark:text-red-400">Delete</span>
+        </SecondaryMenuItem>
+      </SecondaryMenuContent>
+    </ContextMenu.Root>
+  );
+}

autogpt_platform/frontend/src/app/(platform)/build/components/FlowEditor/nodes/CustomNode/components/StickyNoteBlock.tsx

@@ -1,6 +1,6 @@
 import { useMemo } from "react";
 import { FormCreator } from "../../FormCreator";
-import { preprocessInputSchema } from "@/components/renderers/input-renderer/utils/input-schema-pre-processor";
+import { preprocessInputSchema } from "@/components/renderers/InputRenderer/utils/input-schema-pre-processor";
 import { CustomNodeData } from "../CustomNode";
 import { Text } from "@/components/atoms/Text/Text";
 import { cn } from "@/lib/utils";

autogpt_platform/frontend/src/app/(platform)/build/components/FlowEditor/nodes/FormCreator.tsx

@@ -3,7 +3,7 @@ import React from "react";
 import { uiSchema } from "./uiSchema";
 import { useNodeStore } from "../../../stores/nodeStore";
 import { BlockUIType } from "../../types";
-import { FormRenderer } from "@/components/renderers/input-renderer/FormRenderer";
+import { FormRenderer } from "@/components/renderers/InputRenderer/FormRenderer";
 
 export const FormCreator = React.memo(
   ({

autogpt_platform/frontend/src/app/(platform)/build/components/FlowEditor/nodes/OutputHandler.tsx

@@ -4,7 +4,7 @@ import { CaretDownIcon, InfoIcon } from "@phosphor-icons/react";
 import { RJSFSchema } from "@rjsf/utils";
 import { useState } from "react";
 
-import NodeHandle from "../handlers/NodeHandle";
+import { OutputNodeHandle } from "../handlers/NodeHandle";
 import {
   Tooltip,
   TooltipContent,
@@ -13,7 +13,6 @@ import {
 } from "@/components/atoms/Tooltip/BaseTooltip";
 import { useEdgeStore } from "@/app/(platform)/build/stores/edgeStore";
 import { getTypeDisplayInfo } from "./helpers";
-import { generateHandleId } from "../handlers/helpers";
 import { BlockUIType } from "../../types";
 
 export const OutputHandler = ({
@@ -29,8 +28,73 @@ export const OutputHandler = ({
   const properties = outputSchema?.properties || {};
   const [isOutputVisible, setIsOutputVisible] = useState(true);
 
+  const showHandles = uiType !== BlockUIType.OUTPUT;
+
+  const renderOutputHandles = (
+    schema: RJSFSchema,
+    keyPrefix: string = "",
+    titlePrefix: string = "",
+  ): React.ReactNode[] => {
+    return Object.entries(schema).map(
+      ([key, fieldSchema]: [string, RJSFSchema]) => {
+        const fullKey = keyPrefix ? `${keyPrefix}_#_${key}` : key;
+        const fieldTitle = titlePrefix + (fieldSchema?.title || key);
+
+        const isConnected = isOutputConnected(nodeId, fullKey);
+        const shouldShow = isConnected || isOutputVisible;
+        const { displayType, colorClass, hexColor } =
+          getTypeDisplayInfo(fieldSchema);
+
+        return shouldShow ? (
+          <div key={fullKey} className="flex flex-col items-end gap-2">
+            <div className="relative flex items-center gap-2">
+              {fieldSchema?.description && (
+                <TooltipProvider>
+                  <Tooltip>
+                    <TooltipTrigger asChild>
+                      <span
+                        style={{ marginLeft: 6, cursor: "pointer" }}
+                        aria-label="info"
+                        tabIndex={0}
+                      >
+                        <InfoIcon />
+                      </span>
+                    </TooltipTrigger>
+                    <TooltipContent>{fieldSchema?.description}</TooltipContent>
+                  </Tooltip>
+                </TooltipProvider>
+              )}
+              <Text variant="body" className="text-slate-700">
+                {fieldTitle}
+              </Text>
+              <Text variant="small" as="span" className={colorClass}>
+                ({displayType})
+              </Text>
+
+              {showHandles && (
+                <OutputNodeHandle
+                  field_name={fullKey}
+                  nodeId={nodeId}
+                  hexColor={hexColor}
+                />
+              )}
+            </div>
+
+            {/* Recursively render nested properties */}
+            {fieldSchema?.properties &&
+              renderOutputHandles(
+                fieldSchema.properties,
+                fullKey,
+                `${fieldTitle}.`,
+              )}
+          </div>
+        ) : null;
+      },
+    );
+  };
+
   return (
-    <div className="flex flex-col items-end justify-between gap-2 rounded-b-xlarge border-t border-slate-200/50 bg-white py-3.5">
+    <div className="flex flex-col items-end justify-between gap-2 rounded-b-xlarge border-t border-zinc-200 bg-white py-3.5">
       <Button
         variant="ghost"
         className="mr-4 h-fit min-w-0 p-0 hover:border-transparent hover:bg-transparent"
@@ -49,50 +113,9 @@ export const OutputHandler = ({
         </Text>
       </Button>
 
