GNO vs PrivateGPT
Verdict: Both are privacy-first local RAG solutions. PrivateGPT is a Python-first server/app stack, while GNO is a local knowledge workspace with stronger retrieval UX, agent integration, and TypeScript/Bun tooling.
The real choice is “Python-centric local RAG stack” versus “developer-first local workspace that spans CLI, web UI, desktop shell, SDK, and agents.”
At a Glance
- Choose PrivateGPT if you want a Python-heavy local RAG server with flexible backend options.
- Choose GNO if you want stronger search quality, simpler local setup, and direct CLI/API/agent workflows on top of your own files.
Get Started
# GNO
bun install -g @gmickel/gno
gno init ~/notes --name notes && gno index
# PrivateGPT (Ollama setup)
git clone https://github.com/zylon-ai/private-gpt
cd private-gpt
poetry install --extras "ui llms-ollama embeddings-ollama vector-stores-qdrant"
ollama pull llama3.1 && ollama pull nomic-embed-text
PGPT_PROFILES=ollama make run
Quick Summary
| Aspect | GNO | PrivateGPT |
|---|---|---|
| Best for | Developers, AI agents | Python devs, flexible backends |
| Unique strength | CLI, MCP, REST API | Multiple LLM providers |
| Stack | Bun/TypeScript | Python/FastAPI/Gradio |
| License | MIT | Apache-2.0 |
Feature Comparison
| Feature | GNO | PrivateGPT |
|---|---|---|
| File Formats | MD, PDF, DOCX, XLSX, PPTX, TXT | MD, PDF, DOCX, PPTX, EPUB, CSV, JSON, MBOX, IPYNB, images, audio, video |
| Search Modes | BM25, Vector, Hybrid | Vector (Qdrant) |
| Reranking | ✓ Cross-encoder | ✗ |
| AI Answers (RAG) | ✓ | ✓ |
| Web UI | ✓ gno serve |
✓ Gradio |
| REST API | ✓ | ✓ FastAPI (OpenAI-compatible) |
| CLI | ✓ Full-featured | ✗ Scripts only |
| Headless Daemon | ✓ gno daemon |
✓ Server mode |
| MCP Support | ✓ 10+ targets | ✗ |
| Local LLMs | ✓ node-llama-cpp | ✓ llama.cpp, Ollama |
| Database | SQLite (embedded) | Qdrant (requires service) |
| Setup Complexity | Single command | Git clone, Poetry, backend setup |
| Query Expansion | ✓ LLM-powered | ✗ |
| HyDE | ✓ | ✗ |
| Model Presets | ✓ slim/balanced/quality | ✗ |
| Folder Watch | ✗ | ✓ |
LLM Backend Support
| Provider | GNO | PrivateGPT |
|---|---|---|
| Local llama.cpp | ✓ Built-in | ✓ |
| Ollama | ✗ | ✓ |
| OpenAI | ✗ | ✓ |
| Azure OpenAI | ✗ | ✓ |
| Google Gemini | ✗ | ✓ |
| AWS SageMaker | ✗ | ✓ |
| vLLM | ✗ | ✓ |
GNO Advantages
GNO is stronger when search quality, lightweight setup, and agent access matter more than backend flexibility.
CLI-first design: Full-featured command line for scripting and automation.
gno query "authentication flow" --format json | jq '.results[0]'
MCP integration: One-command setup for Claude, Cursor, Windsurf, and more.
gno mcp install --target cursor
Hybrid search with reranking: BM25 + vector search with cross-encoder reranking for better results.
gno ask "how does caching work" --depth thorough --answer
Zero-dependency database: SQLite embedded, no external services needed.
Headless continuous indexing: Keep your local corpus current for APIs, agents, or shell workflows without launching the workspace.
gno daemon
Single command install: npm/bun global install, ready in seconds.
Skills: Native integration for Claude Code, Codex, OpenCode, OpenClaw.
PrivateGPT Advantages
PrivateGPT is stronger when Python ecosystem fit and backend/provider flexibility matter more than a unified local workspace.
Multiple LLM backends: Switch between Ollama, llama.cpp, OpenAI, Azure, Gemini, SageMaker, and vLLM via config profiles.
Broader file format support: Handles EPUB, MBOX, Jupyter notebooks, images, audio, and video files.
OpenAI-compatible API: Drop-in replacement for OpenAI API clients.
Folder watching: Automatic ingestion when files change.
python scripts/ingest_folder.py /docs --watch
Python ecosystem: Built with FastAPI and LlamaIndex, easy to extend for Python developers.
Production deployment options: Docker images and multiple deployment configurations included.
When to Choose GNO
- You want CLI access for scripting and automation
- You need MCP integration for AI coding assistants (Claude, Cursor, Windsurf)
- You prefer zero-config setup with embedded SQLite
- You want hybrid search with BM25 + vector + reranking
- You need fine-grained search control (depth, expansion, HyDE)
- You work in JavaScript/TypeScript ecosystem
When to Choose PrivateGPT
- You want to switch between multiple LLM providers (local and cloud)
- You have EPUB, audio, video, or Jupyter notebook files
- You want OpenAI-compatible API for existing integrations
- You prefer Python ecosystem and LlamaIndex
- You need folder watching for automatic ingestion
- You want production deployment with Docker
Architecture Comparison
GNO: TypeScript/Bun, SQLite + node-llama-cpp, designed for CLI and MCP integration. Single-user, local-first, zero external dependencies.
PrivateGPT: Python/FastAPI/Gradio, Qdrant + LlamaIndex, designed for flexible LLM backends. Requires external services (Qdrant, optionally Ollama).