Add different kinds of data: Youtube videos, PDFs, Internet links and ask questions based on the content provided using an intuitive UI.
A basic POC for a RAG-based chatbot that can be used for a variety of purposes.
This is an AI-powered tool made for researching, by augmenting GPT models with your own data.
We recommend using a 'chat' instance within the app for a singular purpose. For example, you can use it to research a specific large legal document, but adding other documents will likely confuse the model and you are likely to get mixed results.
The app is currently in development and is not ready for production use. One can use it locally by following the instructions below.
Structure:
https://github.com/sebi75/multitype-llm-chat/assets/36008268/c3de520c-9b11-468e-80a0-803a48f61d6d
pnpm run db:push
cd ./indexing-service
docker-compose up
bash cd ../indexing-service
Create a new virtual environment and install the dependencies
python -m venv .venv
Activate the new virtual environment
source .venv/bin/activate
Install the dependencies from the requirements.txt file
pip install -r requirements.txt
Start the Flask API.
python main.py
cd web
pnpm install
pnpm dev