private-gpt README

The project's README from github.com/zylon-ai/private-gpt. As one markdown file: README.md.

Banner image

PrivateGPT is the open-source API layer that turns local models into production AI applications.

Tests Website Discord X (formerly Twitter) Follow

zylon-ai%2Fprivate-gpt | Trendshift

Running a model locally is only the first step. To build useful AI applications you need a set of higher-level building blocks. PrivateGPT provides that layer as an open-source API following the Claude API model — so you can build private AI products without rebuilding the same backend primitives from scratch, and without depending on cloud APIs.

Production-tested: PrivateGPT powers Zylon, the on-premise AI platform providing Private AI to enterprises across the globe.

Your app / agent / workflow / UI
              |
        PrivateGPT API
              |
OpenAI-compatible inference server (Ollama, llama.cpp, vLLM, …)

PrivateGPT does not run models itself. It connects to any OpenAI-compatible inference server via OPENAI_API_BASE. If it implements /v1/chat/completions and /v1/models, it works.

PrivateGPT ships a built-in workbench UI for testing and demos, available at /ui. The API is the actual product.

What PrivateGPT gives you

Quickstart

For Docker, full installation options, and model configuration see the full Quickstart guide.

Prerequisites: You need a running OpenAI-compatible LLM server. Ollama is the easiest starting point.

1. Install PrivateGPT

# macOS
brew tap zylon-ai/tap
brew install private-gpt

# Linux
curl -LsSf https://astral.sh/uv/install.sh | sh

uv tool install --python 3.11 \
  --find-links https://wheels.privategpt.dev/packages/ \
  "private-gpt[core]"

# Windows
powershell -ExecutionPolicy ByPass -c "irm https://astral.sh/uv/install.ps1 | iex"

uv tool install --python 3.11 `
  --find-links https://wheels.privategpt.dev/packages/ `
  "private-gpt[core]"

2. Start your LLM server

# Example with Ollama
ollama pull qwen3.5:35b         # LLM (~24 GB)
ollama pull mxbai-embed-large   # Embeddings (~670 MB)
ollama serve

3. Run PrivateGPT

# macOS / Linux
OPENAI_API_BASE=http://localhost:<llm-port>/v1 \
  OPENAI_EMBEDDING_API_BASE=http://localhost:<embedding-port>/v1 \
  private-gpt serve

# Windows (PowerShell)
$env:OPENAI_API_BASE = "http://localhost:<llm-port>/v1"
$env:OPENAI_EMBEDDING_API_BASE = "http://localhost:<embedding-port>/v1"
private-gpt serve

4. Open the UI

Go to http://localhost:8080/ui. The API is at http://localhost:8080 and follows the Anthropic API spec.

The UI is useful for:

This UI is a demonstrator, not the core product. Developers are expected to build their own applications on top of the API. That said, the UI is intentionally polished enough for demos, videos, internal pilots, and quick local usage.

Integrations
claude cowork
Claude Desktop / Cowork		 ms excel claude
Microsoft Excel Claude add-in		 ms word claude
Microsoft Word Claude add-in
n8n
n8n		 opencode
OpenCode		 privategpt workbench
PrivateGPT Workbench

PrivateGPT works natively as the local backend for the tools developers and end users already use.

Integration Guide What it enables
Claude Code Use your local models as the backend for agentic coding in the terminal
Claude Desktop / Cowork Connect the Claude desktop app and Cowork to your private models
Claude for Microsoft 365 Run private AI inside Word, Excel, Outlook, and PowerPoint
OpenCode Local AI coding assistant in the terminal

Any tool that works with a local OpenAI-compatible provider will also work with PrivateGPT. The list below is non-exhaustive.

Tool Link
n8n n8n.io
OpenClaw openclaw.ai
Hermes Agent hermes-agent.dev
VS Code code.visualstudio.com
Cline cline.bot

Claude API compatibility

PrivateGPT follows the Claude API as the reference for modern AI application APIs. The goal is full coverage where it makes sense for a local, open-source layer.

Area Capability Claude API PrivateGPT
Models Model selection ✅ ✅
Messages Messages API ✅ ✅
Messages Streaming ✅ ✅
Messages Batch / async processing ✅ ✅ async
Messages Token counting ✅ ✅
Knowledge Files / artifacts ✅ ✅
Knowledge PDF and document ingestion ✅ ✅
Knowledge Retrieval with citations ✅ ✅
Knowledge Embeddings ✅ ✅
Tools Tool use ✅ ✅
Tools Tools in streaming ✅ ✅
Tools Built-in web search ✅ ✅
Tools Web extraction / fetch ✅ ✅
Tools Custom tools ✅ ✅
Data Database querying Via tools ✅ built-in
Data CSV / tabular analysis Via tools / code ✅ built-in
Agents MCP in the API ✅ ✅
Agents Remote MCP servers ✅ ✅
Agents Skills ✅ ⚙️ basic
Output Structured outputs ✅ ✅ inference-dependent
Models Vision ✅ ✅ model-dependent
Optimization Prompt caching ✅ ❌
Reasoning Extended thinking ✅ ✅
Platform Token-based auth ✅ ✅
Platform OAuth / organizations ✅ ❌

✅ Supported · ⚙️ Partial / in progress · ❌ Not supported

Contributions are especially welcome in ⚙️ areas.

