# OGX

> The project formerly known as Llama Stack — an OpenAI-compatible agentic API server you run anywhere, with pluggable model providers

- Category: App Orchestration / App Frameworks
- Language: Python
- Licence: MIT
- Repository: https://github.com/ogx-ai/ogx
- Website: https://ogx-ai.github.io/
- Canonical page: https://ai-tldr.dev/tools/ogx/
- Updated: 2026-05-01

## In short

OGX is an open-source agentic API server for building AI applications. It sits in the App Frameworks category of the App Orchestration tools and is open-source, written in Python and licensed MIT. To get started: install the server.

## Overview

OGX is an open-source agentic API server for building AI applications. It is a drop-in replacement for the OpenAI API that runs on a laptop, in a datacenter or in the cloud, so any OpenAI-compatible client or agent framework can talk to it unchanged. The project is the continuation of Meta's Llama Stack: the repository states plainly that Llama Stack is now OGX, and that the mission changed with the name — model-agnostic, multi-SDK, production-grade.

The server covers the standard surface — `/v1/chat/completions`, `/v1/completions` and `/v1/embeddings` — plus the Responses API for server-side agentic orchestration, where tool calling, MCP server integration and built-in file search (RAG) happen inside a single API call. Around that sit `/v1/vector_stores` and `/v1/files` for managed document storage and search, `/v1/batches` for offline batch work, and `/v1alpha/skills` for versioned skill bundles — zip archives with a SKILL.md manifest that agents can invoke. The Responses implementation passes the Open Responses conformance suite.

Multi-SDK support is the other half of the pitch: alongside the OpenAI API, OGX natively serves the Anthropic Messages API at `/v1/messages` and the Google GenAI interactions API at `/v1alpha/interactions`. A pluggable provider architecture keeps the API stable while the backend changes — develop against Ollama locally, deploy on vLLM in production, or point at a managed service. Official client SDKs exist for Python and TypeScript, with an OpenAPI-generated alternative for teams whose tooling needs it.

## What it does

- OpenAI-compatible chat completions, completions and embeddings endpoints, usable from any OpenAI client
- Responses API with server-side tool calling, MCP server integration and built-in file search, verified against the Open Responses conformance suite
- Vector stores and files endpoints for managed document storage and retrieval
- Batches endpoint for offline, high-volume processing
- Skills — versioned zip bundles with a SKILL.md manifest that agents can call at /v1alpha/skills
- Native Anthropic Messages and Google GenAI interactions endpoints alongside the OpenAI surface
- Pluggable providers so the same API runs on Ollama locally and vLLM or a managed service in production
- Official Python and TypeScript client SDKs (ogx_client), plus an OpenAPI-generated alternative

## Getting started

OGX installs as a Python package and starts a server that auto-detects providers from your environment.

1. Install the server

```bash
# One-line install
curl -LsSf https://github.com/ogx-ai/ogx/raw/main/scripts/install.sh | bash

# Or via uv
uv pip install ogx
```

2. Start it

   `ogx go` reads the environment to work out which providers are available.

```bash
uv run ogx go
```

3. Point an OpenAI client at it

   The server listens on port 8321 by default; the API key is ignored for local use.

```python
from openai import OpenAI

client = OpenAI(base_url="http://localhost:8321/v1", api_key="fake")
response = client.chat.completions.create(
    model="llama-3.3-70b",
    messages=[{"role": "user", "content": "Hello"}],
)
```

4. Or use the official client SDK

   Published on PyPI as ogx_client and on npm as ogx-client.

```bash
pip install ogx_client
# or
npm install ogx-client
```

## When to use it

- Put one OpenAI-compatible endpoint in front of several model providers so application code never changes when the model does
- Serve the Responses API self-hosted, with tool calls, MCP servers and file search resolved server-side
- Develop against Ollama on a laptop and deploy the same stack on vLLM without touching the client
- Expose the OpenAI, Anthropic and Google GenAI SDK surfaces from a single server for a mixed-SDK codebase

## Version history

- 2026-05-01 v0.8.0: Llama Stack v0.8.0 added a native Anthropic Messages API, Gemini interactions and 91% OpenAI compatibility. The project has since been renamed OGX.