feat(backend): Implement node-specific auto-approval using key pattern

- Add auto-approval via special nodeExecId key pattern (auto_approve_{graph_exec_id}_{node_id})
- Create auto-approval records in PendingHumanReview when user approves with auto-approve flag
- Check for existing auto-approval before requiring human review
- Remove node_id parameter from get_or_create_human_review
- Load graph settings properly when resuming execution after review

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

@@ -218,6 +218,7 @@ async def save_agent_to_library(
     library_agents = await library_db.create_library_agent(
         graph=created_graph,
         user_id=user_id,
+        sensitive_action_safe_mode=True,
         create_library_agents_for_sub_graphs=False,
     )
 

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

@@ -33,7 +33,7 @@ from .models import (
     UserReadiness,
 )
 from .utils import (
-    check_user_has_required_credentials,
+    build_missing_credentials_from_graph,
     extract_credentials_from_schema,
     fetch_graph_from_store_slug,
     get_or_create_library_agent,
@@ -237,15 +237,13 @@ class RunAgentTool(BaseTool):
                 # Return credentials needed response with input data info
                 # The UI handles credential setup automatically, so the message
                 # focuses on asking about input data
-                credentials = extract_credentials_from_schema(
+                requirements_creds_dict = build_missing_credentials_from_graph(
-                    graph.credentials_input_schema
+                    graph, None
                 )
-                missing_creds_check = await check_user_has_required_credentials(
+                missing_credentials_dict = build_missing_credentials_from_graph(
-                    user_id, credentials
+                    graph, graph_credentials
                 )
-                missing_credentials_dict = {
+                requirements_creds_list = list(requirements_creds_dict.values())
-                    c.id: c.model_dump() for c in missing_creds_check
-                }
 
                 return SetupRequirementsResponse(
                     message=self._build_inputs_message(graph, MSG_WHAT_VALUES_TO_USE),
@@ -259,7 +257,7 @@ class RunAgentTool(BaseTool):
                             ready_to_run=False,
                         ),
                         requirements={
-                            "credentials": [c.model_dump() for c in credentials],
+                            "credentials": requirements_creds_list,
                             "inputs": self._get_inputs_list(graph.input_schema),
                             "execution_modes": self._get_execution_modes(graph),
                         },

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

@@ -22,6 +22,7 @@ from .models import (
     ToolResponseBase,
     UserReadiness,
 )
+from .utils import build_missing_credentials_from_field_info
 
 logger = logging.getLogger(__name__)
 
@@ -189,7 +190,11 @@ class RunBlockTool(BaseTool):
 
         if missing_credentials:
             # Return setup requirements response with missing credentials
-            missing_creds_dict = {c.id: c.model_dump() for c in missing_credentials}
+            credentials_fields_info = block.input_schema.get_credentials_fields_info()
+            missing_creds_dict = build_missing_credentials_from_field_info(
+                credentials_fields_info, set(matched_credentials.keys())
+            )
+            missing_creds_list = list(missing_creds_dict.values())
 
             return SetupRequirementsResponse(
                 message=(
@@ -206,7 +211,7 @@ class RunBlockTool(BaseTool):
                         ready_to_run=False,
                     ),
                     requirements={
-                        "credentials": [c.model_dump() for c in missing_credentials],
+                        "credentials": missing_creds_list,
                         "inputs": self._get_inputs_list(block),
                         "execution_modes": ["immediate"],
                     },

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

@@ -8,7 +8,7 @@ from backend.api.features.library import model as library_model
 from backend.api.features.store import db as store_db
 from backend.data import graph as graph_db
 from backend.data.graph import GraphModel
-from backend.data.model import CredentialsMetaInput
+from backend.data.model import CredentialsFieldInfo, CredentialsMetaInput
 from backend.integrations.creds_manager import IntegrationCredentialsManager
 from backend.util.exceptions import NotFoundError
 
@@ -89,6 +89,59 @@ def extract_credentials_from_schema(
     return credentials
 
 
+def _serialize_missing_credential(
+    field_key: str, field_info: CredentialsFieldInfo
+) -> dict[str, Any]:
+    """
+    Convert credential field info into a serializable dict that preserves all supported
+    credential types (e.g., api_key + oauth2) so the UI can offer multiple options.
+    """
+    supported_types = sorted(field_info.supported_types)
+    provider = next(iter(field_info.provider), "unknown")
+    scopes = sorted(field_info.required_scopes or [])
+
+    return {
+        "id": field_key,
+        "title": field_key.replace("_", " ").title(),
+        "provider": provider,
+        "provider_name": provider.replace("_", " ").title(),
+        "type": supported_types[0] if supported_types else "api_key",
+        "types": supported_types,
+        "scopes": scopes,
+    }
+
+
+def build_missing_credentials_from_graph(
+    graph: GraphModel, matched_credentials: dict[str, CredentialsMetaInput] | None
+) -> dict[str, Any]:
+    """
+    Build a missing_credentials mapping from a graph's aggregated credentials inputs,
+    preserving all supported credential types for each field.
+    """
+    matched_keys = set(matched_credentials.keys()) if matched_credentials else set()
+    aggregated_fields = graph.aggregate_credentials_inputs()
+
+    return {
+        field_key: _serialize_missing_credential(field_key, field_info)
+        for field_key, (field_info, _node_fields) in aggregated_fields.items()
+        if field_key not in matched_keys
+    }
+
+
+def build_missing_credentials_from_field_info(
+    credential_fields: dict[str, CredentialsFieldInfo],
+    matched_keys: set[str],
+) -> dict[str, Any]:
+    """
+    Build missing_credentials mapping from a simple credentials field info dictionary.
+    """
+    return {
+        field_key: _serialize_missing_credential(field_key, field_info)
+        for field_key, field_info in credential_fields.items()
+        if field_key not in matched_keys
+    }
+
+
 def extract_credentials_as_dict(
     credentials_input_schema: dict[str, Any] | None,
 ) -> dict[str, CredentialsMetaInput]:

autogpt_platform/backend/backend/api/features/executions/review/model.py

@@ -179,6 +179,14 @@ class ReviewRequest(BaseModel):
     reviews: List[ReviewItem] = Field(
         description="All reviews with their approval status, data, and messages"
     )
+    auto_approve_future_actions: bool = Field(
+        default=False,
+        description=(
+            "If true, future reviews from the same blocks (nodes) being approved "
+            "will be automatically approved for the remainder of this execution. "
+            "This only affects the current execution run."
+        ),
+    )
 
     @model_validator(mode="after")
     def validate_review_completeness(self):

autogpt_platform/backend/backend/api/features/executions/review/review_routes_test.py

@@ -490,3 +490,321 @@ def test_process_review_action_invalid_node_exec_id(
     # Should be a 400 Bad Request, not 500 Internal Server Error
     assert response.status_code == 400
     assert "Invalid node execution ID format" in response.json()["detail"]
+
+
+def test_process_review_action_auto_approve_creates_auto_approval_records(
+    mocker: pytest_mock.MockerFixture,
+    sample_pending_review: PendingHumanReviewModel,
+    test_user_id: str,
+) -> None:
+    """Test that auto_approve_future_actions flag creates auto-approval records"""
+    from backend.data.execution import ExecutionContext, NodeExecutionResult
+    from backend.data.graph import GraphSettings
+
+    # Mock process_all_reviews
+    mock_process_all_reviews = mocker.patch(
+        "backend.api.features.executions.review.routes.process_all_reviews_for_execution"
+    )
+    approved_review = PendingHumanReviewModel(
+        node_exec_id="test_node_123",
+        user_id=test_user_id,
+        graph_exec_id="test_graph_exec_456",
+        graph_id="test_graph_789",
+        graph_version=1,
+        payload={"data": "test payload"},
+        instructions="Please review",
+        editable=True,
+        status=ReviewStatus.APPROVED,
+        review_message="Approved",
+        was_edited=False,
+        processed=False,
+        created_at=FIXED_NOW,
+        updated_at=FIXED_NOW,
+        reviewed_at=FIXED_NOW,
+    )
+    mock_process_all_reviews.return_value = {"test_node_123": approved_review}
+
+    # Mock get_node_execution to return node_id
+    mock_get_node_execution = mocker.patch(
+        "backend.api.features.executions.review.routes.get_node_execution"
+    )
+    mock_node_exec = mocker.Mock(spec=NodeExecutionResult)
+    mock_node_exec.node_id = "test_node_def_456"
+    mock_get_node_execution.return_value = mock_node_exec
+
+    # Mock create_auto_approval_record
+    mock_create_auto_approval = mocker.patch(
+        "backend.api.features.executions.review.routes.create_auto_approval_record"
+    )
+
+    # Mock has_pending_reviews_for_graph_exec
+    mock_has_pending = mocker.patch(
+        "backend.api.features.executions.review.routes.has_pending_reviews_for_graph_exec"
+    )
+    mock_has_pending.return_value = False
+
+    # Mock get_graph_settings to return custom settings
+    mock_get_settings = mocker.patch(
+        "backend.api.features.executions.review.routes.get_graph_settings"
+    )
+    mock_get_settings.return_value = GraphSettings(
+        human_in_the_loop_safe_mode=True,
+        sensitive_action_safe_mode=True,
+    )
+
+    # Mock add_graph_execution
+    mock_add_execution = mocker.patch(
+        "backend.api.features.executions.review.routes.add_graph_execution"
+    )
+
+    request_data = {
+        "reviews": [
+            {
+                "node_exec_id": "test_node_123",
+                "approved": True,
+                "message": "Approved",
+            }
+        ],
+        "auto_approve_future_actions": True,
+    }
+
+    response = client.post("/api/review/action", json=request_data)
+
+    assert response.status_code == 200
+
+    # Verify process_all_reviews_for_execution was called (without auto_approve param)
+    mock_process_all_reviews.assert_called_once()
+
+    # Verify create_auto_approval_record was called for the approved review
+    mock_create_auto_approval.assert_called_once_with(
+        user_id=test_user_id,
+        graph_exec_id="test_graph_exec_456",
+        graph_id="test_graph_789",
+        graph_version=1,
+        node_id="test_node_def_456",
+        payload={"data": "test payload"},
+    )
+
+    # Verify get_graph_settings was called with correct parameters
+    mock_get_settings.assert_called_once_with(
+        user_id=test_user_id, graph_id="test_graph_789"
+    )
+
+    # Verify add_graph_execution was called with proper ExecutionContext
+    mock_add_execution.assert_called_once()
+    call_kwargs = mock_add_execution.call_args.kwargs
+    execution_context = call_kwargs["execution_context"]
+
+    assert isinstance(execution_context, ExecutionContext)
+    assert execution_context.human_in_the_loop_safe_mode is True
+    assert execution_context.sensitive_action_safe_mode is True
+
+
+def test_process_review_action_without_auto_approve_still_loads_settings(
+    mocker: pytest_mock.MockerFixture,
+    sample_pending_review: PendingHumanReviewModel,
+    test_user_id: str,
+) -> None:
+    """Test that execution context is created with settings even without auto-approve"""
+    from backend.data.execution import ExecutionContext
+    from backend.data.graph import GraphSettings
+
+    # Mock process_all_reviews
+    mock_process_all_reviews = mocker.patch(
+        "backend.api.features.executions.review.routes.process_all_reviews_for_execution"
+    )
+    approved_review = PendingHumanReviewModel(
+        node_exec_id="test_node_123",
+        user_id=test_user_id,
+        graph_exec_id="test_graph_exec_456",
+        graph_id="test_graph_789",
+        graph_version=1,
+        payload={"data": "test payload"},
+        instructions="Please review",
+        editable=True,
+        status=ReviewStatus.APPROVED,
+        review_message="Approved",
+        was_edited=False,
+        processed=False,
+        created_at=FIXED_NOW,
+        updated_at=FIXED_NOW,
+        reviewed_at=FIXED_NOW,
+    )
+    mock_process_all_reviews.return_value = {"test_node_123": approved_review}
+
+    # Mock create_auto_approval_record - should NOT be called when auto_approve is False
+    mock_create_auto_approval = mocker.patch(
+        "backend.api.features.executions.review.routes.create_auto_approval_record"
+    )
+
+    # Mock has_pending_reviews_for_graph_exec
+    mock_has_pending = mocker.patch(
+        "backend.api.features.executions.review.routes.has_pending_reviews_for_graph_exec"
+    )
+    mock_has_pending.return_value = False
+
+    # Mock get_graph_settings with sensitive_action_safe_mode enabled
+    mock_get_settings = mocker.patch(
+        "backend.api.features.executions.review.routes.get_graph_settings"
+    )
+    mock_get_settings.return_value = GraphSettings(
+        human_in_the_loop_safe_mode=False,
+        sensitive_action_safe_mode=True,
+    )
+
+    # Mock add_graph_execution
+    mock_add_execution = mocker.patch(
+        "backend.api.features.executions.review.routes.add_graph_execution"
+    )
+
+    # Request WITHOUT auto_approve_future_actions
+    request_data = {
+        "reviews": [
+            {
+                "node_exec_id": "test_node_123",
+                "approved": True,
+                "message": "Approved",
+            }
+        ],
+        "auto_approve_future_actions": False,
+    }
+
+    response = client.post("/api/review/action", json=request_data)
+
+    assert response.status_code == 200
+
+    # Verify process_all_reviews_for_execution was called
+    mock_process_all_reviews.assert_called_once()
+
+    # Verify create_auto_approval_record was NOT called (auto_approve_future_actions=False)
+    mock_create_auto_approval.assert_not_called()
+
+    # Verify settings were loaded
+    mock_get_settings.assert_called_once()
+
+    # Verify ExecutionContext has proper settings
+    mock_add_execution.assert_called_once()
+    call_kwargs = mock_add_execution.call_args.kwargs
+    execution_context = call_kwargs["execution_context"]
+
+    assert isinstance(execution_context, ExecutionContext)
+    assert execution_context.human_in_the_loop_safe_mode is False
+    assert execution_context.sensitive_action_safe_mode is True
+
+
+def test_process_review_action_auto_approve_only_applies_to_approved_reviews(
+    mocker: pytest_mock.MockerFixture,
+    test_user_id: str,
+) -> None:
+    """Test that auto_approve record is created only for approved reviews"""
+    from backend.data.execution import ExecutionContext, NodeExecutionResult
+    from backend.data.graph import GraphSettings
+
+    # Create two reviews - one approved, one rejected
+    approved_review = PendingHumanReviewModel(
+        node_exec_id="node_exec_approved",
+        user_id=test_user_id,
+        graph_exec_id="test_graph_exec_456",
+        graph_id="test_graph_789",
+        graph_version=1,
+        payload={"data": "approved"},
+        instructions="Review",
+        editable=True,
+        status=ReviewStatus.APPROVED,
+        review_message=None,
+        was_edited=False,
+        processed=False,
+        created_at=FIXED_NOW,
+        updated_at=FIXED_NOW,
+        reviewed_at=FIXED_NOW,
+    )
+    rejected_review = PendingHumanReviewModel(
+        node_exec_id="node_exec_rejected",
+        user_id=test_user_id,
+        graph_exec_id="test_graph_exec_456",
+        graph_id="test_graph_789",
+        graph_version=1,
+        payload={"data": "rejected"},
+        instructions="Review",
+        editable=True,
+        status=ReviewStatus.REJECTED,
+        review_message="Rejected",
+        was_edited=False,
+        processed=False,
+        created_at=FIXED_NOW,
+        updated_at=FIXED_NOW,
+        reviewed_at=FIXED_NOW,
+    )
+
+    # Mock process_all_reviews
+    mock_process_all_reviews = mocker.patch(
+        "backend.api.features.executions.review.routes.process_all_reviews_for_execution"
+    )
+    mock_process_all_reviews.return_value = {
+        "node_exec_approved": approved_review,
+        "node_exec_rejected": rejected_review,
+    }
+
+    # Mock get_node_execution to return node_id (only called for approved review)
+    mock_get_node_execution = mocker.patch(
+        "backend.api.features.executions.review.routes.get_node_execution"
+    )
+    mock_node_exec = mocker.Mock(spec=NodeExecutionResult)
+    mock_node_exec.node_id = "test_node_def_approved"
+    mock_get_node_execution.return_value = mock_node_exec
+
+    # Mock create_auto_approval_record
+    mock_create_auto_approval = mocker.patch(
+        "backend.api.features.executions.review.routes.create_auto_approval_record"
+    )
+
+    # Mock has_pending_reviews_for_graph_exec
+    mock_has_pending = mocker.patch(
+        "backend.api.features.executions.review.routes.has_pending_reviews_for_graph_exec"
+    )
+    mock_has_pending.return_value = False
+
+    # Mock get_graph_settings
+    mock_get_settings = mocker.patch(
+        "backend.api.features.executions.review.routes.get_graph_settings"
+    )
+    mock_get_settings.return_value = GraphSettings()
+
+    # Mock add_graph_execution
+    mock_add_execution = mocker.patch(
+        "backend.api.features.executions.review.routes.add_graph_execution"
+    )
+
+    request_data = {
+        "reviews": [
+            {"node_exec_id": "node_exec_approved", "approved": True},
+            {"node_exec_id": "node_exec_rejected", "approved": False},
+        ],
+        "auto_approve_future_actions": True,
+    }
+
+    response = client.post("/api/review/action", json=request_data)
+
+    assert response.status_code == 200
+
+    # Verify process_all_reviews_for_execution was called
+    mock_process_all_reviews.assert_called_once()
+
+    # Verify create_auto_approval_record was called ONLY for the approved review
+    # (not for the rejected one)
+    mock_create_auto_approval.assert_called_once_with(
+        user_id=test_user_id,
+        graph_exec_id="test_graph_exec_456",
+        graph_id="test_graph_789",
+        graph_version=1,
+        node_id="test_node_def_approved",
+        payload={"data": "approved"},
+    )
+
+    # Verify get_node_execution was called only for approved review
+    mock_get_node_execution.assert_called_once_with("node_exec_approved")
+
+    # Verify ExecutionContext was created (auto-approval is now DB-based)
+    call_kwargs = mock_add_execution.call_args.kwargs
+    execution_context = call_kwargs["execution_context"]
+    assert isinstance(execution_context, ExecutionContext)

autogpt_platform/backend/backend/api/features/executions/review/routes.py

@@ -5,8 +5,14 @@ import autogpt_libs.auth as autogpt_auth_lib
 from fastapi import APIRouter, HTTPException, Query, Security, status
 from prisma.enums import ReviewStatus
 
-from backend.data.execution import get_graph_execution_meta
+from backend.data.execution import (
+    ExecutionContext,
+    get_graph_execution_meta,
+    get_node_execution,
+)
+from backend.data.graph import get_graph_settings
 from backend.data.human_review import (
+    create_auto_approval_record,
     get_pending_reviews_for_execution,
     get_pending_reviews_for_user,
     has_pending_reviews_for_graph_exec,
@@ -128,14 +134,20 @@ async def process_review_action(
         )
 
     # Build review decisions map
+    # When auto_approve_future_actions is true, ignore any edited data
+    # (auto-approved reviews should use original data for consistency)
     review_decisions = {}
     for review in request.reviews:
         review_status = (
             ReviewStatus.APPROVED if review.approved else ReviewStatus.REJECTED
         )
+        # If auto-approving future actions, don't allow data modifications
+        reviewed_data = (
+            None if request.auto_approve_future_actions else review.reviewed_data
+        )
         review_decisions[review.node_exec_id] = (
             review_status,
-            review.reviewed_data,
+            reviewed_data,
             review.message,
         )
 
@@ -145,6 +157,22 @@ async def process_review_action(
         review_decisions=review_decisions,
     )
 
+    # Create auto-approval records for approved reviews if requested
+    if request.auto_approve_future_actions:
+        for node_exec_id, review in updated_reviews.items():
+            if review.status == ReviewStatus.APPROVED:
+                # Look up the node_id from the node execution
+                node_exec = await get_node_execution(node_exec_id)
+                if node_exec:
+                    await create_auto_approval_record(
+                        user_id=user_id,
+                        graph_exec_id=review.graph_exec_id,
+                        graph_id=review.graph_id,
+                        graph_version=review.graph_version,
+                        node_id=node_exec.node_id,
+                        payload=review.payload,
+                    )
+
     # Count results
     approved_count = sum(
         1
@@ -169,10 +197,24 @@ async def process_review_action(
         if not still_has_pending:
             # Resume execution
             try:
+                # Load graph settings to create proper execution context
+                settings = await get_graph_settings(
+                    user_id=user_id, graph_id=first_review.graph_id
+                )
+
+                # Create execution context with settings
+                # Note: auto-approval is now handled via database lookup in
+                # check_auto_approval(), no need to pass auto_approved_node_ids
+                execution_context = ExecutionContext(
+                    human_in_the_loop_safe_mode=settings.human_in_the_loop_safe_mode,
+                    sensitive_action_safe_mode=settings.sensitive_action_safe_mode,
+                )
+
                 await add_graph_execution(
                     graph_id=first_review.graph_id,
                     user_id=user_id,
                     graph_exec_id=graph_exec_id,
+                    execution_context=execution_context,
                 )
                 logger.info(f"Resumed execution {graph_exec_id}")
             except Exception as e:

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

@@ -401,27 +401,11 @@ async def add_generated_agent_image(
     )
 
 
-def _initialize_graph_settings(graph: graph_db.GraphModel) -> GraphSettings:
-    """
-    Initialize GraphSettings based on graph content.
-
-    Args:
-        graph: The graph to analyze
-
-    Returns:
-        GraphSettings with appropriate human_in_the_loop_safe_mode value
-    """
-    if graph.has_human_in_the_loop:
-        # Graph has HITL blocks - set safe mode to True by default
-        return GraphSettings(human_in_the_loop_safe_mode=True)
-    else:
-        # Graph has no HITL blocks - keep None
-        return GraphSettings(human_in_the_loop_safe_mode=None)
-
-
 async def create_library_agent(
     graph: graph_db.GraphModel,
     user_id: str,
+    hitl_safe_mode: bool = True,
+    sensitive_action_safe_mode: bool = False,
     create_library_agents_for_sub_graphs: bool = True,
 ) -> list[library_model.LibraryAgent]:
     """
@@ -430,6 +414,8 @@ async def create_library_agent(
     Args:
         agent: The agent/Graph to add to the library.
         user_id: The user to whom the agent will be added.
+        hitl_safe_mode: Whether HITL blocks require manual review (default True).
+        sensitive_action_safe_mode: Whether sensitive action blocks require review.
         create_library_agents_for_sub_graphs: If True, creates LibraryAgent records for sub-graphs as well.
 
     Returns:
@@ -465,7 +451,11 @@ async def create_library_agent(
                             }
                         },
                         settings=SafeJson(
-                            _initialize_graph_settings(graph_entry).model_dump()
+                            GraphSettings.from_graph(
+                                graph_entry,
+                                hitl_safe_mode=hitl_safe_mode,
+                                sensitive_action_safe_mode=sensitive_action_safe_mode,
+                            ).model_dump()
                         ),
                     ),
                     include=library_agent_include(
@@ -627,33 +617,6 @@ async def update_library_agent(
         raise DatabaseError("Failed to update library agent") from e
 
 
-async def update_library_agent_settings(
-    user_id: str,
-    agent_id: str,
-    settings: GraphSettings,
-) -> library_model.LibraryAgent:
-    """
-    Updates the settings for a specific LibraryAgent.
-
-    Args:
-        user_id: The owner of the LibraryAgent.
-        agent_id: The ID of the LibraryAgent to update.
-        settings: New GraphSettings to apply.
-
-    Returns:
-        The updated LibraryAgent.
-
-    Raises:
-        NotFoundError: If the specified LibraryAgent does not exist.
-        DatabaseError: If there's an error in the update operation.
-    """
-    return await update_library_agent(
-        library_agent_id=agent_id,
-        user_id=user_id,
-        settings=settings,
-    )
-
-
 async def delete_library_agent(
     library_agent_id: str, user_id: str, soft_delete: bool = True
 ) -> None:
@@ -838,7 +801,7 @@ async def add_store_agent_to_library(
                 "isCreatedByUser": False,
                 "useGraphIsActiveVersion": False,
                 "settings": SafeJson(
-                    _initialize_graph_settings(graph_model).model_dump()
+                    GraphSettings.from_graph(graph_model).model_dump()
                 ),
             },
             include=library_agent_include(
@@ -1228,8 +1191,15 @@ async def fork_library_agent(
         )
         new_graph = await on_graph_activate(new_graph, user_id=user_id)
 
-        # Create a library agent for the new graph
+        # Create a library agent for the new graph, preserving safe mode settings
-        return (await create_library_agent(new_graph, user_id))[0]
+        return (
+            await create_library_agent(
+                new_graph,
+                user_id,
+                hitl_safe_mode=original_agent.settings.human_in_the_loop_safe_mode,
+                sensitive_action_safe_mode=original_agent.settings.sensitive_action_safe_mode,
+            )
+        )[0]
     except prisma.errors.PrismaError as e:
         logger.error(f"Database error cloning library agent: {e}")
         raise DatabaseError("Failed to fork library agent") from e

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

@@ -73,6 +73,12 @@ class LibraryAgent(pydantic.BaseModel):
     has_external_trigger: bool = pydantic.Field(
         description="Whether the agent has an external trigger (e.g. webhook) node"
     )
+    has_human_in_the_loop: bool = pydantic.Field(
+        description="Whether the agent has human-in-the-loop blocks"
+    )
+    has_sensitive_action: bool = pydantic.Field(
+        description="Whether the agent has sensitive action blocks"
+    )
     trigger_setup_info: Optional[GraphTriggerInfo] = None
 
     # Indicates whether there's a new output (based on recent runs)
@@ -180,6 +186,8 @@ class LibraryAgent(pydantic.BaseModel):
                 graph.credentials_input_schema if sub_graphs is not None else None
             ),
             has_external_trigger=graph.has_external_trigger,
+            has_human_in_the_loop=graph.has_human_in_the_loop,
+            has_sensitive_action=graph.has_sensitive_action,
             trigger_setup_info=graph.trigger_setup_info,
             new_output=new_output,
             can_access_graph=can_access_graph,

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

@@ -52,6 +52,8 @@ async def test_get_library_agents_success(
                 output_schema={"type": "object", "properties": {}},
                 credentials_input_schema={"type": "object", "properties": {}},
                 has_external_trigger=False,
+                has_human_in_the_loop=False,
+                has_sensitive_action=False,
                 status=library_model.LibraryAgentStatus.COMPLETED,
                 recommended_schedule_cron=None,
                 new_output=False,
@@ -75,6 +77,8 @@ async def test_get_library_agents_success(
                 output_schema={"type": "object", "properties": {}},
                 credentials_input_schema={"type": "object", "properties": {}},
                 has_external_trigger=False,
+                has_human_in_the_loop=False,
+                has_sensitive_action=False,
                 status=library_model.LibraryAgentStatus.COMPLETED,
                 recommended_schedule_cron=None,
                 new_output=False,
@@ -150,6 +154,8 @@ async def test_get_favorite_library_agents_success(
                 output_schema={"type": "object", "properties": {}},
                 credentials_input_schema={"type": "object", "properties": {}},
                 has_external_trigger=False,
+                has_human_in_the_loop=False,
+                has_sensitive_action=False,
                 status=library_model.LibraryAgentStatus.COMPLETED,
                 recommended_schedule_cron=None,
                 new_output=False,
@@ -218,6 +224,8 @@ def test_add_agent_to_library_success(
         output_schema={"type": "object", "properties": {}},
         credentials_input_schema={"type": "object", "properties": {}},
         has_external_trigger=False,
+        has_human_in_the_loop=False,
+        has_sensitive_action=False,
         status=library_model.LibraryAgentStatus.COMPLETED,
         new_output=False,
         can_access_graph=True,

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

@@ -154,6 +154,7 @@ async def store_content_embedding(
 
         # Upsert the embedding
         # WHERE clause in DO UPDATE prevents PostgreSQL 15 bug with NULLS NOT DISTINCT
+        # Use unqualified ::vector - pgvector is in search_path on all environments
         await execute_raw_with_schema(
             """
             INSERT INTO {schema_prefix}"UnifiedContentEmbedding" (
@@ -177,7 +178,6 @@ async def store_content_embedding(
             searchable_text,
             metadata_json,
             client=client,
-            set_public_search_path=True,
         )
 
         logger.info(f"Stored embedding for {content_type}:{content_id}")
@@ -236,7 +236,6 @@ async def get_content_embedding(
             content_type,
             content_id,
             user_id,
-            set_public_search_path=True,
         )
 
         if result and len(result) > 0:
@@ -871,31 +870,45 @@ async def semantic_search(
         # Add content type parameters and build placeholders dynamically
         content_type_start_idx = len(params) + 1
         content_type_placeholders = ", ".join(
-            f'${content_type_start_idx + i}::{{{{schema_prefix}}}}"ContentType"'
+            "$" + str(content_type_start_idx + i) + '::{schema_prefix}"ContentType"'
             for i in range(len(content_types))
         )
         params.extend([ct.value for ct in content_types])
 
