nanoQA 2.0

This repo deploys a simple chat webapp that can answer about your custom data provided. It uses OpenAI endpoints, Langchain library and Pinecone vector DB.

This blog post provides more information about this project

Demo

Quickstart

Try Locally

• Clone the repo git clone https://github.com/miranthajayatilake/nanoQA2.git
• Move into directory cd nanoQA2
• Set up your python>3.8 environment (virtual environment preferred)
• Install the depedencies pip install -r requirements.txt
• Assign the environment variables by running bash env-local.sh. Make sure you have the following API keys and variables replaced
  • OpenAI API key (OPENAI_API_KEY). You can obtain this by creating a account at OpenAI
  • Pinecone API key and environment name (PINECONE_API_KEY, PINECONE_ENV). Obtain these by making an account at Pinecone
    • Next we have to create an index in the Pinecone account. You can use the create_index.py to do this. Make sure to provide the parameters as below.
    • create_index.py --pinecone_api_key <asdf> --pinecone_environment <asdf> --index_name <asdf>
  • Copy the index name used above (INDEX_NAME)
  • Provide a namespace as well (NAMESPACE) just to organize data in the database
  • Provide a name that you want your chatbot to have (EGPTNAME)
• Run the webapp with streamlit run Chat.py

Deploy to cloud with fly.io

Fly.io is a very easy-to-use tool to deploy apps

• Clone the repo git clone https://github.com/miranthajayatilake/nanoQA2.git
• Create an account on fly.io
• Install their CLI tool called flyctl and configure it in your local environment
• Move into directory cd nanoQA2
• Run flyctl launch
  • Follow the instructions in the terminal. Give a name to the app and select N when asked whether we want any database.
  • Whenprompted to deploy, also select N. We have to configure the environment variables before deploying the app
• Assign the environment variables by running bash env-flyio.sh. Make sure you have the following API keys and variables replaced
  • OpenAI API key (OPENAI_API_KEY). You can obtain this by creating a account at OpenAI
  • Pinecone API key and environment name (PINECONE_API_KEY, PINECONE_ENV). Obtain these by making an account at Pinecone
    • Next we have to create an index in the Pinecone account. You can use the create_index.py to do this. Make sure to provide the parameters as below.
    • create_index.py --pinecone_api_key <asdf> --pinecone_environment <asdf> --index_name <asdf>
  • Copy the index name used above (INDEX_NAME)
  • Provide a namespace as well (NAMESPACE) just to organize data in the database
  • Provide a name that you want your chatbot to have (EGPTNAME)
• Now run flyctl deploy. This command will take care of building the docker image, pushing it to the cloud and deplying.
• Once done, we have to increase the resources of the app to run smoothly. Do this by running flyctl machine update <machine ID> --cpus 2 --memory 4096. Replace <machine ID> with the ID of your machine (Can be found via the fly.io dashboard)
• You can also get the URL for the app via the dashboard