langchain-pinecone-chat-bot

This repo is a fully functional Flask app that can be used to create a chatbot app like BibleGPT, KrishnaGPT or Chat app over any other data source.

It uses the following

• Ready made embeddings from embedstore.ai (python package). These text is chunked using LangChain's RecursiveCharacterTextSplitter with chunk_size as 1000, chunk_overlap as 100 and length_function as len. OpenAI embeddings (dimension 1536) are then used to calculate embeddings for each chunk.
• It loads the embeddings and then indexes them into a Pinecone index.
• Now whenever a user query is received, it first creates embedding for it using OpenAI embeddings. Then it search for the nearest 3 neighbour using cosine similarity in Pinecone index.
• Now these documents are passed as context to ChatGPT API with the below prompt and temperature as 0 and max_tokens as 800

You are given a paragraph and a query. You need to answer the query on the basis of paragraph. If the answer is not contained within the text below, say "Sorry, I don't know. Please try again."

P: {documents}
Q: {query}
A:

• Answer retrieved from ChatGPT API is shown to the user.

Setup Instructions

• First make sure that you python3, python-virtualenv and setup tool installed on the system.
• Next clone the repo

git clone https://github.com/embedstore/langchain-pinecone-chat-bot.git

• Now create a virtual environment and install all the dependencies

cd langchain-pinecone-chat-bot
virtualenv -p $(which python3) pyenv
source pyenv/bin/activate

pip install -r requirements.txt

• Now copy the env file and fill in your variables

cp .env.sample .env

• The EMBEDDING_ID variable is the id of the embedding which you can get from embedstore.ai

• Now run the app

python main.py

• You can also create a repl and import the repo and run it easily over there.

License

• MIT License