Issue: <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)>

[KaifAhmad1]

Issue you'd like to raise.

Issue: <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)>

Import necessary packages for Streamlit app, PDF processing, and OpenAI integration.

`import` streamlit as st
import pdfplumber
import os
from langchain.vectorstores import faiss
from langchain.chat_models import ChatOpenAI
from langchain.chains import ConversationalRetrievalChain
from langchain.embeddings.openai import OpenAIEmbeddings
from langchain.chains.conversation.memory import ConversationBufferWindowMemory
from langchain.text_splitter import CharacterTextSplitter
from langchain.chains.summarize import load_summarize_chain
from langchain.docstore.document import Document
from dotenv import load_dotenv

Load and verify environment variables, specifically the OpenAI API key.

Load .env file that is in the same directory as your script.

load_dotenv()
OPENAI_API_KEY = os.getenv("OPENAI_API_KEY")
if OPENAI_API_KEY is None:
    raise ValueError("OpenAI API key not found. Make sure you have an .env file with the key defined.")

Initialize the OpenAI language model with a given API key and temperature setting.

chain = ConversationalRetrievalChain.from_llm(
llm = ChatOpenAI(temperature=0.1,model_name='gpt-4'),
retriever=vectorstore.as_retriever())

Initializing the Embedding Model and OpenAI Model

embeddings = OpenAIEmbeddings()
vectorstore = faiss.from_documents(data, embeddings)

Process an uploaded PDF document and extract its text content.

def process_document(uploaded_file):
    with pdfplumber.open(uploaded_file) as pdf:
        document_text = "\n".join(page.extract_text() for page in pdf.pages if page.extract_text())
    return document_text

Summarize the extracted text from the document using the OpenAI language model.

def summarize_document(llm, document_text):
    text_splitter = CharacterTextSplitter(max_length=1000)
    texts = text_splitter.split_text(document_text)
    docs = [Document(content=t) for t in texts]
    summarize_chain = load_summarize_chain(llm, chain_type='map_reduce')
    return summarize_chain.run(docs)

Initialize a conversation chain with memory capabilities for the chatbot.

def` initialize_conversation_chain(llm):
    return ConversationalRetrievalChain(
        llm=llm,
        memory=ConversationBufferWindowMemory(k=5)  # Stores the last 5 interactions.
    )

Define the main function to run the Streamlit application.

def run_app():
    llm = initialize_llm(OPENAI_API_KEY)

    st.title("Earnings Call Analysis App")

    ### UI for document upload and processing.
   uploaded_file = st.file_uploader("Upload your earnings call transcript", type=["pdf"])
    process_button = st.button("Process Document")

### Process document and generate summaries

    if process_button and uploaded_file:
        with st.spinner('Processing Document...'):
            document_text = process_document(uploaded_file)
            summaries = summarize_document(llm, document_text)
            display_summaries(summaries)
            st.success("Document processed!")

### UI for interactive chatbot with memory feature.

    conversation_chain = initialize_conversation_chain(llm)
    user_input = st.text_input("Ask a question about the earnings call:")
    if st.button('Get Response'):
        with st.spinner('Generating response...'):
            response = generate_chat_response(conversation_chain, user_input, document_text)
            st.write(response)

Display summaries on the app interface and provide download option for each.

def display_summaries(summaries):
    if summaries:
        for i, summary in enumerate(summaries):
            st.subheader(f"Topic {i+1}")
            st.write("One-line topic descriptor: ", summary.get("one_line_summary", ""))
            st.write("Detailed bulleted topic summaries: ", summary.get("bulleted_summary", ""))
            download_summary(summary.get("bulleted_summary", ""), i+1)

Create a downloadable summary file.

def download_summary(summary, topic_number):
    summary_filename = f"topic_{topic_number}_summary.txt"
    st.download_button(
        label=f"Download Topic {topic_number} Summary",
        data=summary,
        file_name=summary_filename,
        mime="text/plain"
    )

