AgentExecutor ainvoke stopped working after version upgrade. error: "__aenter__"

[mrctito]

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Example Code

Relevant points from my source code:

agent_runnable= create_openai_tools_agent(llm=self.llm_with_tools, tools=self.tools, prompt=prompt_obj)
or
agent_runnable= create_tool_calling_agent(llm=self.llm_with_tools, tools=self.tools, prompt=prompt_obj)
or
agent_runnable= create_openai_functions_agent(llm=self.llm_with_tools, tools=self.tools, prompt=prompt_obj)

...
agent_executor = AgentExecutor(agent=self.agent_runnable,
tools=self.tools,
memory=memory,
max_iterations=35,
max_execution_time=90,
#early_stopping_method='generate',
early_stopping_method='force',
verbose=app_keys.DEBUG(2),
handle_parsing_errors=True,
#handle_parsing_errors=False,
return_intermediate_steps=return_intermediate_steps,
callbacks=chat.callbacks
).with_config({"run_name": "Agent"})

...
result = await self.agent_executor.ainvoke(self.context, return_only_outputs=True)

Description

Dear friends, I need help!

Context: I have a production multi-agent application that stopped working at some point after these versions:

langchain==0.2.1
langchain-community==0.2.1
langchain-experimental==0.0.59
langchain-openai==0.1.7
langchain-qdrant==0.1.0
langgraph==0.0.55

Only after the update did it start presenting the error: "aenter"

The error message is simply: "aenter"

Relevant points from my source code:

To try to solve the problem I have already tried with these 3 methods below, but it did not work:

agent_runnable= create_openai_tools_agent(llm=self.llm_with_tools, tools=self.tools, prompt=prompt_obj)
or
agent_runnable= create_tool_calling_agent(llm=self.llm_with_tools, tools=self.tools, prompt=prompt_obj)
or
agent_runnable= create_openai_functions_agent(llm=self.llm_with_tools, tools=self.tools, prompt=prompt_obj)

...
agent_executor = AgentExecutor(agent=self.agent_runnable,
tools=self.tools,
memory=memory,
max_iterations=35,
max_execution_time=90,
#early_stopping_method='generate',
early_stopping_method='force',
verbose=app_keys.DEBUG(2),
handle_parsing_errors=True,
#handle_parsing_errors=False,
return_intermediate_steps=return_intermediate_steps,
callbacks=chat.callbacks
).with_config({"run_name": "Agent"})

...
**result = await self.agent_executor.ainvoke(self.context, return_only_outputs=True)

This is where the error happens: "aenter"**

The error message is simply: "aenter"

I emphasize that the application worked without problems for a long time before version upgrade.

Can someone please help me?

Thank you!

System Info

langchain==0.2.6
langchain-community==0.2.6
langchain-core==0.2.10
langchain-experimental==0.0.62
langchain-openai==0.1.13
langchain-qdrant==0.1.0
langchain-text-splitters==0.2.1

[dosubot[bot]]

To resolve the __aenter__ error after upgrading the LangChain-related packages, you need to ensure that you are using the correct asynchronous context management methods provided by the updated LangChain library. The __aenter__ method is part of the asynchronous context management protocol, and its absence or misconfiguration can lead to such errors.

Here's an example of how you might use asynchronous context management correctly with LangChain agents:

import asyncio
from langchain.agents import AgentExecutor

async def main():
    # Initialize your agent executor
    agent_executor = AgentExecutor(
        agent=self.agent_runnable,
        tools=self.tools,
        memory=memory,
        max_iterations=35,
        max_execution_time=90,
        early_stopping_method='force',
        verbose=app_keys.DEBUG(2),
        handle_parsing_errors=True,
        return_intermediate_steps=return_intermediate_steps,
        callbacks=chat.callbacks
    ).with_config({"run_name": "Agent"})

    # Use asynchronous context management
    async with agent_executor as executor:
        # Perform actions with the executor
        result = await executor.ainvoke(self.context, return_only_outputs=True)
        print(result)

# Run the main function
asyncio.run(main())

Ensure that any class or function you are using that requires asynchronous context management is properly awaited and used within an async with block. This should help resolve the __aenter__ error ^[1].

