🦜️🔗 Living Infrastructure Chatbot

This chatbot was developed for Spherical.io . It ingests data from notion pages and indexes into FAISS vector DB.

The app leverages LangChain's streaming support and async API to update the page in real time for multiple users.

✅ Running locally

1. Install dependencies: pip install -r requirements.txt
2. Run ingest.sh to ingest LangChain docs data into the vectorstore (only needs to be done once).
   1. You can use other Document Loaders to load your own data into the vectorstore.
3. Run the app: make start
4. Open localhost:9000 in your browser.

Question-Answering has the following steps, all handled by ChatVectorDBChain:

1. Given the chat history and new user input, determine what a standalone question would be (using GPT-3).
2. Given that standalone question, look up relevant documents from the vectorstore.
3. Pass the standalone question and relevant documents to GPT-3 to generate a final answer.