This is an app that let's you ask questions about any data source by leveraging embeddings, vector databases, large language models and last but not least langchains
- Upload any
file
or enter anypath
orurl
- The data source is detected and loaded into text documents
- The text documents are embedded using openai embeddings
- The embeddings are stored as a vector dataset to activeloop's database hub
- A langchain is created consisting of a LLM model (
gpt-3.5-turbo
by default) and the embedding database index as retriever - When sending questions to the bot this chain is used as context to answer your questions
- Finally the chat history is cached locally to enable a ChatGPT like Q&A conversation
- As default context this git repository is taken so you can directly start asking question about its functionality without chosing an own data source.
- To run locally or deploy somewhere, execute
cp .env.template .env
and set credentials in the newly created .env file. Other options are manually setting of system environment variables, or storing them into.streamlit/secrets.toml
. - If you have credentials set like explained above, you can just hit
submit
in the authentication without reentering your credentials in the app. - Your data won't load? Feel free to open an Issue or PR and contribute!
- Yes, Chad in
DataChad
refers to the well-known meme
If you like to contribute, feel free to grab any task
- Add option to choose model and embeddings
- Enable fully local / private mode
- Refactor utils, especially the loaders
- Add Image caption and Audio transcription support