To continue talking to Dosu, mention @dosu.

[mrctito]

First of all, I made it clear that my application was working without errors before updating LangChain. After the update, this error appeared. And as soon as I revert to the previous version, the error disappears again. Therefore, I do not understand your recommendations. Em ter., 2 de jul. de 2024, 09:56, dosubot[bot] ***@***.***> escreveu:

…

To resolve the __aenter__ error after upgrading the LangChain-related packages, you need to ensure that you are using the correct asynchronous context management methods provided by the updated LangChain library. The __aenter__ method is part of the asynchronous context management protocol, and its absence or misconfiguration can lead to such errors. Here's an example of how you might use asynchronous context management correctly with LangChain agents: import asynciofrom langchain.agents import AgentExecutor async def main(): # Initialize your agent executor agent_executor = AgentExecutor( agent=self.agent_runnable, tools=self.tools, memory=memory, max_iterations=35, max_execution_time=90, early_stopping_method='force', verbose=app_keys.DEBUG(2), handle_parsing_errors=True, return_intermediate_steps=return_intermediate_steps, callbacks=chat.callbacks ).with_config({"run_name": "Agent"}) # Use asynchronous context management async with agent_executor as executor: # Perform actions with the executor result = await executor.ainvoke(self.context, return_only_outputs=True) print(result) # Run the main functionasyncio.run(main()) Ensure that any class or function you are using that requires asynchronous context management is properly awaited and used within an async with block. This should help resolve the __aenter__ error [1] <https://github.com/langchain-ai/langchain/blob/master/libs/langchain/langchain/agents/__init__.py> . *To continue talking to Dosu <https://dosu.dev>, mention @dosu <https://github.com/dosu>.* — Reply to this email directly, view it on GitHub <#23762 (comment)>, or unsubscribe <https://github.com/notifications/unsubscribe-auth/AAGFVVUTZZ3BLIISNBKPEGDZKKPQDAVCNFSM6AAAAABKHOHZGWVHI2DSMVQWIX3LMV43SRDJONRXK43TNFXW4Q3PNVWWK3TUHM4TSMZWGU4DE> . You are receiving this because you authored the thread.Message ID: ***@***.*** com>

[mrctito]

I did this but the error "aenter" persistis:

async with agent_executor as executor:
    # Perform actions with the executor
    result = await executor.ainvoke(self.context, return_only_outputs=True)
    print(result)

[dosubot[bot]]

The __aenter__ error you're encountering is likely due to recent changes in the AgentExecutor class and its methods related to asynchronous context management. Specifically, the AgentExecutorIterator class now includes asynchronous iteration methods __aiter__ and _aprocess_next_step_output, which handle asynchronous context management ^[1].

To address this, ensure that your AgentExecutor class and related methods are up-to-date and correctly implemented. Here is an updated example that aligns with the latest changes:

import asyncio
from langchain.agents import AgentExecutor, create_openai_tools_agent

async def main():
    # Initialize your agent
    agent_runnable = create_openai_tools_agent(
        llm=self.llm_with_tools,
        tools=self.tools,
        prompt=prompt_obj
    )

    # Initialize your agent executor
    agent_executor = AgentExecutor(
        agent=agent_runnable,
        tools=self.tools,
        memory=memory,
        max_iterations=35,
        max_execution_time=90,
        early_stopping_method='force',
        verbose=app_keys.DEBUG(2),
        handle_parsing_errors=True,
        return_intermediate_steps=return_intermediate_steps,
        callbacks=chat.callbacks
    ).with_config({"run_name": "Agent"})

    # Use asynchronous context management
    async with agent_executor as executor:
        # Perform actions with the executor
        result = await executor.ainvoke(self.context, return_only_outputs=True)
        print(result)

# Run the main function
asyncio.run(main())

Ensure that you are using the latest version of LangChain and its dependencies. If the issue persists, you might want to check for any breaking changes or updates in the migration guide and changelog:

• Breaking Changes & Deprecations
• LangChain Changelog ^[2][3].

These resources provide detailed information on recent changes and how to migrate your code accordingly.

@eyurtsev, this one's a bit out of my wheelhouse, could you step in and provide your guidance?

To continue talking to Dosu, mention @dosu.