Generate a response from the chatbot based on the user's input and document's context.

def generate_chat_response(conversation_chain, user_input, document_text):
    response = conversation_chain.generate_response(
        prompt=user_input,
        context=document_text
    )
    return response.get('text', "Sorry, I couldn't generate a response.")

if __name__ == "__main__":
    run_app()

Suggestion:

No response

[dosubot[bot]]

🤖

Hello @KaifAhmad1,

I'm Dosu, a bot here to assist you with your queries, bug reports, and contributions to the LangChain project. I'm here to bridge the time until a human maintainer can assist you. I understand you've encountered an issue, I'm currently reviewing it and will provide a detailed response shortly. Thanks for your patience!

[dosubot[bot]]

🤖

Based on the context provided, it seems like you're encountering a ValidationError that says openai has no ChatCompletion attribute. This error is likely due to an outdated version of the openai package that does not have the ChatCompletion attribute.

To resolve this issue, you should update your openai package to the latest version. You can do this using pip:

pip install --upgrade openai

After updating the package, you should be able to use the ChatCompletion attribute without any issues.

In the code you've shared, the ChatOpenAI class from the langchain.chat_models module is being used, which is a wrapper for the OpenAI API. This class also uses the ChatCompletion attribute of the openai package. If you're using this class, make sure to also update the openai package to the latest version.

Additionally, ensure that the OPENAI_API_KEY is correctly set when initializing the ChatOpenAI class. If you're using an older version of the OpenAI API (v1), you'll need to instantiate the client differently than if you're using a newer version.

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

Sources

• openai has no ChatCompletion attribute
• libs/langchain/langchain/chat_models/openai.py
• templates/openai-functions-agent/pyproject.toml
• libs/langchain/langchain/chat_models/azure_openai.py
• libs/langchain/langchain/llms/openai.py
• libs/langchain/langchain/utils/openai.py

---

This response is meant to be useful and save you time. It is not meant to be a precise solution, but rather a starting point for your own research.

Help me be more useful! Please leave a 👍 if this is helpful and 👎 if it is irrelevant.

If you want to continue the conversation, start your reply with @dosu-bot.

[yeshwanthjagannath]

I am seeing this issue as well, since the openai package has been updated from 1.1.1 to 1.1.2. Looks like the wrapper is broken. I have tried updating both openai(1.1.2) & langchain(0.0.332) versions to the latest, but continue to face the error.

Below is the error message I get: "pydantic.v1.error_wrappers.ValidationError: 1 validation error for AzureChatOpenAI 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)"

[batmanscode]

@yeshwanthjagannath use openai==0.28.1 for now. That works for me!

[yeshwanthjagannath]

@batmanscode - Thanks for the suggestion, that worked!

[cbornet]

You should install the OpenAI package with the Langchain extra: pip install langchain[openai] This way a compatible version of OpenAI will be pulled.

[dosubot[bot]]

Hi, @KaifAhmad1,

I'm helping the LangChain team manage their backlog and am marking this issue as stale. From what I understand, you raised an issue regarding a validation error for the ChatOpenAI package, indicating that the openai package has no ChatCompletion attribute, likely due to an outdated version. Dosubot provided a detailed response suggesting to upgrade the openai package using pip install --upgrade openai. Other users, such as yeshwanthjagannath and batmanscode, also encountered the issue and suggested using a specific version of the openai package or installing it with the Langchain extra to ensure compatibility. The issue has been resolved by upgrading the openai package using pip install --upgrade openai. Other users also suggested using a specific version of the openai package or installing it with the Langchain extra to ensure compatibility.

Could you please confirm if this issue is still relevant to the latest version of the LangChain repository? If it is, please let the LangChain team know by commenting on the issue. Otherwise, feel free to close the issue yourself, or the issue will be automatically closed in 7 days.

Thank you!