-        sql = f"""
+        # Build min_similarity param index before appending
+        min_similarity_idx = len(params) + 1
+        params.append(min_similarity)
+
+        # Use unqualified ::vector and <=> operator - pgvector is in search_path on all environments
+        sql = (
+            """
             SELECT
                 "contentId" as content_id,
                 "contentType" as content_type,
                 "searchableText" as searchable_text,
                 metadata,
-                1 - (embedding <=> '{embedding_str}'::vector) as similarity
+                1 - (embedding <=> '"""
-            FROM {{{{schema_prefix}}}}"UnifiedContentEmbedding"
+            + embedding_str
-            WHERE "contentType" IN ({content_type_placeholders})
+            + """'::vector) as similarity
-            {user_filter}
+            FROM {schema_prefix}"UnifiedContentEmbedding"
-            AND 1 - (embedding <=> '{embedding_str}'::vector) >= ${len(params) + 1}
+            WHERE "contentType" IN ("""
+            + content_type_placeholders
+            + """)
+            """
+            + user_filter
+            + """
+            AND 1 - (embedding <=> '"""
+            + embedding_str
+            + """'::vector) >= $"""
+            + str(min_similarity_idx)
+            + """
             ORDER BY similarity DESC
             LIMIT $1
         """
-        params.append(min_similarity)
+        )
 
         try:
-            results = await query_raw_with_schema(
+            results = await query_raw_with_schema(sql, *params)
-                sql, *params, set_public_search_path=True
-            )
             return [
                 {
                     "content_id": row["content_id"],
@@ -922,31 +935,41 @@ async def semantic_search(
     # Add content type parameters and build placeholders dynamically
     content_type_start_idx = len(params_lexical) + 1
     content_type_placeholders_lexical = ", ".join(
-        f'${content_type_start_idx + i}::{{{{schema_prefix}}}}"ContentType"'
+        "$" + str(content_type_start_idx + i) + '::{schema_prefix}"ContentType"'
         for i in range(len(content_types))
     )
     params_lexical.extend([ct.value for ct in content_types])
 
-    sql_lexical = f"""
+    # Build query param index before appending
+    query_param_idx = len(params_lexical) + 1
+    params_lexical.append(f"%{query}%")
+
+    # Use regular string (not f-string) for template to preserve {schema_prefix} placeholders
+    sql_lexical = (
+        """
         SELECT
             "contentId" as content_id,
             "contentType" as content_type,
             "searchableText" as searchable_text,
             metadata,
             0.0 as similarity
-        FROM {{{{schema_prefix}}}}"UnifiedContentEmbedding"
+        FROM {schema_prefix}"UnifiedContentEmbedding"
-        WHERE "contentType" IN ({content_type_placeholders_lexical})
+        WHERE "contentType" IN ("""
-        {user_filter}
+        + content_type_placeholders_lexical
-        AND "searchableText" ILIKE ${len(params_lexical) + 1}
+        + """)
+        """
+        + user_filter
+        + """
+        AND "searchableText" ILIKE $"""
+        + str(query_param_idx)
+        + """
         ORDER BY "updatedAt" DESC
         LIMIT $1
     """
-    params_lexical.append(f"%{query}%")
+    )
 
     try:
-        results = await query_raw_with_schema(
+        results = await query_raw_with_schema(sql_lexical, *params_lexical)
-            sql_lexical, *params_lexical, set_public_search_path=True
-        )
         return [
             {
                 "content_id": row["content_id"],

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

@@ -155,18 +155,14 @@ async def test_store_embedding_success(mocker):
     )
 
     assert result is True
-    # execute_raw is called twice: once for SET search_path, once for INSERT
+    # execute_raw is called once for INSERT (no separate SET search_path needed)
-    assert mock_client.execute_raw.call_count == 2
+    assert mock_client.execute_raw.call_count == 1
 
-    # First call: SET search_path
+    # Verify the INSERT query with the actual data
-    first_call_args = mock_client.execute_raw.call_args_list[0][0]
+    call_args = mock_client.execute_raw.call_args_list[0][0]
-    assert "SET search_path" in first_call_args[0]
+    assert "test-version-id" in call_args
-
+    assert "[0.1,0.2,0.3]" in call_args
-    # Second call: INSERT query with the actual data
+    assert None in call_args  # userId should be None for store agents
-    second_call_args = mock_client.execute_raw.call_args_list[1][0]
-    assert "test-version-id" in second_call_args
-    assert "[0.1,0.2,0.3]" in second_call_args
-    assert None in second_call_args  # userId should be None for store agents
 
 
 @pytest.mark.asyncio(loop_scope="session")

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

@@ -12,7 +12,7 @@ from dataclasses import dataclass
 from typing import Any, Literal
 
 from prisma.enums import ContentType
-from rank_bm25 import BM25Okapi
+from rank_bm25 import BM25Okapi  # type: ignore[import-untyped]
 
 from backend.api.features.store.embeddings import (
     EMBEDDING_DIM,
@@ -363,9 +363,7 @@ async def unified_hybrid_search(
         LIMIT {limit_param} OFFSET {offset_param}
     """
 
-    results = await query_raw_with_schema(
+    results = await query_raw_with_schema(sql_query, *params)
-        sql_query, *params, set_public_search_path=True
-    )
 
     total = results[0]["total_count"] if results else 0
     # Apply BM25 reranking
@@ -688,9 +686,7 @@ async def hybrid_search(
         LIMIT {limit_param} OFFSET {offset_param}
     """
 
-    results = await query_raw_with_schema(
+    results = await query_raw_with_schema(sql_query, *params)
-        sql_query, *params, set_public_search_path=True
-    )
 
     total = results[0]["total_count"] if results else 0
 

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

@@ -761,10 +761,8 @@ async def create_new_graph(
     graph.reassign_ids(user_id=user_id, reassign_graph_id=True)
     graph.validate_graph(for_run=False)
 
-    # The return value of the create graph & library function is intentionally not used here,
-    # as the graph already valid and no sub-graphs are returned back.
     await graph_db.create_graph(graph, user_id=user_id)
-    await library_db.create_library_agent(graph, user_id=user_id)
+    await library_db.create_library_agent(graph, user_id)
     activated_graph = await on_graph_activate(graph, user_id=user_id)
 
     if create_graph.source == "builder":
@@ -888,21 +886,19 @@ async def set_graph_active_version(
 async def _update_library_agent_version_and_settings(
     user_id: str, agent_graph: graph_db.GraphModel
 ) -> library_model.LibraryAgent:
-    # Keep the library agent up to date with the new active version
     library = await library_db.update_agent_version_in_library(
         user_id, agent_graph.id, agent_graph.version
     )
-    # If the graph has HITL node, initialize the setting if it's not already set.
+    updated_settings = GraphSettings.from_graph(
-    if (
+        graph=agent_graph,
-        agent_graph.has_human_in_the_loop
+        hitl_safe_mode=library.settings.human_in_the_loop_safe_mode,
-        and library.settings.human_in_the_loop_safe_mode is None
+        sensitive_action_safe_mode=library.settings.sensitive_action_safe_mode,
-    ):
+    )
-        await library_db.update_library_agent_settings(
+    if updated_settings != library.settings:
+        library = await library_db.update_library_agent(
+            library_agent_id=library.id,
             user_id=user_id,
-            agent_id=library.id,
+            settings=updated_settings,
-            settings=library.settings.model_copy(
-                update={"human_in_the_loop_safe_mode": True}
-            ),
         )
     return library
 
@@ -919,21 +915,18 @@ async def update_graph_settings(
     user_id: Annotated[str, Security(get_user_id)],
 ) -> GraphSettings:
     """Update graph settings for the user's library agent."""
-    # Get the library agent for this graph
     library_agent = await library_db.get_library_agent_by_graph_id(
         graph_id=graph_id, user_id=user_id
     )
     if not library_agent:
         raise HTTPException(404, f"Graph #{graph_id} not found in user's library")
 
-    # Update the library agent settings
+    updated_agent = await library_db.update_library_agent(
-    updated_agent = await library_db.update_library_agent_settings(
+        library_agent_id=library_agent.id,
         user_id=user_id,
-        agent_id=library_agent.id,
         settings=settings,
     )
 
-    # Return the updated settings
     return GraphSettings.model_validate(updated_agent.settings)
 
 

autogpt_platform/backend/backend/blocks/basic.py

@@ -116,6 +116,7 @@ class PrintToConsoleBlock(Block):
             input_schema=PrintToConsoleBlock.Input,
             output_schema=PrintToConsoleBlock.Output,
             test_input={"text": "Hello, World!"},
+            is_sensitive_action=True,
             test_output=[
                 ("output", "Hello, World!"),
                 ("status", "printed"),

autogpt_platform/backend/backend/blocks/data_manipulation.py

@@ -680,3 +680,58 @@ class ListIsEmptyBlock(Block):
 
     async def run(self, input_data: Input, **kwargs) -> BlockOutput:
         yield "is_empty", len(input_data.list) == 0
+
+
+class ConcatenateListsBlock(Block):
+    class Input(BlockSchemaInput):
+        lists: List[List[Any]] = SchemaField(
+            description="A list of lists to concatenate together. All lists will be combined in order into a single list.",
+            placeholder="e.g., [[1, 2], [3, 4], [5, 6]]",
+        )
+
+    class Output(BlockSchemaOutput):
+        concatenated_list: List[Any] = SchemaField(
+            description="The concatenated list containing all elements from all input lists in order."
+        )
+        error: str = SchemaField(
+            description="Error message if concatenation failed due to invalid input types."
+        )
+
+    def __init__(self):
+        super().__init__(
+            id="3cf9298b-5817-4141-9d80-7c2cc5199c8e",
+            description="Concatenates multiple lists into a single list. All elements from all input lists are combined in order.",
+            categories={BlockCategory.BASIC},
+            input_schema=ConcatenateListsBlock.Input,
+            output_schema=ConcatenateListsBlock.Output,
+            test_input=[
+                {"lists": [[1, 2, 3], [4, 5, 6]]},
+                {"lists": [["a", "b"], ["c"], ["d", "e", "f"]]},
+                {"lists": [[1, 2], []]},
+                {"lists": []},
+            ],
+            test_output=[
+                ("concatenated_list", [1, 2, 3, 4, 5, 6]),
+                ("concatenated_list", ["a", "b", "c", "d", "e", "f"]),
+                ("concatenated_list", [1, 2]),
+                ("concatenated_list", []),
+            ],
+        )
+
+    async def run(self, input_data: Input, **kwargs) -> BlockOutput:
+        concatenated = []
+        for idx, lst in enumerate(input_data.lists):
+            if lst is None:
+                # Skip None values to avoid errors
+                continue
+            if not isinstance(lst, list):
+                # Type validation: each item must be a list
+                # Strings are iterable and would cause extend() to iterate character-by-character
+                # Non-iterable types would raise TypeError
+                yield "error", (
+                    f"Invalid input at index {idx}: expected a list, got {type(lst).__name__}. "
+                    f"All items in 'lists' must be lists (e.g., [[1, 2], [3, 4]])."
+                )
+                return
+            concatenated.extend(lst)
+        yield "concatenated_list", concatenated

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

@@ -10,7 +10,7 @@ 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.data.human_review import ReviewResult, check_auto_approval
 from backend.executor.manager import async_update_node_execution_status
 from backend.util.clients import get_database_manager_async_client
 
@@ -55,6 +55,7 @@ class HITLReviewHelper:
     async def _handle_review_request(
         input_data: Any,
         user_id: str,
+        node_id: str,
         node_exec_id: str,
         graph_exec_id: str,
         graph_id: str,
@@ -69,6 +70,7 @@ class HITLReviewHelper:
         Args:
             input_data: The input data to be reviewed
             user_id: ID of the user requesting the review
+            node_id: ID of the node in the graph definition
             node_exec_id: ID of the node execution
             graph_exec_id: ID of the graph execution
             graph_id: ID of the graph
@@ -83,15 +85,27 @@ class HITLReviewHelper:
         Raises:
             Exception: If review creation or status update fails
         """
-        # Skip review if safe mode is disabled - return auto-approved result
+        # Note: Safe mode checks (human_in_the_loop_safe_mode, sensitive_action_safe_mode)
-        if not execution_context.safe_mode:
+        # are handled by the caller:
+        # - HITL blocks check human_in_the_loop_safe_mode in their run() method
+        # - Sensitive action blocks check sensitive_action_safe_mode in is_block_exec_need_review()
+        # This function only handles auto-approval for specific nodes.
+
+        # Check if this node has been auto-approved in a previous review
+        auto_approval = await check_auto_approval(
+            graph_exec_id=graph_exec_id,
+            node_id=node_id,
+        )
+        if auto_approval:
             logger.info(
-                f"Block {block_name} skipping review for node {node_exec_id} - safe mode disabled"
+                f"Block {block_name} skipping review for node {node_exec_id} - "
+                f"node {node_id} has auto-approval from previous review"
             )
+            # Return a new ReviewResult with the current node_exec_id but approved status
             return ReviewResult(
                 data=input_data,
                 status=ReviewStatus.APPROVED,
-                message="Auto-approved (safe mode disabled)",
+                message="Auto-approved (user approved all future actions for this block)",
                 processed=True,
                 node_exec_id=node_exec_id,
             )
@@ -129,6 +143,7 @@ class HITLReviewHelper:
     async def handle_review_decision(
         input_data: Any,
         user_id: str,
+        node_id: str,
         node_exec_id: str,
         graph_exec_id: str,
         graph_id: str,
@@ -143,6 +158,7 @@ class HITLReviewHelper:
         Args:
             input_data: The input data to be reviewed
             user_id: ID of the user requesting the review
+            node_id: ID of the node in the graph definition
             node_exec_id: ID of the node execution
             graph_exec_id: ID of the graph execution
             graph_id: ID of the graph
@@ -158,6 +174,7 @@ class HITLReviewHelper:
         review_result = await HITLReviewHelper._handle_review_request(
             input_data=input_data,
             user_id=user_id,
+            node_id=node_id,
             node_exec_id=node_exec_id,
             graph_exec_id=graph_exec_id,
             graph_id=graph_id,

autogpt_platform/backend/backend/blocks/human_in_the_loop.py

@@ -97,6 +97,7 @@ class HumanInTheLoopBlock(Block):
         input_data: Input,
         *,
         user_id: str,
+        node_id: str,
         node_exec_id: str,
         graph_exec_id: str,
         graph_id: str,
@@ -104,7 +105,7 @@ class HumanInTheLoopBlock(Block):
         execution_context: ExecutionContext,
         **_kwargs,
     ) -> BlockOutput:
-        if not execution_context.safe_mode:
+        if not execution_context.human_in_the_loop_safe_mode:
             logger.info(
                 f"HITL block skipping review for node {node_exec_id} - safe mode disabled"
             )
@@ -115,6 +116,7 @@ class HumanInTheLoopBlock(Block):
         decision = await self.handle_review_decision(
             input_data=input_data.data,
             user_id=user_id,
+            node_id=node_id,
             node_exec_id=node_exec_id,
             graph_exec_id=graph_exec_id,
             graph_id=graph_id,

autogpt_platform/backend/backend/blocks/llm.py

@@ -79,6 +79,10 @@ class ModelMetadata(NamedTuple):
     provider: str
     context_window: int
     max_output_tokens: int | None
+    display_name: str
+    provider_name: str
+    creator_name: str
+    price_tier: Literal[1, 2, 3]
 
 
 class LlmModelMeta(EnumMeta):
@@ -171,6 +175,26 @@ class LlmModel(str, Enum, metaclass=LlmModelMeta):
     V0_1_5_LG = "v0-1.5-lg"
     V0_1_0_MD = "v0-1.0-md"
 
+    @classmethod
+    def __get_pydantic_json_schema__(cls, schema, handler):
+        json_schema = handler(schema)
+        llm_model_metadata = {}
+        for model in cls:
+            model_name = model.value
+            metadata = model.metadata
+            llm_model_metadata[model_name] = {
+                "creator": metadata.creator_name,
+                "creator_name": metadata.creator_name,
+                "title": metadata.display_name,
+                "provider": metadata.provider,
+                "provider_name": metadata.provider_name,
+                "name": model_name,
+                "price_tier": metadata.price_tier,
+            }
+        json_schema["llm_model"] = True
+        json_schema["llm_model_metadata"] = llm_model_metadata
+        return json_schema
+
     @property
     def metadata(self) -> ModelMetadata:
         return MODEL_METADATA[self]
@@ -190,119 +214,291 @@ class LlmModel(str, Enum, metaclass=LlmModelMeta):
 
