README

Archyve is a web app that makes pretrained LLMs aware of a user's documents, while keeping those documents on the user's own devices and infrastructure.

Overview

It enables Retrieval-Augmented Generation (RAG) by providing an API to query the user's docs for relevant context. The client provides the prompt the user gave, and Archyve will return relevant text chunks.

Archyve provides:

• a document upload and indexing UI, where the user can upload documents and test similarity searches against them
• a built-in LLM chat UI, so the user can test the effectiveness of their documents with an LLM
• an API, so the user can provide Archyve search results in dedicated LLM chat UIs

Getting started

To run Archyve, use docker compose or podman compose.

1. Clone this repo
2. cp dotenv_template local.env
3. Run openssl rand -hex 64 and put the value in the SECRET_KEY_BASE variable in your local.env file
4. Run the container

docker compose up --build

If you see "✘ archyve-worker Error", don't worry about it. Docker will build the image and run it.

1. Browse to http://127.0.0.1:3300 and log in with [email protected] / password (you can change these values by setting USERNAME and PASSWORD in your local.env file and restarting the container)

See the next section for setting up Ollama for use by Archyve or document uploads and chat will fail.

Dependencies

Ollama

You can run a dedicated instance of Ollama in a container by adding it to the compose.yaml file, but it takes a while to pull a chat model, so the default here is to assume you already have an Ollama instance.

Archyve will use a local instance of Ollama by default. Ensure you have Ollama installed and running (with ollama serve) and then run the following commands to set up your Ollama instance for Archyve:

• embedding model: ollama pull all-minilm
• chat model: ollama pull mistral:instruct
• alternative chat model: ollama pull gemma:7b (if you intend to use Gemma)

You can change the embedding model and the summarization model by changing those variables in your local.env file and restarting the server. If you change these values, make sure you pull the new models in Ollama.

Admin UI

There is an admin UI running at http://127.0.0.1:3300/admin. There, you can view and change ModelConfigs and ModelServers.