Merge branch 'master' into dev

autogpt_platform/backend/backend/executor/utils.py

@@ -548,7 +548,7 @@ async def validate_graph_with_credentials(
     return node_input_errors
 
 
-async def _construct_node_execution_input(
+async def _construct_starting_node_execution_input(
     graph: GraphModel,
     user_id: str,
     graph_inputs: BlockInput,
@@ -622,7 +622,7 @@ async def validate_and_construct_node_execution_input(
     graph_version: Optional[int] = None,
     graph_credentials_inputs: Optional[dict[str, CredentialsMetaInput]] = None,
     nodes_input_masks: Optional[dict[str, dict[str, JsonValue]]] = None,
-) -> tuple[GraphModel, list[tuple[str, BlockInput]]]:
+) -> tuple[GraphModel, list[tuple[str, BlockInput]], dict[str, dict[str, JsonValue]]]:
     """
     Public wrapper that handles graph fetching, credential mapping, and validation+construction.
     This centralizes the logic used by both scheduler validation and actual execution.
@@ -666,14 +666,14 @@ async def validate_and_construct_node_execution_input(
         nodes_input_masks or {},
     )
 
-    starting_nodes_input = await _construct_node_execution_input(
+    starting_nodes_input = await _construct_starting_node_execution_input(
         graph=graph,
         user_id=user_id,
         graph_inputs=graph_inputs,
         nodes_input_masks=nodes_input_masks,
     )
 
-    return graph, starting_nodes_input
+    return graph, starting_nodes_input, nodes_input_masks
 
 
 def _merge_nodes_input_masks(
@@ -856,13 +856,15 @@ async def add_graph_execution(
     else:
         edb = get_database_manager_async_client()
 
-    graph, starting_nodes_input = await validate_and_construct_node_execution_input(
-        graph_id=graph_id,
-        user_id=user_id,
-        graph_inputs=inputs or {},
-        graph_version=graph_version,
-        graph_credentials_inputs=graph_credentials_inputs,
-        nodes_input_masks=nodes_input_masks,
+    graph, starting_nodes_input, nodes_input_masks = (
+        await validate_and_construct_node_execution_input(
+            graph_id=graph_id,
+            user_id=user_id,
+            graph_inputs=inputs or {},
+            graph_version=graph_version,
+            graph_credentials_inputs=graph_credentials_inputs,
+            nodes_input_masks=nodes_input_masks,
+        )
     )
     graph_exec = None
 

autogpt_platform/backend/backend/server/routers/v1.py

@@ -676,7 +676,15 @@ async def update_graph(
             # Handle deactivation of the previously active version
             await on_graph_deactivate(current_active_version, user_id=user_id)
 
-    return new_graph_version
+    # Fetch new graph version *with sub-graphs* (needed for credentials input schema)
+    new_graph_version_with_subgraphs = await graph_db.get_graph(
+        graph_id,
+        new_graph_version.version,
+        user_id=user_id,
+        include_subgraphs=True,
+    )
+    assert new_graph_version_with_subgraphs  # make type checker happy
+    return new_graph_version_with_subgraphs
 
 
 @v1_router.put(

autogpt_platform/backend/backend/server/v2/library/db.py

@@ -241,7 +241,11 @@ async def get_library_agent_by_graph_id(
         )
         if not agent:
             return None
-        return library_model.LibraryAgent.from_db(agent)
+
+        assert agent.AgentGraph  # make type checker happy
+        # Include sub-graphs so we can make a full credentials input schema
+        sub_graphs = await graph_db.get_sub_graphs(agent.AgentGraph)
+        return library_model.LibraryAgent.from_db(agent, sub_graphs=sub_graphs)
     except prisma.errors.PrismaError as e:
         logger.error(f"Database error fetching library agent by graph ID: {e}")
         raise store_exceptions.DatabaseError("Failed to fetch library agent") from e

autogpt_platform/backend/backend/util/exceptions.py

@@ -71,4 +71,10 @@ class GraphValidationError(ValueError):
         self.node_errors = node_errors or {}
 
     def __str__(self):
-        return self.message
+        return self.message + "".join(
+            [
+                f"\n  {node_id}:"
+                + "".join([f"\n    {k}: {e}" for k, e in errors.items()])
+                for node_id, errors in self.node_errors.items()
+            ]
+        )