 MODEL_METADATA = {
     # https://platform.openai.com/docs/models
-    LlmModel.O3: ModelMetadata("openai", 200000, 100000),
+    LlmModel.O3: ModelMetadata("openai", 200000, 100000, "O3", "OpenAI", "OpenAI", 2),
-    LlmModel.O3_MINI: ModelMetadata("openai", 200000, 100000),  # o3-mini-2025-01-31
+    LlmModel.O3_MINI: ModelMetadata(
-    LlmModel.O1: ModelMetadata("openai", 200000, 100000),  # o1-2024-12-17
+        "openai", 200000, 100000, "O3 Mini", "OpenAI", "OpenAI", 1
-    LlmModel.O1_MINI: ModelMetadata("openai", 128000, 65536),  # o1-mini-2024-09-12
+    ),  # o3-mini-2025-01-31
+    LlmModel.O1: ModelMetadata(
+        "openai", 200000, 100000, "O1", "OpenAI", "OpenAI", 3
+    ),  # o1-2024-12-17
+    LlmModel.O1_MINI: ModelMetadata(
+        "openai", 128000, 65536, "O1 Mini", "OpenAI", "OpenAI", 2
+    ),  # o1-mini-2024-09-12
     # GPT-5 models
-    LlmModel.GPT5_2: ModelMetadata("openai", 400000, 128000),
+    LlmModel.GPT5_2: ModelMetadata(
-    LlmModel.GPT5_1: ModelMetadata("openai", 400000, 128000),
+        "openai", 400000, 128000, "GPT-5.2", "OpenAI", "OpenAI", 3
-    LlmModel.GPT5: ModelMetadata("openai", 400000, 128000),
+    ),
-    LlmModel.GPT5_MINI: ModelMetadata("openai", 400000, 128000),
+    LlmModel.GPT5_1: ModelMetadata(
-    LlmModel.GPT5_NANO: ModelMetadata("openai", 400000, 128000),
+        "openai", 400000, 128000, "GPT-5.1", "OpenAI", "OpenAI", 2
-    LlmModel.GPT5_CHAT: ModelMetadata("openai", 400000, 16384),
+    ),
-    LlmModel.GPT41: ModelMetadata("openai", 1047576, 32768),
+    LlmModel.GPT5: ModelMetadata(
-    LlmModel.GPT41_MINI: ModelMetadata("openai", 1047576, 32768),
+        "openai", 400000, 128000, "GPT-5", "OpenAI", "OpenAI", 1
+    ),
+    LlmModel.GPT5_MINI: ModelMetadata(
+        "openai", 400000, 128000, "GPT-5 Mini", "OpenAI", "OpenAI", 1
+    ),
+    LlmModel.GPT5_NANO: ModelMetadata(
+        "openai", 400000, 128000, "GPT-5 Nano", "OpenAI", "OpenAI", 1
+    ),
+    LlmModel.GPT5_CHAT: ModelMetadata(
+        "openai", 400000, 16384, "GPT-5 Chat Latest", "OpenAI", "OpenAI", 2
+    ),
+    LlmModel.GPT41: ModelMetadata(
+        "openai", 1047576, 32768, "GPT-4.1", "OpenAI", "OpenAI", 1
+    ),
+    LlmModel.GPT41_MINI: ModelMetadata(
+        "openai", 1047576, 32768, "GPT-4.1 Mini", "OpenAI", "OpenAI", 1
+    ),
     LlmModel.GPT4O_MINI: ModelMetadata(
-        "openai", 128000, 16384
+        "openai", 128000, 16384, "GPT-4o Mini", "OpenAI", "OpenAI", 1
     ),  # gpt-4o-mini-2024-07-18
-    LlmModel.GPT4O: ModelMetadata("openai", 128000, 16384),  # gpt-4o-2024-08-06
+    LlmModel.GPT4O: ModelMetadata(
+        "openai", 128000, 16384, "GPT-4o", "OpenAI", "OpenAI", 2
+    ),  # gpt-4o-2024-08-06
     LlmModel.GPT4_TURBO: ModelMetadata(
-        "openai", 128000, 4096
+        "openai", 128000, 4096, "GPT-4 Turbo", "OpenAI", "OpenAI", 3
     ),  # gpt-4-turbo-2024-04-09
-    LlmModel.GPT3_5_TURBO: ModelMetadata("openai", 16385, 4096),  # gpt-3.5-turbo-0125
+    LlmModel.GPT3_5_TURBO: ModelMetadata(
+        "openai", 16385, 4096, "GPT-3.5 Turbo", "OpenAI", "OpenAI", 1
+    ),  # gpt-3.5-turbo-0125
     # https://docs.anthropic.com/en/docs/about-claude/models
     LlmModel.CLAUDE_4_1_OPUS: ModelMetadata(
-        "anthropic", 200000, 32000
+        "anthropic", 200000, 32000, "Claude Opus 4.1", "Anthropic", "Anthropic", 3
     ),  # claude-opus-4-1-20250805
     LlmModel.CLAUDE_4_OPUS: ModelMetadata(
-        "anthropic", 200000, 32000
+        "anthropic", 200000, 32000, "Claude Opus 4", "Anthropic", "Anthropic", 3
     ),  # claude-4-opus-20250514
     LlmModel.CLAUDE_4_SONNET: ModelMetadata(
-        "anthropic", 200000, 64000
+        "anthropic", 200000, 64000, "Claude Sonnet 4", "Anthropic", "Anthropic", 2
     ),  # claude-4-sonnet-20250514
     LlmModel.CLAUDE_4_5_OPUS: ModelMetadata(
-        "anthropic", 200000, 64000
+        "anthropic", 200000, 64000, "Claude Opus 4.5", "Anthropic", "Anthropic", 3
     ),  # claude-opus-4-5-20251101
     LlmModel.CLAUDE_4_5_SONNET: ModelMetadata(
-        "anthropic", 200000, 64000
+        "anthropic", 200000, 64000, "Claude Sonnet 4.5", "Anthropic", "Anthropic", 3
     ),  # claude-sonnet-4-5-20250929
     LlmModel.CLAUDE_4_5_HAIKU: ModelMetadata(
-        "anthropic", 200000, 64000
+        "anthropic", 200000, 64000, "Claude Haiku 4.5", "Anthropic", "Anthropic", 2
     ),  # claude-haiku-4-5-20251001
     LlmModel.CLAUDE_3_7_SONNET: ModelMetadata(
-        "anthropic", 200000, 64000
+        "anthropic", 200000, 64000, "Claude 3.7 Sonnet", "Anthropic", "Anthropic", 2
     ),  # claude-3-7-sonnet-20250219
     LlmModel.CLAUDE_3_HAIKU: ModelMetadata(
-        "anthropic", 200000, 4096
+        "anthropic", 200000, 4096, "Claude 3 Haiku", "Anthropic", "Anthropic", 1
     ),  # claude-3-haiku-20240307
     # https://docs.aimlapi.com/api-overview/model-database/text-models
-    LlmModel.AIML_API_QWEN2_5_72B: ModelMetadata("aiml_api", 32000, 8000),
+    LlmModel.AIML_API_QWEN2_5_72B: ModelMetadata(
-    LlmModel.AIML_API_LLAMA3_1_70B: ModelMetadata("aiml_api", 128000, 40000),
+        "aiml_api", 32000, 8000, "Qwen 2.5 72B Instruct Turbo", "AI/ML", "Qwen", 1
-    LlmModel.AIML_API_LLAMA3_3_70B: ModelMetadata("aiml_api", 128000, None),
+    ),
-    LlmModel.AIML_API_META_LLAMA_3_1_70B: ModelMetadata("aiml_api", 131000, 2000),
+    LlmModel.AIML_API_LLAMA3_1_70B: ModelMetadata(
-    LlmModel.AIML_API_LLAMA_3_2_3B: ModelMetadata("aiml_api", 128000, None),
+        "aiml_api",
-    # https://console.groq.com/docs/models
+        128000,
-    LlmModel.LLAMA3_3_70B: ModelMetadata("groq", 128000, 32768),
+        40000,
-    LlmModel.LLAMA3_1_8B: ModelMetadata("groq", 128000, 8192),
+        "Llama 3.1 Nemotron 70B Instruct",
-    # https://ollama.com/library
+        "AI/ML",
-    LlmModel.OLLAMA_LLAMA3_3: ModelMetadata("ollama", 8192, None),
+        "Nvidia",
-    LlmModel.OLLAMA_LLAMA3_2: ModelMetadata("ollama", 8192, None),
+        1,
-    LlmModel.OLLAMA_LLAMA3_8B: ModelMetadata("ollama", 8192, None),
+    ),
-    LlmModel.OLLAMA_LLAMA3_405B: ModelMetadata("ollama", 8192, None),
+    LlmModel.AIML_API_LLAMA3_3_70B: ModelMetadata(
-    LlmModel.OLLAMA_DOLPHIN: ModelMetadata("ollama", 32768, None),
+        "aiml_api", 128000, None, "Llama 3.3 70B Instruct Turbo", "AI/ML", "Meta", 1
-    # https://openrouter.ai/models
+    ),
-    LlmModel.GEMINI_2_5_PRO: ModelMetadata("open_router", 1050000, 8192),
+    LlmModel.AIML_API_META_LLAMA_3_1_70B: ModelMetadata(
-    LlmModel.GEMINI_3_PRO_PREVIEW: ModelMetadata("open_router", 1048576, 65535),
+        "aiml_api", 131000, 2000, "Llama 3.1 70B Instruct Turbo", "AI/ML", "Meta", 1
-    LlmModel.GEMINI_2_5_FLASH: ModelMetadata("open_router", 1048576, 65535),
+    ),
-    LlmModel.GEMINI_2_0_FLASH: ModelMetadata("open_router", 1048576, 8192),
+    LlmModel.AIML_API_LLAMA_3_2_3B: ModelMetadata(
-    LlmModel.GEMINI_2_5_FLASH_LITE_PREVIEW: ModelMetadata(
+        "aiml_api", 128000, None, "Llama 3.2 3B Instruct Turbo", "AI/ML", "Meta", 1
-        "open_router", 1048576, 65535
+    ),
+    # https://console.groq.com/docs/models
+    LlmModel.LLAMA3_3_70B: ModelMetadata(
+        "groq", 128000, 32768, "Llama 3.3 70B Versatile", "Groq", "Meta", 1
+    ),
+    LlmModel.LLAMA3_1_8B: ModelMetadata(
+        "groq", 128000, 8192, "Llama 3.1 8B Instant", "Groq", "Meta", 1
+    ),
+    # https://ollama.com/library
+    LlmModel.OLLAMA_LLAMA3_3: ModelMetadata(
+        "ollama", 8192, None, "Llama 3.3", "Ollama", "Meta", 1
+    ),
+    LlmModel.OLLAMA_LLAMA3_2: ModelMetadata(
+        "ollama", 8192, None, "Llama 3.2", "Ollama", "Meta", 1
+    ),
+    LlmModel.OLLAMA_LLAMA3_8B: ModelMetadata(
+        "ollama", 8192, None, "Llama 3", "Ollama", "Meta", 1
+    ),
+    LlmModel.OLLAMA_LLAMA3_405B: ModelMetadata(
+        "ollama", 8192, None, "Llama 3.1 405B", "Ollama", "Meta", 1
+    ),
+    LlmModel.OLLAMA_DOLPHIN: ModelMetadata(
+        "ollama", 32768, None, "Dolphin Mistral Latest", "Ollama", "Mistral AI", 1
+    ),
+    # https://openrouter.ai/models
+    LlmModel.GEMINI_2_5_PRO: ModelMetadata(
+        "open_router",
+        1050000,
+        8192,
+        "Gemini 2.5 Pro Preview 03.25",
+        "OpenRouter",
+        "Google",
+        2,
+    ),
+    LlmModel.GEMINI_3_PRO_PREVIEW: ModelMetadata(
+        "open_router", 1048576, 65535, "Gemini 3 Pro Preview", "OpenRouter", "Google", 2
+    ),
+    LlmModel.GEMINI_2_5_FLASH: ModelMetadata(
+        "open_router", 1048576, 65535, "Gemini 2.5 Flash", "OpenRouter", "Google", 1
+    ),
+    LlmModel.GEMINI_2_0_FLASH: ModelMetadata(
+        "open_router", 1048576, 8192, "Gemini 2.0 Flash 001", "OpenRouter", "Google", 1
+    ),
+    LlmModel.GEMINI_2_5_FLASH_LITE_PREVIEW: ModelMetadata(
+        "open_router",
+        1048576,
+        65535,
+        "Gemini 2.5 Flash Lite Preview 06.17",
+        "OpenRouter",
+        "Google",
+        1,
+    ),
+    LlmModel.GEMINI_2_0_FLASH_LITE: ModelMetadata(
+        "open_router",
+        1048576,
+        8192,
+        "Gemini 2.0 Flash Lite 001",
+        "OpenRouter",
+        "Google",
+        1,
+    ),
+    LlmModel.MISTRAL_NEMO: ModelMetadata(
+        "open_router", 128000, 4096, "Mistral Nemo", "OpenRouter", "Mistral AI", 1
+    ),
+    LlmModel.COHERE_COMMAND_R_08_2024: ModelMetadata(
+        "open_router", 128000, 4096, "Command R 08.2024", "OpenRouter", "Cohere", 1
+    ),
+    LlmModel.COHERE_COMMAND_R_PLUS_08_2024: ModelMetadata(
+        "open_router", 128000, 4096, "Command R Plus 08.2024", "OpenRouter", "Cohere", 2
+    ),
+    LlmModel.DEEPSEEK_CHAT: ModelMetadata(
+        "open_router", 64000, 2048, "DeepSeek Chat", "OpenRouter", "DeepSeek", 1
+    ),
+    LlmModel.DEEPSEEK_R1_0528: ModelMetadata(
+        "open_router", 163840, 163840, "DeepSeek R1 0528", "OpenRouter", "DeepSeek", 1
+    ),
+    LlmModel.PERPLEXITY_SONAR: ModelMetadata(
+        "open_router", 127000, 8000, "Sonar", "OpenRouter", "Perplexity", 1
+    ),
+    LlmModel.PERPLEXITY_SONAR_PRO: ModelMetadata(
+        "open_router", 200000, 8000, "Sonar Pro", "OpenRouter", "Perplexity", 2
     ),
-    LlmModel.GEMINI_2_0_FLASH_LITE: ModelMetadata("open_router", 1048576, 8192),
-    LlmModel.MISTRAL_NEMO: ModelMetadata("open_router", 128000, 4096),
-    LlmModel.COHERE_COMMAND_R_08_2024: ModelMetadata("open_router", 128000, 4096),
-    LlmModel.COHERE_COMMAND_R_PLUS_08_2024: ModelMetadata("open_router", 128000, 4096),
-    LlmModel.DEEPSEEK_CHAT: ModelMetadata("open_router", 64000, 2048),
-    LlmModel.DEEPSEEK_R1_0528: ModelMetadata("open_router", 163840, 163840),
-    LlmModel.PERPLEXITY_SONAR: ModelMetadata("open_router", 127000, 8000),
-    LlmModel.PERPLEXITY_SONAR_PRO: ModelMetadata("open_router", 200000, 8000),
     LlmModel.PERPLEXITY_SONAR_DEEP_RESEARCH: ModelMetadata(
         "open_router",
         128000,
         16000,
+        "Sonar Deep Research",
+        "OpenRouter",
+        "Perplexity",
+        3,
     ),
     LlmModel.NOUSRESEARCH_HERMES_3_LLAMA_3_1_405B: ModelMetadata(
-        "open_router", 131000, 4096
+        "open_router",
+        131000,
+        4096,
+        "Hermes 3 Llama 3.1 405B",
+        "OpenRouter",
+        "Nous Research",
+        1,
     ),
     LlmModel.NOUSRESEARCH_HERMES_3_LLAMA_3_1_70B: ModelMetadata(
-        "open_router", 12288, 12288
+        "open_router",
+        12288,
+        12288,
+        "Hermes 3 Llama 3.1 70B",
+        "OpenRouter",
+        "Nous Research",
+        1,
+    ),
+    LlmModel.OPENAI_GPT_OSS_120B: ModelMetadata(
+        "open_router", 131072, 131072, "GPT-OSS 120B", "OpenRouter", "OpenAI", 1
+    ),
+    LlmModel.OPENAI_GPT_OSS_20B: ModelMetadata(
+        "open_router", 131072, 32768, "GPT-OSS 20B", "OpenRouter", "OpenAI", 1
+    ),
+    LlmModel.AMAZON_NOVA_LITE_V1: ModelMetadata(
+        "open_router", 300000, 5120, "Nova Lite V1", "OpenRouter", "Amazon", 1
+    ),
+    LlmModel.AMAZON_NOVA_MICRO_V1: ModelMetadata(
+        "open_router", 128000, 5120, "Nova Micro V1", "OpenRouter", "Amazon", 1
+    ),
+    LlmModel.AMAZON_NOVA_PRO_V1: ModelMetadata(
+        "open_router", 300000, 5120, "Nova Pro V1", "OpenRouter", "Amazon", 1
+    ),
+    LlmModel.MICROSOFT_WIZARDLM_2_8X22B: ModelMetadata(
+        "open_router", 65536, 4096, "WizardLM 2 8x22B", "OpenRouter", "Microsoft", 1
+    ),
+    LlmModel.GRYPHE_MYTHOMAX_L2_13B: ModelMetadata(
+        "open_router", 4096, 4096, "MythoMax L2 13B", "OpenRouter", "Gryphe", 1
+    ),
+    LlmModel.META_LLAMA_4_SCOUT: ModelMetadata(
+        "open_router", 131072, 131072, "Llama 4 Scout", "OpenRouter", "Meta", 1
+    ),
+    LlmModel.META_LLAMA_4_MAVERICK: ModelMetadata(
+        "open_router", 1048576, 1000000, "Llama 4 Maverick", "OpenRouter", "Meta", 1
+    ),
+    LlmModel.GROK_4: ModelMetadata(
+        "open_router", 256000, 256000, "Grok 4", "OpenRouter", "xAI", 3
+    ),
+    LlmModel.GROK_4_FAST: ModelMetadata(
+        "open_router", 2000000, 30000, "Grok 4 Fast", "OpenRouter", "xAI", 1
+    ),
+    LlmModel.GROK_4_1_FAST: ModelMetadata(
+        "open_router", 2000000, 30000, "Grok 4.1 Fast", "OpenRouter", "xAI", 1
+    ),
+    LlmModel.GROK_CODE_FAST_1: ModelMetadata(
+        "open_router", 256000, 10000, "Grok Code Fast 1", "OpenRouter", "xAI", 1
+    ),
+    LlmModel.KIMI_K2: ModelMetadata(
+        "open_router", 131000, 131000, "Kimi K2", "OpenRouter", "Moonshot AI", 1
+    ),
+    LlmModel.QWEN3_235B_A22B_THINKING: ModelMetadata(
+        "open_router",
+        262144,
+        262144,
+        "Qwen 3 235B A22B Thinking 2507",
+        "OpenRouter",
+        "Qwen",
+        1,
+    ),
+    LlmModel.QWEN3_CODER: ModelMetadata(
+        "open_router", 262144, 262144, "Qwen 3 Coder", "OpenRouter", "Qwen", 3
     ),
-    LlmModel.OPENAI_GPT_OSS_120B: ModelMetadata("open_router", 131072, 131072),
-    LlmModel.OPENAI_GPT_OSS_20B: ModelMetadata("open_router", 131072, 32768),
-    LlmModel.AMAZON_NOVA_LITE_V1: ModelMetadata("open_router", 300000, 5120),
-    LlmModel.AMAZON_NOVA_MICRO_V1: ModelMetadata("open_router", 128000, 5120),
-    LlmModel.AMAZON_NOVA_PRO_V1: ModelMetadata("open_router", 300000, 5120),
-    LlmModel.MICROSOFT_WIZARDLM_2_8X22B: ModelMetadata("open_router", 65536, 4096),
-    LlmModel.GRYPHE_MYTHOMAX_L2_13B: ModelMetadata("open_router", 4096, 4096),
-    LlmModel.META_LLAMA_4_SCOUT: ModelMetadata("open_router", 131072, 131072),
-    LlmModel.META_LLAMA_4_MAVERICK: ModelMetadata("open_router", 1048576, 1000000),
-    LlmModel.GROK_4: ModelMetadata("open_router", 256000, 256000),
-    LlmModel.GROK_4_FAST: ModelMetadata("open_router", 2000000, 30000),
-    LlmModel.GROK_4_1_FAST: ModelMetadata("open_router", 2000000, 30000),
-    LlmModel.GROK_CODE_FAST_1: ModelMetadata("open_router", 256000, 10000),
-    LlmModel.KIMI_K2: ModelMetadata("open_router", 131000, 131000),
-    LlmModel.QWEN3_235B_A22B_THINKING: ModelMetadata("open_router", 262144, 262144),
-    LlmModel.QWEN3_CODER: ModelMetadata("open_router", 262144, 262144),
     # Llama API models
-    LlmModel.LLAMA_API_LLAMA_4_SCOUT: ModelMetadata("llama_api", 128000, 4028),
+    LlmModel.LLAMA_API_LLAMA_4_SCOUT: ModelMetadata(
-    LlmModel.LLAMA_API_LLAMA4_MAVERICK: ModelMetadata("llama_api", 128000, 4028),
+        "llama_api",
-    LlmModel.LLAMA_API_LLAMA3_3_8B: ModelMetadata("llama_api", 128000, 4028),
+        128000,
-    LlmModel.LLAMA_API_LLAMA3_3_70B: ModelMetadata("llama_api", 128000, 4028),
+        4028,
+        "Llama 4 Scout 17B 16E Instruct FP8",
+        "Llama API",
+        "Meta",
+        1,
+    ),
+    LlmModel.LLAMA_API_LLAMA4_MAVERICK: ModelMetadata(
+        "llama_api",
+        128000,
+        4028,
+        "Llama 4 Maverick 17B 128E Instruct FP8",
+        "Llama API",
+        "Meta",
+        1,
+    ),
+    LlmModel.LLAMA_API_LLAMA3_3_8B: ModelMetadata(
+        "llama_api", 128000, 4028, "Llama 3.3 8B Instruct", "Llama API", "Meta", 1
+    ),
+    LlmModel.LLAMA_API_LLAMA3_3_70B: ModelMetadata(
+        "llama_api", 128000, 4028, "Llama 3.3 70B Instruct", "Llama API", "Meta", 1
+    ),
     # v0 by Vercel models
-    LlmModel.V0_1_5_MD: ModelMetadata("v0", 128000, 64000),
+    LlmModel.V0_1_5_MD: ModelMetadata("v0", 128000, 64000, "v0 1.5 MD", "V0", "V0", 1),
-    LlmModel.V0_1_5_LG: ModelMetadata("v0", 512000, 64000),
+    LlmModel.V0_1_5_LG: ModelMetadata("v0", 512000, 64000, "v0 1.5 LG", "V0", "V0", 1),
-    LlmModel.V0_1_0_MD: ModelMetadata("v0", 128000, 64000),
+    LlmModel.V0_1_0_MD: ModelMetadata("v0", 128000, 64000, "v0 1.0 MD", "V0", "V0", 1),
 }
 
 DEFAULT_LLM_MODEL = LlmModel.GPT5_2

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

@@ -242,7 +242,7 @@ async def test_smart_decision_maker_tracks_llm_stats():
         outputs = {}
         # Create execution context
 
-        mock_execution_context = ExecutionContext(safe_mode=False)
+        mock_execution_context = ExecutionContext(human_in_the_loop_safe_mode=False)
 
         # Create a mock execution processor for tests
 
@@ -343,7 +343,7 @@ async def test_smart_decision_maker_parameter_validation():
 
         # Create execution context
 
-        mock_execution_context = ExecutionContext(safe_mode=False)
+        mock_execution_context = ExecutionContext(human_in_the_loop_safe_mode=False)
 
         # Create a mock execution processor for tests
 
@@ -409,7 +409,7 @@ async def test_smart_decision_maker_parameter_validation():
 
         # Create execution context
 
-        mock_execution_context = ExecutionContext(safe_mode=False)
+        mock_execution_context = ExecutionContext(human_in_the_loop_safe_mode=False)
 
         # Create a mock execution processor for tests
 
@@ -471,7 +471,7 @@ async def test_smart_decision_maker_parameter_validation():
         outputs = {}
         # Create execution context
 
-        mock_execution_context = ExecutionContext(safe_mode=False)
+        mock_execution_context = ExecutionContext(human_in_the_loop_safe_mode=False)
 
         # Create a mock execution processor for tests
 
@@ -535,7 +535,7 @@ async def test_smart_decision_maker_parameter_validation():
         outputs = {}
         # Create execution context
 
-        mock_execution_context = ExecutionContext(safe_mode=False)
+        mock_execution_context = ExecutionContext(human_in_the_loop_safe_mode=False)
 
         # Create a mock execution processor for tests
 
@@ -658,7 +658,7 @@ async def test_smart_decision_maker_raw_response_conversion():
         outputs = {}
         # Create execution context
 
-        mock_execution_context = ExecutionContext(safe_mode=False)
+        mock_execution_context = ExecutionContext(human_in_the_loop_safe_mode=False)
 
         # Create a mock execution processor for tests
 
@@ -730,7 +730,7 @@ async def test_smart_decision_maker_raw_response_conversion():
         outputs = {}
         # Create execution context
 
-        mock_execution_context = ExecutionContext(safe_mode=False)
+        mock_execution_context = ExecutionContext(human_in_the_loop_safe_mode=False)
 
         # Create a mock execution processor for tests
 
@@ -786,7 +786,7 @@ async def test_smart_decision_maker_raw_response_conversion():
         outputs = {}
         # Create execution context
 
-        mock_execution_context = ExecutionContext(safe_mode=False)
+        mock_execution_context = ExecutionContext(human_in_the_loop_safe_mode=False)
 
         # Create a mock execution processor for tests
 
@@ -905,7 +905,7 @@ async def test_smart_decision_maker_agent_mode():
         # Create a mock execution context
 
         mock_execution_context = ExecutionContext(
-            safe_mode=False,
+            human_in_the_loop_safe_mode=False,
         )
 
         # Create a mock execution processor for agent mode tests
@@ -1027,7 +1027,7 @@ async def test_smart_decision_maker_traditional_mode_default():
 
         # Create execution context
 
-        mock_execution_context = ExecutionContext(safe_mode=False)
+        mock_execution_context = ExecutionContext(human_in_the_loop_safe_mode=False)
 
         # Create a mock execution processor for tests
 

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

@@ -386,7 +386,7 @@ async def test_output_yielding_with_dynamic_fields():
             outputs = {}
             from backend.data.execution import ExecutionContext
 
-            mock_execution_context = ExecutionContext(safe_mode=False)
+            mock_execution_context = ExecutionContext(human_in_the_loop_safe_mode=False)
             mock_execution_processor = MagicMock()
 
             async for output_name, output_value in block.run(
@@ -609,7 +609,9 @@ async def test_validation_errors_dont_pollute_conversation():
                 outputs = {}
                 from backend.data.execution import ExecutionContext
 
-                mock_execution_context = ExecutionContext(safe_mode=False)
+                mock_execution_context = ExecutionContext(
+                    human_in_the_loop_safe_mode=False
+                )
 
                 # Create a proper mock execution processor for agent mode
                 from collections import defaultdict

autogpt_platform/backend/backend/data/block.py

@@ -441,6 +441,7 @@ class Block(ABC, Generic[BlockSchemaInputType, BlockSchemaOutputType]):
         static_output: bool = False,
         block_type: BlockType = BlockType.STANDARD,
         webhook_config: Optional[BlockWebhookConfig | BlockManualWebhookConfig] = None,
+        is_sensitive_action: bool = False,
     ):
         """
         Initialize the block with the given schema.
@@ -473,8 +474,8 @@ class Block(ABC, Generic[BlockSchemaInputType, BlockSchemaOutputType]):
         self.static_output = static_output
         self.block_type = block_type
         self.webhook_config = webhook_config
+        self.is_sensitive_action = is_sensitive_action
         self.execution_stats: NodeExecutionStats = NodeExecutionStats()
-        self.requires_human_review: bool = False
 
         if self.webhook_config:
             if isinstance(self.webhook_config, BlockWebhookConfig):
@@ -622,6 +623,7 @@ class Block(ABC, Generic[BlockSchemaInputType, BlockSchemaOutputType]):
         input_data: BlockInput,
         *,
         user_id: str,
+        node_id: str,
         node_exec_id: str,
         graph_exec_id: str,
         graph_id: str,
@@ -637,8 +639,9 @@ class Block(ABC, Generic[BlockSchemaInputType, BlockSchemaOutputType]):
             - 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 (
-        if not self.requires_human_review or not execution_context.safe_mode:
+            self.is_sensitive_action and execution_context.sensitive_action_safe_mode
+        ):
             return False, input_data
 
         from backend.blocks.helpers.review import HITLReviewHelper
@@ -647,6 +650,7 @@ class Block(ABC, Generic[BlockSchemaInputType, BlockSchemaOutputType]):
         decision = await HITLReviewHelper.handle_review_decision(
             input_data=input_data,
             user_id=user_id,
+            node_id=node_id,
             node_exec_id=node_exec_id,
             graph_exec_id=graph_exec_id,
             graph_id=graph_id,

autogpt_platform/backend/backend/data/block_cost_config.py

@@ -99,10 +99,15 @@ MODEL_COST: dict[LlmModel, int] = {
     LlmModel.OPENAI_GPT_OSS_20B: 1,
     LlmModel.GEMINI_2_5_PRO: 4,
     LlmModel.GEMINI_3_PRO_PREVIEW: 5,
+    LlmModel.GEMINI_2_5_FLASH: 1,
+    LlmModel.GEMINI_2_0_FLASH: 1,
+    LlmModel.GEMINI_2_5_FLASH_LITE_PREVIEW: 1,
+    LlmModel.GEMINI_2_0_FLASH_LITE: 1,
     LlmModel.MISTRAL_NEMO: 1,
     LlmModel.COHERE_COMMAND_R_08_2024: 1,
     LlmModel.COHERE_COMMAND_R_PLUS_08_2024: 3,
     LlmModel.DEEPSEEK_CHAT: 2,
+    LlmModel.DEEPSEEK_R1_0528: 1,
     LlmModel.PERPLEXITY_SONAR: 1,
     LlmModel.PERPLEXITY_SONAR_PRO: 5,
     LlmModel.PERPLEXITY_SONAR_DEEP_RESEARCH: 10,
@@ -126,11 +131,6 @@ MODEL_COST: dict[LlmModel, int] = {
     LlmModel.KIMI_K2: 1,
     LlmModel.QWEN3_235B_A22B_THINKING: 1,
     LlmModel.QWEN3_CODER: 9,
-    LlmModel.GEMINI_2_5_FLASH: 1,
-    LlmModel.GEMINI_2_0_FLASH: 1,
-    LlmModel.GEMINI_2_5_FLASH_LITE_PREVIEW: 1,
-    LlmModel.GEMINI_2_0_FLASH_LITE: 1,
-    LlmModel.DEEPSEEK_R1_0528: 1,
     # v0 by Vercel models
     LlmModel.V0_1_5_MD: 1,
     LlmModel.V0_1_5_LG: 2,

autogpt_platform/backend/backend/data/db.py

@@ -38,20 +38,6 @@ POOL_TIMEOUT = os.getenv("DB_POOL_TIMEOUT")
 if POOL_TIMEOUT:
     DATABASE_URL = add_param(DATABASE_URL, "pool_timeout", POOL_TIMEOUT)
 
-# Add public schema to search_path for pgvector type access
-# The vector extension is in public schema, but search_path is determined by schema parameter
-# Extract the schema from DATABASE_URL or default to 'public' (matching get_database_schema())
-parsed_url = urlparse(DATABASE_URL)
-url_params = dict(parse_qsl(parsed_url.query))
-db_schema = url_params.get("schema", "public")
-# Build search_path, avoiding duplicates if db_schema is already 'public'
-search_path_schemas = list(
-    dict.fromkeys([db_schema, "public"])
-)  # Preserves order, removes duplicates
-search_path = ",".join(search_path_schemas)
-# This allows using ::vector without schema qualification
-DATABASE_URL = add_param(DATABASE_URL, "options", f"-c search_path={search_path}")
-
 HTTP_TIMEOUT = int(POOL_TIMEOUT) if POOL_TIMEOUT else None
 
 prisma = Prisma(
@@ -127,38 +113,48 @@ async def _raw_with_schema(
     *args,
     execute: bool = False,
     client: Prisma | None = None,
-    set_public_search_path: bool = False,
 ) -> list[dict] | int:
     """Internal: Execute raw SQL with proper schema handling.
 
     Use query_raw_with_schema() or execute_raw_with_schema() instead.
 
+    Supports placeholders:
+        - {schema_prefix}: Table/type prefix (e.g., "platform".)
+        - {schema}: Raw schema name for application tables (e.g., platform)
+
+    Note on pgvector types:
+        Use unqualified ::vector and <=> operator in queries. PostgreSQL resolves
+        these via search_path, which includes the schema where pgvector is installed
+        on all environments (local, CI, dev).
+
     Args:
-        query_template: SQL query with {schema_prefix} placeholder
+        query_template: SQL query with {schema_prefix} and/or {schema} placeholders
         *args: Query parameters
         execute: If False, executes SELECT query. If True, executes INSERT/UPDATE/DELETE.
         client: Optional Prisma client for transactions (only used when execute=True).
-        set_public_search_path: If True, sets search_path to include public schema.
-                                Needed for pgvector types and other public schema objects.
 
     Returns:
         - list[dict] if execute=False (query results)
         - int if execute=True (number of affected rows)
+
+    Example with vector type:
+        await execute_raw_with_schema(
+            'INSERT INTO {schema_prefix}"Embedding" (vec) VALUES ($1::vector)',
+            embedding_data
+        )
     """
     schema = get_database_schema()
     schema_prefix = f'"{schema}".' if schema != "public" else ""
-    formatted_query = query_template.format(schema_prefix=schema_prefix)
+
+    formatted_query = query_template.format(
+        schema_prefix=schema_prefix,
+        schema=schema,
+    )
 
     import prisma as prisma_module
 
     db_client = client if client else prisma_module.get_client()
 
-    # Set search_path to include public schema if requested
-    # Prisma doesn't support the 'options' connection parameter, so we set it per-session
-    # This is idempotent and safe to call multiple times
-    if set_public_search_path:
-        await db_client.execute_raw(f"SET search_path = {schema}, public")  # type: ignore
-
     if execute:
         result = await db_client.execute_raw(formatted_query, *args)  # type: ignore
     else:
@@ -167,16 +163,12 @@ async def _raw_with_schema(
     return result
 
 
-async def query_raw_with_schema(
+async def query_raw_with_schema(query_template: str, *args) -> list[dict]:
-    query_template: str, *args, set_public_search_path: bool = False
-) -> list[dict]:
     """Execute raw SQL SELECT query with proper schema handling.
 
     Args:
-        query_template: SQL query with {schema_prefix} placeholder
+        query_template: SQL query with {schema_prefix} and/or {schema} placeholders
         *args: Query parameters
-        set_public_search_path: If True, sets search_path to include public schema.
-                                Needed for pgvector types and other public schema objects.
 
     Returns:
         List of result rows as dictionaries
@@ -187,23 +179,20 @@ async def query_raw_with_schema(
             user_id
         )
     """
-    return await _raw_with_schema(query_template, *args, execute=False, set_public_search_path=set_public_search_path)  # type: ignore
+    return await _raw_with_schema(query_template, *args, execute=False)  # type: ignore
 
 
 async def execute_raw_with_schema(
     query_template: str,
     *args,
     client: Prisma | None = None,
-    set_public_search_path: bool = False,
 ) -> int:
     """Execute raw SQL command (INSERT/UPDATE/DELETE) with proper schema handling.
 
     Args:
-        query_template: SQL query with {schema_prefix} placeholder
+        query_template: SQL query with {schema_prefix} and/or {schema} placeholders
         *args: Query parameters
         client: Optional Prisma client for transactions
-        set_public_search_path: If True, sets search_path to include public schema.
-                                Needed for pgvector types and other public schema objects.
 
