Goal Completion Detection Issue (#316)

* Goal Completion Detection Issue

Problem: When the AI called the mark_goal_complete function, the completion signal wasn't being propagated through the system. The iterative strategy kept running indefinitely even after the AI indicated the goal was complete.

Fix: Modified the LLM manager to detect when mark_goal_complete returns a `FunctionExecutionResult` with `completed=True`` and pass this signal through in the `LLMManagerResponse`

Signed-off-by: Luke Hinds <lukehinds@gmail.com>

* Release v0.7.2

Signed-off-by: Luke Hinds <lukehinds@gmail.com>

---------

Signed-off-by: Luke Hinds <lukehinds@gmail.com>

Author: lukehinds

pyproject.toml

@@ -1,6 +1,6 @@
 [project]
 name = "agentup"
-version = "0.7.1"
+version = "0.7.2"
 description = "Create AI agents with all the trappings, out of the box."
 readme = "README.md"
 requires-python = ">=3.11"

src/agent/services/builtin_capabilities.py

@@ -205,8 +205,8 @@ async def capabilities_executor(task: Task) -> str:
 
         # Echo capability
         async def echo_executor(task: Task) -> str:
-            if hasattr(task, "params") and task.params and "message" in task.params:
-                return f"Echo: {task.params['message']}"
+            if hasattr(task, "metadata") and task.metadata and "message" in task.metadata:
+                return f"Echo: {task.metadata['message']}"
             return "Echo: No message provided"
 
         # Register core capabilities

src/agent/services/llm/manager.py

@@ -168,10 +168,23 @@ async def llm_with_functions(
                     logger.debug(
                         f"Final LLM response after function execution: {final_response.content[:200]}{'...' if len(str(final_response.content)) > 200 else ''}"
                     )
+                    # If a completion was detected, pass it through in the response
+                    if completion_detected and completion_result:
+                        return LLMManagerResponse(
+                            content=final_response.content,
+                            completed=True,
+                            completion_data=completion_result.completion_data,
+                        )
                     return LLMManagerResponse(content=final_response.content)
                 except Exception as e:
                     logger.error(f"Failed to get final response from LLM after function execution: {e}")
                     # Return function results directly as fallback
+                    if completion_detected and completion_result:
+                        return LLMManagerResponse(
+                            content=f"Function executed successfully: {'; '.join(str(result) for result in function_results)}",
+                            completed=True,
+                            completion_data=completion_result.completion_data,
+                        )
                     return LLMManagerResponse(
                         content=f"Function executed successfully: {'; '.join(str(result) for result in function_results)}"
                     )