Why PrivateGPT? A brief history

PrivateGPT started as a proof of concept in 2023: a script that let you chat with your documents, fully offline, with no data leaving your machine. It went viral on GitHub, crossed 50K stars, and became one of the most-watched AI repos of that year.

That early version made one thing clear: there was serious demand for private, local AI that worked without cloud dependencies.

PrivateGPT 1.0 is the evolution of that idea — rebuilt from the ground up as a proper API layer for private AI applications.

Star History Chart

How PrivateGPT compares

vs Ollama, LM Studio, LocalAI, vLLM, llama.cpp

These projects make it possible to run and serve models locally. They answer: how do I run a model?

PrivateGPT answers the next question: how do I build a useful AI application on top of that model?

Ollama / LM Studio / LocalAI / vLLM / llama.cpp  =  local inference layer
PrivateGPT                                        =  local AI application API layer

Use them together. Run your model with whichever inference server you prefer, then point PrivateGPT at it.

vs Onyx, Open WebUI

Both are valuable, but they are app-first experiences focused on chat and enterprise search. PrivateGPT is API-first. It provides the standardized local backend underneath those products — not the final product itself.

Onyx / Open WebUI  =  self-hosted AI applications
PrivateGPT         =  API layer for building self-hosted AI applications

PrivateGPT vs Zylon

PrivateGPT is maintained by the team at Zylon.

PrivateGPT is the open-source application API layer: messages, ingestion, tools, retrieval, citations, database access, tabular analysis, MCP, skills, and custom tools.

Zylon is the end-to-end AI Infrastructure orchestrating the hardware and software layers into a complete production platform for regulated organizations. On top of PrivateGPT, Zylon adds:

Use PrivateGPT if you want the open-source local AI application layer and developer API.

Use Zylon if you need the full enterprise AI infrastructure around it: deployment, governance, operations, user management, integrations, auditability, and support.

Learn more at zylon.ai · Book a demo

Community and contributing

Pull requests are welcome. If your PR doesn't fit the upstream roadmap, you can add your fork to the Community Forks page instead.

private-gpt (zylon-ai/private-gpt)

Searching Database…

57.6K ·GitHub
Private-gpt
What is this?PrivateGPT is an open-source API layer that turns any local, OpenAI-compatible model into a full production-ready AI application backend, covering RAG, tools, MCP, text-to-sql and more.
Is PrivateGPT a model runner like Ollama, or something else?It is not an inference engine — it does not run models itself. It connects to any OpenAI-compatible inference server (e.g. Ollama, vLLM, LocalAI) that exposes /v1/chat/completions and /v1/models, and builds a Claude-style API on top.
How do I get it running?Install PrivateGPT, start an OpenAI-compatible LLM server (Ollama is the easiest option), run PrivateGPT, then open the built-in workbench UI at /ui to send messages, upload documents and test retrieval.
Do I need an inference server before I start?Yes — you need a separately running OpenAI-compatible LLM server; Ollama is recommended as the easiest starting point.
Is it already at full Claude-API feature parity?Not entirely: Skills support is only basic/in progress, prompt caching is not supported yet, and there's no OAuth or organization-level auth — only token-based auth is available.
Does it run on any OS, or only Linux servers?It ships as a Python project with a Docker image, so it can be run on Linux, macOS, or Windows wherever Docker or Python is available; README quickstart and Docker instructions don't restrict it to one OS.
Does any of my data leave my machine?The project's origin is explicitly offline-first: the original PrivateGPT let you chat with your documents fully offline with no data leaving your machine, and this API layer keeps that same local-first model.
How is PrivateGPT different from just running Ollama or vLLM?Ollama, vLLM, LocalAI, and llama.cpp answer 'how do I run a model?'. PrivateGPT answers the next question, 'how do I build an application on top of that model?' — you run the model with any of those tools and point PrivateGPT at it.
What is the relationship between PrivateGPT and Zylon?PrivateGPT is the open-source API layer maintained by the Zylon team. Zylon is the commercial, end-to-end enterprise platform built on top of it, adding things like an integrated inference server, Kubernetes deployment, RBAC, SIEM audit logs, and air-gapped operation.
What was PrivateGPT before this rewrite?It started in 2023 as a simple proof-of-concept script for chatting with your documents fully offline, which went viral and crossed 50K GitHub stars; this version is a ground-up rebuild as a proper production API layer.
What tools can plug into PrivateGPT as their local AI backend?Claude Desktop/Cowork, Claude for Microsoft 365 (Word/Excel/Outlook/PowerPoint), Claude Code, n8n, OpenCode, OpenClaw, Hermes Agent, VS Code, and Cline can all use PrivateGPT as a drop-in local OpenAI-compatible backend.
What are similar projects?SurfSense, OpenViking, unsloth, claude-context, DB-GPT, Baize, QAnything, LangBot
Which topics is it in?on-premise, text-to-sql, agentic-rag, ai-tools, embeddings, openai-compatible, local-llm, knowledge-base, ollama, rag, mcp-server, agent
Creator
zylon-ai
Size
221.2 MB
Stars
57.6K
Updated
CommitOct 16Releasev1.0.1Jun 18
Age
3y
Commits · 90 Days