This is a LlamaIndex project bootstrapped with create-llama.
First, startup the backend as described in the backend README.
Go to ./backend and run qdrant docker
1)docker pull qdrant/qdrant
2)docker run -d -p 6333:6333 -p 6334:6334
-v $(pwd)/qdrant_storage:/qdrant/storage:z
qdrant/qdrant
Second, run the development server of the frontend as described in the frontend README.
Open http://localhost:3000 with your browser to see the result.
For Production, Go to ./frontend 1)npm run build 2)npx serve@latest out -l 80 (-l 80 if you want to run in port 80)
Default HuggingFace Hub is used so export HUGGINGFACEHUB_API_TOKEN=hf_XXXXX before running the backend If you want to use LLamaCPP and models locally, the copy index.py and chat.py from root folder to backend ( ./backend/app/api/routers/chat.py and ./backend/app/utils/index.py and update the model_path in index.py where you have donloaded GGUF from Hugging Face )
To learn more about LlamaIndex, take a look at the following resources:
- LlamaIndex Documentation - learn about LlamaIndex (Python features).
- LlamaIndexTS Documentation - learn about LlamaIndex (Typescript features).
You can check out the LlamaIndexTS GitHub repository - your feedback and contributions are welcome!