https://twitter.com/olshansky/status/1672827218563850240
- Get your OpenAI key from here; make sure you're logged in
- Get your PinconeAI key from here; make sure you're logged in
- Create an index called
my-index
orvitalik-index
as showing here depending on which option you choose below
cp .streamlit/secrets.toml.template .streamlit/secrets.toml
Update the env vars appropriately.
- Start the virtual environment and install the requirements:
$(make env_source)
make pip_install
- Download Vitalik's articles
make download_vitalik_articles
- Create the embeddings and upload them to Pinecone
make prepare_db
- Run it locally and ask a question:
make streamlit_app
- Start the virtual environment and install the requirements:
$(make env_source)
make pip_install
- Get your pdfs and put them in
./data/my_data
mv or cp or w/e floats your boat into `./data/my_data`
3.Prepare the database with your pdfs
# DATADIR and INDEX_NAME are customizable but you can start with the defaults if you don't know what you're doing yet
make prepare_db DATADIR=data/my_data INDEX_NAME=my-index
-
Open up
query_db.py
and updateprompt_template
appropriately -
Run it locally and ask a question:
make streamlit_app
- Initial reference for this repo: https://blog.bytebytego.com/p/how-to-build-a-smart-chatbot-in-10
- Langchain docs: https://python.langchain.com/
- A full book I haven't read yet: https://www.pinecone.io/learn/langchain-intro/
- OpenAI API: https://beta.openai.com/docs/introduction
- Easily host infra: fly.io or render.com
- Easily deploy WIP app in python: https://streamlit.io/generative-ai
- Building a backend API w/ nothing: https://github.com/fern-api/fern
- Notion - Add support for pulling data from notion
- Twitter - Use user tweet accounts to do this as well
- OpenAI - Use the OpenAI Chat Completion API directly
- Pinecone - Need to be able to update existing index