by schmitech
Self-hosted, OpenAI-compatible AI gateway for private RAG, natural-language data access, and tool-calling agents.
# Add to your Claude Code skills
git clone https://github.com/schmitech/orbitLast scanned: 5/30/2026
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}orbit is an open-source ai agents skill for AI coding assistants such as Claude Code, Codex CLI, and ChatGPT, built by schmitech. Self-hosted, OpenAI-compatible AI gateway for private RAG, natural-language data access, and tool-calling agents. It has 307 GitHub stars.
Yes. orbit passed SkillsLLM's automated security scan — a dependency vulnerability audit plus prompt-injection heuristics — with no high-severity issues. You can read the full report in the Security Report section on this page.
Clone the repository with "git clone https://github.com/schmitech/orbit" and add it to your Claude Code skills directory (see the Installation section above).
orbit is primarily written in Python. It is open-source under schmitech on GitHub, so you can review or fork the full source.
Yes. SkillsLLM lists many other AI Agents skills you can browse and compare side by side. Open the AI Agents category from the badge at the top of this page, or use the Related Skills and comparison links further down to weigh orbit against similar tools.
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A self-hosted, OpenAI-compatible AI gateway for private RAG, natural-language data access, and tool-calling agents — run it in your own environment across 37+ model providers.
ORBIT is a self-hosted AI gateway that lets you chat with private data through one OpenAI-compatible endpoint.
Put it in front of local or cloud models, connect files, SQL, NoSQL, vector stores, APIs, and tools, then operate everything from an admin panel with keys, quotas, prompts, metrics, and audit logs.
Reach for ORBIT when you need to:
Comparisons: ORBIT vs. Open WebUI · ORBIT vs. LiteLLM
[!NOTE] Real-world example: dialoga.ca is a Canadian AI chat tool built on ORBIT. It is currently available only from Canadian IP addresses; use a Canadian VPN endpoint if you are outside Canada.
Install the latest stable release, then start ORBIT locally.
curl -LO https://github.com/schmitech/orbit/releases/download/v2.9.4/orbit-2.9.4.tar.gz
tar -xzf orbit-2.9.4.tar.gz && cd orbit-2.9.4
./install/setup.sh # add --wizard for interactive setup
./bin/orbit.sh start
Open the admin panel:
| URL | Login |
|---|---|
| http://localhost:3000/admin | admin / admin123 |
Verify the gateway. default-key is a pre-seeded example key (mapped to the simple-chat adapter) shipped in the release/Docker database for evaluation — create your own keys via /admin or the orbit key create CLI command before going further than local testing:
curl -X POST http://localhost:3000/v1/chat \
-H 'Content-Type: application/json' \
-H 'X-API-Key: default-key' \
-H 'X-Session-ID: local-test' \
-d '{"messages": [{"role": "user", "content": "Summarize ORBIT in one sentence."}], "stream": false}'
Install orbitchat:
npm install -g orbitchat@latest
Open a browser chat client:
ORBIT_ADAPTER_KEYS='{"simple-chat":"default-key"}' orbitchat --open
What you should see: the server responds through the OpenAI-compatible /v1/chat endpoint, the admin panel shows live health and adapters, and OrbitChat opens a local chat UI.
For a Docker-based local demo with Ollama, use the development compose stack:
git clone https://github.com/schmitech/orbit.git
cd orbit/docker
docker compose up -d
The first Docker run can take a few minutes while the local model is downloaded.
[!WARNING] Docker from
mainis for local evaluation and development. For production installs, use the latest stable release tarball from GitHub Releases.
More setup paths: Docker Guide · Tutorial · Windows native install
If ORBIT saves you setup time, a GitHub star helps other developers find it.
Pick the path closest to what you want to build.
| Demo | What it shows | Run it |
|---|---|---|
| Chat with private files | Upload PDFs, spreadsheets, and images, then query them in one thread. | Tutorial |
| Ask SQL questions in English | Generate and run safe parameterized queries over a sample HR database. | Tutorial |
| Operate the gateway | Create personas and API keys, inspect adapters, watch metrics, and audit changes from /admin. |
First chat |
| Capability | What you get |
|---|---|
| OpenAI-compatible gateway | One /v1/chat interface across local, self-hosted, and cloud providers. |
| Model routing (37+ providers) | Local: Ollama, llama.cpp, vLLM, TensorRT-LLM, Transformers, LM Studio, BitNet. Cloud: OpenAI, Anthropic, Gemini, Bedrock, Vertex, Azure, Groq, Mistral, DeepSeek, xAI, and many more. |
| Natural-language data access | Plain English → SQL, MongoDB, Elasticsearch DSL, REST, GraphQL across Postgres, MySQL, Oracle, SQL Server, DuckDB, Athena, Supabase, Cassandra, Redis, and composite multi-source answers. |
| Vector RAG | Chroma, Qdrant, Pinecone, Milvus, Weaviate, Marqo, pgvector, FAISS, DuckDB, Redis, Elasticsearch. |
| File & multimodal RAG | PDFs, DOCX, spreadsheets, CSVs, markdown, images, and audio — with cached file context across conversations. |
| Pluggable file storage | Store uploads and generated media on local disk (default) or in the cloud — AWS S3, MinIO / SeaweedFS (S3-compatible), Azure Blob, or Google Cloud Storage — selected with one config key. |
| File encryption at rest | AES-256-GCM encryption for uploaded files, opt-in per adapter — keep classified or regulated documents encrypted on disk or in the cloud without touching adapters that don't need it. |
| Cloud secrets management | Resolve API keys, DB passwords, and connection strings from AWS Secrets Manager, Azure Key Vault, or GCP Secret Manager instead of (or alongside) .env — selected with one config key. Guide. |
| Web search | Provider-agnostic real-time context via DuckDuckGo (free), Brave, SearXNG, Serper, Tavily, Google PSE, Perplexity — decoupled from synthesis so any LLM can answer. |
| MCP tool agents | Connect MCP servers (filesystem, GitHub, Slack, Postgres, Jira, Notion, and more) over stdio/SSE with bounded, server-side agent loops. |
| A2A peer protocol | Google Agent-to-Agent support — discovery via /.well-known/agent.json and task delegation over JSON-RPC. Guide. |
| Message-queue (async) surface | Broker-native RabbitMQ ingestion — publish requests to a queue, ORBIT consumes them through the same pipeline and replies on a results queue. Decoupled, at-least-once, batch/async processing instead o |