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 340 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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⚠️ Third-Party Software Notice
This skill is third-party open-source software developed and hosted independently on GitHub. SkillsLLM is an informational directory and does not control or maintain the underlying repository.
Any security checks, ratings, or warnings displayed by SkillsLLM are automated and limited in scope. They do not constitute a security certification or guarantee that the software is safe, error-free, or free from malicious code, vulnerabilities, compromised dependencies, or prompt-injection risks.
Review the source code, permissions, dependencies, and configuration before installing or running any third-party skill. Use is at your own risk. To the maximum extent permitted by applicable law, SkillsLLM is not liable for losses arising from third-party software.
Connect your data (files, databases, APIs, and MCP tools) to any local or cloud LLM. Exposes a unified endpoint for your apps, with built-in authentication and observability.
| What ORBIT gives you | |
|---|---|
| Connect anything | Query files, SQL, NoSQL, vector stores, Elasticsearch, REST/GraphQL APIs, and MCP tools in natural language across multiple languages. |
| Use any model | Route one API contract across local models such as Ollama, llama.cpp, and vLLM or cloud providers such as OpenAI, Anthropic, Gemini, Bedrock, and Azure. |
| Operate it safely | Ship with API keys, RBAC, SSO, quotas, moderation, fallbacks, metrics, audit logs, and an admin panel instead of assembling them yourself. |
ORBIT sits between your applications and the models, data, and tools they need. Define adapters in YAML, expose them through one OpenAI-compatible endpoint, and move from a local prototype to a governed deployment without replacing the architecture.
ORBIT is actively maintained. See the release history, changelog, and commit history.
| Capability | Included |
|---|---|
| Model gateway | 41 configured inference backends and providers, OpenAI-compatible APIs, per-key routing, model switching, retries, and fallbacks. |
| Retrieval | Vector RAG, file and multimodal RAG, SQL, MongoDB, Elasticsearch, REST, GraphQL, web search, and multi-source answers. |
| Agents and protocols | MCP tool calling, bounded multi-step loops, natural-language skill routing, A2A, and asynchronous RabbitMQ requests. |
| Media | Image, video, speech, PDF, Word, Excel, PowerPoint, CSV, and markdown generation. |
| Security | API keys, RBAC, Entra ID and Auth0 SSO, rate limits, quotas, moderation, file encryption, and cloud secret managers. |
| Operations | Admin UI, health checks, metrics, audit logs, per-request token and estimated-cost tracking, spend analytics, circuit breakers, datasource pooling, and hot adapter reloads. |
Browse all adapters · See provider configuration · Read the configuration reference
⭐ Finding ORBIT useful? Star the repository to help other developers discover it and support continued investment in new model, datasource, and agent integrations.
Prerequisites: Linux or macOS, Python 3.12+, and an internet connection for downloading dependencies.
Download and install the latest stable release:
curl -L https://github.com/schmitech/orbit/releases/download/v2.15.7/orbit-2.15.7.tar.gz -o orbit-2.15.7.tar.gz
tar -xzf orbit-2.15.7.tar.gz
cd orbit-2.15.7
./install/setup.sh --profile default
./bin/orbit.sh start
ORBIT starts on http://localhost:3000. For Windows, follow the Windows installation guide.
ORBIT is highly configurable. The main server settings live in ./config/config.yaml; inference providers, adapters, models, data sources, and other capabilities are configured in the other files under ./config/.
See the server management guide for commands to start, stop, restart, pause, and monitor ORBIT.
To use the optional ORBIT chatbot web interface, install and run orbitchat from your host machine:
npm install -g orbitchat
ORBIT_ADAPTER_KEYS='{"simple-chat":"default-key"}' orbitchat
Then open http://localhost:5173 in your browser.
See the OrbitChat project and documentation for configuration, custom adapters, authentication, and advanced usage.
Prerequisites: Docker, 4 GB of free RAM, and 3 GB of disk space.
docker pull schmitech/orbit-ollama:latest
docker run -d --name orbit -p 5173:5173 -p 3000:3000 \
-v orbit-data:/orbit/data \
-v orbit-models:/orbit/models \
schmitech/orbit-ollama:latest
The first run downloads the local chat/vision model (gemma4:e2b, ~7.2 GB) inside the container and will take some time to complete startup depending on your internet connection speed. Once pulled, open http://localhost:5173 and start chatting — upload a PDF, a spreadsheet, or an image and ask about it. No cloud account or API key required.
| Model | |
|---|---|
| Chat | gemma4:e2b (Ollama) |
| Vision | gemma4:e2b (Ollama) |
| Embeddings | nomic-embed-text (Ollama) |
export OPENAI_API_KEY=sk-...
docker pull schmitech/orbit-openai:latest
docker run -d --name orbit -p 5173:5173 -p 3000:3000 \
-e OPENAI_API_KEY \
-v orbit-data:/orbit/data \
schmitech/orbit-openai:latest
| Model | |
|---|---|
| Chat | gpt-5.4-mini (also selectable: gpt-5.4, gpt-5.4-nano) |
| Vision | gpt-5.5 |
| Embeddings | text-embedding-3-small |
export GOOGLE_API_KEY=...
docker pull schmitech/orbit-gemini:latest
docker run -d --name orbit -p 5173:5173 -p 3000:3000 \
-e GOOGLE_API_KEY \
-v orbit-data:/orbit/data \
schmitech/orbit-gemini:latest
| Model | |
|---|---|
| Chat | gemini-3.1-pro-preview (also selectable: gemini-3.6-flash) |
| Vision | gemini-3.6-flash |
| Embeddings | gemini-embedding-2-preview |
Port 5173 is the chat UI, 3000 is the OpenAI-compatible API if you want to call ORBIT directly:
curl -X POST http://localhost:3000/v1/chat/completions \
-H 'Content-Type: application/json' \
-H 'X-API-Key: multimodal' \
-H 'X-Session-ID: local-test' \
-d '{"messages":[{"role":"user","content":"What can ORBIT connect to?"}]}'
Admin Panel at http://localhost:3000/admin (default credentials: username admin, password admin123, set via auth.default_admin_password in config.yaml — change this immediately after first login).
For custom Docker deployments, follow [Docker guide](docker/REA