     Returns:
         Number of affected rows
@@ -215,7 +204,7 @@ async def execute_raw_with_schema(
             client=tx  # Optional transaction client
         )
     """
-    return await _raw_with_schema(query_template, *args, execute=True, client=client, set_public_search_path=set_public_search_path)  # type: ignore
+    return await _raw_with_schema(query_template, *args, execute=True, client=client)  # type: ignore
 
 
 class BaseDbModel(BaseModel):

autogpt_platform/backend/backend/data/event_bus.py

@@ -103,8 +103,18 @@ class RedisEventBus(BaseRedisEventBus[M], ABC):
         return redis.get_redis()
 
     def publish_event(self, event: M, channel_key: str):
-        message, full_channel_name = self._serialize_message(event, channel_key)
+        """
-        self.connection.publish(full_channel_name, message)
+        Publish an event to Redis. Gracefully handles connection failures
+        by logging the error instead of raising exceptions.
+        """
+        try:
+            message, full_channel_name = self._serialize_message(event, channel_key)
+            self.connection.publish(full_channel_name, message)
+        except Exception:
+            logger.exception(
+                f"Failed to publish event to Redis channel {channel_key}. "
+                "Event bus operation will continue without Redis connectivity."
+            )
 
     def listen_events(self, channel_key: str) -> Generator[M, None, None]:
         pubsub, full_channel_name = self._get_pubsub_channel(
@@ -128,9 +138,19 @@ class AsyncRedisEventBus(BaseRedisEventBus[M], ABC):
         return await redis.get_redis_async()
 
     async def publish_event(self, event: M, channel_key: str):
-        message, full_channel_name = self._serialize_message(event, channel_key)
+        """
-        connection = await self.connection
+        Publish an event to Redis. Gracefully handles connection failures
-        await connection.publish(full_channel_name, message)
+        by logging the error instead of raising exceptions.
+        """
+        try:
+            message, full_channel_name = self._serialize_message(event, channel_key)
+            connection = await self.connection
+            await connection.publish(full_channel_name, message)
+        except Exception:
+            logger.exception(
+                f"Failed to publish event to Redis channel {channel_key}. "
+                "Event bus operation will continue without Redis connectivity."
+            )
 
     async def listen_events(self, channel_key: str) -> AsyncGenerator[M, None]:
         pubsub, full_channel_name = self._get_pubsub_channel(

autogpt_platform/backend/backend/data/event_bus_test.py

@@ -0,0 +1,56 @@
+"""
+Tests for event_bus graceful degradation when Redis is unavailable.
+"""
+
+from unittest.mock import AsyncMock, patch
+
+import pytest
+from pydantic import BaseModel
+
+from backend.data.event_bus import AsyncRedisEventBus
+
+
+class TestEvent(BaseModel):
+    """Test event model."""
+
+    message: str
+
+
+class TestNotificationBus(AsyncRedisEventBus[TestEvent]):
+    """Test implementation of AsyncRedisEventBus."""
+
+    Model = TestEvent
+
+    @property
+    def event_bus_name(self) -> str:
+        return "test_event_bus"
+
+
+@pytest.mark.asyncio
+async def test_publish_event_handles_connection_failure_gracefully():
+    """Test that publish_event logs exception instead of raising when Redis is unavailable."""
+    bus = TestNotificationBus()
+    event = TestEvent(message="test message")
+
+    # Mock get_redis_async to raise connection error
+    with patch(
+        "backend.data.event_bus.redis.get_redis_async",
+        side_effect=ConnectionError("Authentication required."),
+    ):
+        # Should not raise exception
+        await bus.publish_event(event, "test_channel")
+
+
+@pytest.mark.asyncio
+async def test_publish_event_works_with_redis_available():
+    """Test that publish_event works normally when Redis is available."""
+    bus = TestNotificationBus()
+    event = TestEvent(message="test message")
+
+    # Mock successful Redis connection
+    mock_redis = AsyncMock()
+    mock_redis.publish = AsyncMock()
+
+    with patch("backend.data.event_bus.redis.get_redis_async", return_value=mock_redis):
+        await bus.publish_event(event, "test_channel")
+        mock_redis.publish.assert_called_once()

autogpt_platform/backend/backend/data/execution.py

@@ -81,7 +81,10 @@ class ExecutionContext(BaseModel):
     This includes information needed by blocks, sub-graphs, and execution management.
     """
 
-    safe_mode: bool = True
+    model_config = {"extra": "ignore"}
+
+    human_in_the_loop_safe_mode: bool = True
+    sensitive_action_safe_mode: bool = False
     user_timezone: str = "UTC"
     root_execution_id: Optional[str] = None
     parent_execution_id: Optional[str] = None

autogpt_platform/backend/backend/data/graph.py

@@ -3,7 +3,7 @@ import logging
 import uuid
 from collections import defaultdict
 from datetime import datetime, timezone
-from typing import TYPE_CHECKING, Any, Literal, Optional, cast
+from typing import TYPE_CHECKING, Annotated, Any, Literal, Optional, cast
 
 from prisma.enums import SubmissionStatus
 from prisma.models import (
@@ -20,7 +20,7 @@ from prisma.types import (
     AgentNodeLinkCreateInput,
     StoreListingVersionWhereInput,
 )
-from pydantic import BaseModel, Field, create_model
+from pydantic import BaseModel, BeforeValidator, Field, create_model
 from pydantic.fields import computed_field
 
 from backend.blocks.agent import AgentExecutorBlock
@@ -62,7 +62,31 @@ logger = logging.getLogger(__name__)
 
 
 class GraphSettings(BaseModel):
-    human_in_the_loop_safe_mode: bool | None = None
+    # Use Annotated with BeforeValidator to coerce None to default values.
+    # This handles cases where the database has null values for these fields.
+    model_config = {"extra": "ignore"}
+
+    human_in_the_loop_safe_mode: Annotated[
+        bool, BeforeValidator(lambda v: v if v is not None else True)
+    ] = True
+    sensitive_action_safe_mode: Annotated[
+        bool, BeforeValidator(lambda v: v if v is not None else False)
+    ] = False
+
+    @classmethod
+    def from_graph(
+        cls,
+        graph: "GraphModel",
+        hitl_safe_mode: bool | None = None,
+        sensitive_action_safe_mode: bool = False,
+    ) -> "GraphSettings":
+        # Default to True if not explicitly set
+        if hitl_safe_mode is None:
+            hitl_safe_mode = True
+        return cls(
+            human_in_the_loop_safe_mode=hitl_safe_mode,
+            sensitive_action_safe_mode=sensitive_action_safe_mode,
+        )
 
 
 class Link(BaseDbModel):
@@ -244,10 +268,14 @@ class BaseGraph(BaseDbModel):
         return any(
             node.block_id
             for node in self.nodes
-            if (
+            if node.block.block_type == BlockType.HUMAN_IN_THE_LOOP
-                node.block.block_type == BlockType.HUMAN_IN_THE_LOOP
+        )
-                or node.block.requires_human_review
+
-            )
+    @computed_field
+    @property
+    def has_sensitive_action(self) -> bool:
+        return any(
+            node.block_id for node in self.nodes if node.block.is_sensitive_action
         )
 
     @property

autogpt_platform/backend/backend/data/human_review.py

@@ -32,6 +32,87 @@ class ReviewResult(BaseModel):
     node_exec_id: str
 
 
+def get_auto_approve_key(graph_exec_id: str, node_id: str) -> str:
+    """Generate the special nodeExecId key for auto-approval records."""
+    return f"auto_approve_{graph_exec_id}_{node_id}"
+
+
+async def check_auto_approval(
+    graph_exec_id: str,
+    node_id: str,
+) -> Optional[ReviewResult]:
+    """
+    Check if there's an existing auto-approval record for this node in this execution.
+
+    Auto-approval records are stored as PendingHumanReview entries with a special
+    nodeExecId pattern: "auto_approve_{graph_exec_id}_{node_id}"
+
+    Args:
+        graph_exec_id: ID of the graph execution
+        node_id: ID of the node definition (not execution)
+
+    Returns:
+        ReviewResult if auto-approval found, None otherwise
+    """
+    auto_approve_key = get_auto_approve_key(graph_exec_id, node_id)
+
+    # Look for the auto-approval record by its special key
+    auto_approved_review = await PendingHumanReview.prisma().find_unique(
+        where={"nodeExecId": auto_approve_key},
+    )
+
+    if auto_approved_review and auto_approved_review.status == ReviewStatus.APPROVED:
+        logger.info(
+            f"Found auto-approval for node {node_id} in execution {graph_exec_id}"
+        )
+        return ReviewResult(
+            data=auto_approved_review.payload,
+            status=ReviewStatus.APPROVED,
+            message="Auto-approved (user approved all future actions for this block)",
+            processed=True,
+            node_exec_id=auto_approve_key,
+        )
+
+    return None
+
+
+async def create_auto_approval_record(
+    user_id: str,
+    graph_exec_id: str,
+    graph_id: str,
+    graph_version: int,
+    node_id: str,
+    payload: SafeJsonData,
+) -> None:
+    """
+    Create an auto-approval record for a node in this execution.
+
+    This is stored as a PendingHumanReview with a special nodeExecId pattern
+    and status=APPROVED, so future executions of the same node can skip review.
+    """
+    auto_approve_key = get_auto_approve_key(graph_exec_id, node_id)
+
+    await PendingHumanReview.prisma().upsert(
+        where={"nodeExecId": auto_approve_key},
+        data={
+            "create": {
+                "nodeExecId": auto_approve_key,
+                "userId": user_id,
+                "graphExecId": graph_exec_id,
+                "graphId": graph_id,
+                "graphVersion": graph_version,
+                "payload": SafeJson(payload),
+                "instructions": "Auto-approval record",
+                "editable": False,
+                "status": ReviewStatus.APPROVED,
+                "processed": True,
+                "reviewedAt": datetime.now(timezone.utc),
+            },
+            "update": {},  # Already exists, no update needed
+        },
+    )
+
+
 async def get_or_create_human_review(
     user_id: str,
     node_exec_id: str,

autogpt_platform/backend/backend/data/human_review_test.py

@@ -46,8 +46,8 @@ async def test_get_or_create_human_review_new(
     sample_db_review.status = ReviewStatus.WAITING
     sample_db_review.processed = False
 
-    mock_upsert = mocker.patch("backend.data.human_review.PendingHumanReview.prisma")
+    mock_prisma = mocker.patch("backend.data.human_review.PendingHumanReview.prisma")
-    mock_upsert.return_value.upsert = AsyncMock(return_value=sample_db_review)
+    mock_prisma.return_value.upsert = AsyncMock(return_value=sample_db_review)
 
     result = await get_or_create_human_review(
         user_id="test-user-123",
@@ -75,8 +75,8 @@ async def test_get_or_create_human_review_approved(
     sample_db_review.processed = False
     sample_db_review.reviewMessage = "Looks good"
 
-    mock_upsert = mocker.patch("backend.data.human_review.PendingHumanReview.prisma")
+    mock_prisma = mocker.patch("backend.data.human_review.PendingHumanReview.prisma")
-    mock_upsert.return_value.upsert = AsyncMock(return_value=sample_db_review)
+    mock_prisma.return_value.upsert = AsyncMock(return_value=sample_db_review)
 
     result = await get_or_create_human_review(
         user_id="test-user-123",

autogpt_platform/backend/backend/executor/scheduler.py

@@ -309,7 +309,7 @@ def ensure_embeddings_coverage():
 
         # Process in batches until no more missing embeddings
         while True:
-            result = db_client.backfill_missing_embeddings(batch_size=10)
+            result = db_client.backfill_missing_embeddings(batch_size=100)
 
             total_processed += result["processed"]
             total_success += result["success"]

autogpt_platform/backend/backend/executor/utils.py

@@ -873,11 +873,8 @@ async def add_graph_execution(
         settings = await gdb.get_graph_settings(user_id=user_id, graph_id=graph_id)
 
         execution_context = ExecutionContext(
-            safe_mode=(
+            human_in_the_loop_safe_mode=settings.human_in_the_loop_safe_mode,
-                settings.human_in_the_loop_safe_mode
+            sensitive_action_safe_mode=settings.sensitive_action_safe_mode,
-                if settings.human_in_the_loop_safe_mode is not None
-                else True
-            ),
             user_timezone=(
                 user.timezone if user.timezone != USER_TIMEZONE_NOT_SET else "UTC"
             ),

autogpt_platform/backend/backend/executor/utils_test.py

@@ -386,6 +386,7 @@ async def test_add_graph_execution_is_repeatable(mocker: MockerFixture):
     mock_user.timezone = "UTC"
     mock_settings = mocker.MagicMock()
     mock_settings.human_in_the_loop_safe_mode = True
+    mock_settings.sensitive_action_safe_mode = False
 
     mock_udb.get_user_by_id = mocker.AsyncMock(return_value=mock_user)
     mock_gdb.get_graph_settings = mocker.AsyncMock(return_value=mock_settings)
@@ -651,6 +652,7 @@ async def test_add_graph_execution_with_nodes_to_skip(mocker: MockerFixture):
     mock_user.timezone = "UTC"
     mock_settings = mocker.MagicMock()
     mock_settings.human_in_the_loop_safe_mode = True
+    mock_settings.sensitive_action_safe_mode = False
 
     mock_udb.get_user_by_id = mocker.AsyncMock(return_value=mock_user)
     mock_gdb.get_graph_settings = mocker.AsyncMock(return_value=mock_settings)

autogpt_platform/backend/migrations/20260109181714_add_docs_embedding/migration.sql

@@ -1,9 +1,10 @@
 -- CreateExtension
 -- Supabase: pgvector must be enabled via Dashboard → Database → Extensions first
--- Create in public schema so vector type is available across all schemas
+-- Creates extension in current schema (determined by search_path from DATABASE_URL ?schema= param)
+-- This ensures vector type is in the same schema as tables, making ::vector work without explicit qualification
 DO $$
 BEGIN
-    CREATE EXTENSION IF NOT EXISTS "vector" WITH SCHEMA "public";
+    CREATE EXTENSION IF NOT EXISTS "vector";
 EXCEPTION WHEN OTHERS THEN
     RAISE NOTICE 'vector extension not available or already exists, skipping';
 END $$;
@@ -19,7 +20,7 @@ CREATE TABLE "UnifiedContentEmbedding" (
     "contentType" "ContentType" NOT NULL,
     "contentId" TEXT NOT NULL,
     "userId" TEXT,
-    "embedding" public.vector(1536) NOT NULL,
+    "embedding" vector(1536) NOT NULL,
     "searchableText" TEXT NOT NULL,
     "metadata" JSONB NOT NULL DEFAULT '{}',
 
@@ -45,4 +46,4 @@ CREATE UNIQUE INDEX "UnifiedContentEmbedding_contentType_contentId_userId_key" O
 -- Uses cosine distance operator (<=>), which matches the query in hybrid_search.py
 -- Note: Drop first in case Prisma created a btree index (Prisma doesn't support HNSW)
 DROP INDEX IF EXISTS "UnifiedContentEmbedding_embedding_idx";
-CREATE INDEX "UnifiedContentEmbedding_embedding_idx" ON "UnifiedContentEmbedding" USING hnsw ("embedding" public.vector_cosine_ops);
+CREATE INDEX "UnifiedContentEmbedding_embedding_idx" ON "UnifiedContentEmbedding" USING hnsw ("embedding" vector_cosine_ops);

autogpt_platform/backend/migrations/20260121200000_remove_node_execution_fk_from_pending_human_review/migration.sql

@@ -0,0 +1,7 @@
+-- Remove NodeExecution foreign key from PendingHumanReview
+-- The nodeExecId column remains as the primary key, but we remove the FK constraint
+-- to AgentNodeExecution since PendingHumanReview records can persist after node
+-- execution records are deleted.
+
+-- Drop foreign key constraint that linked PendingHumanReview.nodeExecId to AgentNodeExecution.id
+ALTER TABLE "platform"."PendingHumanReview" DROP CONSTRAINT IF EXISTS "PendingHumanReview_nodeExecId_fkey";

autogpt_platform/backend/schema.prisma

@@ -517,8 +517,6 @@ model AgentNodeExecution {
 
   stats Json?
 
-  PendingHumanReview PendingHumanReview?
-
   @@index([agentGraphExecutionId, agentNodeId, executionStatus])
   @@index([agentNodeId, executionStatus])
   @@index([addedTime, queuedTime])
@@ -567,6 +565,7 @@ enum ReviewStatus {
 }
 
 // Pending human reviews for Human-in-the-loop blocks
+// Also stores auto-approval records with special nodeExecId patterns (e.g., "auto_approve_{graph_exec_id}_{node_id}")
 model PendingHumanReview {
   nodeExecId    String       @id
   userId        String
@@ -585,7 +584,6 @@ model PendingHumanReview {
   reviewedAt    DateTime?
 
   User           User                @relation(fields: [userId], references: [id], onDelete: Cascade)
-  NodeExecution  AgentNodeExecution  @relation(fields: [nodeExecId], references: [id], onDelete: Cascade)
   GraphExecution AgentGraphExecution @relation(fields: [graphExecId], references: [id], onDelete: Cascade)
 
   @@unique([nodeExecId]) // One pending review per node execution

autogpt_platform/backend/scripts/generate_block_docs.py

@@ -366,12 +366,12 @@ def generate_block_markdown(
     lines.append("")
 
     # What it is (full description)
-    lines.append(f"### What it is")
+    lines.append("### What it is")
     lines.append(block.description or "No description available.")
     lines.append("")
 
     # How it works (manual section)
-    lines.append(f"### How it works")
+    lines.append("### How it works")
     how_it_works = manual_content.get(
         "how_it_works", "_Add technical explanation here._"
     )
@@ -383,7 +383,7 @@ def generate_block_markdown(
     # Inputs table (auto-generated)
     visible_inputs = [f for f in block.inputs if not f.hidden]
     if visible_inputs:
-        lines.append(f"### Inputs")
+        lines.append("### Inputs")
         lines.append("")
         lines.append("| Input | Description | Type | Required |")
         lines.append("|-------|-------------|------|----------|")
@@ -400,7 +400,7 @@ def generate_block_markdown(
     # Outputs table (auto-generated)
     visible_outputs = [f for f in block.outputs if not f.hidden]
     if visible_outputs:
-        lines.append(f"### Outputs")
+        lines.append("### Outputs")
         lines.append("")
         lines.append("| Output | Description | Type |")
         lines.append("|--------|-------------|------|")
@@ -414,7 +414,7 @@ def generate_block_markdown(
         lines.append("")
 
     # Possible use case (manual section)
-    lines.append(f"### Possible use case")
+    lines.append("### Possible use case")
     use_case = manual_content.get("use_case", "_Add practical use case examples here._")
     lines.append("<!-- MANUAL: use_case -->")
     lines.append(use_case)

autogpt_platform/backend/snapshots/grph_single

@@ -11,6 +11,7 @@
   "forked_from_version": null,
   "has_external_trigger": false,
   "has_human_in_the_loop": false,
+  "has_sensitive_action": false,
   "id": "graph-123",
   "input_schema": {
     "properties": {},

autogpt_platform/backend/snapshots/grphs_all

@@ -11,6 +11,7 @@
     "forked_from_version": null,
     "has_external_trigger": false,
     "has_human_in_the_loop": false,
+    "has_sensitive_action": false,
     "id": "graph-123",
     "input_schema": {
       "properties": {},

autogpt_platform/backend/snapshots/lib_agts_search

@@ -27,6 +27,8 @@
         "properties": {}
       },
       "has_external_trigger": false,
+      "has_human_in_the_loop": false,
+      "has_sensitive_action": false,
       "trigger_setup_info": null,
       "new_output": false,
       "can_access_graph": true,
@@ -34,7 +36,8 @@
       "is_favorite": false,
       "recommended_schedule_cron": null,
       "settings": {
-        "human_in_the_loop_safe_mode": null
+        "human_in_the_loop_safe_mode": true,
+        "sensitive_action_safe_mode": false
       },
       "marketplace_listing": null
     },
@@ -65,6 +68,8 @@
         "properties": {}
       },
       "has_external_trigger": false,
+      "has_human_in_the_loop": false,
+      "has_sensitive_action": false,
       "trigger_setup_info": null,
       "new_output": false,
       "can_access_graph": false,
@@ -72,7 +77,8 @@
       "is_favorite": false,
       "recommended_schedule_cron": null,
       "settings": {
-        "human_in_the_loop_safe_mode": null
+        "human_in_the_loop_safe_mode": true,
+        "sensitive_action_safe_mode": false
       },
       "marketplace_listing": null
     }

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

@@ -5,10 +5,11 @@ import {
   TooltipContent,
   TooltipTrigger,
 } from "@/components/atoms/Tooltip/BaseTooltip";
-import { PlayIcon, StopIcon } from "@phosphor-icons/react";
+import { CircleNotchIcon, PlayIcon, StopIcon } from "@phosphor-icons/react";
 import { useShallow } from "zustand/react/shallow";
 import { RunInputDialog } from "../RunInputDialog/RunInputDialog";
 import { useRunGraph } from "./useRunGraph";
+import { cn } from "@/lib/utils";
 
 export const RunGraph = ({ flowID }: { flowID: string | null }) => {
   const {
@@ -24,6 +25,31 @@ export const RunGraph = ({ flowID }: { flowID: string | null }) => {
     useShallow((state) => state.isGraphRunning),
   );
 
+  const isLoading = isExecutingGraph || isTerminatingGraph || isSaving;
+
+  // Determine which icon to show with proper animation
+  const renderIcon = () => {
+    const iconClass = cn(
+      "size-4 transition-transform duration-200 ease-out",
+      !isLoading && "group-hover:scale-110",
+    );
+
+    if (isLoading) {
+      return (
+        <CircleNotchIcon
+          className={cn(iconClass, "animate-spin")}
+          weight="bold"
+        />
+      );
+    }
+
+    if (isGraphRunning) {
+      return <StopIcon className={iconClass} weight="fill" />;
+    }
+
+    return <PlayIcon className={iconClass} weight="fill" />;
+  };
+
   return (
     <>
       <Tooltip>
@@ -33,18 +59,18 @@ export const RunGraph = ({ flowID }: { flowID: string | null }) => {
             variant={isGraphRunning ? "destructive" : "primary"}
             data-id={isGraphRunning ? "stop-graph-button" : "run-graph-button"}
             onClick={isGraphRunning ? handleStopGraph : handleRunGraph}
-            disabled={!flowID || isExecutingGraph || isTerminatingGraph}
+            disabled={!flowID || isLoading}
-            loading={isExecutingGraph || isTerminatingGraph || isSaving}
+            className="group"
           >
-            {!isGraphRunning ? (
+            {renderIcon()}
-              <PlayIcon className="size-4" />
-            ) : (
-              <StopIcon className="size-4" />
-            )}
           </Button>
         </TooltipTrigger>
         <TooltipContent>
-          {isGraphRunning ? "Stop agent" : "Run agent"}
+          {isLoading
+            ? "Processing..."
+            : isGraphRunning
+              ? "Stop agent"
+              : "Run agent"}
         </TooltipContent>
       </Tooltip>
       <RunInputDialog

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

@@ -61,63 +61,67 @@ export const RunInputDialog = ({
           isOpen,
           set: setIsOpen,
         }}
-        styling={{ maxWidth: "600px", minWidth: "600px" }}
+        styling={{ maxWidth: "700px", minWidth: "700px" }}
       >
         <Dialog.Content>
-          <div className="space-y-6 p-1" data-id="run-input-dialog-content">
+          <div
-            {/* Credentials Section */}
+            className="grid grid-cols-[1fr_auto] gap-10 p-1"
-            {hasCredentials() && credentialFields.length > 0 && (
+            data-id="run-input-dialog-content"
-              <div data-id="run-input-credentials-section">
+          >
-                <div className="mb-4">
+            <div className="space-y-6">
-                  <Text variant="h4" className="text-gray-900">
+              {/* Credentials Section */}
-                    Credentials
+              {hasCredentials() && credentialFields.length > 0 && (
-                  </Text>
+                <div data-id="run-input-credentials-section">
+                  <div className="mb-4">
+                    <Text variant="h4" className="text-gray-900">
+                      Credentials
+                    </Text>
+                  </div>
+                  <div className="px-2" data-id="run-input-credentials-form">
+                    <CredentialsGroupedView
+                      credentialFields={credentialFields}
+                      requiredCredentials={requiredCredentials}
+                      inputCredentials={credentialValues}
+                      inputValues={inputValues}
+                      onCredentialChange={handleCredentialFieldChange}
+                    />
+                  </div>
                 </div>
-                <div className="px-2" data-id="run-input-credentials-form">
+              )}
-                  <CredentialsGroupedView
-                    credentialFields={credentialFields}
-                    requiredCredentials={requiredCredentials}
-                    inputCredentials={credentialValues}
-                    inputValues={inputValues}
-                    onCredentialChange={handleCredentialFieldChange}
-                  />
-                </div>
-              </div>
-            )}
 
-            {/* Inputs Section */}
+              {/* Inputs Section */}
-            {hasInputs() && (
+              {hasInputs() && (
-              <div data-id="run-input-inputs-section">
+                <div data-id="run-input-inputs-section">
-                <div className="mb-4">
+                  <div className="mb-4">
-                  <Text variant="h4" className="text-gray-900">
+                    <Text variant="h4" className="text-gray-900">
-                    Inputs
+                      Inputs
-                  </Text>
+                    </Text>
+                  </div>
+                  <div data-id="run-input-inputs-form">
+                    <FormRenderer
+                      jsonSchema={inputSchema as RJSFSchema}
+                      handleChange={(v) => handleInputChange(v.formData)}
+                      uiSchema={uiSchema}
+                      initialValues={{}}
+                      formContext={{
+                        showHandles: false,
+                        size: "large",
+                      }}
+                    />
+                  </div>
                 </div>
-                <div data-id="run-input-inputs-form">
+              )}
-                  <FormRenderer
+            </div>
-                    jsonSchema={inputSchema as RJSFSchema}
-                    handleChange={(v) => handleInputChange(v.formData)}
-                    uiSchema={uiSchema}
-                    initialValues={{}}
-                    formContext={{
-                      showHandles: false,
-                      size: "large",
-                    }}
-                  />
-                </div>
-              </div>
-            )}
 
-            {/* Action Button */}
             <div
-              className="flex justify-end pt-2"
+              className="flex flex-col items-end justify-start"
               data-id="run-input-actions-section"
             >
               {purpose === "run" && (
                 <Button
                   variant="primary"
                   size="large"
-                  className="group h-fit min-w-0 gap-2"
+                  className="group h-fit min-w-0 gap-2 px-10"
                   onClick={handleManualRun}
                   loading={isExecutingGraph}
                   data-id="run-input-manual-run-button"
@@ -132,7 +136,7 @@ export const RunInputDialog = ({
                 <Button
                   variant="primary"
                   size="large"
-                  className="group h-fit min-w-0 gap-2"
+                  className="group h-fit min-w-0 gap-2 px-10"
                   onClick={() => setOpenCronSchedulerDialog(true)}
                   data-id="run-input-schedule-button"
                 >

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

@@ -18,69 +18,110 @@ interface Props {
   fullWidth?: boolean;
 }
 
+interface SafeModeButtonProps {
+  isEnabled: boolean;
+  label: string;
+  tooltipEnabled: string;
+  tooltipDisabled: string;
+  onToggle: () => void;
+  isPending: boolean;
+  fullWidth?: boolean;
+}
+
+function SafeModeButton({
+  isEnabled,
+  label,
+  tooltipEnabled,
+  tooltipDisabled,
+  onToggle,
+  isPending,
+  fullWidth = false,
+}: SafeModeButtonProps) {
+  return (
+    <Tooltip delayDuration={100}>
+      <TooltipTrigger asChild>
+        <Button
+          variant={isEnabled ? "primary" : "outline"}
+          size="small"
+          onClick={onToggle}
+          disabled={isPending}
+          className={cn("justify-start", fullWidth ? "w-full" : "")}
+        >
+          {isEnabled ? (
+            <>
+              <ShieldCheckIcon weight="bold" size={16} />
+              <Text variant="body" className="text-zinc-200">
+                {label}: ON
+              </Text>
+            </>
+          ) : (
+            <>
+              <ShieldIcon weight="bold" size={16} />
+              <Text variant="body" className="text-zinc-600">
+                {label}: OFF
+              </Text>
+            </>
+          )}
+        </Button>
+      </TooltipTrigger>
+      <TooltipContent>
+        <div className="text-center">
+          <div className="font-medium">
+            {label}: {isEnabled ? "ON" : "OFF"}
+          </div>
+          <div className="mt-1 text-xs text-muted-foreground">
+            {isEnabled ? tooltipEnabled : tooltipDisabled}
+          </div>
+        </div>
+      </TooltipContent>
+    </Tooltip>
+  );
+}
+
 export function FloatingSafeModeToggle({
   graph,
   className,
   fullWidth = false,
 }: Props) {
   const {
-    currentSafeMode,
+    currentHITLSafeMode,
+    showHITLToggle,
+    handleHITLToggle,
+    currentSensitiveActionSafeMode,
+    showSensitiveActionToggle,
+    handleSensitiveActionToggle,
     isPending,
     shouldShowToggle,
-    isStateUndetermined,
-    handleToggle,
   } = useAgentSafeMode(graph);
 
-  if (!shouldShowToggle || isStateUndetermined || isPending) {
+  if (!shouldShowToggle || isPending) {
     return null;
   }
 
   return (
-    <div className={cn("fixed z-50", className)}>
+    <div className={cn("fixed z-50 flex flex-col gap-2", className)}>
-      <Tooltip delayDuration={100}>
+      {showHITLToggle && (
-        <TooltipTrigger asChild>
+        <SafeModeButton
-          <Button
+          isEnabled={currentHITLSafeMode}
-            variant={currentSafeMode! ? "primary" : "outline"}
+          label="Human in the loop block approval"
-            key={graph.id}
+          tooltipEnabled="The agent will pause at human-in-the-loop blocks and wait for your approval"
-            size="small"
+          tooltipDisabled="Human in the loop blocks will proceed automatically"
-            title={
+          onToggle={handleHITLToggle}
-              currentSafeMode!
+          isPending={isPending}
-                ? "Safe Mode: ON. Human in the loop blocks require manual review"
+          fullWidth={fullWidth}
-                : "Safe Mode: OFF. Human in the loop blocks proceed automatically"
+        />
-            }
+      )}
-            onClick={handleToggle}
+      {showSensitiveActionToggle && (
-            className={cn(fullWidth ? "w-full" : "")}
+        <SafeModeButton
-          >
+          isEnabled={currentSensitiveActionSafeMode}
-            {currentSafeMode! ? (
+          label="Sensitive actions blocks approval"
-              <>
+          tooltipEnabled="The agent will pause at sensitive action blocks and wait for your approval"
-                <ShieldCheckIcon weight="bold" size={16} />
+          tooltipDisabled="Sensitive action blocks will proceed automatically"
-                <Text variant="body" className="text-zinc-200">
+          onToggle={handleSensitiveActionToggle}
-                  Safe Mode: ON
+          isPending={isPending}
-                </Text>
+          fullWidth={fullWidth}
-              </>
+        />
-            ) : (
+      )}
-              <>
-                <ShieldIcon weight="bold" size={16} />
-                <Text variant="body" className="text-zinc-600">
-                  Safe Mode: OFF
-                </Text>
-              </>
-            )}
-          </Button>
-        </TooltipTrigger>
-        <TooltipContent>
-          <div className="text-center">
-            <div className="font-medium">
-              Safe Mode: {currentSafeMode! ? "ON" : "OFF"}
-            </div>
-            <div className="mt-1 text-xs text-muted-foreground">
-              {currentSafeMode!
-                ? "Human in the loop blocks require manual review"
-                : "Human in the loop blocks proceed automatically"}
-            </div>
-          </div>
-        </TooltipContent>
-      </Tooltip>
     </div>
   );
 }

