fix(platform): Fix timer & step-through block

autogpt_platform/backend/backend/blocks/iteration.py

@@ -2,13 +2,28 @@
 
 from backend.data.block import Block, BlockCategory, BlockOutput, BlockSchema
 from backend.data.model import SchemaField
+from backend.util.json import json
 
 
 class StepThroughItemsBlock(Block):
     class Input(BlockSchema):
-        items: list | dict = SchemaField(
+        items: list = SchemaField(
+            advanced=False,
             description="The list or dictionary of items to iterate over",
             placeholder="[1, 2, 3, 4, 5] or {'key1': 'value1', 'key2': 'value2'}",
+            default=[],
+        )
+        items_object: dict = SchemaField(
+            advanced=False,
+            description="The list or dictionary of items to iterate over",
+            placeholder="[1, 2, 3, 4, 5] or {'key1': 'value1', 'key2': 'value2'}",
+            default={},
+        )
+        items_str: str = SchemaField(
+            advanced=False,
+            description="The list or dictionary of items to iterate over",
+            placeholder="[1, 2, 3, 4, 5] or {'key1': 'value1', 'key2': 'value2'}",
+            default="",
         )
 
     class Output(BlockSchema):
@@ -39,14 +54,20 @@ def __init__(self):
         )
 
     def run(self, input_data: Input, **kwargs) -> BlockOutput:
-        items = input_data.items
-        if isinstance(items, dict):
-            # If items is a dictionary, iterate over its values
-            for item in items.values():
-                yield "item", item
-                yield "key", item
-        else:
-            # If items is a list, iterate over the list
-            for index, item in enumerate(items):
-                yield "item", item
-                yield "key", index
+        for data in [input_data.items, input_data.items_object, input_data.items_str]:
+            if not data:
+                continue
+            if isinstance(data, str):
+                items = json.loads(data)
+            else:
+                items = data
+            if isinstance(items, dict):
+                # If items is a dictionary, iterate over its values
+                for item in items.values():
+                    yield "item", item
+                    yield "key", item
+            else:
+                # If items is a list, iterate over the list
+                for index, item in enumerate(items):
+                    yield "item", item
+                    yield "key", index

autogpt_platform/backend/backend/blocks/time_blocks.py

@@ -139,23 +139,26 @@ def run(self, input_data: Input, **kwargs) -> BlockOutput:
 
 class CountdownTimerBlock(Block):
     class Input(BlockSchema):
-        input_message: Any = SchemaField(
+        input_data: Any = SchemaField(
+            advanced=False,
             description="Message to output after the timer finishes",
             default="timer finished",
         )
         seconds: Union[int, str] = SchemaField(
-            description="Duration in seconds", default=0
+            advanced=False, description="Duration in seconds", default=0
         )
         minutes: Union[int, str] = SchemaField(
-            description="Duration in minutes", default=0
+            advanced=False, description="Duration in minutes", default=0
+        )
+        hours: Union[int, str] = SchemaField(
+            advanced=False, description="Duration in hours", default=0
+        )
+        days: Union[int, str] = SchemaField(
+            advanced=False, description="Duration in days", default=0
         )
-        hours: Union[int, str] = SchemaField(description="Duration in hours", default=0)
-        days: Union[int, str] = SchemaField(description="Duration in days", default=0)
 
     class Output(BlockSchema):
-        output_message: str = SchemaField(
-            description="Message after the timer finishes"
-        )
+        output_data: Any = SchemaField(description="Message after the timer finishes")
 
     def __init__(self):
         super().__init__(
@@ -166,11 +169,11 @@ def __init__(self):
             output_schema=CountdownTimerBlock.Output,
             test_input=[
                 {"seconds": 1},
-                {"input_message": "Custom message"},
+                {"input_data": "Custom message"},
             ],
             test_output=[
-                ("output_message", "timer finished"),
-                ("output_message", "Custom message"),
+                ("output_data", "timer finished"),
+                ("output_data", "Custom message"),
             ],
         )
 
@@ -183,4 +186,4 @@ def run(self, input_data: Input, **kwargs) -> BlockOutput:
         total_seconds = seconds + minutes * 60 + hours * 3600 + days * 86400
 
         time.sleep(total_seconds)
-        yield "output_message", input_data.input_message
+        yield "output_data", input_data.input_data

autogpt_platform/backend/backend/executor/manager.py

@@ -148,7 +148,7 @@ def update_execution(status: ExecutionStatus) -> ExecutionResult:
     input_data_str = json.dumps(input_data)
     input_size = len(input_data_str)
     log_metadata.info("Executed node with input", input=input_data_str)
-    update_execution(ExecutionStatus.RUNNING)
+    exec_res = update_execution(ExecutionStatus.RUNNING)
 
     extra_exec_kwargs = {}
     # Last-minute fetch credentials + acquire a system-wide read-write lock to prevent
@@ -173,6 +173,8 @@ def update_execution(status: ExecutionStatus) -> ExecutionResult:
             output_size += len(json.dumps(output_data))
             log_metadata.info("Node produced output", output_name=output_data)
             db_client.upsert_execution_output(node_exec_id, output_name, output_data)
+            exec_res.output_data.setdefault(output_name, []).append(output_data)
+            db_client.send_execution_update(exec_res.model_dump())
 
             for execution in _enqueue_next_nodes(
                 db_client=db_client,

autogpt_platform/frontend/src/components/node-input-components.tsx

@@ -507,7 +507,6 @@ const NodeArrayInput: FC<{
     typeof errors[selfKey] === "string" ? errors[selfKey] : undefined;
   return (
     <div className={cn(className, "flex flex-col")}>
-      {displayName && <strong>{displayName}</strong>}
       {entries.map((entry: any, index: number) => {
         const entryKey = `${selfKey}_$_${index}`;
         const isConnected =

autogpt_platform/frontend/src/hooks/useAgentGraph.ts

@@ -117,7 +117,7 @@ export default function useAgentGraph(
       if (!outputSchema) return "unknown";
 
       const outputHandle = outputSchema.properties[handleId];
-      if (!("type" in outputHandle)) return "unknown";
+      if (!outputHandle || !("type" in outputHandle)) return "unknown";
       return outputHandle.type;
     },
     [],