zori 0.3.0

An open-source multi-agent research assistant for your Zotero library

An open-source multi-agent research assistant that connects to your Zotero library. Search, summarize, and explore your research papers through a conversational interface.

Features

• Hybrid search — combines semantic (vector) and keyword (BM25) search across titles, abstracts, tags, and full text
• Summarization — generates structured summaries and saves them as notes directly in Zotero
• Web UI — clean chat interface built on FastAPI; no browser issues, works on any platform
• Conversational context — references like "the first one" or "that paper" are resolved across turns
• Flexible LLM support — OpenAI, Anthropic, or Ollama (free, runs locally)

Web UI

zori ui

Open http://localhost:7860 in your browser. The web UI is the recommended interface on Windows, where terminal hyperlinks may not render correctly.

Requirements

• A Zotero account with API access
• An LLM provider: OpenAI, Anthropic, or Ollama (free, runs locally)

Setup

1. Install

pip install zori

Install from source

git clone https://github.com/nazbn/zori.git
cd zori
uv sync

When installed from source, prefix all commands with uv run (e.g. uv run zori init, uv run zori ingest, uv run zori).

2. Initialize

mkdir my-zori && cd my-zori
zori init

zori init creates config.yaml and .env in the current directory. Always run zori from this directory.

3. Configure

Edit .env with your Zotero API key and library ID, and config.yaml to choose your LLM and embeddings provider (see LLM options and Embeddings options).

4. Ingest your library

zori ingest

Downloads your Zotero PDFs, extracts text, and builds the search index in .zori/. Run time depends on library size and embedding provider. You only need to do a full ingest once. To index new or modified items added to Zotero since the last ingest, run zori ingest --sync.

5. Start the assistant

Web UI (recommended):

zori ui

Or use the terminal REPL:

zori

Usage

Zori supports natural language queries for searching and summarizing papers:

> papers on diffusion models
> papers by Vaswani
> papers from 2023 on neural radiance fields
> summarize the first one
> find attention is all you need
> summarize it

Queries use hybrid search (keyword + semantic). References to previous results are resolved in context (e.g. "the first one", "that paper").

In the terminal REPL: type exit to quit, --new-session to reset conversation history.

LLM options

Provider	config.yaml	Requires
OpenAI	provider: openai	OPENAI_API_KEY in .env
Anthropic	provider: anthropic	ANTHROPIC_API_KEY in .env
Ollama (free, local)	provider: ollama	Ollama running locally

Embeddings options

LLM and embeddings are configured independently — any combination works.

Provider	config.yaml	Setup
OpenAI	provider: openai, model: text-embedding-3-small	OPENAI_API_KEY in .env
Ollama (free, local)	provider: ollama, model: nomic-embed-text	Ollama running + ollama pull nomic-embed-text
HuggingFace (free, local)	provider: huggingface, model: <model> (e.g. all-MiniLM-L6-v2)	pip install "zori[huggingface]"

License

MIT — see LICENSE.

Contact

For questions, bug reports, or feature requests, open an issue on the GitHub issue tracker or reach out at [e-mail].

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This repository was developed with the assistance of Claude (Anthropic).