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langchain-ai / langchain

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https://python.langchain.com
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Bugs in importing when Deploying a LangChain web app to multiple hosting platforms! #15074

Closed SaiFUllaH-KhaN1 closed 5 months ago

SaiFUllaH-KhaN1 commented 8 months ago

System Info

I have observed that while using the command belonging to importing "langchain.llms (for example as in from langchain.llms import HuggingFaceHub") have no problem when I deploy my web app to multiple hosting sites like streamlit, Render, Heroku etc. However, using the "langchain.memory" as in from langchain.memory import ConversationBufferMemory and "langchain.prompts" as in from langchain.prompts import PromptTemplate causes deployment to fail in all said hosting sites. They throw a module not found error for the langchain.memory and langchain.prompts. Please note: that running in google colab or vscode does not have this error. Also, python version and langchain versions are irrelevant to this problem since I have tested through a lot of variations. Please help out. Thanks in advance

Who can help?

@hwchase17 @agola11 @eyurtsev

Information

Related Components

Reproduction

import soundfile as sf from langchain.llms import HuggingFaceHub

Below line gives error not in vscode or google colab but in deployment to render, heroku, streamlit and other hosting sites as well. I have not used ConversationBufferMemory in below code even, since the this line causes problem even in initial importing

from langchain.memory import ConversationBufferMemory

import speech_recognition as sr

Initialize any API keys that are needed

import os from flask import Flask, render_template, request, session, flash, get_flashed_messages

os.environ["HUGGINGFACEHUB_API_TOKEN"] = "write your own api here"

app = Flask(name) app.secret_key = '123' @app.route("/LLMEXP", methods=['GET', 'POST']) def llmexp(): if 'chat_messages' not in session: session['chat_messages'] = []

conversation = HuggingFaceHub(repo_id="google/flan-t5-small", model_kwargs={"temperature": 0.1, "max_length": 256})

if request.method == 'POST':
    if 'record_audio' in request.form:
        # Record audio and convert to text
        user_input = request.form['user_input']
    else:
        # User input from textarea
        user_input = request.form['user_input']

    if not user_input or user_input.isspace():
        flash("Please provide a valid input.")

    else:
        user_message = {'role': 'user', 'content': f"User: {user_input}"}
        session['chat_messages'].append(user_message)

        response = conversation(user_input)

        if not response.strip():
            response = "I didn't understand the question."

        #text_to_speech(response)

        assistant_message = {'role': 'assistant', 'content': f"Bot: {response}"}
        session['chat_messages'].append(assistant_message)

        session.modified = True

return render_template("index.html", chat_messages=session['chat_messages'])

if name == "main": app.run(debug=True)

Expected behavior

I expect that I do not receive any error related to "langchain.memory" or "langchain.prompts" error while deploying to a hosting site.

dosubot[bot] commented 8 months ago

🤖

Hello @SaiFUllaH-KhaN1! 🤖 I'm Dosu, a bot here to help you navigate the waters of LangChain while we wait for a human maintainer to assist. I'm here to help with bug troubleshooting, answer your questions, and guide you in becoming an ace contributor! Let's code and conquer together. 😉🚀

Based on the context provided, it's clear that the LangChain codebase does include the modules "langchain.memory" and "langchain.prompts". The issue you're experiencing might be due to the hosting platforms not being able to locate these modules during deployment.

One possible reason could be the structure of the LangChain package in your deployment environment. It's possible that the hosting platforms are not correctly recognizing the package structure, hence they are unable to locate the "langchain.memory" and "langchain.prompts" modules.

To troubleshoot this, you could try the following steps:

  1. Check the package structure in your deployment environment: Make sure that the LangChain package is correctly installed and its structure is intact. You can do this by logging into your hosting platform's console and navigating to the directory where LangChain is installed. Then, check if the "memory" and "prompts" directories exist under the "langchain" directory.

  2. Check the PYTHONPATH: The PYTHONPATH is an environment variable that specifies additional locations where Python should look for modules. If the LangChain package is installed in a location that's not included in the PYTHONPATH, Python won't be able to find the "langchain.memory" and "langchain.prompts" modules. You can check the PYTHONPATH by running echo $PYTHONPATH in the console. If the directory containing the LangChain package is not included in the PYTHONPATH, you can add it by running export PYTHONPATH=$PYTHONPATH:/path/to/langchain.

  3. Check the import statements: Make sure that the import statements in your code are correct. The import statements should match the structure of the LangChain package. For example, if the "memory" directory is a subdirectory of the "langchain" directory, the import statement should be from langchain.memory import ConversationBufferMemory.

If none of the above steps solve the issue, it would be helpful if you could provide more information about the error messages you're seeing. Specifically, the full text of the error messages and the stack traces would be very useful for further troubleshooting.

I hope this helps! If you have any further questions, please don't hesitate to ask.

Best regards, Dosu

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