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A newer version of the Streamlit SDK is available: 1.40.0

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metadata
title: Chatbot For Files Langchain
emoji: 
colorFrom: yellow
colorTo: pink
sdk: streamlit
sdk_version: 1.19.0
app_file: app.py
pinned: false
license: mit

Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

This is a chatbot that uses Langchain's Conversational Retrieval Chain to generate responses to user input. The chatbot can ingest files and use Pinecone (Pinecone API key required) or Chroma vector stores (no API key required) to retrieve relevant documents for generating responses. OpenAI's API key is also required. The UI is based on Streamlit.

Fun fact

This README file is generated by this app after ingesting this python file. See the screenshot below.

Installation

To install the required packages, run:

pip install -r requirements.txt

Usage

To run the chatbot, run:

streamlit run app.py

The chatbot will prompt the user for inputs and generate a response based on user's question and the chat history.

Ingesting Files

To ingest files, select "Yes" when prompted and upload the files. The chatbot will split the files into smaller documents and ingest them into the vector store.

Using Pinecone

To use Pinecone, select "Yes" when prompted and enter the name of the Pinecone index. Make sure to set the PINECONE_API_KEY and PINECONE_API_ENV environment variables.

Using Chroma

To use Chroma, enter the name of the Chroma collection when prompted. The chatbot will create a Chroma vector store in the persist_directory specified in the code.

Screenshot

Use Pinecone and not ingest files:

Use Pinecone

Use Chroma and ingest files:

Use Chroma