-      {
-        <div className="flex flex-col items-end gap-2">
-          {Object.entries(properties).map(([key, property]: [string, any]) => {
-            const isConnected = isOutputConnected(nodeId, key);
-            const shouldShow = isConnected || isOutputVisible;
-            const { displayType, colorClass } = getTypeDisplayInfo(property);
-
-            return shouldShow ? (
-              <div key={key} className="relative flex items-center gap-2">
-                {property?.description && (
-                  <TooltipProvider>
-                    <Tooltip>
-                      <TooltipTrigger asChild>
-                        <span
-                          style={{ marginLeft: 6, cursor: "pointer" }}
-                          aria-label="info"
-                          tabIndex={0}
-                        >
-                          <InfoIcon />
-                        </span>
-                      </TooltipTrigger>
-                      <TooltipContent>{property?.description}</TooltipContent>
-                    </Tooltip>
-                  </TooltipProvider>
-                )}
-                <Text variant="body" className="text-slate-700">
-                  {property?.title || key}{" "}
-                </Text>
-                <Text variant="small" as="span" className={colorClass}>
-                  ({displayType})
-                </Text>
-
-                <NodeHandle
-                  handleId={
-                    uiType === BlockUIType.AGENT ? key : generateHandleId(key)
-                  }
-                  isConnected={isConnected}
-                  side="right"
-                />
-              </div>
-            ) : null;
-          })}
-        </div>
-      }
+      <div className="flex flex-col items-end gap-2">
+        {renderOutputHandles(properties)}
+      </div>
     </div>
   );
 };

autogpt_platform/frontend/src/app/(platform)/build/components/FlowEditor/nodes/helpers.ts

@@ -89,17 +89,53 @@ export function extractOptions(
 
 // get display type and color for schema types [need for type display next to field name]
 export const getTypeDisplayInfo = (schema: any) => {
+  if (
+    schema?.type === "array" &&
+    "format" in schema &&
+    schema.format === "table"
+  ) {
+    return {
+      displayType: "table",
+      colorClass: "!text-indigo-500",
+      hexColor: "#6366f1",
+    };
+  }
+
   if (schema?.type === "string" && schema?.format) {
     const formatMap: Record<
       string,
-      { displayType: string; colorClass: string }
+      { displayType: string; colorClass: string; hexColor: string }
     > = {
-      file: { displayType: "file", colorClass: "!text-green-500" },
-      date: { displayType: "date", colorClass: "!text-blue-500" },
-      time: { displayType: "time", colorClass: "!text-blue-500" },
-      "date-time": { displayType: "datetime", colorClass: "!text-blue-500" },
-      "long-text": { displayType: "text", colorClass: "!text-green-500" },
-      "short-text": { displayType: "text", colorClass: "!text-green-500" },
+      file: {
+        displayType: "file",
+        colorClass: "!text-green-500",
+        hexColor: "#22c55e",
+      },
+      date: {
+        displayType: "date",
+        colorClass: "!text-blue-500",
+        hexColor: "#3b82f6",
+      },
+      time: {
+        displayType: "time",
+        colorClass: "!text-blue-500",
+        hexColor: "#3b82f6",
+      },
+      "date-time": {
+        displayType: "datetime",
+        colorClass: "!text-blue-500",
+        hexColor: "#3b82f6",
+      },
+      "long-text": {
+        displayType: "text",
+        colorClass: "!text-green-500",
+        hexColor: "#22c55e",
+      },
+      "short-text": {
+        displayType: "text",
+        colorClass: "!text-green-500",
+        hexColor: "#22c55e",
+      },
     };
 
     const formatInfo = formatMap[schema.format];
@@ -131,10 +167,23 @@ export const getTypeDisplayInfo = (schema: any) => {
     any: "!text-gray-500",
   };
 
