Issue: Langchain ChatOpenAI chat_model.complete error message: 'chatopenai' object has no attribute 'complete'

[ZinanYang1995]

I am new to Langchain and OpenAI models. I am creating a custom PDF reading in Python using Langchain ChatOpenAI model to interact with the chat completion endpoint. I keep getting this error message and I don't know what to do. Please help. All suggestions are welcome!

Here is a part of my code where the error message was generated.

User Input

    current_prompt = st.session_state.get('user_input', '')

    prompt_placeholder = st.empty()

    # Check if a submission has been made
    if 'submitted' in st.session_state and st.session_state.submitted:
        prompt = prompt_placeholder.text_area("Ask questions about your PDF:", value='', placeholder="Send a message", key="new_user_input")
    else:
        prompt = prompt_placeholder.text_area("Ask questions about your PDF:", value=current_prompt, placeholder="Send a message", key="user_input")

    submit_button = st.button("Submit")

    if submit_button and prompt:
        # Indicate that a submission has been made
        st.session_state.submitted = True

        # Update the last input in session state
        st.session_state.last_input = prompt

        # Process user message
        user_message = HumanMessage(content=prompt)
        st.session_state.chat_history.append(user_message)

        try:
            # Similarity check
            docs = VectorStore.similarity_search(query=prompt, k=3)
            
            # Initialize chat model
            chat_model = ChatOpenAI(model_name="gpt-3.5-turbo")

            # Add a system message to the chat history to define the role
            system_message = SystemMessage(content="You're a helpful assistant")
            st.session_state.chat_history.append(system_message)

            # Get a response from the chat model
            completion_response = chat_model.complete(
                messages=st.session_state.chat_history,
                temperature=0.9  # Adjust temperature as needed
            )
            response_content = completion_response.choices[0].message['content']

            # Process AI message using AIMessage
            assistant_message = AIMessage(content=response_content)
            st.session_state.chat_history.append(assistant_message)

            # Load the question-answering chain
            llm = OpenAI(model_name='gpt-3.5-turbo')
            chain = load_qa_chain(llm=llm, chain_type="stuff")

            # Run the question-answering chain with the documents and the user's prompt
            with get_openai_callback() as cb:
                response = chain.run(input_documents=docs, question=prompt)
                # This print statement is for debugging purposes
                print(cb)
            # st.write(response)
            # st.write(docs)

            # Append the QA chain response as an AI message
            qa_response_message = AIMessage(content=response)
            st.session_state.chat_history.append(qa_response_message)
            
        except Exception as e:
            st.error(f"An error occurred: {e}")
        
        # Clear the input after processing
        prompt_placeholder.text_area("Ask questions about your PDF:", value='', placeholder="Send a message", key="pdf_prompt") 

    # Save chat history
    with open(chat_history_file, "wb") as f:
        pickle.dump(st.session_state.chat_history, f)
        
    # Display the entire chat 
    chat_content = ""
    for message in st.session_state.chat_history:
        if isinstance(message, HumanMessage):
            role = "User"  # Set the role manually for HumanMessage
            content = message.content  # Access the content attribute directly
        elif isinstance(message, AIMessage):
            role = "AI"  # Set the role manually for AIMessage
            content = message.content  # Access the content attribute directly
        else:
            # Handle other types of messages or raise an error
            role = "Unknown"
            content = "Unsupported message type"

        chat_content += f"<div style='background-color: #222222; color: white; padding: 10px;'>**{role}:** {content}</div>"
    st.markdown(chat_content, unsafe_allow_html=True)

if name == 'main':
main()

[dosubot]

🤖

Hi @ZinanYang1995,

I'm Dosu, a friendly bot here to assist you with LangChain. I'm capable of helping you debug issues, answer any queries you might have, and guide you in becoming a contributor. While we await a response from a human maintainer, I'm here to provide you with immediate support.

I'm currently reviewing your issue and will provide a comprehensive response shortly.

[dosubot]

🤖

Based on the error message you're encountering, it seems like there's a misunderstanding about the methods available in the ChatOpenAI class. Specifically, the ChatOpenAI class does not have a complete method, which is why you're seeing the error message 'chatopenai' object has no attribute 'complete'.

Instead, you should use one of the available methods for generating completions. These include 'generate', '_generate', 'agenerate', 'stream', 'astream', 'batch', 'abatch', 'invoke', and 'ainvoke'. The 'generate' and '_generate' methods are used for synchronous operations, while 'agenerate', 'stream', 'astream', 'batch', 'abatch', 'invoke', and 'ainvoke' are used for asynchronous operations.

Here's an example of how you might use 'generate':

chat_model = ChatOpenAI(...)  # Initialize with your parameters
response = chat_model.generate([[message], [message]])

And here's an example of how you might use 'agenerate' in an asynchronous context:

chat_model = ChatOpenAI(...)  # Initialize with your parameters
response = await chat_model.agenerate([[message], [message]])

In both examples, 'message' is a HumanMessage object. You can find more details about these methods in the LangChain repository.

Also, please ensure that you're initializing the ChatOpenAI model correctly. Here's an example of how to do it:

from langchain.chat_models.openai import ChatOpenAI

chat_model = ChatOpenAI(
    model_name="gpt-3.5-turbo",
    temperature=0.7,
    model_kwargs={},
    openai_api_key="your_openai_api_key",
    openai_api_base="https://api.openai.com",
    openai_organization="your_organization",
    openai_proxy=None,
    request_timeout=600,
    max_retries=6,
    streaming=False,
    n=1,
    max_tokens=1000,
    tiktoken_model_name=None
)

Please replace "your_openai_api_key" and "your_organization" with your actual OpenAI API key and organization name. The other parameters can be adjusted according to your needs.

I hope this helps! If you have any other questions or need further clarification, feel free to ask.

Sources

• openai has no ChatCompletion attribute
• Invalid model when use chain
• libs/langchain/langchain/chat_models/openai.py
• libs/langchain/tests/integration_tests/chat_models/test_openai.py

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[kathy-lee]

I have a simlar problem with running chat_model = ChatOpenAI(...) # Initialize with your parameters.

ValidationError: 1 validation error for ChatOpenAI
__root__
  `openai` has no `ChatCompletion` attribute, this is likely due to an old version of the openai package. Try upgrading it with `pip install --upgrade openai`. (type=value_error)

Is it because the latest openai v1.1.1 change has not been adapted into langchain.chat_models.ChatOpenAI? Does anyone can help?