mirror of
https://github.com/hwchase17/langchain
synced 2024-11-06 03:20:49 +00:00
ebf998acb6
Co-authored-by: Harrison Chase <hw.chase.17@gmail.com> Co-authored-by: Lance Martin <lance@langchain.dev> Co-authored-by: Jacob Lee <jacoblee93@gmail.com>
1.2 KiB
1.2 KiB
Private RAG
This template performs privae RAG (no reliance on external APIs) using:
- Ollama for the LLM
- GPT4All for embeddings
LLM
Follow instructions here to download Ollama.
The instructions also show how to download your LLM of interest with Ollama:
- This template uses
llama2:13b-chat - But you can pick from many here
Set up local embeddings
This will use GPT4All embeddings.
Chroma
Chroma is an open-source vector database.
This template will create and add documents to the vector database in chain.py.
By default, this will load a popular blog post on agents.
However, you can choose from a large number of document loaders here.
Adding the template
Create your LangServe app:
langchain serve new my-app
cd my-app
Add template:
langchain serve add rag-chroma-private
Start server:
langchain start
See Jupyter notebook rag_chroma_private for various way to connect to the template.