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

@@ -53,14 +53,14 @@ export const CustomControls = memo(
     const controls = [
       {
         id: "zoom-in-button",
-        icon: <PlusIcon className="size-4" />,
+        icon: <PlusIcon className="size-3.5 text-zinc-600" />,
         label: "Zoom In",
         onClick: () => zoomIn(),
         className: "h-10 w-10 border-none",
       },
       {
         id: "zoom-out-button",
-        icon: <MinusIcon className="size-4" />,
+        icon: <MinusIcon className="size-3.5 text-zinc-600" />,
         label: "Zoom Out",
         onClick: () => zoomOut(),
         className: "h-10 w-10 border-none",
@@ -68,9 +68,9 @@ export const CustomControls = memo(
       {
         id: "tutorial-button",
         icon: isTutorialLoading ? (
-          <CircleNotchIcon className="size-4 animate-spin" />
+          <CircleNotchIcon className="size-3.5 animate-spin text-zinc-600" />
         ) : (
-          <ChalkboardIcon className="size-4" />
+          <ChalkboardIcon className="size-3.5 text-zinc-600" />
         ),
         label: isTutorialLoading ? "Loading Tutorial..." : "Start Tutorial",
         onClick: handleTutorialClick,
@@ -79,7 +79,7 @@ export const CustomControls = memo(
       },
       {
         id: "fit-view-button",
-        icon: <FrameCornersIcon className="size-4" />,
+        icon: <FrameCornersIcon className="size-3.5 text-zinc-600" />,
         label: "Fit View",
         onClick: () => fitView({ padding: 0.2, duration: 800, maxZoom: 1 }),
         className: "h-10 w-10 border-none",
@@ -87,9 +87,9 @@ export const CustomControls = memo(
       {
         id: "lock-button",
         icon: !isLocked ? (
-          <LockOpenIcon className="size-4" />
+          <LockOpenIcon className="size-3.5 text-zinc-600" />
         ) : (
-          <LockIcon className="size-4" />
+          <LockIcon className="size-3.5 text-zinc-600" />
         ),
         label: "Toggle Lock",
         onClick: () => setIsLocked(!isLocked),

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

@@ -19,6 +19,8 @@ export type CustomEdgeData = {
   beadUp?: number;
   beadDown?: number;
   beadData?: Map<string, NodeExecutionResult["status"]>;
+  edgeColorClass?: string;
+  edgeHexColor?: string;
 };
 
 export type CustomEdge = XYEdge<CustomEdgeData, "custom">;
@@ -36,7 +38,6 @@ const CustomEdge = ({
   selected,
 }: EdgeProps<CustomEdge>) => {
   const removeConnection = useEdgeStore((state) => state.removeEdge);
-  // Subscribe to the brokenEdgeIDs map and check if this edge is broken across any node
   const isBroken = useNodeStore((state) => state.isEdgeBroken(id));
   const [isHovered, setIsHovered] = useState(false);
 
@@ -52,6 +53,7 @@ const CustomEdge = ({
   const isStatic = data?.isStatic ?? false;
   const beadUp = data?.beadUp ?? 0;
   const beadDown = data?.beadDown ?? 0;
+  const edgeColorClass = data?.edgeColorClass;
 
   const handleRemoveEdge = () => {
     removeConnection(id);
@@ -70,7 +72,9 @@ const CustomEdge = ({
             ? "!stroke-red-500 !stroke-[2px] [stroke-dasharray:4]"
             : selected
               ? "stroke-zinc-800"
-              : "stroke-zinc-500/50 hover:stroke-zinc-500",
+              : edgeColorClass
+                ? cn(edgeColorClass, "opacity-70 hover:opacity-100")
+                : "stroke-zinc-500/50 hover:stroke-zinc-500",
         )}
       />
       <JSBeads

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

@@ -8,6 +8,7 @@ import { useCallback } from "react";
 import { useNodeStore } from "../../../stores/nodeStore";
 import { useHistoryStore } from "../../../stores/historyStore";
 import { CustomEdge } from "./CustomEdge";
+import { getEdgeColorFromOutputType } from "../nodes/helpers";
 
 export const useCustomEdge = () => {
   const edges = useEdgeStore((s) => s.edges);
@@ -34,8 +35,13 @@ export const useCustomEdge = () => {
       if (exists) return;
 
       const nodes = useNodeStore.getState().nodes;
-      const isStatic = nodes.find((n) => n.id === conn.source)?.data
+      const sourceNode = nodes.find((n) => n.id === conn.source);
-        ?.staticOutput;
+      const isStatic = sourceNode?.data?.staticOutput;
+
+      const { colorClass, hexColor } = getEdgeColorFromOutputType(
+        sourceNode?.data?.outputSchema,
+        conn.sourceHandle,
+      );
 
       addEdge({
         source: conn.source,
@@ -44,6 +50,8 @@ export const useCustomEdge = () => {
         targetHandle: conn.targetHandle,
         data: {
           isStatic,
+          edgeColorClass: colorClass,
+          edgeHexColor: hexColor,
         },
       });
     },

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

@@ -187,3 +187,38 @@ export const getTypeDisplayInfo = (schema: any) => {
     hexColor,
   };
 };
+
+export function getEdgeColorFromOutputType(
+  outputSchema: RJSFSchema | undefined,
+  sourceHandle: string,
+): { colorClass: string; hexColor: string } {
+  const defaultColor = {
+    colorClass: "stroke-zinc-500/50",
+    hexColor: "#6b7280",
+  };
+
+  if (!outputSchema?.properties) return defaultColor;
+
+  const properties = outputSchema.properties as Record<string, unknown>;
+  const handleParts = sourceHandle.split("_#_");
+  let currentSchema: Record<string, unknown> = properties;
+
+  for (let i = 0; i < handleParts.length; i++) {
+    const part = handleParts[i];
+    const fieldSchema = currentSchema[part] as Record<string, unknown>;
+    if (!fieldSchema) return defaultColor;
+
+    if (i === handleParts.length - 1) {
+      const { hexColor, colorClass } = getTypeDisplayInfo(fieldSchema);
+      return { colorClass: colorClass.replace("!text-", "stroke-"), hexColor };
+    }
+
+    if (fieldSchema.properties) {
+      currentSchema = fieldSchema.properties as Record<string, unknown>;
+    } else {
+      return defaultColor;
+    }
+  }
+
+  return defaultColor;
+}

autogpt_platform/frontend/src/app/(platform)/build/components/FlowEditor/tutorial/icons.ts

@@ -1,7 +1,32 @@
-// These are SVG Phosphor icons
+type IconOptions = {
+  size?: number;
+  color?: string;
+};
+
+const DEFAULT_SIZE = 16;
+const DEFAULT_COLOR = "#52525b"; // zinc-600
+
+const iconPaths = {
+  ClickIcon: `M88,24V16a8,8,0,0,1,16,0v8a8,8,0,0,1-16,0ZM16,104h8a8,8,0,0,0,0-16H16a8,8,0,0,0,0,16ZM124.42,39.16a8,8,0,0,0,10.74-3.58l8-16a8,8,0,0,0-14.31-7.16l-8,16A8,8,0,0,0,124.42,39.16Zm-96,81.69-16,8a8,8,0,0,0,7.16,14.31l16-8a8,8,0,1,0-7.16-14.31ZM219.31,184a16,16,0,0,1,0,22.63l-12.68,12.68a16,16,0,0,1-22.63,0L132.7,168,115,214.09c0,.1-.08.21-.13.32a15.83,15.83,0,0,1-14.6,9.59l-.79,0a15.83,15.83,0,0,1-14.41-11L32.8,52.92A16,16,0,0,1,52.92,32.8L213,85.07a16,16,0,0,1,1.41,29.8l-.32.13L168,132.69ZM208,195.31,156.69,144h0a16,16,0,0,1,4.93-26l.32-.14,45.95-17.64L48,48l52.2,159.86,17.65-46c0-.11.08-.22.13-.33a16,16,0,0,1,11.69-9.34,16.72,16.72,0,0,1,3-.28,16,16,0,0,1,11.3,4.69L195.31,208Z`,
+  Keyboard: `M224,48H32A16,16,0,0,0,16,64V192a16,16,0,0,0,16,16H224a16,16,0,0,0,16-16V64A16,16,0,0,0,224,48Zm0,144H32V64H224V192Zm-16-64a8,8,0,0,1-8,8H56a8,8,0,0,1,0-16H200A8,8,0,0,1,208,128Zm0-32a8,8,0,0,1-8,8H56a8,8,0,0,1,0-16H200A8,8,0,0,1,208,96ZM72,160a8,8,0,0,1-8,8H56a8,8,0,0,1,0-16h8A8,8,0,0,1,72,160Zm96,0a8,8,0,0,1-8,8H96a8,8,0,0,1,0-16h64A8,8,0,0,1,168,160Zm40,0a8,8,0,0,1-8,8h-8a8,8,0,0,1,0-16h8A8,8,0,0,1,208,160Z`,
+  Drag: `M188,80a27.79,27.79,0,0,0-13.36,3.4,28,28,0,0,0-46.64-11A28,28,0,0,0,80,92v20H68a28,28,0,0,0-28,28v12a88,88,0,0,0,176,0V108A28,28,0,0,0,188,80Zm12,72a72,72,0,0,1-144,0V140a12,12,0,0,1,12-12H80v24a8,8,0,0,0,16,0V92a12,12,0,0,1,24,0v28a8,8,0,0,0,16,0V92a12,12,0,0,1,24,0v28a8,8,0,0,0,16,0V108a12,12,0,0,1,24,0Z`,
+};
+
+function createIcon(path: string, options: IconOptions = {}): string {
+  const size = options.size ?? DEFAULT_SIZE;
+  const color = options.color ?? DEFAULT_COLOR;
+  return `<svg xmlns="http://www.w3.org/2000/svg" width="${size}" height="${size}" fill="${color}" viewBox="0 0 256 256"><path d="${path}"></path></svg>`;
+}
 
 export const ICONS = {
-  ClickIcon: `<svg xmlns="http://www.w3.org/2000/svg" width="20" height="20" fill="#000000" viewBox="0 0 256 256"><path d="M88,24V16a8,8,0,0,1,16,0v8a8,8,0,0,1-16,0ZM16,104h8a8,8,0,0,0,0-16H16a8,8,0,0,0,0,16ZM124.42,39.16a8,8,0,0,0,10.74-3.58l8-16a8,8,0,0,0-14.31-7.16l-8,16A8,8,0,0,0,124.42,39.16Zm-96,81.69-16,8a8,8,0,0,0,7.16,14.31l16-8a8,8,0,1,0-7.16-14.31ZM219.31,184a16,16,0,0,1,0,22.63l-12.68,12.68a16,16,0,0,1-22.63,0L132.7,168,115,214.09c0,.1-.08.21-.13.32a15.83,15.83,0,0,1-14.6,9.59l-.79,0a15.83,15.83,0,0,1-14.41-11L32.8,52.92A16,16,0,0,1,52.92,32.8L213,85.07a16,16,0,0,1,1.41,29.8l-.32.13L168,132.69ZM208,195.31,156.69,144h0a16,16,0,0,1,4.93-26l.32-.14,45.95-17.64L48,48l52.2,159.86,17.65-46c0-.11.08-.22.13-.33a16,16,0,0,1,11.69-9.34,16.72,16.72,0,0,1,3-.28,16,16,0,0,1,11.3,4.69L195.31,208Z"></path></svg>`,
+  ClickIcon: createIcon(iconPaths.ClickIcon),
-  Keyboard: `<svg xmlns="http://www.w3.org/2000/svg" width="20" height="20" fill="#000000" viewBox="0 0 256 256"><path d="M224,48H32A16,16,0,0,0,16,64V192a16,16,0,0,0,16,16H224a16,16,0,0,0,16-16V64A16,16,0,0,0,224,48Zm0,144H32V64H224V192Zm-16-64a8,8,0,0,1-8,8H56a8,8,0,0,1,0-16H200A8,8,0,0,1,208,128Zm0-32a8,8,0,0,1-8,8H56a8,8,0,0,1,0-16H200A8,8,0,0,1,208,96ZM72,160a8,8,0,0,1-8,8H56a8,8,0,0,1,0-16h8A8,8,0,0,1,72,160Zm96,0a8,8,0,0,1-8,8H96a8,8,0,0,1,0-16h64A8,8,0,0,1,168,160Zm40,0a8,8,0,0,1-8,8h-8a8,8,0,0,1,0-16h8A8,8,0,0,1,208,160Z"></path></svg>`,
+  Keyboard: createIcon(iconPaths.Keyboard),
-  Drag: `<svg xmlns="http://www.w3.org/2000/svg" width="20" height="20" fill="#000000" viewBox="0 0 256 256"><path d="M188,80a27.79,27.79,0,0,0-13.36,3.4,28,28,0,0,0-46.64-11A28,28,0,0,0,80,92v20H68a28,28,0,0,0-28,28v12a88,88,0,0,0,176,0V108A28,28,0,0,0,188,80Zm12,72a72,72,0,0,1-144,0V140a12,12,0,0,1,12-12H80v24a8,8,0,0,0,16,0V92a12,12,0,0,1,24,0v28a8,8,0,0,0,16,0V92a12,12,0,0,1,24,0v28a8,8,0,0,0,16,0V108a12,12,0,0,1,24,0Z"></path></svg>`,
+  Drag: createIcon(iconPaths.Drag),
 };
+
+export function getIcon(
+  name: keyof typeof iconPaths,
+  options?: IconOptions,
+): string {
+  return createIcon(iconPaths[name], options);
+}

autogpt_platform/frontend/src/app/(platform)/build/components/FlowEditor/tutorial/index.ts

@@ -11,6 +11,7 @@ import {
 } from "./helpers";
 import { useNodeStore } from "../../../stores/nodeStore";
 import { useEdgeStore } from "../../../stores/edgeStore";
+import { useTutorialStore } from "../../../stores/tutorialStore";
 
 let isTutorialLoading = false;
 let tutorialLoadingCallback: ((loading: boolean) => void) | null = null;
@@ -60,12 +61,14 @@ export const startTutorial = async () => {
     handleTutorialComplete();
     removeTutorialStyles();
     clearPrefetchedBlocks();
+    useTutorialStore.getState().setIsTutorialRunning(false);
   });
 
   tour.on("cancel", () => {
     handleTutorialCancel(tour);
     removeTutorialStyles();
     clearPrefetchedBlocks();
+    useTutorialStore.getState().setIsTutorialRunning(false);
   });
 
   for (const step of tour.steps) {

autogpt_platform/frontend/src/app/(platform)/chat/components/Chat/components/ChatContainer/helpers.ts

@@ -267,23 +267,34 @@ export function extractCredentialsNeeded(
       | undefined;
     if (missingCreds && Object.keys(missingCreds).length > 0) {
       const agentName = (setupInfo?.agent_name as string) || "this block";
-      const credentials = Object.values(missingCreds).map((credInfo) => ({
+      const credentials = Object.values(missingCreds).map((credInfo) => {
-        provider: (credInfo.provider as string) || "unknown",
+        // Normalize to array at boundary - prefer 'types' array, fall back to single 'type'
-        providerName:
+        const typesArray = credInfo.types as
-          (credInfo.provider_name as string) ||
+          | Array<"api_key" | "oauth2" | "user_password" | "host_scoped">
-          (credInfo.provider as string) ||
+          | undefined;
-          "Unknown Provider",
+        const singleType =
-        credentialType:
           (credInfo.type as
             | "api_key"
             | "oauth2"
             | "user_password"
-            | "host_scoped") || "api_key",
+            | "host_scoped"
-        title:
+            | undefined) || "api_key";
-          (credInfo.title as string) ||
+        const credentialTypes =
-          `${(credInfo.provider_name as string) || (credInfo.provider as string)} credentials`,
+          typesArray && typesArray.length > 0 ? typesArray : [singleType];
-        scopes: credInfo.scopes as string[] | undefined,
+
-      }));
+        return {
+          provider: (credInfo.provider as string) || "unknown",
+          providerName:
+            (credInfo.provider_name as string) ||
+            (credInfo.provider as string) ||
+            "Unknown Provider",
+          credentialTypes,
+          title:
+            (credInfo.title as string) ||
+            `${(credInfo.provider_name as string) || (credInfo.provider as string)} credentials`,
+          scopes: credInfo.scopes as string[] | undefined,
+        };
+      });
       return {
         type: "credentials_needed",
         toolName,
@@ -358,11 +369,14 @@ export function extractInputsNeeded(
       credentials.forEach((cred) => {
         const id = cred.id as string;
         if (id) {
+          const credentialTypes = Array.isArray(cred.types)
+            ? cred.types
+            : [(cred.type as string) || "api_key"];
           credentialsSchema[id] = {
             type: "object",
             properties: {},
             credentials_provider: [cred.provider as string],
-            credentials_types: [(cred.type as string) || "api_key"],
+            credentials_types: credentialTypes,
             credentials_scopes: cred.scopes as string[] | undefined,
           };
         }

autogpt_platform/frontend/src/app/(platform)/chat/components/Chat/components/ChatCredentialsSetup/ChatCredentialsSetup.tsx

@@ -9,7 +9,9 @@ import { useChatCredentialsSetup } from "./useChatCredentialsSetup";
 export interface CredentialInfo {
   provider: string;
   providerName: string;
-  credentialType: "api_key" | "oauth2" | "user_password" | "host_scoped";
+  credentialTypes: Array<
+    "api_key" | "oauth2" | "user_password" | "host_scoped"
+  >;
   title: string;
   scopes?: string[];
 }
@@ -30,7 +32,7 @@ function createSchemaFromCredentialInfo(
     type: "object",
     properties: {},
     credentials_provider: [credential.provider],
-    credentials_types: [credential.credentialType],
+    credentials_types: credential.credentialTypes,
     credentials_scopes: credential.scopes,
     discriminator: undefined,
     discriminator_mapping: undefined,

autogpt_platform/frontend/src/app/(platform)/chat/components/Chat/components/ChatMessage/useChatMessage.ts

@@ -41,7 +41,9 @@ export type ChatMessageData =
       credentials: Array<{
         provider: string;
         providerName: string;
-        credentialType: "api_key" | "oauth2" | "user_password" | "host_scoped";
+        credentialTypes: Array<
+          "api_key" | "oauth2" | "user_password" | "host_scoped"
+        >;
         title: string;
         scopes?: string[];
       }>;

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

@@ -31,10 +31,18 @@ export function AgentSettingsModal({
     }
   }
 
-  const { currentSafeMode, isPending, hasHITLBlocks, handleToggle } =
+  const {
-    useAgentSafeMode(agent);
+    currentHITLSafeMode,
+    showHITLToggle,
+    handleHITLToggle,
+    currentSensitiveActionSafeMode,
+    showSensitiveActionToggle,
+    handleSensitiveActionToggle,
+    isPending,
+    shouldShowToggle,
+  } = useAgentSafeMode(agent);
 
-  if (!hasHITLBlocks) return null;
+  if (!shouldShowToggle) return null;
 
   return (
     <Dialog
@@ -57,23 +65,48 @@ export function AgentSettingsModal({
       )}
       <Dialog.Content>
         <div className="space-y-6">
-          <div className="flex w-full flex-col items-start gap-4 rounded-xl border border-zinc-100 bg-white p-6">
+          {showHITLToggle && (
-            <div className="flex w-full items-start justify-between gap-4">
+            <div className="flex w-full flex-col items-start gap-4 rounded-xl border border-zinc-100 bg-white p-6">
-              <div className="flex-1">
+              <div className="flex w-full items-start justify-between gap-4">
-                <Text variant="large-semibold">Require human approval</Text>
+                <div className="flex-1">
-                <Text variant="large" className="mt-1 text-zinc-900">
+                  <Text variant="large-semibold">
-                  The agent will pause and wait for your review before
+                    Human-in-the-loop approval
-                  continuing
+                  </Text>
-                </Text>
+                  <Text variant="large" className="mt-1 text-zinc-900">
+                    The agent will pause at human-in-the-loop blocks and wait
+                    for your review before continuing
+                  </Text>
+                </div>
+                <Switch
+                  checked={currentHITLSafeMode || false}
+                  onCheckedChange={handleHITLToggle}
+                  disabled={isPending}
+                  className="mt-1"
+                />
               </div>
-              <Switch
-                checked={currentSafeMode || false}
-                onCheckedChange={handleToggle}
-                disabled={isPending}
-                className="mt-1"
-              />
             </div>
-          </div>
+          )}
+          {showSensitiveActionToggle && (
+            <div className="flex w-full flex-col items-start gap-4 rounded-xl border border-zinc-100 bg-white p-6">
+              <div className="flex w-full items-start justify-between gap-4">
+                <div className="flex-1">
+                  <Text variant="large-semibold">
+                    Sensitive action approval
+                  </Text>
+                  <Text variant="large" className="mt-1 text-zinc-900">
+                    The agent will pause at sensitive action blocks and wait for
+                    your review before continuing
+                  </Text>
+                </div>
+                <Switch
+                  checked={currentSensitiveActionSafeMode}
+                  onCheckedChange={handleSensitiveActionToggle}
+                  disabled={isPending}
+                  className="mt-1"
+                />
+              </div>
+            </div>
+          )}
         </div>
       </Dialog.Content>
     </Dialog>

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

@@ -14,6 +14,10 @@ import {
 import { Dialog } from "@/components/molecules/Dialog/Dialog";
 import { useEffect, useRef, useState } from "react";
 import { ScheduleAgentModal } from "../ScheduleAgentModal/ScheduleAgentModal";
+import {
+  AIAgentSafetyPopup,
+  useAIAgentSafetyPopup,
+} from "./components/AIAgentSafetyPopup/AIAgentSafetyPopup";
 import { ModalHeader } from "./components/ModalHeader/ModalHeader";
 import { ModalRunSection } from "./components/ModalRunSection/ModalRunSection";
 import { RunActions } from "./components/RunActions/RunActions";
@@ -83,8 +87,17 @@ export function RunAgentModal({
 
   const [isScheduleModalOpen, setIsScheduleModalOpen] = useState(false);
   const [hasOverflow, setHasOverflow] = useState(false);
+  const [isSafetyPopupOpen, setIsSafetyPopupOpen] = useState(false);
+  const [pendingRunAction, setPendingRunAction] = useState<(() => void) | null>(
+    null,
+  );
   const contentRef = useRef<HTMLDivElement>(null);
 
+  const { shouldShowPopup, dismissPopup } = useAIAgentSafetyPopup(
+    agent.has_sensitive_action,
+    agent.has_human_in_the_loop,
+  );
+
   const hasAnySetupFields =
     Object.keys(agentInputFields || {}).length > 0 ||
     Object.keys(agentCredentialsInputFields || {}).length > 0;
@@ -165,6 +178,24 @@ export function RunAgentModal({
     onScheduleCreated?.(schedule);
   }
 
+  function handleRunWithSafetyCheck() {
+    if (shouldShowPopup) {
+      setPendingRunAction(() => handleRun);
+      setIsSafetyPopupOpen(true);
+    } else {
+      handleRun();
+    }
+  }
+
+  function handleSafetyPopupAcknowledge() {
+    setIsSafetyPopupOpen(false);
+    dismissPopup();
+    if (pendingRunAction) {
+      pendingRunAction();
+      setPendingRunAction(null);
+    }
+  }
+
   return (
     <>
       <Dialog
@@ -248,7 +279,7 @@ export function RunAgentModal({
                 )}
                 <RunActions
                   defaultRunType={defaultRunType}
-                  onRun={handleRun}
+                  onRun={handleRunWithSafetyCheck}
                   isExecuting={isExecuting}
                   isSettingUpTrigger={isSettingUpTrigger}
                   isRunReady={allRequiredInputsAreSet}
@@ -266,6 +297,11 @@ export function RunAgentModal({
           </div>
         </Dialog.Content>
       </Dialog>
+
+      <AIAgentSafetyPopup
+        isOpen={isSafetyPopupOpen}
+        onAcknowledge={handleSafetyPopupAcknowledge}
+      />
     </>
   );
 }

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

@@ -0,0 +1,95 @@
+"use client";
+
+import { Button } from "@/components/atoms/Button/Button";
+import { Text } from "@/components/atoms/Text/Text";
+import { Dialog } from "@/components/molecules/Dialog/Dialog";
+import { Key, storage } from "@/services/storage/local-storage";
+import { ShieldCheckIcon } from "@phosphor-icons/react";
+import { useCallback, useEffect, useState } from "react";
+
+interface Props {
+  onAcknowledge: () => void;
+  isOpen: boolean;
+}
+
+export function AIAgentSafetyPopup({ onAcknowledge, isOpen }: Props) {
+  function handleAcknowledge() {
+    // Mark popup as shown so it won't appear again
+    storage.set(Key.AI_AGENT_SAFETY_POPUP_SHOWN, "true");
+    onAcknowledge();
+  }
+
+  if (!isOpen) return null;
+
+  return (
+    <Dialog
+      controlled={{ isOpen, set: () => {} }}
+      styling={{ maxWidth: "480px" }}
+    >
+      <Dialog.Content>
+        <div className="flex flex-col items-center p-6 text-center">
+          <div className="mb-6 flex h-16 w-16 items-center justify-center rounded-full bg-blue-50">
+            <ShieldCheckIcon
+              weight="fill"
+              size={32}
+              className="text-blue-600"
+            />
+          </div>
+
+          <Text variant="h3" className="mb-4">
+            Safety Checks Enabled
+          </Text>
+
+          <Text variant="body" className="mb-2 text-zinc-700">
+            AI-generated agents may take actions that affect your data or
+            external systems.
+          </Text>
+
+          <Text variant="body" className="mb-8 text-zinc-700">
+            AutoGPT includes safety checks so you&apos;ll always have the
+            opportunity to review and approve sensitive actions before they
+            happen.
+          </Text>
+
+          <Button
+            variant="primary"
+            size="large"
+            className="w-full"
+            onClick={handleAcknowledge}
+          >
+            Got it
+          </Button>
+        </div>
+      </Dialog.Content>
+    </Dialog>
+  );
+}
+
+export function useAIAgentSafetyPopup(
+  hasSensitiveAction: boolean,
+  hasHumanInTheLoop: boolean,
+) {
+  const [shouldShowPopup, setShouldShowPopup] = useState(false);
+  const [hasChecked, setHasChecked] = useState(false);
+
+  useEffect(() => {
+    // Only check once after mount (to avoid SSR issues)
+    if (hasChecked) return;
+
+    const hasSeenPopup =
+      storage.get(Key.AI_AGENT_SAFETY_POPUP_SHOWN) === "true";
+    const isRelevantAgent = hasSensitiveAction || hasHumanInTheLoop;
+
+    setShouldShowPopup(!hasSeenPopup && isRelevantAgent);
+    setHasChecked(true);
+  }, [hasSensitiveAction, hasHumanInTheLoop, hasChecked]);
+
+  const dismissPopup = useCallback(() => {
+    setShouldShowPopup(false);
+  }, []);
+
+  return {
+    shouldShowPopup,
+    dismissPopup,
+  };
+}

autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/NewAgentLibraryView/components/selected-views/SelectedRunView/components/SafeModeToggle.tsx

@@ -5,48 +5,104 @@ import { Graph } from "@/lib/autogpt-server-api/types";
 import { cn } from "@/lib/utils";
 import { ShieldCheckIcon, ShieldIcon } from "@phosphor-icons/react";
 import { useAgentSafeMode } from "@/hooks/useAgentSafeMode";
+import {
+  Tooltip,
+  TooltipContent,
+  TooltipTrigger,
+} from "@/components/atoms/Tooltip/BaseTooltip";
 
 interface Props {
   graph: GraphModel | LibraryAgent | Graph;
   className?: string;
-  fullWidth?: boolean;
 }
 
-export function SafeModeToggle({ graph }: Props) {
+interface SafeModeIconButtonProps {
+  isEnabled: boolean;
+  label: string;
+  tooltipEnabled: string;
+  tooltipDisabled: string;
+  onToggle: () => void;
+  isPending: boolean;
+}
+
+function SafeModeIconButton({
+  isEnabled,
+  label,
+  tooltipEnabled,
+  tooltipDisabled,
+  onToggle,
+  isPending,
+}: SafeModeIconButtonProps) {
+  return (
+    <Tooltip delayDuration={100}>
+      <TooltipTrigger asChild>
+        <Button
+          variant="icon"
+          size="icon"
+          aria-label={`${label}: ${isEnabled ? "ON" : "OFF"}. ${isEnabled ? tooltipEnabled : tooltipDisabled}`}
+          onClick={onToggle}
+          disabled={isPending}
+          className={cn(isPending ? "opacity-0" : "opacity-100")}
+        >
+          {isEnabled ? (
+            <ShieldCheckIcon weight="bold" size={16} />
+          ) : (
+            <ShieldIcon weight="bold" size={16} />
+          )}
+        </Button>
+      </TooltipTrigger>
+      <TooltipContent>
+        <div className="text-center">
+          <div className="font-medium">
+            {label}: {isEnabled ? "ON" : "OFF"}
+          </div>
+          <div className="mt-1 text-xs text-muted-foreground">
+            {isEnabled ? tooltipEnabled : tooltipDisabled}
+          </div>
+        </div>
+      </TooltipContent>
+    </Tooltip>
+  );
+}
+
+export function SafeModeToggle({ graph, className }: Props) {
   const {
-    currentSafeMode,
+    currentHITLSafeMode,
+    showHITLToggle,
+    handleHITLToggle,
+    currentSensitiveActionSafeMode,
+    showSensitiveActionToggle,
+    handleSensitiveActionToggle,
     isPending,
     shouldShowToggle,
-    isStateUndetermined,
-    handleToggle,
   } = useAgentSafeMode(graph);
 
