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/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/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/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
-        if not execution_context.human_in_the_loop_safe_mode:
+        # Note: Safe mode checks (human_in_the_loop_safe_mode, sensitive_action_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,
@@ -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/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.is_sensitive_action: 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,
@@ -648,6 +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/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_upsert.return_value.upsert = AsyncMock(return_value=sample_db_review)
+    mock_prisma = mocker.patch("backend.data.human_review.PendingHumanReview.prisma")
+    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_upsert.return_value.upsert = AsyncMock(return_value=sample_db_review)
+    mock_prisma = mocker.patch("backend.data.human_review.PendingHumanReview.prisma")
+    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/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/frontend/src/app/(platform)/build/components/FloatingSafeModeToogle.tsx

@@ -86,7 +86,6 @@ export function FloatingSafeModeToggle({
   const {
     currentHITLSafeMode,
     showHITLToggle,
-    isHITLStateUndetermined,
     handleHITLToggle,
     currentSensitiveActionSafeMode,
     showSensitiveActionToggle,
@@ -99,16 +98,9 @@ export function FloatingSafeModeToggle({
     return null;
   }
 
-  const showHITL = showHITLToggle && !isHITLStateUndetermined;
-  const showSensitive = showSensitiveActionToggle;
-
-  if (!showHITL && !showSensitive) {
-    return null;
-  }
-
   return (
     <div className={cn("fixed z-50 flex flex-col gap-2", className)}>
-      {showHITL && (
+      {showHITLToggle && (
         <SafeModeButton
           isEnabled={currentHITLSafeMode}
           label="Human in the loop block approval"
@@ -119,7 +111,7 @@ export function FloatingSafeModeToggle({
           fullWidth={fullWidth}
         />
       )}
-      {showSensitive && (
+      {showSensitiveActionToggle && (
         <SafeModeButton
           isEnabled={currentSensitiveActionSafeMode}
           label="Sensitive actions blocks approval"

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

@@ -69,7 +69,6 @@ export function SafeModeToggle({ graph, className }: Props) {
   const {
     currentHITLSafeMode,
     showHITLToggle,
-    isHITLStateUndetermined,
     handleHITLToggle,
     currentSensitiveActionSafeMode,
     showSensitiveActionToggle,
@@ -78,20 +77,13 @@ export function SafeModeToggle({ graph, className }: Props) {
     shouldShowToggle,
   } = useAgentSafeMode(graph);
 
-  if (!shouldShowToggle || isHITLStateUndetermined) {
-    return null;
-  }
-
-  const showHITL = showHITLToggle && !isHITLStateUndetermined;
-  const showSensitive = showSensitiveActionToggle;
-
-  if (!showHITL && !showSensitive) {
+  if (!shouldShowToggle) {
     return null;
   }
 
   return (
     <div className={cn("flex gap-1", className)}>
-      {showHITL && (
+      {showHITLToggle && (
         <SafeModeIconButton
           isEnabled={currentHITLSafeMode}
           label="Human-in-the-loop"
@@ -101,7 +93,7 @@ export function SafeModeToggle({ graph, className }: Props) {
           isPending={isPending}
         />
       )}
-      {showSensitive && (
+      {showSensitiveActionToggle && (
         <SafeModeIconButton
           isEnabled={currentSensitiveActionSafeMode}
           label="Sensitive actions"

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

@@ -9425,6 +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/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 (review.editable && reviewData) {
-        try {
-          parsedData = JSON.parse(reviewData);
-        } catch (error) {
-          toast({
-            title: "Invalid JSON",
-            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;
+      if (!autoApproveFuture) {
+        // For regular approve/reject, use edited data if available
+        if (review.editable && reviewData) {
+          try {
+            parsedData = JSON.parse(reviewData);
+          } catch (error) {
+            toast({
+              title: "Invalid JSON",
+              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;
+          }
+        } 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">
-        <Text variant="body" className="text-textGrey">
-          Note: Changes you make here apply only to this task
-        </Text>
+      <div className="space-y-4">
+        {/* Auto-approve toggle */}
+        <div className="flex items-center gap-3">
+          <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/hooks/usePendingReviews.ts

@@ -15,8 +15,22 @@ export function usePendingReviews() {
   };
 }
 
-export function usePendingReviewsForExecution(graphExecId: string) {
-  const query = useGetV2GetPendingReviewsForExecution(graphExecId);
+interface UsePendingReviewsForExecutionOptions {
+  enabled?: boolean;
+  refetchInterval?: number | false;
+}
+
+export function usePendingReviewsForExecution(
+  graphExecId: string,
+  options?: UsePendingReviewsForExecutionOptions,
+) {
+  const query = useGetV2GetPendingReviewsForExecution(graphExecId, {
+    query: {
+      enabled: options?.enabled ?? !!graphExecId,
+      refetchInterval: options?.refetchInterval,
+      refetchIntervalInBackground: !!options?.refetchInterval,
+    },
+  });
 
   return {
     pendingReviews: okData(query.data) || [],

autogpt_platform/frontend/src/services/storage/local-storage.ts

@@ -10,6 +10,7 @@ export enum Key {
   LIBRARY_AGENTS_CACHE = "library-agents-cache",
   CHAT_SESSION_ID = "chat_session_id",
   COOKIE_CONSENT = "autogpt_cookie_consent",
+  AI_AGENT_SAFETY_POPUP_SHOWN = "ai-agent-safety-popup-shown",
 }
 
 function get(key: Key) {