This repo contains a notebook that guides you through the process of using Jina Embeddings V2 in a retrieval augmented generation pipeline.
It uses the model jinaai/jina-embeddings-v2-base-de
from HuggingFace, which is a bilingual German-English embedding model trained by Jina AI.
Install the requirements in requirements.txt
in a fresh environment.
To run the notebook rag.ipynb
, it is also necessary to host a service that serves a (small) large language model. You can do this on an ordinary local machine without GPUs using ollama. To setup such a service:
- Follow the installation instruction for ollama
- Pull the mistral (or any other small) LLM model using
ollama pull mistral
- Start a service by running
ollama serve
Now you can execute all blocks in the notebook.
Disclaimer: The data in the data/
folder was generated using GPT4 for the purpose of demonstrating the RAG pipeline on unseen, "private" data.