-  if (!shouldShowToggle || isStateUndetermined) {
+  if (!shouldShowToggle) {
     return null;
   }
 
   return (
-    <Button
+    <div className={cn("flex gap-1", className)}>
-      variant="icon"
+      {showHITLToggle && (
-      key={graph.id}
+        <SafeModeIconButton
-      size="icon"
+          isEnabled={currentHITLSafeMode}
-      aria-label={
+          label="Human-in-the-loop"
-        currentSafeMode!
+          tooltipEnabled="The agent will pause at human-in-the-loop blocks and wait for your approval"
-          ? "Safe Mode: ON. Human in the loop blocks require manual review"
+          tooltipDisabled="Human-in-the-loop blocks will proceed automatically"
-          : "Safe Mode: OFF. Human in the loop blocks proceed automatically"
+          onToggle={handleHITLToggle}
-      }
+          isPending={isPending}
-      onClick={handleToggle}
+        />
-      className={cn(isPending ? "opacity-0" : "opacity-100")}
-    >
-      {currentSafeMode! ? (
-        <>
-          <ShieldCheckIcon weight="bold" size={16} />
-        </>
-      ) : (
-        <>
-          <ShieldIcon weight="bold" size={16} />
-        </>
       )}
-    </Button>
+      {showSensitiveActionToggle && (
+        <SafeModeIconButton
+          isEnabled={currentSensitiveActionSafeMode}
+          label="Sensitive actions"
+          tooltipEnabled="The agent will pause at sensitive action blocks and wait for your approval"
+          tooltipDisabled="Sensitive action blocks will proceed automatically"
+          onToggle={handleSensitiveActionToggle}
+          isPending={isPending}
+        />
+      )}
+    </div>
   );
 }

autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/NewAgentLibraryView/components/selected-views/SelectedSettingsView/SelectedSettingsView.tsx

@@ -13,8 +13,16 @@ interface Props {
 }
 
 export function SelectedSettingsView({ agent, onClearSelectedRun }: Props) {
-  const { currentSafeMode, isPending, hasHITLBlocks, handleToggle } =
+  const {
-    useAgentSafeMode(agent);
+    currentHITLSafeMode,
+    showHITLToggle,
+    handleHITLToggle,
+    currentSensitiveActionSafeMode,
+    showSensitiveActionToggle,
+    handleSensitiveActionToggle,
+    isPending,
+    shouldShowToggle,
+  } = useAgentSafeMode(agent);
 
   return (
     <SelectedViewLayout agent={agent}>
@@ -34,24 +42,51 @@ export function SelectedSettingsView({ agent, onClearSelectedRun }: Props) {
         </div>
 
         <div className={`${AGENT_LIBRARY_SECTION_PADDING_X} space-y-6`}>
-          {hasHITLBlocks ? (
+          {shouldShowToggle ? (
-            <div className="flex w-full max-w-2xl flex-col items-start gap-4 rounded-xl border border-zinc-100 bg-white p-6">
+            <>
-              <div className="flex w-full items-start justify-between gap-4">
+              {showHITLToggle && (
-                <div className="flex-1">
+                <div className="flex w-full max-w-2xl flex-col items-start gap-4 rounded-xl border border-zinc-100 bg-white p-6">
-                  <Text variant="large-semibold">Require human approval</Text>
+                  <div className="flex w-full items-start justify-between gap-4">
-                  <Text variant="large" className="mt-1 text-zinc-900">
+                    <div className="flex-1">
-                    The agent will pause and wait for your review before
+                      <Text variant="large-semibold">
-                    continuing
+                        Human-in-the-loop approval
-                  </Text>
+                      </Text>
+                      <Text variant="large" className="mt-1 text-zinc-900">
+                        The agent will pause at human-in-the-loop blocks and
+                        wait for your review before continuing
+                      </Text>
+                    </div>
+                    <Switch
+                      checked={currentHITLSafeMode || false}
+                      onCheckedChange={handleHITLToggle}
+                      disabled={isPending}
+                      className="mt-1"
+                    />
+                  </div>
                 </div>
-                <Switch
+              )}
-                  checked={currentSafeMode || false}
+              {showSensitiveActionToggle && (
-                  onCheckedChange={handleToggle}
+                <div className="flex w-full max-w-2xl flex-col items-start gap-4 rounded-xl border border-zinc-100 bg-white p-6">
-                  disabled={isPending}
+                  <div className="flex w-full items-start justify-between gap-4">
-                  className="mt-1"
+                    <div className="flex-1">
-                />
+                      <Text variant="large-semibold">
-              </div>
+                        Sensitive action approval
-            </div>
+                      </Text>
+                      <Text variant="large" className="mt-1 text-zinc-900">
+                        The agent will pause at sensitive action blocks and wait
+                        for your review before continuing
+                      </Text>
+                    </div>
+                    <Switch
+                      checked={currentSensitiveActionSafeMode}
+                      onCheckedChange={handleSensitiveActionToggle}
+                      disabled={isPending}
+                      className="mt-1"
+                    />
+                  </div>
+                </div>
+              )}
+            </>
           ) : (
             <div className="rounded-xl border border-zinc-100 bg-white p-6">
               <Text variant="body" className="text-muted-foreground">

autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/OldAgentLibraryView/components/agent-run-draft-view.tsx

@@ -1,8 +1,15 @@
 "use client";
-import React, { useCallback, useEffect, useMemo, useState } from "react";
+import React, {
+  useCallback,
+  useContext,
+  useEffect,
+  useMemo,
+  useState,
+} from "react";
 
 import {
   CredentialsMetaInput,
+  CredentialsType,
   GraphExecutionID,
   GraphMeta,
   LibraryAgentPreset,
@@ -29,7 +36,11 @@ import {
 } from "@/components/__legacy__/ui/icons";
 import { Input } from "@/components/__legacy__/ui/input";
 import { Button } from "@/components/atoms/Button/Button";
-import { CredentialsInput } from "@/components/contextual/CredentialsInput/CredentialsInput";
+import { CredentialsGroupedView } from "@/components/contextual/CredentialsInput/components/CredentialsGroupedView/CredentialsGroupedView";
+import {
+  findSavedCredentialByProviderAndType,
+  findSavedUserCredentialByProviderAndType,
+} from "@/components/contextual/CredentialsInput/components/CredentialsGroupedView/helpers";
 import { InformationTooltip } from "@/components/molecules/InformationTooltip/InformationTooltip";
 import {
   useToast,
@@ -37,6 +48,7 @@ import {
 } from "@/components/molecules/Toast/use-toast";
 import { humanizeCronExpression } from "@/lib/cron-expression-utils";
 import { cn, isEmpty } from "@/lib/utils";
+import { CredentialsProvidersContext } from "@/providers/agent-credentials/credentials-provider";
 import { ClockIcon, CopyIcon, InfoIcon } from "@phosphor-icons/react";
 import { CalendarClockIcon, Trash2Icon } from "lucide-react";
 
@@ -90,6 +102,7 @@ export function AgentRunDraftView({
   const api = useBackendAPI();
   const { toast } = useToast();
   const toastOnFail = useToastOnFail();
+  const allProviders = useContext(CredentialsProvidersContext);
 
   const [inputValues, setInputValues] = useState<Record<string, any>>({});
   const [inputCredentials, setInputCredentials] = useState<
@@ -128,6 +141,77 @@ export function AgentRunDraftView({
     () => graph.credentials_input_schema.properties,
     [graph],
   );
+  const credentialFields = useMemo(
+    function getCredentialFields() {
+      return Object.entries(agentCredentialsInputFields);
+    },
+    [agentCredentialsInputFields],
+  );
+  const requiredCredentials = useMemo(
+    function getRequiredCredentials() {
+      return new Set(
+        (graph.credentials_input_schema?.required as string[]) || [],
+      );
+    },
+    [graph.credentials_input_schema?.required],
+  );
+
+  useEffect(
+    function initializeDefaultCredentials() {
+      if (!allProviders) return;
+      if (!graph.credentials_input_schema?.properties) return;
+      if (requiredCredentials.size === 0) return;
+
+      setInputCredentials(function updateCredentials(currentCreds) {
+        const next = { ...currentCreds };
+        let didAdd = false;
+
+        for (const key of requiredCredentials) {
+          if (next[key]) continue;
+          const schema = graph.credentials_input_schema.properties[key];
+          if (!schema) continue;
+
+          const providerNames = schema.credentials_provider || [];
+          const credentialTypes = schema.credentials_types || [];
+          const requiredScopes = schema.credentials_scopes;
+
+          const userCredential = findSavedUserCredentialByProviderAndType(
+            providerNames,
+            credentialTypes,
+            requiredScopes,
+            allProviders,
+          );
+
+          const savedCredential =
+            userCredential ||
+            findSavedCredentialByProviderAndType(
+              providerNames,
+              credentialTypes,
+              requiredScopes,
+              allProviders,
+            );
+
+          if (!savedCredential) continue;
+
+          next[key] = {
+            id: savedCredential.id,
+            provider: savedCredential.provider,
+            type: savedCredential.type as CredentialsType,
+            title: savedCredential.title,
+          };
+          didAdd = true;
+        }
+
+        if (!didAdd) return currentCreds;
+        return next;
+      });
+    },
+    [
+      allProviders,
+      graph.credentials_input_schema?.properties,
+      requiredCredentials,
+    ],
+  );
 
   const [allRequiredInputsAreSet, missingInputs] = useMemo(() => {
     const nonEmptyInputs = new Set(
@@ -145,18 +229,35 @@ export function AgentRunDraftView({
     );
     return [isSuperset, difference];
   }, [agentInputSchema.required, inputValues]);
-  const [allCredentialsAreSet, missingCredentials] = useMemo(() => {
+  const [allCredentialsAreSet, missingCredentials] = useMemo(
-    const availableCredentials = new Set(Object.keys(inputCredentials));
+    function getCredentialStatus() {
-    const allCredentials = new Set(Object.keys(agentCredentialsInputFields));
+      const missing = Array.from(requiredCredentials).filter((key) => {
-    // Backwards-compatible implementation of isSupersetOf and difference
+        const cred = inputCredentials[key];
-    const isSuperset = Array.from(allCredentials).every((item) =>
+        return !cred || !cred.id;
-      availableCredentials.has(item),
+      });
-    );
+      return [missing.length === 0, missing];
-    const difference = Array.from(allCredentials).filter(
+    },
-      (item) => !availableCredentials.has(item),
+    [requiredCredentials, inputCredentials],
-    );
+  );
-    return [isSuperset, difference];
+  function addChangedCredentials(prev: Set<keyof LibraryAgentPresetUpdatable>) {
-  }, [agentCredentialsInputFields, inputCredentials]);
+    const next = new Set(prev);
+    next.add("credentials");
+    return next;
+  }
+
+  function handleCredentialChange(key: string, value?: CredentialsMetaInput) {
+    setInputCredentials(function updateInputCredentials(currentCreds) {
+      const next = { ...currentCreds };
+      if (value === undefined) {
+        delete next[key];
+        return next;
+      }
+      next[key] = value;
+      return next;
+    });
+    setChangedPresetAttributes(addChangedCredentials);
+  }
+
   const notifyMissingInputs = useCallback(
     (needPresetName: boolean = true) => {
       const allMissingFields = (
@@ -649,35 +750,6 @@ export function AgentRunDraftView({
               </>
             )}
 
-            {/* Credentials inputs */}
-            {Object.entries(agentCredentialsInputFields).map(
-              ([key, inputSubSchema]) => (
-                <CredentialsInput
-                  key={key}
-                  schema={{ ...inputSubSchema, discriminator: undefined }}
-                  selectedCredentials={
-                    inputCredentials[key] ?? inputSubSchema.default
-                  }
-                  onSelectCredentials={(value) => {
-                    setInputCredentials((obj) => {
-                      const newObj = { ...obj };
-                      if (value === undefined) {
-                        delete newObj[key];
-                        return newObj;
-                      }
-                      return {
-                        ...obj,
-                        [key]: value,
-                      };
-                    });
-                    setChangedPresetAttributes((prev) =>
-                      prev.add("credentials"),
-                    );
-                  }}
-                />
-              ),
-            )}
-
             {/* Regular inputs */}
             {Object.entries(agentInputFields).map(([key, inputSubSchema]) => (
               <RunAgentInputs
@@ -695,6 +767,17 @@ export function AgentRunDraftView({
                 data-testid={`agent-input-${key}`}
               />
             ))}
+
+            {/* Credentials inputs */}
+            {credentialFields.length > 0 && (
+              <CredentialsGroupedView
+                credentialFields={credentialFields}
+                requiredCredentials={requiredCredentials}
+                inputCredentials={inputCredentials}
+                inputValues={inputValues}
+                onCredentialChange={handleCredentialChange}
+              />
+            )}
           </CardContent>
         </Card>
       </div>

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

@@ -2,6 +2,7 @@
 import { Button } from "@/components/atoms/Button/Button";
 import { FileInput } from "@/components/atoms/FileInput/FileInput";
 import { Input } from "@/components/atoms/Input/Input";
+import { LoadingSpinner } from "@/components/atoms/LoadingSpinner/LoadingSpinner";
 import { Dialog } from "@/components/molecules/Dialog/Dialog";
 import {
   Form,
@@ -120,7 +121,7 @@ export default function LibraryUploadAgentDialog() {
           >
             {isUploading ? (
               <div className="flex items-center gap-2">
-                <div className="h-4 w-4 animate-spin rounded-full border-b-2 border-t-2 border-white"></div>
+                <LoadingSpinner size="small" className="text-white" />
                 <span>Uploading...</span>
               </div>
             ) : (

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

@@ -5,8 +5,6 @@ import {
   CarouselContent,
   CarouselItem,
 } from "@/components/__legacy__/ui/carousel";
-import { FadeIn } from "@/components/molecules/FadeIn/FadeIn";
-import { StaggeredList } from "@/components/molecules/StaggeredList/StaggeredList";
 import { useAgentsSection } from "./useAgentsSection";
 import { StoreAgent } from "@/app/api/__generated__/models/storeAgent";
 import { StoreCard } from "../StoreCard/StoreCard";
@@ -43,14 +41,12 @@ export const AgentsSection = ({
   return (
     <div className="flex flex-col items-center justify-center">
       <div className="w-full max-w-[1360px]">
-        <FadeIn direction="left" duration={0.5}>
+        <h2
-          <h2
+          style={{ marginBottom: margin }}
-            style={{ marginBottom: margin }}
+          className="font-poppins text-lg font-semibold text-[#282828] dark:text-neutral-200"
-            className="font-poppins text-lg font-semibold text-neutral-800 dark:text-neutral-200"
+        >
-          >
+          {sectionTitle}
-            {sectionTitle}
+        </h2>
-          </h2>
-        </FadeIn>
         {!displayedAgents || displayedAgents.length === 0 ? (
           <div className="text-center text-gray-500 dark:text-gray-400">
             No agents found
@@ -58,38 +54,32 @@ export const AgentsSection = ({
         ) : (
           <>
             {/* Mobile Carousel View */}
-            <FadeIn direction="up" className="md:hidden">
+            <Carousel
-              <Carousel
+              className="md:hidden"
-                opts={{
+              opts={{
-                  loop: true,
+                loop: true,
-                }}
+              }}
-              >
-                <CarouselContent>
-                  {displayedAgents.map((agent, index) => (
-                    <CarouselItem key={index} className="min-w-64 max-w-71">
-                      <StoreCard
-                        agentName={agent.agent_name}
-                        agentImage={agent.agent_image}
-                        description={agent.description}
-                        runs={agent.runs}
-                        rating={agent.rating}
-                        avatarSrc={agent.creator_avatar}
-                        creatorName={agent.creator}
-                        hideAvatar={hideAvatars}
-                        onClick={() => handleCardClick(agent.creator, agent.slug)}
-                      />
-                    </CarouselItem>
-                  ))}
-                </CarouselContent>
-              </Carousel>
-            </FadeIn>
-
-            {/* Desktop Grid View with Staggered Animation */}
-            <StaggeredList
-              direction="up"
-              staggerDelay={0.08}
-              className="hidden grid-cols-1 place-items-center gap-6 md:grid md:grid-cols-2 lg:grid-cols-3 2xl:grid-cols-4"
             >
+              <CarouselContent>
+                {displayedAgents.map((agent, index) => (
+                  <CarouselItem key={index} className="min-w-64 max-w-71">
+                    <StoreCard
+                      agentName={agent.agent_name}
+                      agentImage={agent.agent_image}
+                      description={agent.description}
+                      runs={agent.runs}
+                      rating={agent.rating}
+                      avatarSrc={agent.creator_avatar}
+                      creatorName={agent.creator}
+                      hideAvatar={hideAvatars}
+                      onClick={() => handleCardClick(agent.creator, agent.slug)}
+                    />
+                  </CarouselItem>
+                ))}
+              </CarouselContent>
+            </Carousel>
+
+            <div className="hidden grid-cols-1 place-items-center gap-6 md:grid md:grid-cols-2 lg:grid-cols-3 2xl:grid-cols-4">
               {displayedAgents.map((agent, index) => (
                 <StoreCard
                   key={index}
@@ -104,7 +94,7 @@ export const AgentsSection = ({
                   onClick={() => handleCardClick(agent.creator, agent.slug)}
                 />
               ))}
-            </StaggeredList>
+            </div>
           </>
         )}
       </div>

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

@@ -38,7 +38,7 @@ export function BecomeACreator({
 
         <PublishAgentModal
           trigger={
-            <button className="inline-flex h-[48px] cursor-pointer items-center justify-center rounded-[38px] bg-neutral-800 px-8 py-3 transition-colors hover:bg-neutral-700 focus-visible:outline-none focus-visible:ring-2 focus-visible:ring-neutral-950 focus-visible:ring-offset-2 dark:bg-neutral-700 dark:hover:bg-neutral-600 dark:focus-visible:ring-neutral-50 md:h-[56px] md:px-10 md:py-4 lg:h-[68px] lg:px-12 lg:py-5">
+            <button className="inline-flex h-[48px] cursor-pointer items-center justify-center rounded-[38px] bg-neutral-800 px-8 py-3 transition-colors hover:bg-neutral-700 dark:bg-neutral-700 dark:hover:bg-neutral-600 md:h-[56px] md:px-10 md:py-4 lg:h-[68px] lg:px-12 lg:py-5">
               <span className="whitespace-nowrap font-poppins text-base font-medium leading-normal text-neutral-50 md:text-lg md:leading-relaxed lg:text-xl lg:leading-7">
                 {buttonText}
               </span>

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

@@ -20,18 +20,9 @@ export const CreatorCard = ({
 }: CreatorCardProps) => {
   return (
     <div
-      className={`h-[264px] w-full px-[18px] pb-5 pt-6 ${backgroundColor(index)} inline-flex cursor-pointer flex-col items-start justify-start gap-3.5 rounded-[26px] transition-[filter] duration-200 hover:brightness-95 focus-visible:outline-none focus-visible:ring-2 focus-visible:ring-neutral-950 focus-visible:ring-offset-2 dark:focus-visible:ring-neutral-50`}
+      className={`h-[264px] w-full px-[18px] pb-5 pt-6 ${backgroundColor(index)} inline-flex cursor-pointer flex-col items-start justify-start gap-3.5 rounded-[26px] transition-all duration-200 hover:brightness-95`}
       onClick={onClick}
-      onKeyDown={(e) => {
-        if (e.key === "Enter" || e.key === " ") {
-          e.preventDefault();
-          onClick();
-        }
-      }}
       data-testid="creator-card"
-      role="button"
-      tabIndex={0}
-      aria-label={`View ${creatorName}'s profile - ${agentsUploaded} agents`}
     >
       <div className="relative h-[64px] w-[64px]">
         <div className="absolute inset-0 overflow-hidden rounded-full">

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

@@ -1,7 +1,5 @@
 "use client";
 
-import { FadeIn } from "@/components/molecules/FadeIn/FadeIn";
-import { StaggeredList } from "@/components/molecules/StaggeredList/StaggeredList";
 import { CreatorCard } from "../CreatorCard/CreatorCard";
 import { useFeaturedCreators } from "./useFeaturedCreators";
 import { Creator } from "@/app/api/__generated__/models/creator";
@@ -21,17 +19,11 @@ export const FeaturedCreators = ({
   return (
     <div className="flex w-full flex-col items-center justify-center">
       <div className="w-full max-w-[1360px]">
-        <FadeIn direction="left" duration={0.5}>
+        <h2 className="mb-9 font-poppins text-lg font-semibold text-neutral-800 dark:text-neutral-200">
-          <h2 className="mb-9 font-poppins text-lg font-semibold text-neutral-800 dark:text-neutral-200">
+          {title}
-            {title}
+        </h2>
-          </h2>
-        </FadeIn>
 
-        <StaggeredList
+        <div className="grid grid-cols-1 gap-6 md:grid-cols-2 lg:grid-cols-4">
-          direction="up"
-          staggerDelay={0.1}
-          className="grid grid-cols-1 gap-6 md:grid-cols-2 lg:grid-cols-4"
-        >
           {displayedCreators.map((creator, index) => (
             <CreatorCard
               key={index}
@@ -43,7 +35,7 @@ export const FeaturedCreators = ({
               index={index}
             />
           ))}
-        </StaggeredList>
+        </div>
       </div>
     </div>
   );

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

@@ -8,7 +8,6 @@ import {
   CarouselNext,
   CarouselIndicator,
 } from "@/components/__legacy__/ui/carousel";
-import { FadeIn } from "@/components/molecules/FadeIn/FadeIn";
 import Link from "next/link";
 import { useFeaturedSection } from "./useFeaturedSection";
 import { StoreAgent } from "@/app/api/__generated__/models/storeAgent";
@@ -26,44 +25,40 @@ export const FeaturedSection = ({ featuredAgents }: FeaturedSectionProps) => {
 
   return (
     <section className="w-full">
-      <FadeIn direction="left" duration={0.5}>
+      <h2 className="mb-8 font-poppins text-2xl font-semibold leading-7 text-neutral-800 dark:text-neutral-200">
-        <h2 className="mb-8 font-poppins text-2xl font-semibold leading-7 text-neutral-800 dark:text-neutral-200">
+        Featured agents
-          Featured agents
+      </h2>
-        </h2>
-      </FadeIn>
 
-      <FadeIn direction="up" duration={0.6} delay={0.1}>
+      <Carousel
-        <Carousel
+        opts={{
-          opts={{
+          align: "center",
-            align: "center",
+          containScroll: "trimSnaps",
-            containScroll: "trimSnaps",
+        }}
-          }}
+      >
-        >
+        <CarouselContent>
-          <CarouselContent>
+          {featuredAgents.map((agent, index) => (
-            {featuredAgents.map((agent, index) => (
+            <CarouselItem
-              <CarouselItem
+              key={index}
-                key={index}
+              className="h-[480px] md:basis-1/2 lg:basis-1/3"
-                className="h-[480px] md:basis-1/2 lg:basis-1/3"
+            >
+              <Link
+                href={`/marketplace/agent/${encodeURIComponent(agent.creator)}/${encodeURIComponent(agent.slug)}`}
+                className="block h-full"
               >
-                <Link
+                <FeaturedAgentCard
-                  href={`/marketplace/agent/${encodeURIComponent(agent.creator)}/${encodeURIComponent(agent.slug)}`}
+                  agent={agent}
-                  className="block h-full"
+                  backgroundColor={getBackgroundColor(index)}
-                >
+                />
-                  <FeaturedAgentCard
+              </Link>
-                    agent={agent}
+            </CarouselItem>
-                    backgroundColor={getBackgroundColor(index)}
+          ))}
-                  />
+        </CarouselContent>
-                </Link>
+        <div className="relative mt-4">
-              </CarouselItem>
+          <CarouselIndicator />
-            ))}
+          <CarouselPrevious afterClick={handlePrevSlide} />
-          </CarouselContent>
+          <CarouselNext afterClick={handleNextSlide} />
-          <div className="relative mt-4">
+        </div>
-            <CarouselIndicator />
+      </Carousel>
-            <CarouselPrevious afterClick={handlePrevSlide} />
-            <CarouselNext afterClick={handleNextSlide} />
-          </div>
-        </Carousel>
-      </FadeIn>
     </section>
   );
 };

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

@@ -1,6 +1,6 @@
 "use client";
 
-import { FilterChip } from "@/components/atoms/FilterChip/FilterChip";
+import { Badge } from "@/components/__legacy__/ui/badge";
 import { useFilterChips } from "./useFilterChips";
 
 interface FilterChipsProps {
@@ -9,6 +9,8 @@ interface FilterChipsProps {
   multiSelect?: boolean;
 }
 
+// Some flaws in its logic
+// FRONTEND-TODO : This needs to be fixed
 export const FilterChips = ({
   badges,
   onFilterChange,
@@ -20,20 +22,18 @@ export const FilterChips = ({
   });
 
   return (
-    <div
+    <div className="flex h-auto min-h-8 flex-wrap items-center justify-center gap-3 lg:min-h-14 lg:justify-start lg:gap-5">
-      className="flex h-auto min-h-8 flex-wrap items-center justify-center gap-3 lg:min-h-14 lg:justify-start lg:gap-5"
-      role="group"
-      aria-label="Filter options"
-    >
       {badges.map((badge) => (
-        <FilterChip
+        <Badge
           key={badge}
-          label={badge}
+          variant={selectedFilters.includes(badge) ? "secondary" : "outline"}
-          selected={selectedFilters.includes(badge)}
+          className="mb-2 flex cursor-pointer items-center justify-center gap-2 rounded-full border border-black/50 px-3 py-1 dark:border-white/50 lg:mb-3 lg:gap-2.5 lg:px-6 lg:py-2"
           onClick={() => handleBadgeClick(badge)}
-          size="lg"
+        >
-          className="mb-2 lg:mb-3"
+          <div className="text-sm font-light tracking-tight text-[#474747] dark:text-[#e0e0e0] lg:text-xl lg:font-medium lg:leading-9">
-        />
+            {badge}
+          </div>
+        </Badge>
       ))}
     </div>
   );

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

@@ -1,6 +1,5 @@
 "use client";
 