+  const hexColorMap: Record<string, string> = {
+    string: "#22c55e",
+    number: "#3b82f6",
+    integer: "#3b82f6",
+    boolean: "#eab308",
+    object: "#a855f7",
+    array: "#6366f1",
+    null: "#6b7280",
+    any: "#6b7280",
+  };
+
   const colorClass = colorMap[schema?.type] || "!text-gray-500";
+  const hexColor = hexColorMap[schema?.type] || "#6b7280";
 
   return {
     displayType,
     colorClass,
+    hexColor,
   };
 };

autogpt_platform/frontend/src/app/(platform)/build/components/FlowEditor/nodes/uiSchema.ts

@@ -1,6 +1,6 @@
 export const uiSchema = {
   credentials: {
-    "ui:field": "credentials",
+    "ui:field": "custom/credential_field",
     provider: { "ui:widget": "hidden" },
     type: { "ui:widget": "hidden" },
     id: { "ui:autofocus": true },

autogpt_platform/frontend/src/app/(platform)/build/components/NewControlPanel/ControlPanelButton.tsx

@@ -24,7 +24,7 @@ export const ControlPanelButton: React.FC<Props> = ({
       role={as === "div" ? "button" : undefined}
       disabled={as === "button" ? disabled : undefined}
       className={cn(
-        "flex h-[4.25rem] w-[4.25rem] items-center justify-center whitespace-normal bg-white p-[1.38rem] text-zinc-800 shadow-none hover:cursor-pointer hover:bg-zinc-100 hover:text-zinc-950 focus:ring-0",
+        "flex w-auto items-center justify-center whitespace-normal bg-white px-4 py-4 text-zinc-800 shadow-none hover:cursor-pointer hover:bg-zinc-100 hover:text-zinc-950 focus:ring-0",
         selected &&
           "bg-violet-50 text-violet-700 hover:cursor-default hover:bg-violet-50 hover:text-violet-700 active:bg-violet-50 active:text-violet-700",
         disabled && "cursor-not-allowed opacity-50 hover:cursor-not-allowed",

autogpt_platform/frontend/src/app/(platform)/build/components/NewControlPanel/NewBlockMenu/BlockMenu/BlockMenu.tsx

@@ -1,18 +1,17 @@
-import React from "react";
+import { useControlPanelStore } from "@/app/(platform)/build/stores/controlPanelStore";
 import {
   Popover,
   PopoverContent,
   PopoverTrigger,
 } from "@/components/__legacy__/ui/popover";
-import { BlockMenuContent } from "../BlockMenuContent/BlockMenuContent";
-import { ControlPanelButton } from "../../ControlPanelButton";
-import { LegoIcon } from "@phosphor-icons/react";
-import { useControlPanelStore } from "@/app/(platform)/build/stores/controlPanelStore";
 import {
   Tooltip,
   TooltipContent,
   TooltipTrigger,
 } from "@/components/atoms/Tooltip/BaseTooltip";
+import { LegoIcon } from "@phosphor-icons/react";
+import { ControlPanelButton } from "../../ControlPanelButton";
+import { BlockMenuContent } from "../BlockMenuContent/BlockMenuContent";
 
 export const BlockMenu = () => {
   const { blockMenuOpen, setBlockMenuOpen } = useControlPanelStore();
@@ -28,7 +27,7 @@ export const BlockMenu = () => {
               selected={blockMenuOpen}
               className="rounded-none"
             >
-              <LegoIcon className="h-6 w-6" />
+              <LegoIcon className="size-5" />
             </ControlPanelButton>
           </PopoverTrigger>
         </TooltipTrigger>