ORBIT provides a unified, self-hosted gateway for interacting with over 20 Large Language Model (LLM) providers, diverse databases, and file storage. It targets developers and power users seeking to simplify complex AI application development by abstracting away provider-specific APIs and data source complexities. ORBIT enables rapid prototyping and production deployment of RAG, voice-enabled, and agentic workflows with built-in guardrails and robust self-hosting capabilities.

How It Works

ORBIT centralizes LLM interactions and data retrieval through a single, OpenAI-compatible API endpoint. It employs a modular adapter system to seamlessly switch between numerous LLM providers (e.g., OpenAI, Anthropic, Gemini, Ollama) and connect to various data sources including SQL databases (PostgreSQL, MySQL, SQLite), NoSQL (MongoDB, Elasticsearch), APIs (REST, GraphQL), and DuckDB. Retrieval-Augmented Generation (RAG) is integrated for querying documents, PDFs, and images. The architecture supports full-duplex voice communication and agentic workflows via MCP compatibility, offering a flexible and extensible foundation for AI applications.

Quick Start & Requirements

The quickest setup involves Docker Compose:

git clone https://github.com/schmitech/orbit.git && cd orbit/docker
docker compose up -d

This command starts ORBIT with Ollama and a default model, exposing the API on port 3000. An admin panel is available at localhost:3000/admin (login: admin/admin123). For GPU acceleration, use docker compose -f docker-compose.yml -f docker-compose.gpu.yml up -d. Prerequisites include Docker and Docker Compose. Further details are available in the Docker Guide.

Highlighted Details

• Broad Integration: Supports 20+ LLM providers (OpenAI, Anthropic, Gemini, Ollama, vLLM, etc.) and multiple data sources (SQL, NoSQL, APIs, GraphQL).
• RAG Capabilities: Out-of-the-box retrieval over PDFs, images, and documents.
• Voice & Guardrails: Integrates speech-to-text (Whisper, Google) and text-to-speech (OpenAI, ElevenLabs) via PersonaPlex, alongside content moderation using OpenAI, Anthropic, or Llama Guard.
• Self-Hosted Control: Offers RBAC, rate limiting, and audit logging for private deployments.
• Agentic Workflow Support: MCP-compatible, allowing AI agents to utilize ORBIT as a tool.

Maintenance & Community

The project actively encourages contributions via GitHub Issues. A project star is requested to aid discoverability. No specific community channels (like Discord or Slack) or details on core maintainers/sponsorships were provided in the README excerpt.

Licensing & Compatibility

ORBIT is licensed under the permissive Apache 2.0 license, allowing for commercial use and integration into closed-source projects. Its OpenAI-compatible API facilitates easy integration with existing tools and SDKs.

Limitations & Caveats

No explicit limitations, alpha status, or known bugs were detailed in the provided README content. The focus is on the breadth of features and ease of integration.