When i run my demo,It just stuck at llm.invoke().I can't figure what wrong with it

[jscksy]

Checked other resources

• I added a very descriptive title to this question.
• I searched the LangChain documentation with the integrated search.
• I used the GitHub search to find a similar question and didn't find it.

Commit to Help

• I commit to help with one of those options 👆

Example Code

openai_api_key = os.environ['OPENAI_API_KEY']
    base_url = os.environ['BASE_URL']

    llm = ChatOpenAI(model='gpt-3.5-turbo',
                     temperature=0.1,
                     api_key=openai_api_key,
                     base_url=base_url)

    output = llm.invoke("hi")
    output_parser = StrOutputParser()
    output_parser.invoke(output)

Description

When i run my demo,It just stuck at llm.invoke().I can't figure what wrong with it

System Info

in windows10 with pycharm

[dosubot[bot]]

Your code might be getting stuck at llm.invoke() due to missing or incorrect environment variables required for the ChatOpenAI model to function properly. Ensure that the following environment variables are correctly set:

• OPENAI_API_KEY
• OPENAI_API_BASE (if using a proxy or service emulator)
• OPENAI_ORG_ID (if applicable)

Additionally, make sure that the client or async_client is properly set up. Here is an example of how to mock the client for synchronous invocations:

from unittest.mock import MagicMock, patch

def test_openai_invoke(mock_completion: dict) -> None:
    llm = ChatOpenAI(api_key=openai_api_key, base_url=base_url)
    mock_client = MagicMock()
    completed = False

    def mock_create(*args: Any, **kwargs: Any) -> Any:
        nonlocal completed
        completed = True
        return mock_completion

    mock_client.create = mock_create
    with patch.object(llm, "client", mock_client):
        res = llm.invoke("hi")
        assert res.content == "Expected Response"
    assert completed

If you are using the Azure OpenAI integration, ensure that the following environment variables are set:

• AZURE_OPENAI_API_KEY
• AZURE_OPENAI_ENDPOINT

To enable detailed logs for debugging, you can use the set_debug mode:

from langchain.globals import set_debug

set_debug(True)
llm = ChatOpenAI(api_key=openai_api_key, base_url=base_url)
output = llm.invoke("hi")

This will print the inputs and outputs of all LangChain components, providing a comprehensive view of the chain's execution ^[1][2].

To continue talking to Dosu, mention @dosu.