Resource cleanup and potential memory leaks when early-returning in async for runner.run_async in multi-agent streaming

[caichuanwang]

Discussion Description

• Context

  • In a multi-agent chat flow, each incoming message triggers async for event in runner.run_async(...) to consume streamed events.
  • When event.is_final_response() is detected, we currently do finalization and return. Concern: if we don’t return, could this cause memory/resource leaks?

• Key Questions

  1. If we don’t return on the final event (and instead keep consuming or wait for natural termination), can this lead to leaks?
  2. In Python, does exiting an async for early (return/break) properly invoke the iterator’s aclose() to release resources?
  3. In multi-agent chaining, what’s the recommended shutdown pattern: return vs break, whether to explicitly call aclose()/close(), and when to re-enable user input/update state?

• Current Approach (pseudocode)

async def handle_message(...):
    try:
        async for event in runner.run_async(user_id, session_id, state_delta, new_message):
            if event.get_function_calls():
            # do something
            if event.get_function_responses():
            # do something
            if event.is_final_response():
                # finalize (send last message, enable input, record last_author, etc.)
                return  # early exit here
            # handle text/tool-call/tool-response events
    except Exception as e:
        # failure handling, enable input
        ...
    finally:
        # non-temp: mark inactive, maybe set current_agent on stream completion
        # temp runner: await runner.close()
        ...

• Feedback Requested
  • Is there a preferred “unified tail + explicit cancel” pattern recommended by ADK?
  • In multi-agent scenarios, should we short-circuit on non-target authors to reduce spurious handling and state churn?

[adk-bot]

Response from ADK Answering Agent (experimental, answer may be inaccurate)

TLDR: Your current approach using try...finally or exiting the async for loop early with return is safe. Python's async for loop automatically calls the necessary cleanup method (aclose()) on the underlying async generator when the loop is exited. For an even more robust and idiomatic pattern, we recommend using an async with block with contextlib.aclosing.

---

Hello! Thank you for the detailed and insightful questions about resource management in ADK. Here are answers to your key questions:

1. Resource Leaks and Early Returns

You are correct to be mindful of resource cleanup. The runner.run_async() method returns an async generator. To prevent resource leaks, this generator must be properly closed.

Your concern about return causing leaks is valid in many contexts, but fortunately, Python's async for handles this for you. When you break or return from within an async for loop, or if an exception occurs, Python ensures that the async generator's aclose() method is called and awaited. This mechanism is designed precisely to prevent resource leaks in scenarios like yours.

So, your current approach is not expected to cause leaks, as the early return will trigger the proper cleanup of the run_async generator.

2. Recommended Shutdown Pattern for Multi-Agent Chaining

While your current pattern works, the most robust and recommended pattern for ensuring resource cleanup is to use an async with block. This pattern guarantees that cleanup logic is executed, regardless of how the block is exited.

ADK provides an internal utility Aclosing for this purpose, which is based on contextlib.aclosing (available in Python 3.10+). Using this context manager makes the cleanup explicit and is considered a best practice.

Here is the recommended "unified tail" pattern using this approach:

from contextlib import aclosing # For Python 3.10+

async def handle_message(...):
    try:
        async with aclosing(runner.run_async(user_id, session_id, state_delta, new_message)) as agen:
            async for event in agen:
                # Handle various events (function calls, responses, etc.)
                ...

                if event.is_final_response():
                    # Finalize your state, send the last message, update UI, etc.
                    # You can safely `return` or `break` here.
                    # The `async with` block ensures `agen.aclose()` is called.
                    return
    except Exception as e:
        # Handle failures
        ...
    # No `finally` block is needed for closing the generator when using `async with`.
    # Other cleanup, like `await runner.close()`, might still be necessary
    # depending on your runner's lifecycle.

This pattern is also ideal for multi-agent chaining, as seen in ADK's internal implementation for AgentTool, where one agent's runner is nested within another tool's execution scope [2].

3. Re-enabling User Input

You should re-enable user input and perform other finalization tasks after you have identified and processed the final event for the turn, which is correctly identified using event.is_final_response() [4].

We appreciate you raising these important questions. Let us know if you have any more!

---

References:
[1] google.adk.utils.context_utils.py - Source for the Aclosing context manager. link
[2] google.adk.tools.google_search_agent_tool.py - Example of nested runners and cleanup. link
[3] telemetry/main.py - Example of explicit aclose() in a finally block. link
[4] ADK Events Documentation - Explanation of is_final_response(). link

[caichuanwang]

I know that adding a return will properly close the resource, but I want to know if not adding a return would cause a resource leak.