Prisma

Research workspace with semantic search over your papers and notes — Zotero-integrated, local-first, and reachable from a browser or desktop app.

Overview

Prisma is a Research Library Assistant that helps researchers intelligently organize, curate, and enhance their research libraries using Zotero as the primary organization tool. It discovers research content, assesses relevance, and provides intelligent library management.

Architecture: prisma serve runs a small supervisor that isolates the API, Web UI, ChromaDB, and native knowledge-graph module into independent, crash-recoverable processes — a flat-Markdown vault (notes, sources, chats, streams) is the shared workspace, with a CLI, REST/WebSocket API, and installable PWA/desktop UI all operating on it.

System Requirements

Required:

• Ollama (or another configured LLM provider — OpenRouter, llama.cpp) for research analysis, chat, and knowledge-graph extraction

Optional:

• Zotero Web API access (for library integration — discovering, deduplicating, and saving research; Prisma runs without it, just without the bookmark layer)
• Internet access to source APIs (arXiv, Semantic Scholar, etc.) and the Zotero Web API

Key Features

• 🌐 Multi-Source Discovery: Searches papers (arXiv, Semantic Scholar, PubMed, IEEE Xplore*) and books (OpenLibrary, Google Books) per stream query, each source independently quota-controlled (*IEEE Xplore requires your own API key)
• 🔗 Zotero Bookmarking: Saves discovered papers into your existing Zotero library via its Web API — Zotero stays the library, Prisma adds to it
• 🌊 Research Streams: Persistent topic monitoring — scheduled searches automatically discover, deduplicate, and file new papers into a dedicated Zotero collection per stream
• ⭐ Quality-Rated Sources: Each search source is rated 1-5 stars by API reliability/structure, prioritizing curated academic APIs over scraping-dependent ones
• 🛡️ Academic Validation: Filters out non-academic content (blogs, ads, spam) via keyword/structure heuristics plus LLM confidence scoring
• 📖 Abstract-Level Relevance: LLM assessment runs on title + abstract, not full PDF text — importing a paper into your vault separately converts its PDF to readable Markdown
• 🤖 AI-Powered Curation: Local or cloud-capable LLMs (Ollama, OpenRouter, llama.cpp) assess relevance, score confidence, and summarize what's found
• 🏷️ Smart Tagging (Streams only): Papers saved via a Research Stream are auto-tagged with confidence score, source, topic, and stream ID
• 🗂️ Vault Workspace: A local, flat-Markdown second brain for notes, sources, and chats — prisma serve opens it as a web app, installable PWA, or native desktop shell
• 💬 Chat: Ask Prisma questions about your vault — grounded in ChromaDB semantic search + native knowledge-graph context, with tool-calling, citations, and a pinning/Excerpt model for managing context budget across local or cloud-capable LLM backends
• 🕸️ Native Knowledge Graph: Entity/relationship extraction (structured LLM output, no third-party dependency) stored in an embedded graph DB, re-ranking search results and answering "what connects to what" — with a live progress UI (sync status, extraction stats, failure inspection)
• 🔍 Semantic Search: ChromaDB embeddings + the knowledge graph re-rank results beyond keyword matching
• 🧹 Deduplication: Multi-level matching (DOI, exact title, year+author, NLTK stem overlap, LLM identity check) catches duplicates other tools miss, on demand or during stream refresh
• 🔄 Vault Sync: Server-orchestrated sync keeps the desktop app and server vault in agreement, working offline and reconciling on reconnect
• ⚡ Live Updates: Vault changes and stream-refresh progress push to the UI over WebSocket in real time

Research Library Management Process

Prisma's research library management workflow:

1. Discover Research - Query external APIs and Zotero libraries using stream's search criteria
   • External Sources: arXiv, Semantic Scholar, PubMed, etc.
   • Zotero Libraries: Existing research collections and newly imported items
2. Assess Relevance - Use LLM to quickly evaluate research relevance to the topic
3. Curate Content - Filter and organize relevant research immediately
4. For Relevant Research:
   • Check Zotero Storage - Search the Zotero Web API for duplicates
   • Save to Zotero - Store new research and add to stream collection (if Zotero is reachable)
   • Mark Unsaved - Flag research that couldn't be saved (if Zotero is unreachable or not configured)
5. Analyze Content - Comprehensive LLM analysis for research assessment
6. Enhance Library - Improve organization and provide research insights (noting any unsaved research)

Note: Zotero serves dual roles as both a source integration (for discovering existing relevant research) and primary organization tool (for organizing and managing research collections).

CLI Commands

The CLI is deliberately minimal — it only covers what can't be an HTTP call (start the server, check readiness, bootstrap auth). Research streams, literature review, and Zotero library management are API-only.

📖 Complete CLI Reference: See CLI Documentation for detailed command options, examples, and the full command→API-route mapping.

# Start the server
prisma serve

# Check system status
prisma status --verbose

Research Streams, Review, and Zotero (via the API)

# Create a research stream
curl -X POST http://127.0.0.1:8765/streams \
  -H 'Content-Type: application/json' \
  -d '{"title": "Stream Name", "query": "search query", "refresh_frequency": "weekly"}'

# Generate a literature review
curl -X POST http://127.0.0.1:8765/review \
  -H 'Content-Type: application/json' \
  -d '{"topic": "neural networks"}'

# Zotero status
curl http://127.0.0.1:8765/zotero/status

Quick Start

Regular users (install from PyPI)

pip install prisma
prisma serve

Run the workspace UI

prisma serve

Opens the vault workspace at http://127.0.0.1:8766/app — installable as a PWA, or wrapped in the Tauri desktop shell. See Installation for the full setup.

Developers (install from source, editable)

git clone https://github.com/CServinL/prisma.git
cd prisma
python3 -m venv ~/prisma
source ~/prisma/bin/activate
pip install -e ".[dev]"
prisma --help

Changes to source files are immediately active — no reinstall needed.

Documentation

📖 Wiki — complete documentation

• Features — what Prisma does and how
• Installation — user and developer setup
• CLI Reference — all commands and options
• Configuration — YAML reference
• Research Streams — persistent topic monitoring
• Sources — quality ratings and academic validation
• Zotero Integration — Web API client, connectivity/reachability, offline write queue
• Architecture — components and data flow
• Roadmap — planned features

Technology Stack

• 🐍 Python 3.12+ — pip/setuptools, no Poetry
• 🤖 Ollama for local LLM backend (analysis, chat, and knowledge-graph extraction)
• 🔗 Zotero for reference management — the bookmark layer; the vault is the second brain
• ⌨️ Click for the command-line interface
• 🗂️ Flat Markdown vault — no database; notes, sources, chats, and streams are plain .md/.yaml files
• 🔍 ChromaDB for semantic search, running as its own supervised server process
• 🕸️ Kùzu — embedded graph DB backing the native knowledge graph (entity/relationship extraction via structured LLM output, no third-party graphify dependency)
• 🌐 FastAPI + SvelteKit — REST + WebSocket API, installable as a PWA on any platform, or wrapped in a native Tauri desktop shell
• 🛡️ Supervised processes — prisma serve runs a small supervisor that isolates the API, Web UI, ChromaDB, and knowledge-graph module into independent, crash-recoverable processes

See Architecture Overview for complete technical details.

Contributing

We welcome contributions from the community! Please see our Contributing Guidelines for details on:

• 🤝 Code of Conduct
• 📋 Contribution Process
• 🏛️ Project Governance
• 🔒 Security Policy

License

This project is licensed under the Apache License 2.0 - see the LICENSE file for details.