-import { FadeIn } from "@/components/molecules/FadeIn/FadeIn";
 import { FilterChips } from "../FilterChips/FilterChips";
 import { SearchBar } from "../SearchBar/SearchBar";
 import { useHeroSection } from "./useHeroSection";
@@ -10,36 +9,30 @@ export const HeroSection = () => {
   return (
     <div className="mb-2 mt-8 flex flex-col items-center justify-center px-4 sm:mb-4 sm:mt-12 sm:px-6 md:mb-6 md:mt-16 lg:my-24 lg:px-8 xl:my-16">
       <div className="w-full max-w-3xl lg:max-w-4xl xl:max-w-5xl">
-        <FadeIn direction="down" duration={0.6} delay={0}>
+        <div className="mb-4 text-center md:mb-8">
-          <div className="mb-4 text-center md:mb-8">
+          <h1 className="text-center">
-            <h1 className="text-center">
+            <span className="font-poppins text-[48px] font-semibold leading-[54px] text-neutral-950 dark:text-neutral-50">
-              <span className="font-poppins text-[48px] font-semibold leading-[54px] text-neutral-950 dark:text-neutral-50">
+              Explore AI agents built for{" "}
-                Explore AI agents built for{" "}
+            </span>
-              </span>
+            <span className="font-poppins text-[48px] font-semibold leading-[54px] text-violet-600">
-              <span className="font-poppins text-[48px] font-semibold leading-[54px] text-violet-600">
+              you
-                you
+            </span>
-              </span>
+            <br />
-              <br />
+            <span className="font-poppins text-[48px] font-semibold leading-[54px] text-neutral-950 dark:text-neutral-50">
-              <span className="font-poppins text-[48px] font-semibold leading-[54px] text-neutral-950 dark:text-neutral-50">
+              by the{" "}
-                by the{" "}
+            </span>
-              </span>
+            <span className="font-poppins text-[48px] font-semibold leading-[54px] text-blue-500">
-              <span className="font-poppins text-[48px] font-semibold leading-[54px] text-blue-500">
+              community
-                community
+            </span>
-              </span>
+          </h1>
-            </h1>
+        </div>
-          </div>
+        <h3 className="mb:text-2xl mb-6 text-center font-sans text-xl font-normal leading-loose text-neutral-700 dark:text-neutral-300 md:mb-12">
-        </FadeIn>
+          Bringing you AI agents designed by thinkers from around the world
-        <FadeIn direction="up" duration={0.6} delay={0.15}>
+        </h3>
-          <h3 className="mb:text-2xl mb-6 text-center font-sans text-xl font-normal leading-loose text-neutral-700 dark:text-neutral-300 md:mb-12">
+        <div className="mb-4 flex justify-center sm:mb-5">
-            Bringing you AI agents designed by thinkers from around the world
+          <SearchBar height="h-[74px]" />
-          </h3>
+        </div>
-        </FadeIn>
+        <div>
-        <FadeIn direction="up" duration={0.5} delay={0.3}>
-          <div className="mb-4 flex justify-center sm:mb-5">
-            <SearchBar height="h-[74px]" />
-          </div>
-        </FadeIn>
-        <FadeIn direction="up" duration={0.5} delay={0.4}>
           <div className="flex justify-center">
             <FilterChips
               badges={searchTerms}
@@ -47,7 +40,7 @@ export const HeroSection = () => {
               multiSelect={false}
             />
           </div>
-        </FadeIn>
+        </div>
       </div>
     </div>
   );

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

@@ -1,6 +1,5 @@
 "use client";
-import { Separator } from "@/components/atoms/Separator/Separator";
+import { Separator } from "@/components/__legacy__/ui/separator";
-import { FadeIn } from "@/components/molecules/FadeIn/FadeIn";
 import { FeaturedSection } from "../FeaturedSection/FeaturedSection";
 import { BecomeACreator } from "../BecomeACreator/BecomeACreator";
 import { HeroSection } from "../HeroSection/HeroSection";
@@ -55,13 +54,11 @@ export const MainMarkeplacePage = () => {
           <FeaturedCreators featuredCreators={featuredCreators.creators} />
         )}
         <Separator className="mb-[25px] mt-[60px]" />
-        <FadeIn direction="up" duration={0.6}>
+        <BecomeACreator
-          <BecomeACreator
+          title="Become a Creator"
-            title="Become a Creator"
+          description="Join our ever-growing community of hackers and tinkerers"
-            description="Join our ever-growing community of hackers and tinkerers"
+          buttonText="Become a Creator"
-            buttonText="Become a Creator"
+        />
-          />
-        </FadeIn>
       </main>
     </div>
   );

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

@@ -16,9 +16,9 @@ interface SearchBarProps {
 export const SearchBar = ({
   placeholder = 'Search for tasks like "optimise SEO"',
   backgroundColor = "bg-neutral-100 dark:bg-neutral-800",
-  iconColor = "text-neutral-500 dark:text-neutral-400",
+  iconColor = "text-[#646464] dark:text-neutral-400",
-  textColor = "text-neutral-500 dark:text-neutral-200",
+  textColor = "text-[#707070] dark:text-neutral-200",
-  placeholderColor = "text-neutral-500 dark:text-neutral-400",
+  placeholderColor = "text-[#707070] dark:text-neutral-400",
   width = "w-9/10 lg:w-[56.25rem]",
   height = "h-[60px]",
 }: SearchBarProps) => {
@@ -32,13 +32,10 @@ export const SearchBar = ({
     >
       <MagnifyingGlassIcon className={`h-5 w-5 md:h-7 md:w-7 ${iconColor}`} />
       <input
-        type="search"
+        type="text"
-        name="search"
-        autoComplete="off"
         value={searchQuery}
         onChange={(e) => setSearchQuery(e.target.value)}
         placeholder={placeholder}
-        aria-label="Search for AI agents"
         className={`flex-grow border-none bg-transparent ${textColor} font-sans text-lg font-normal leading-[2.25rem] tracking-tight md:text-xl placeholder:${placeholderColor} focus:outline-none`}
         data-testid="store-search-input"
       />

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

@@ -1,25 +1,10 @@
 import Image from "next/image";
-import { Star } from "@phosphor-icons/react";
+import { StarRatingIcons } from "@/components/__legacy__/ui/icons";
 import Avatar, {
   AvatarFallback,
   AvatarImage,
 } from "@/components/atoms/Avatar/Avatar";
 
-function StarRating({ rating }: { rating: number }) {
-  const stars = [];
-  const clampedRating = Math.max(0, Math.min(5, rating));
-  for (let i = 1; i <= 5; i++) {
-    stars.push(
-      <Star
-        key={i}
-        weight={i <= clampedRating ? "fill" : "regular"}
-        className="h-4 w-4 text-neutral-900 dark:text-yellow-500"
-      />,
-    );
-  }
-  return <>{stars}</>;
-}
-
 interface StoreCardProps {
   agentName: string;
   agentImage: string;
@@ -49,7 +34,7 @@ export const StoreCard: React.FC<StoreCardProps> = ({
 
   return (
     <div
-      className="flex h-[27rem] w-full max-w-md cursor-pointer flex-col items-start rounded-3xl bg-background transition-shadow duration-300 hover:shadow-lg focus-visible:outline-none focus-visible:ring-2 focus-visible:ring-neutral-950 focus-visible:ring-offset-2 dark:hover:shadow-gray-700 dark:focus-visible:ring-neutral-50"
+      className="flex h-[27rem] w-full max-w-md cursor-pointer flex-col items-start rounded-3xl bg-background transition-all duration-300 hover:shadow-lg dark:hover:shadow-gray-700"
       onClick={handleClick}
       data-testid="store-card"
       role="button"
@@ -91,7 +76,7 @@ export const StoreCard: React.FC<StoreCardProps> = ({
       <div className="mt-3 flex w-full flex-1 flex-col px-4">
         {/* Second Section: Agent Name and Creator Name */}
         <div className="flex w-full flex-col">
-          <h3 className="line-clamp-2 font-poppins text-2xl font-semibold text-neutral-800 dark:text-neutral-100">
+          <h3 className="line-clamp-2 font-poppins text-2xl font-semibold text-[#272727] dark:text-neutral-100">
             {agentName}
           </h3>
           {!hideAvatar && creatorName && (
@@ -122,11 +107,11 @@ export const StoreCard: React.FC<StoreCardProps> = ({
                 {rating.toFixed(1)}
               </span>
               <div
-                className="inline-flex items-center gap-0.5"
+                className="inline-flex items-center"
                 role="img"
                 aria-label={`Rating: ${rating.toFixed(1)} out of 5 stars`}
               >
-                <StarRating rating={rating} />
+                {StarRatingIcons(rating)}
               </div>
             </div>
           </div>

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

@@ -6383,6 +6383,11 @@
             "title": "Has Human In The Loop",
             "readOnly": true
           },
+          "has_sensitive_action": {
+            "type": "boolean",
+            "title": "Has Sensitive Action",
+            "readOnly": true
+          },
           "trigger_setup_info": {
             "anyOf": [
               { "$ref": "#/components/schemas/GraphTriggerInfo" },
@@ -6399,6 +6404,7 @@
           "output_schema",
           "has_external_trigger",
           "has_human_in_the_loop",
+          "has_sensitive_action",
           "trigger_setup_info"
         ],
         "title": "BaseGraph"
@@ -7629,6 +7635,11 @@
             "title": "Has Human In The Loop",
             "readOnly": true
           },
+          "has_sensitive_action": {
+            "type": "boolean",
+            "title": "Has Sensitive Action",
+            "readOnly": true
+          },
           "trigger_setup_info": {
             "anyOf": [
               { "$ref": "#/components/schemas/GraphTriggerInfo" },
@@ -7652,6 +7663,7 @@
           "output_schema",
           "has_external_trigger",
           "has_human_in_the_loop",
+          "has_sensitive_action",
           "trigger_setup_info",
           "credentials_input_schema"
         ],
@@ -7730,6 +7742,11 @@
             "title": "Has Human In The Loop",
             "readOnly": true
           },
+          "has_sensitive_action": {
+            "type": "boolean",
+            "title": "Has Sensitive Action",
+            "readOnly": true
+          },
           "trigger_setup_info": {
             "anyOf": [
               { "$ref": "#/components/schemas/GraphTriggerInfo" },
@@ -7754,6 +7771,7 @@
           "output_schema",
           "has_external_trigger",
           "has_human_in_the_loop",
+          "has_sensitive_action",
           "trigger_setup_info",
           "credentials_input_schema"
         ],
@@ -7762,8 +7780,14 @@
       "GraphSettings": {
         "properties": {
           "human_in_the_loop_safe_mode": {
-            "anyOf": [{ "type": "boolean" }, { "type": "null" }],
+            "type": "boolean",
-            "title": "Human In The Loop Safe Mode"
+            "title": "Human In The Loop Safe Mode",
+            "default": true
+          },
+          "sensitive_action_safe_mode": {
+            "type": "boolean",
+            "title": "Sensitive Action Safe Mode",
+            "default": false
           }
         },
         "type": "object",
@@ -7921,6 +7945,16 @@
             "title": "Has External Trigger",
             "description": "Whether the agent has an external trigger (e.g. webhook) node"
           },
+          "has_human_in_the_loop": {
+            "type": "boolean",
+            "title": "Has Human In The Loop",
+            "description": "Whether the agent has human-in-the-loop blocks"
+          },
+          "has_sensitive_action": {
+            "type": "boolean",
+            "title": "Has Sensitive Action",
+            "description": "Whether the agent has sensitive action blocks"
+          },
           "trigger_setup_info": {
             "anyOf": [
               { "$ref": "#/components/schemas/GraphTriggerInfo" },
@@ -7967,6 +8001,8 @@
           "output_schema",
           "credentials_input_schema",
           "has_external_trigger",
+          "has_human_in_the_loop",
+          "has_sensitive_action",
           "new_output",
           "can_access_graph",
           "is_latest_version",
@@ -9389,6 +9425,12 @@
             "type": "array",
             "title": "Reviews",
             "description": "All reviews with their approval status, data, and messages"
+          },
+          "auto_approve_future_actions": {
+            "type": "boolean",
+            "title": "Auto Approve Future Actions",
+            "description": "If true, future reviews from the same blocks (nodes) being approved will be automatically approved for the remainder of this execution. This only affects the current execution run.",
+            "default": false
           }
         },
         "type": "object",

autogpt_platform/frontend/src/components/atoms/FilterChip/FilterChip.stories.tsx

@@ -1,151 +0,0 @@
-import type { Meta, StoryObj } from "@storybook/react";
-import { useState } from "react";
-import { FilterChip } from "./FilterChip";
-
-const meta: Meta<typeof FilterChip> = {
-  title: "Atoms/FilterChip",
-  component: FilterChip,
-  tags: ["autodocs"],
-  parameters: {
-    layout: "centered",
-  },
-  argTypes: {
-    size: {
-      control: "select",
-      options: ["sm", "md", "lg"],
-    },
-  },
-};
-
-export default meta;
-type Story = StoryObj<typeof FilterChip>;
-
-export const Default: Story = {
-  args: {
-    label: "Marketing",
-  },
-};
-
-export const Selected: Story = {
-  args: {
-    label: "Marketing",
-    selected: true,
-  },
-};
-
-export const Dismissible: Story = {
-  args: {
-    label: "Marketing",
-    selected: true,
-    dismissible: true,
-  },
-};
-
-export const Sizes: Story = {
-  render: () => (
-    <div className="flex items-center gap-4">
-      <FilterChip label="Small" size="sm" />
-      <FilterChip label="Medium" size="md" />
-      <FilterChip label="Large" size="lg" />
-    </div>
-  ),
-};
-
-export const Disabled: Story = {
-  args: {
-    label: "Disabled",
-    disabled: true,
-  },
-};
-
-function FilterChipGroupDemo() {
-  const filters = [
-    "Marketing",
-    "Sales",
-    "Development",
-    "Design",
-    "Research",
-    "Analytics",
-  ];
-  const [selected, setSelected] = useState<string[]>(["Marketing"]);
-
-  function handleToggle(filter: string) {
-    setSelected((prev) =>
-      prev.includes(filter)
-        ? prev.filter((f) => f !== filter)
-        : [...prev, filter],
-    );
-  }
-
-  return (
-    <div className="flex flex-wrap gap-3">
-      {filters.map((filter) => (
-        <FilterChip
-          key={filter}
-          label={filter}
-          selected={selected.includes(filter)}
-          onClick={() => handleToggle(filter)}
-        />
-      ))}
-    </div>
-  );
-}
-
-export const FilterGroup: Story = {
-  render: () => <FilterChipGroupDemo />,
-};
-
-function SingleSelectDemo() {
-  const filters = ["All", "Featured", "Popular", "New"];
-  const [selected, setSelected] = useState("All");
-
-  return (
-    <div className="flex flex-wrap gap-3">
-      {filters.map((filter) => (
-        <FilterChip
-          key={filter}
-          label={filter}
-          selected={selected === filter}
-          onClick={() => setSelected(filter)}
-        />
-      ))}
-    </div>
-  );
-}
-
-export const SingleSelect: Story = {
-  render: () => <SingleSelectDemo />,
-};
-
-function DismissibleDemo() {
-  const [filters, setFilters] = useState([
-    "Marketing",
-    "Sales",
-    "Development",
-  ]);
-
-  function handleDismiss(filter: string) {
-    setFilters((prev) => prev.filter((f) => f !== filter));
-  }
-
-  return (
-    <div className="flex flex-wrap gap-3">
-      {filters.map((filter) => (
-        <FilterChip
-          key={filter}
-          label={filter}
-          selected
-          dismissible
-          onDismiss={() => handleDismiss(filter)}
-        />
-      ))}
-      {filters.length === 0 && (
-        <span className="text-neutral-500">No filters selected</span>
-      )}
-    </div>
-  );
-}
-
-export const DismissibleGroup: Story = {
-  render: () => <DismissibleDemo />,
-};

autogpt_platform/frontend/src/components/atoms/FilterChip/FilterChip.tsx

@@ -1,100 +0,0 @@
-"use client";
-
-import { cn } from "@/lib/utils";
-import { X } from "@phosphor-icons/react";
-
-type FilterChipSize = "sm" | "md" | "lg";
-
-interface FilterChipProps {
-  /** The label text displayed in the chip */
-  label: string;
-  /** Whether the chip is currently selected */
-  selected?: boolean;
-  /** Callback when the chip is clicked */
-  onClick?: () => void;
-  /** Whether to show a dismiss/remove button */
-  dismissible?: boolean;
-  /** Callback when the dismiss button is clicked */
-  onDismiss?: () => void;
-  /** Size variant of the chip */
-  size?: FilterChipSize;
-  /** Whether the chip is disabled */
-  disabled?: boolean;
-  /** Additional CSS classes */
-  className?: string;
-}
-
-const sizeStyles: Record<FilterChipSize, string> = {
-  sm: "px-3 py-1 text-sm gap-1.5",
-  md: "px-4 py-1.5 text-base gap-2",
-  lg: "px-6 py-2 text-lg gap-2.5 lg:text-xl lg:leading-9",
-};
-
-const iconSizes: Record<FilterChipSize, string> = {
-  sm: "h-3 w-3",
-  md: "h-4 w-4",
-  lg: "h-5 w-5",
-};
-
-/**
- * A filter chip component for selecting/deselecting filter options.
- * Supports single and multi-select patterns with proper accessibility.
- */
-export function FilterChip({
-  label,
-  selected = false,
-  onClick,
-  dismissible = false,
-  onDismiss,
-  size = "md",
-  disabled = false,
-  className,
-}: FilterChipProps) {
-  function handleDismiss(e: React.MouseEvent) {
-    e.stopPropagation();
-    onDismiss?.();
-  }
-
-  return (
-    <button
-      type="button"
-      onClick={onClick}
-      disabled={disabled}
-      aria-pressed={selected}
-      className={cn(
-        // Base styles
-        "inline-flex items-center justify-center rounded-full border font-medium transition-colors",
-        // Focus styles
-        "focus-visible:outline-none focus-visible:ring-2 focus-visible:ring-neutral-950 focus-visible:ring-offset-2 dark:focus-visible:ring-neutral-50",
-        // Size styles
-        sizeStyles[size],
-        // State styles
-        selected
-          ? "border-neutral-900 bg-neutral-100 text-neutral-800 dark:border-neutral-100 dark:bg-neutral-800 dark:text-neutral-200"
-          : "border-neutral-400 bg-transparent text-neutral-600 hover:bg-neutral-50 dark:border-neutral-500 dark:text-neutral-300 dark:hover:bg-neutral-800",
-        // Disabled styles
-        disabled && "pointer-events-none opacity-50",
-        className,
-      )}
-    >
-      <span>{label}</span>
-      {dismissible && selected && (
-        <span
-          role="button"
-          tabIndex={0}
-          onClick={handleDismiss}
-          onKeyDown={(e) => {
-            if (e.key === "Enter" || e.key === " ") {
-              e.preventDefault();
-              handleDismiss(e as unknown as React.MouseEvent);
-            }
-          }}
-          className="rounded-full p-0.5 hover:bg-neutral-200 dark:hover:bg-neutral-700"
-          aria-label={`Remove ${label} filter`}
-        >
-          <X className={iconSizes[size]} weight="bold" />
-        </span>
-      )}
-    </button>
-  );
-}

autogpt_platform/frontend/src/components/atoms/Separator/Separator.stories.tsx

@@ -1,72 +0,0 @@
-import type { Meta, StoryObj } from "@storybook/react";
-import { Separator } from "./Separator";
-
-const meta: Meta<typeof Separator> = {
-  title: "Atoms/Separator",
-  component: Separator,
-  tags: ["autodocs"],
-  parameters: {
-    layout: "padded",
-  },
-};
-
-export default meta;
-type Story = StoryObj<typeof Separator>;
-
-export const Horizontal: Story = {
-  render: () => (
-    <div className="w-full max-w-md">
-      <p className="mb-4 text-neutral-700 dark:text-neutral-300">
-        Content above the separator
-      </p>
-      <Separator />
-      <p className="mt-4 text-neutral-700 dark:text-neutral-300">
-        Content below the separator
-      </p>
-    </div>
-  ),
-};
-
-export const Vertical: Story = {
-  render: () => (
-    <div className="flex h-16 items-center gap-4">
-      <span className="text-neutral-700 dark:text-neutral-300">Left</span>
-      <Separator orientation="vertical" />
-      <span className="text-neutral-700 dark:text-neutral-300">Right</span>
-    </div>
-  ),
-};
-
-export const WithCustomStyles: Story = {
-  render: () => (
-    <div className="w-full max-w-md space-y-4">
-      <Separator className="bg-violet-500" />
-      <Separator className="h-0.5 bg-gradient-to-r from-violet-500 to-blue-500" />
-      <Separator className="bg-neutral-400 dark:bg-neutral-600" />
-    </div>
-  ),
-};
-
-export const InSection: Story = {
-  render: () => (
-    <div className="w-full max-w-md space-y-6">
-      <section>
-        <h2 className="mb-2 text-lg font-semibold text-neutral-900 dark:text-neutral-100">
-          Featured Agents
-        </h2>
-        <p className="text-neutral-600 dark:text-neutral-400">
-          Browse our collection of featured AI agents.
-        </p>
-      </section>
-      <Separator className="my-6" />
-      <section>
-        <h2 className="mb-2 text-lg font-semibold text-neutral-900 dark:text-neutral-100">
-          Top Creators
-        </h2>
-        <p className="text-neutral-600 dark:text-neutral-400">
-          Meet the creators behind the most popular agents.
-        </p>
-      </section>
-    </div>
-  ),
-};

autogpt_platform/frontend/src/components/atoms/Separator/Separator.tsx

@@ -1,43 +0,0 @@
-import { cn } from "@/lib/utils";
-
-type SeparatorOrientation = "horizontal" | "vertical";
-
-interface SeparatorProps {
-  /** The orientation of the separator */
-  orientation?: SeparatorOrientation;
-  /** Whether the separator is purely decorative (true) or represents a semantic boundary (false) */
-  decorative?: boolean;
-  /** Additional CSS classes */
-  className?: string;
-}
-
-/**
- * A visual separator that divides content.
- * Uses semantic `<hr>` for horizontal separators and a styled `<div>` for vertical.
- */
-export function Separator({
-  orientation = "horizontal",
-  decorative = true,
-  className,
-}: SeparatorProps) {
-  const baseStyles = "shrink-0 bg-neutral-200 dark:bg-neutral-800";
-
-  if (orientation === "horizontal") {
-    return (
-      <hr
-        className={cn(baseStyles, "h-px w-full border-0", className)}
-        aria-hidden={decorative}
-        role={decorative ? "none" : "separator"}
-      />
-    );
-  }
-
-  return (
-    <div
-      className={cn(baseStyles, "h-full w-px", className)}
-      aria-hidden={decorative}
-      role={decorative ? "none" : "separator"}
-      aria-orientation="vertical"
-    />
-  );
-}

autogpt_platform/frontend/src/components/contextual/CredentialsInput/components/CredentialsGroupedView/helpers.ts

@@ -1,5 +1,5 @@
 import { CredentialsProvidersContextType } from "@/providers/agent-credentials/credentials-provider";
-import { getSystemCredentials } from "../../helpers";
+import { filterSystemCredentials, getSystemCredentials } from "../../helpers";
 
 export type CredentialField = [string, any];
 
@@ -208,3 +208,42 @@ export function findSavedCredentialByProviderAndType(
 
   return undefined;
 }
+
+export function findSavedUserCredentialByProviderAndType(
+  providerNames: string[],
+  credentialTypes: string[],
+  requiredScopes: string[] | undefined,
+  allProviders: CredentialsProvidersContextType | null,
+): SavedCredential | undefined {
+  for (const providerName of providerNames) {
+    const providerData = allProviders?.[providerName];
+    if (!providerData) continue;
+
+    const userCredentials = filterSystemCredentials(
+      providerData.savedCredentials ?? [],
+    );
+
+    const matchingCredentials: SavedCredential[] = [];
+
+    for (const credential of userCredentials) {
+      const typeMatches =
+        credentialTypes.length === 0 ||
+        credentialTypes.includes(credential.type);
+      const scopesMatch = hasRequiredScopes(credential, requiredScopes);
+
+      if (!typeMatches) continue;
+      if (!scopesMatch) continue;
+
+      matchingCredentials.push(credential as SavedCredential);
+    }
+
+    if (matchingCredentials.length === 1) {
+      return matchingCredentials[0];
+    }
+    if (matchingCredentials.length > 1) {
+      return undefined;
+    }
+  }
+
+  return undefined;
+}

autogpt_platform/frontend/src/components/contextual/CredentialsInput/useCredentialsInput.ts

@@ -98,24 +98,20 @@ export function useCredentialsInput({
 
   // Auto-select the first available credential on initial mount
   // Once a user has made a selection, we don't override it
-  useEffect(() => {
+  useEffect(
-    if (readOnly) return;
+    function autoSelectCredential() {
-    if (!credentials || !("savedCredentials" in credentials)) return;
+      if (readOnly) return;
+      if (!credentials || !("savedCredentials" in credentials)) return;
+      if (selectedCredential?.id) return;
 
-    // If already selected, don't auto-select
+      const savedCreds = credentials.savedCredentials;
-    if (selectedCredential?.id) return;
+      if (savedCreds.length === 0) return;
 
-    // Only attempt auto-selection once
+      if (hasAttemptedAutoSelect.current) return;
-    if (hasAttemptedAutoSelect.current) return;
+      hasAttemptedAutoSelect.current = true;
-    hasAttemptedAutoSelect.current = true;
 
-    // If optional, don't auto-select (user can choose "None")
+      if (isOptional) return;
-    if (isOptional) return;
 
