/wikichat

Primary LanguagePython

WikiChat

This project is a starter for creating a chatbot using Astra DB. It's designed to be easy to deploy and use, with a focus on performance and usability.

Features

  • Astra DB Integration: Store and retrieve data from your Astra DB database with ease.
  • LangChain.js Integration: Uses the new Astra DB vectorstore to implement RAG.
  • Easy Deployment: Deploy your chatbot to Vercel with just a few clicks.
  • Customizable: Modify and extend the chatbot to suit your needs.

Getting Started

Prerequisites

  • An Astra DB account. You can create one here.
    • An Astra Vector Database
  • An OpenAI Account and API key.
  • A Cohere Account and API key. Note that due to the large volume of ingested data, you'll need a paid plan.

Setup

  1. Clone this repository to your local machine.
  2. Install the dependencies by running npm install in your terminal.
  3. Set up the following environment variables in your IDE or .env file:
    • ASTRA_DB_ENDPOINT: Your Astra DB vector database id in a vector-enabled DB
    • ASTRA_DB_APPLICATION_TOKEN: The generated app token for your Astra database
      • To create a new token go to your database's Connect tab and click Generate Token. (your Application Token begins with AstraCS:...)
    • OPENAI_API_KEY: Your OpenAI API key.
    • COHERE_API_KEY: Your Cohere API key for embeddings.
    • LANGCHAIN_TRACING_V2 (optional): Set to true to enable tracing
    • LANGCHAIN_SESSION (optional): The LangSmith project that will receive traced runs.
    • LANGCHAIN_API_KEY (optional): LangSmith API key
  4. Populate your database by following the instructions here

Running the Project

To start the development server, run npm run dev in your terminal. Open http://localhost:3000 to view the chatbot in your browser.

Deployment

You can easily deploy your chatbot to Vercel by clicking the button below:

Deploy with Vercel

Remember to set your environment variables to the values obtained when setting up your Astra DB and OpenAI accounts.