-    const savedCreds = credentials.savedCredentials;
-
-    // Auto-select the first credential if any are available
-    if (savedCreds.length > 0) {
       const cred = savedCreds[0];
       onSelectCredential({
         id: cred.id,
@@ -123,14 +119,15 @@ export function useCredentialsInput({
         provider: credentials.provider,
         title: (cred as any).title,
       });
-    }
+    },
-  }, [
+    [
-    credentials,
+      credentials,
-    selectedCredential?.id,
+      selectedCredential?.id,
-    readOnly,
+      readOnly,
-    isOptional,
+      isOptional,
-    onSelectCredential,
+      onSelectCredential,
-  ]);
+    ],
+  );
 
   if (
     !credentials ||

autogpt_platform/frontend/src/components/molecules/FadeIn/FadeIn.stories.tsx

@@ -1,128 +0,0 @@
-import type { Meta, StoryObj } from "@storybook/react";
-import { FadeIn } from "./FadeIn";
-
-const meta: Meta<typeof FadeIn> = {
-  title: "Molecules/FadeIn",
-  component: FadeIn,
-  tags: ["autodocs"],
-  parameters: {
-    layout: "padded",
-  },
-  argTypes: {
-    direction: {
-      control: "select",
-      options: ["up", "down", "left", "right", "none"],
-    },
-  },
-};
-
-export default meta;
-type Story = StoryObj<typeof FadeIn>;
-
-const DemoCard = ({ title }: { title: string }) => (
-  <div className="rounded-xl bg-neutral-100 p-6 dark:bg-neutral-800">
-    <h3 className="mb-2 text-lg font-semibold text-neutral-900 dark:text-neutral-100">
-      {title}
-    </h3>
-    <p className="text-neutral-600 dark:text-neutral-400">
-      This card fades in with a smooth animation.
-    </p>
-  </div>
-);
-
-export const Default: Story = {
-  args: {
-    direction: "up",
-    children: <DemoCard title="Fade Up" />,
-  },
-};
-
-export const FadeDown: Story = {
-  args: {
-    direction: "down",
-    children: <DemoCard title="Fade Down" />,
-  },
-};
-
-export const FadeLeft: Story = {
-  args: {
-    direction: "left",
-    children: <DemoCard title="Fade Left" />,
-  },
-};
-
-export const FadeRight: Story = {
-  args: {
-    direction: "right",
-    children: <DemoCard title="Fade Right" />,
-  },
-};
-
-export const FadeOnly: Story = {
-  args: {
-    direction: "none",
-    children: <DemoCard title="Fade Only (No Direction)" />,
-  },
-};
-
-export const WithDelay: Story = {
-  args: {
-    direction: "up",
-    delay: 0.5,
-    children: <DemoCard title="Delayed Fade (0.5s)" />,
-  },
-};
-
-export const SlowAnimation: Story = {
-  args: {
-    direction: "up",
-    duration: 1.5,
-    children: <DemoCard title="Slow Animation (1.5s)" />,
-  },
-};
-
-export const LargeDistance: Story = {
-  args: {
-    direction: "up",
-    distance: 60,
-    children: <DemoCard title="Large Distance (60px)" />,
-  },
-};
-
-export const MultipleElements: Story = {
-  render: () => (
-    <div className="space-y-4">
-      <FadeIn direction="up" delay={0}>
-        <DemoCard title="First Card" />
-      </FadeIn>
-      <FadeIn direction="up" delay={0.1}>
-        <DemoCard title="Second Card" />
-      </FadeIn>
-      <FadeIn direction="up" delay={0.2}>
-        <DemoCard title="Third Card" />
-      </FadeIn>
-    </div>
-  ),
-};
-
-export const HeroExample: Story = {
-  render: () => (
-    <div className="text-center">
-      <FadeIn direction="down" delay={0}>
-        <h1 className="mb-4 text-4xl font-bold text-neutral-900 dark:text-neutral-100">
-          Welcome to the Marketplace
-        </h1>
-      </FadeIn>
-      <FadeIn direction="up" delay={0.2}>
-        <p className="mb-8 text-xl text-neutral-600 dark:text-neutral-400">
-          Discover AI agents built by the community
-        </p>
-      </FadeIn>
-      <FadeIn direction="up" delay={0.4}>
-        <button className="rounded-full bg-violet-600 px-8 py-3 text-white hover:bg-violet-700">
-          Get Started
-        </button>
-      </FadeIn>
-    </div>
-  ),
-};

autogpt_platform/frontend/src/components/molecules/FadeIn/FadeIn.tsx

@@ -1,109 +0,0 @@
-"use client";
-
-import { cn } from "@/lib/utils";
-import { motion, useReducedMotion, type Variants } from "framer-motion";
-import { ReactNode } from "react";
-
-type FadeDirection = "up" | "down" | "left" | "right" | "none";
-
-interface FadeInProps {
-  /** Content to animate */
-  children: ReactNode;
-  /** Direction the content fades in from */
-  direction?: FadeDirection;
-  /** Distance to travel in pixels (only applies when direction is not "none") */
-  distance?: number;
-  /** Animation duration in seconds */
-  duration?: number;
-  /** Delay before animation starts in seconds */
-  delay?: number;
-  /** Whether to trigger animation when element enters viewport */
-  viewport?: boolean;
-  /** How much of element must be visible to trigger (0-1) */
-  viewportAmount?: number;
-  /** Whether animation should only trigger once */
-  once?: boolean;
-  /** Additional CSS classes */
-  className?: string;
-  /** HTML element to render as */
-  as?: keyof JSX.IntrinsicElements;
-}
-
-function getDirectionOffset(
-  direction: FadeDirection,
-  distance: number,
-): { x: number; y: number } {
-  switch (direction) {
-    case "up":
-      return { x: 0, y: distance };
-    case "down":
-      return { x: 0, y: -distance };
-    case "left":
-      return { x: distance, y: 0 };
-    case "right":
-      return { x: -distance, y: 0 };
-    case "none":
-    default:
-      return { x: 0, y: 0 };
-  }
-}
-
-/**
- * A fade-in animation wrapper component.
- * Animates children with a fade effect and optional directional slide.
- * Respects user's reduced motion preferences.
- */
-export function FadeIn({
-  children,
-  direction = "up",
-  distance = 24,
-  duration = 0.5,
-  delay = 0,
-  viewport = true,
-  viewportAmount = 0.2,
-  once = true,
-  className,
-  as = "div",
-}: FadeInProps) {
-  const shouldReduceMotion = useReducedMotion();
-  const offset = getDirectionOffset(direction, distance);
-
-  // If user prefers reduced motion, render without animation
-  if (shouldReduceMotion) {
-    const Component = as as keyof JSX.IntrinsicElements;
-    return <Component className={className}>{children}</Component>;
-  }
-
-  const variants: Variants = {
-    hidden: {
-      opacity: 0,
-      x: offset.x,
-      y: offset.y,
-    },
-    visible: {
-      opacity: 1,
-      x: 0,
-      y: 0,
-      transition: {
-        duration,
-        delay,
-        ease: [0.25, 0.1, 0.25, 1], // Custom easing for smooth feel
-      },
-    },
-  };
-
-  const MotionComponent = motion[as as keyof typeof motion] as typeof motion.div;
-
-  return (
-    <MotionComponent
-      className={cn(className)}
-      initial="hidden"
-      animate={viewport ? undefined : "visible"}
-      whileInView={viewport ? "visible" : undefined}
-      viewport={viewport ? { once, amount: viewportAmount } : undefined}
-      variants={variants}
-    >
-      {children}
-    </MotionComponent>
-  );
-}

autogpt_platform/frontend/src/components/molecules/Popover/Popover.tsx

@@ -0,0 +1,33 @@
+"use client";
+
+import * as PopoverPrimitive from "@radix-ui/react-popover";
+import * as React from "react";
+
+import { cn } from "@/lib/utils";
+
+const Popover = PopoverPrimitive.Root;
+
+const PopoverTrigger = PopoverPrimitive.Trigger;
+
+const PopoverAnchor = PopoverPrimitive.Anchor;
+
+const PopoverContent = React.forwardRef<
+  React.ElementRef<typeof PopoverPrimitive.Content>,
+  React.ComponentPropsWithoutRef<typeof PopoverPrimitive.Content>
+>(({ className, align = "center", sideOffset = 4, ...props }, ref) => (
+  <PopoverPrimitive.Portal>
+    <PopoverPrimitive.Content
+      ref={ref}
+      align={align}
+      sideOffset={sideOffset}
+      className={cn(
+        "z-50 w-72 rounded-lg border border-zinc-200 bg-white p-4 text-zinc-900 shadow-md outline-none data-[state=open]:animate-in data-[state=closed]:animate-out data-[state=closed]:fade-out-0 data-[state=open]:fade-in-0 data-[state=closed]:zoom-out-95 data-[state=open]:zoom-in-95 data-[side=bottom]:slide-in-from-top-2 data-[side=left]:slide-in-from-right-2 data-[side=right]:slide-in-from-left-2 data-[side=top]:slide-in-from-bottom-2",
+        className,
+      )}
+      {...props}
+    />
+  </PopoverPrimitive.Portal>
+));
+PopoverContent.displayName = PopoverPrimitive.Content.displayName;
+
+export { Popover, PopoverAnchor, PopoverContent, PopoverTrigger };

autogpt_platform/frontend/src/components/molecules/StaggeredList/StaggeredList.stories.tsx

@@ -1,180 +0,0 @@
-import type { Meta, StoryObj } from "@storybook/react";
-import { StaggeredList } from "./StaggeredList";
-
-const meta: Meta<typeof StaggeredList> = {
-  title: "Molecules/StaggeredList",
-  component: StaggeredList,
-  tags: ["autodocs"],
-  parameters: {
-    layout: "padded",
-  },
-  argTypes: {
-    direction: {
-      control: "select",
-      options: ["up", "down", "left", "right", "none"],
-    },
-  },
-};
-
-export default meta;
-type Story = StoryObj<typeof StaggeredList>;
-
-const DemoCard = ({ title, index }: { title: string; index: number }) => (
-  <div className="rounded-xl bg-neutral-100 p-4 dark:bg-neutral-800">
-    <h3 className="mb-1 font-semibold text-neutral-900 dark:text-neutral-100">
-      {title}
-    </h3>
-    <p className="text-sm text-neutral-600 dark:text-neutral-400">
-      Card #{index + 1} with staggered animation
-    </p>
-  </div>
-);
-
-const items = ["First Item", "Second Item", "Third Item", "Fourth Item"];
-
-export const Default: Story = {
-  args: {
-    direction: "up",
-    className: "space-y-4",
-    children: items.map((item, i) => <DemoCard key={i} title={item} index={i} />),
-  },
-};
-
-export const FadeDown: Story = {
-  args: {
-    direction: "down",
-    className: "space-y-4",
-    children: items.map((item, i) => <DemoCard key={i} title={item} index={i} />),
-  },
-};
-
-export const FadeLeft: Story = {
-  args: {
-    direction: "left",
-    className: "flex gap-4",
-    children: items.map((item, i) => <DemoCard key={i} title={item} index={i} />),
-  },
-};
-
-export const FadeRight: Story = {
-  args: {
-    direction: "right",
-    className: "flex gap-4",
-    children: items.map((item, i) => <DemoCard key={i} title={item} index={i} />),
-  },
-};
-
-export const FastStagger: Story = {
-  args: {
-    direction: "up",
-    staggerDelay: 0.05,
-    className: "space-y-4",
-    children: items.map((item, i) => <DemoCard key={i} title={item} index={i} />),
-  },
-};
-
-export const SlowStagger: Story = {
-  args: {
-    direction: "up",
-    staggerDelay: 0.3,
-    className: "space-y-4",
-    children: items.map((item, i) => <DemoCard key={i} title={item} index={i} />),
-  },
-};
-
-export const WithInitialDelay: Story = {
-  args: {
-    direction: "up",
-    initialDelay: 0.5,
-    className: "space-y-4",
-    children: items.map((item, i) => <DemoCard key={i} title={item} index={i} />),
-  },
-};
-
-export const GridLayout: Story = {
-  args: {
-    direction: "up",
-    staggerDelay: 0.08,
-    className: "grid grid-cols-2 gap-4 md:grid-cols-4",
-    children: [
-      ...items,
-      "Fifth Item",
-      "Sixth Item",
-      "Seventh Item",
-      "Eighth Item",
-    ].map((item, i) => <DemoCard key={i} title={item} index={i} />),
-  },
-};
-
-export const AgentCardsExample: Story = {
-  render: () => {
-    const agents = [
-      { name: "SEO Optimizer", runs: 1234 },
-      { name: "Content Writer", runs: 987 },
-      { name: "Data Analyzer", runs: 756 },
-      { name: "Code Reviewer", runs: 543 },
-    ];
-
-    return (
-      <StaggeredList
-        direction="up"
-        staggerDelay={0.1}
-        className="grid grid-cols-2 gap-6 md:grid-cols-4"
-      >
-        {agents.map((agent, i) => (
-          <div
-            key={i}
-            className="rounded-2xl bg-white p-4 shadow-md dark:bg-neutral-900"
-          >
-            <div className="mb-3 aspect-video rounded-xl bg-gradient-to-br from-violet-500 to-blue-500" />
-            <h3 className="mb-1 font-semibold text-neutral-900 dark:text-neutral-100">
-              {agent.name}
-            </h3>
-            <p className="text-sm text-neutral-500">{agent.runs} runs</p>
-          </div>
-        ))}
-      </StaggeredList>
-    );
-  },
-};
-
-export const CreatorCardsExample: Story = {
-  render: () => {
-    const creators = [
-      { name: "Alice", agents: 12 },
-      { name: "Bob", agents: 8 },
-      { name: "Charlie", agents: 15 },
-      { name: "Diana", agents: 6 },
-    ];
-
-    const colors = [
-      "bg-violet-100 dark:bg-violet-900/30",
-      "bg-blue-100 dark:bg-blue-900/30",
-      "bg-green-100 dark:bg-green-900/30",
-      "bg-orange-100 dark:bg-orange-900/30",
-    ];
-
-    return (
-      <StaggeredList
-        direction="up"
-        staggerDelay={0.12}
-        className="grid grid-cols-2 gap-6 md:grid-cols-4"
-      >
-        {creators.map((creator, i) => (
-          <div
-            key={i}
-            className={`rounded-2xl p-5 ${colors[i % colors.length]}`}
-          >
-            <div className="mb-3 h-12 w-12 rounded-full bg-neutral-300 dark:bg-neutral-700" />
-            <h3 className="mb-1 font-semibold text-neutral-900 dark:text-neutral-100">
-              {creator.name}
-            </h3>
-            <p className="text-sm text-neutral-600 dark:text-neutral-400">
-              {creator.agents} agents
-            </p>
-          </div>
-        ))}
-      </StaggeredList>
-    );
-  },
-};

autogpt_platform/frontend/src/components/molecules/StaggeredList/StaggeredList.tsx

@@ -1,130 +0,0 @@
-"use client";
-
-import { cn } from "@/lib/utils";
-import { motion, useReducedMotion, type Variants } from "framer-motion";
-import { ReactNode } from "react";
-
-type StaggerDirection = "up" | "down" | "left" | "right" | "none";
-
-interface StaggeredListProps {
-  /** Array of items to render with staggered animation */
-  children: ReactNode[];
-  /** Direction items animate from */
-  direction?: StaggerDirection;
-  /** Distance to travel in pixels */
-  distance?: number;
-  /** Base duration for each item's animation */
-  duration?: number;
-  /** Delay between each item's animation start */
-  staggerDelay?: number;
-  /** Initial delay before first item animates */
-  initialDelay?: number;
-  /** Whether to trigger animation when element enters viewport */
-  viewport?: boolean;
-  /** How much of container must be visible to trigger */
-  viewportAmount?: number;
-  /** Whether animation should only trigger once */
-  once?: boolean;
-  /** Additional CSS classes for the container */
-  className?: string;
-  /** Additional CSS classes for each item wrapper */
-  itemClassName?: string;
-}
-
-function getDirectionOffset(
-  direction: StaggerDirection,
-  distance: number,
-): { x: number; y: number } {
-  switch (direction) {
-    case "up":
-      return { x: 0, y: distance };
-    case "down":
-      return { x: 0, y: -distance };
-    case "left":
-      return { x: distance, y: 0 };
-    case "right":
-      return { x: -distance, y: 0 };
-    case "none":
-    default:
-      return { x: 0, y: 0 };
-  }
-}
-
-/**
- * Animates a list of children with staggered fade-in effects.
- * Each child appears sequentially with a configurable delay.
- * Respects user's reduced motion preferences.
- */
-export function StaggeredList({
-  children,
-  direction = "up",
-  distance = 20,
-  duration = 0.4,
-  staggerDelay = 0.1,
-  initialDelay = 0,
-  viewport = true,
-  viewportAmount = 0.1,
-  once = true,
-  className,
-  itemClassName,
-}: StaggeredListProps) {
-  const shouldReduceMotion = useReducedMotion();
-  const offset = getDirectionOffset(direction, distance);
-
-  // If user prefers reduced motion, render without animation
-  if (shouldReduceMotion) {
-    return (
-      <div className={className}>
-        {children.map((child, index) => (
-          <div key={index} className={itemClassName}>
-            {child}
-          </div>
-        ))}
-      </div>
-    );
-  }
-
-  const containerVariants: Variants = {
-    hidden: {},
-    visible: {
-      transition: {
-        staggerChildren: staggerDelay,
-        delayChildren: initialDelay,
-      },
-    },
-  };
-
-  const itemVariants: Variants = {
-    hidden: {
-      opacity: 0,
-      x: offset.x,
-      y: offset.y,
-    },
-    visible: {
-      opacity: 1,
-      x: 0,
-      y: 0,
-      transition: {
-        duration,
-        ease: [0.25, 0.1, 0.25, 1],
-      },
-    },
-  };
-
-  return (
-    <motion.div
-      className={cn(className)}
-      initial="hidden"
-      animate={viewport ? undefined : "visible"}
-      whileInView={viewport ? "visible" : undefined}
-      viewport={viewport ? { once, amount: viewportAmount } : undefined}
-      variants={containerVariants}
-    >
-      {children.map((child, index) => (
-        <motion.div key={index} className={itemClassName} variants={itemVariants}>
-          {child}
-        </motion.div>
-      ))}
-    </motion.div>
-  );
-}

autogpt_platform/frontend/src/components/organisms/FloatingReviewsPanel/FloatingReviewsPanel.tsx

@@ -31,6 +31,29 @@ export function FloatingReviewsPanel({
       query: {
         enabled: !!(graphId && executionId),
         select: okData,
+        // Poll while execution is in progress to detect status changes
+        refetchInterval: (q) => {
+          // Note: refetchInterval callback receives raw data before select transform
+          const rawData = q.state.data as
+            | { status: number; data?: { status?: string } }
+            | undefined;
+          if (rawData?.status !== 200) return false;
+
+          const status = rawData?.data?.status;
+          if (!status) return false;
+
+          // Poll every 2 seconds while running or in review
+          if (
+            status === AgentExecutionStatus.RUNNING ||
+            status === AgentExecutionStatus.QUEUED ||
+            status === AgentExecutionStatus.INCOMPLETE ||
+            status === AgentExecutionStatus.REVIEW
+          ) {
+            return 2000;
+          }
+          return false;
+        },
+        refetchIntervalInBackground: true,
       },
     },
   );
@@ -40,23 +63,27 @@ export function FloatingReviewsPanel({
     useShallow((state) => state.graphExecutionStatus),
   );
 
+  // Determine if we should poll for pending reviews
+  const isInReviewStatus =
+    executionDetails?.status === AgentExecutionStatus.REVIEW ||
+    graphExecutionStatus === AgentExecutionStatus.REVIEW;
+
   const { pendingReviews, isLoading, refetch } = usePendingReviewsForExecution(
     executionId || "",
+    {
+      enabled: !!executionId,
+      // Poll every 2 seconds when in REVIEW status to catch new reviews
+      refetchInterval: isInReviewStatus ? 2000 : false,
+    },
   );
 
+  // Refetch pending reviews when execution status changes
   useEffect(() => {
-    if (executionId) {
+    if (executionId && executionDetails?.status) {
       refetch();
     }
   }, [executionDetails?.status, executionId, refetch]);
 
-  // Refetch when graph execution status changes to REVIEW
-  useEffect(() => {
-    if (graphExecutionStatus === AgentExecutionStatus.REVIEW && executionId) {
-      refetch();
-    }
-  }, [graphExecutionStatus, executionId, refetch]);
-
   if (
     !executionId ||
     (!isLoading &&

autogpt_platform/frontend/src/components/organisms/PendingReviewsList/PendingReviewsList.tsx

@@ -1,8 +1,9 @@
-import { useState } from "react";
+import { useState, useCallback } from "react";
 import { PendingHumanReviewModel } from "@/app/api/__generated__/models/pendingHumanReviewModel";
 import { PendingReviewCard } from "@/components/organisms/PendingReviewCard/PendingReviewCard";
 import { Text } from "@/components/atoms/Text/Text";
 import { Button } from "@/components/atoms/Button/Button";
+import { Switch } from "@/components/atoms/Switch/Switch";
 import { useToast } from "@/components/molecules/Toast/use-toast";
 import { ClockIcon, WarningIcon } from "@phosphor-icons/react";
 import { usePostV2ProcessReviewAction } from "@/app/api/__generated__/endpoints/executions/executions";
@@ -40,6 +41,8 @@ export function PendingReviewsList({
     "approve" | "reject" | null
   >(null);
 
+  const [autoApproveFuture, setAutoApproveFuture] = useState(false);
+
   const { toast } = useToast();
 
   const reviewActionMutation = usePostV2ProcessReviewAction({
@@ -92,6 +95,26 @@ export function PendingReviewsList({
     setReviewMessageMap((prev) => ({ ...prev, [nodeExecId]: message }));
   }
 
+  // Reset data to original values when toggling auto-approve
+  const handleAutoApproveFutureToggle = useCallback(
+    (enabled: boolean) => {
+      setAutoApproveFuture(enabled);
+      if (enabled) {
+        // Reset all data to original values
+        const originalData: Record<string, string> = {};
+        reviews.forEach((review) => {
+          originalData[review.node_exec_id] = JSON.stringify(
+            review.payload,
+            null,
+            2,
+          );
+        });
+        setReviewDataMap(originalData);
+      }
+    },
+    [reviews],
+  );
+
   function processReviews(approved: boolean) {
     if (reviews.length === 0) {
       toast({
@@ -109,22 +132,31 @@ export function PendingReviewsList({
       const reviewData = reviewDataMap[review.node_exec_id];
       const reviewMessage = reviewMessageMap[review.node_exec_id];
 
-      let parsedData: any = review.payload; // Default to original payload
+      // When auto-approving future actions, send undefined (use original data)
+      // Otherwise, parse and send the edited data if available
+      let parsedData: any = undefined;
 
-      // Parse edited data if available and editable
+      if (!autoApproveFuture) {
-      if (review.editable && reviewData) {
+        // For regular approve/reject, use edited data if available
-        try {
+        if (review.editable && reviewData) {
-          parsedData = JSON.parse(reviewData);
+          try {
-        } catch (error) {
+            parsedData = JSON.parse(reviewData);
-          toast({
+          } catch (error) {
-            title: "Invalid JSON",
+            toast({
-            description: `Please fix the JSON format in review for node ${review.node_exec_id}: ${error instanceof Error ? error.message : "Invalid syntax"}`,
+              title: "Invalid JSON",
-            variant: "destructive",
+              description: `Please fix the JSON format in review for node ${review.node_exec_id}: ${error instanceof Error ? error.message : "Invalid syntax"}`,
-          });
+              variant: "destructive",
-          setPendingAction(null);
+            });
-          return;
+            setPendingAction(null);
+            return;
+          }
+        } else {
+          // No edits, use original payload
+          parsedData = review.payload;
         }
       }
+      // When autoApproveFuture is true, parsedData stays undefined
+      // Backend will use the original payload stored in the database
 
       reviewItems.push({
         node_exec_id: review.node_exec_id,
@@ -137,6 +169,7 @@ export function PendingReviewsList({
     reviewActionMutation.mutate({
       data: {
         reviews: reviewItems,
+        auto_approve_future_actions: autoApproveFuture && approved,
       },
     });
   }
@@ -182,21 +215,37 @@ export function PendingReviewsList({
       <div className="space-y-7">
         {reviews.map((review) => (
           <PendingReviewCard
-            key={review.node_exec_id}
+            key={`${review.node_exec_id}-${autoApproveFuture}`}
             review={review}
             onReviewDataChange={handleReviewDataChange}
             onReviewMessageChange={handleReviewMessageChange}
             reviewMessage={reviewMessageMap[review.node_exec_id] || ""}
+            isDisabled={autoApproveFuture}
           />
         ))}
       </div>
 
-      <div className="space-y-7">
+      <div className="space-y-4">
-        <Text variant="body" className="text-textGrey">
+        {/* Auto-approve toggle */}
-          Note: Changes you make here apply only to this task
+        <div className="flex items-center gap-3">
-        </Text>
+          <Switch
+            checked={autoApproveFuture}
+            onCheckedChange={handleAutoApproveFutureToggle}
+            disabled={reviewActionMutation.isPending}
+          />
+          <Text variant="body" className="text-textBlack">
+            Auto-approve all future actions from these blocks
+          </Text>
+        </div>
 
-        <div className="flex gap-2">
+        {autoApproveFuture && (
+          <Text variant="small" className="text-amber-600">
+            Editing is disabled. Original data will be used for this and all
+            future reviews from these blocks.
+          </Text>
+        )}
+
+        <div className="flex flex-wrap gap-2">
           <Button
             onClick={() => processReviews(true)}
             disabled={reviewActionMutation.isPending || reviews.length === 0}
@@ -220,6 +269,11 @@ export function PendingReviewsList({
             Reject
           </Button>
         </div>
+
+        <Text variant="small" className="text-textGrey">
+          You can turn auto-approval on or off anytime in this agent&apos;s
+          settings.
+        </Text>
       </div>
     </div>
   );

autogpt_platform/frontend/src/components/renderers/InputRenderer/custom/CredentialField/components/CredentialFieldTitle.tsx

@@ -35,12 +35,13 @@ export const CredentialFieldTitle = (props: {
     uiOptions,
   );
 
-  const credentialProvider = toDisplayName(
+  const provider = getCredentialProviderFromSchema(
-    getCredentialProviderFromSchema(
+    useNodeStore.getState().getHardCodedValues(nodeId),
-      useNodeStore.getState().getHardCodedValues(nodeId),
+    schema as BlockIOCredentialsSubSchema,
-      schema as BlockIOCredentialsSubSchema,
-    ) ?? "",
   );
+  const credentialProvider = provider
+    ? `${toDisplayName(provider)} credential`
+    : "credential";
 
   const updatedUiSchema = updateUiOption(uiSchema, {
     showHandles: false,

autogpt_platform/frontend/src/components/renderers/InputRenderer/custom/LlmModelField/LlmModelField.tsx

@@ -0,0 +1,92 @@
+"use client";
+
+import {
+  descriptionId,
+  FieldProps,
+  getTemplate,
+  RJSFSchema,
+  titleId,
+} from "@rjsf/utils";
+import { useMemo } from "react";
+import { LlmModelPicker } from "./components/LlmModelPicker";
+import { LlmModelMetadataMap } from "./types";
+import { updateUiOption } from "../../helpers";
+
+type LlmModelSchema = RJSFSchema & {
+  llm_model_metadata?: LlmModelMetadataMap;
+};
+
+export function LlmModelField(props: FieldProps) {
+  const { schema, formData, onChange, disabled, readonly, fieldPathId } = props;
+
+  const metadata = useMemo(() => {
+    return (schema as LlmModelSchema)?.llm_model_metadata ?? {};
+  }, [schema]);
+
+  const models = useMemo(() => {
+    return Object.values(metadata);
+  }, [metadata]);
+
+  const selectedName =
+    typeof formData === "string"
+      ? formData
+      : typeof schema.default === "string"
+        ? schema.default
+        : "";
+
+  const selectedModel = selectedName
+    ? (metadata[selectedName] ??
+      models.find((model) => model.name === selectedName))
+    : undefined;
+
+  const recommendedName =
+    typeof schema.default === "string" ? schema.default : models[0]?.name;
+
+  const recommendedModel =
+    recommendedName && metadata[recommendedName]
+      ? metadata[recommendedName]
+      : undefined;
+
+  if (models.length === 0) {
+    return null;
+  }
+
+  const TitleFieldTemplate = getTemplate("TitleFieldTemplate", props.registry);
+  const DescriptionFieldTemplate = getTemplate(
+    "DescriptionFieldTemplate",
+    props.registry,
+  );
+
+  const updatedUiSchema = updateUiOption(props.uiSchema, {
+    showHandles: false,
+  });
+
+  return (
+    <>
+      <div className="flex items-center gap-2">
+        <TitleFieldTemplate
+          id={titleId(fieldPathId)}
+          title={schema.title || ""}
+          required={true}
+          schema={schema}
+          uiSchema={updatedUiSchema}
+          registry={props.registry}
+        />
+        <DescriptionFieldTemplate
+          id={descriptionId(fieldPathId)}
+          description={schema.description || ""}
+          schema={schema}
+          registry={props.registry}
+        />
+      </div>
+
+      <LlmModelPicker
+        models={models}
+        selectedModel={selectedModel}
+        recommendedModel={recommendedModel}
+        onSelect={(value) => onChange(value, fieldPathId?.path)}
+        disabled={disabled || readonly}
+      />
+    </>
+  );
+}

autogpt_platform/frontend/src/components/renderers/InputRenderer/custom/LlmModelField/components/LlmIcon.tsx

@@ -0,0 +1,66 @@
+"use client";
+
+import Image from "next/image";
+import { Text } from "@/components/atoms/Text/Text";
+
+const creatorIconMap: Record<string, string> = {
+  anthropic: "/integrations/anthropic-color.png",
+  openai: "/integrations/openai.png",
+  google: "/integrations/gemini.png",
+  nvidia: "/integrations/nvidia.png",
+  groq: "/integrations/groq.png",
+  ollama: "/integrations/ollama.png",
+  openrouter: "/integrations/open_router.png",
+  v0: "/integrations/v0.png",
+  xai: "/integrations/xai.webp",
+  meta: "/integrations/llama_api.png",
+  amazon: "/integrations/amazon.png",
+  cohere: "/integrations/cohere.png",
+  deepseek: "/integrations/deepseek.png",
+  gryphe: "/integrations/gryphe.png",
+  microsoft: "/integrations/microsoft.webp",
+  moonshotai: "/integrations/moonshot.png",
+  mistral: "/integrations/mistral.png",
+  mistralai: "/integrations/mistral.png",
+  nousresearch: "/integrations/nousresearch.avif",
+  perplexity: "/integrations/perplexity.webp",
+  qwen: "/integrations/qwen.png",
+};
+
+type Props = {
+  value: string;
+  size?: number;
+};
+
+export function LlmIcon({ value, size = 20 }: Props) {
+  const normalized = value.trim().toLowerCase().replace(/\s+/g, "");
+  const src = creatorIconMap[normalized];
+  if (src) {
+    return (
+      <div
+        className="flex items-center justify-center overflow-hidden rounded-xsmall"
+        style={{ width: size, height: size }}
+      >
+        <Image
+          src={src}
+          alt={value}
+          width={size}
+          height={size}
+          className="h-full w-full object-cover"
+        />
+      </div>
+    );
+  }
+
+  const fallback = value?.trim().slice(0, 1).toUpperCase() || "?";
+  return (
+    <div
+      className="flex items-center justify-center rounded-xsmall bg-zinc-100"
+      style={{ width: size, height: size }}
+    >
+      <Text variant="small" className="text-zinc-500">
+        {fallback}
+      </Text>
+    </div>
+  );
+}

autogpt_platform/frontend/src/components/renderers/InputRenderer/custom/LlmModelField/components/LlmMenuHeader.tsx

@@ -0,0 +1,24 @@
+"use client";
+
+import { ArrowLeftIcon } from "@phosphor-icons/react";
+import { Text } from "@/components/atoms/Text/Text";
+
+type Props = {
+  label: string;
+  onBack: () => void;
+};
+
+export function LlmMenuHeader({ label, onBack }: Props) {
+  return (
+    <button
+      type="button"
+      onClick={onBack}
+      className="flex w-full items-center gap-2 px-2 py-2 text-left hover:bg-zinc-100"
+    >
+      <ArrowLeftIcon className="h-4 w-4 text-zinc-800" weight="bold" />
+      <Text variant="body" className="text-zinc-900">
+        {label}
+      </Text>
+    </button>
+  );
+}