ORBIT (Open Retrieval-Based Inference Toolkit) is a middleware platform that provides a unified API for AI inference. It acts as a central gateway, allowing you to connect various local and remote AI models with your private data sources like SQL databases and vector stores.

ORBIT gives you a single, consistent API to run LLMs (local or cloud) against your private data sources with portability, performance, high-availability, and security at the core.

⭐️ If ORBIT helps you ship faster, please consider starring the repo to support the roadmap.

• ✨ Highlights
• 🚀 Quick Start
• 🛠️ Why ORBIT
• 🏗️ Architecture Overview
• ✨ What Can You Build with ORBIT?
• ⭐ Support the Project
• 📖 Documentation
• 🤝 Community & Support
• 📄 License

• Unified AI gateway that normalizes requests across local models, cloud APIs, and hybrid deployments.
• Bring-your-own data with production-grade RAG adapters for SQL, vector stores, and custom datasources.
• Secure by default with token-based auth, role-aware API keys, and pluggable content moderation.
• Ready for teams thanks to batteries-included clients (CLI, React widget, Node/Python SDKs) and automation scripts.

• Python 3.12+ (for running the server or CLI locally)
• Docker Engine 24+ (if you prefer containers)
• MongoDB (Atlas or local) to unlock authentication, RAG, and history persistence
• Optional: Redis cache plus your choice of vector DB (Chroma, Qdrant, Pinecone, Milvus)

Refer to the Docker Setup Guide or run the bundled scripts from the docker/ directory:

cd docker
chmod +x docker-init.sh orbit-docker.sh
./docker-init.sh --build --profile minimal

# Download the latest release archive
curl -L https://github.com/schmitech/orbit/releases/download/v1.5.3/orbit-1.5.3.tar.gz -o orbit-1.5.3.tar.gz
tar -xzf orbit-1.5.3.tar.gz
cd orbit-1.5.3

# Bootstrap dependencies and download a small model
cp .env.example .env
./install/setup.sh --profile minimal --download-gguf gemma3-270m

# Start the ORBIT server
source venv/bin/activate
./bin/orbit.sh start # Logs: ./logs/orbit.log

Keep an eye on the logs, then browse to http://localhost:3000 to confirm your instance is responding.

pip install schmitech-orbit-client

# Point to a running ORBIT instance (defaults to http://localhost:3000)
orbit-chat

cd clients/chat-app
npm install
npm run dev

• Create an API key tied to the adapter you want to expose (./bin/orbit.py key create).
• Enable or customize adapters in config/adapters.yaml and redeploy to connect new datasources.
• Skim the docs for deep dives on auth, configuration, and deployment patterns.

• Run securely with your data thanks to first-class support for on-prem hardware, air-gapped installs, and strict authentication defaults.
• Mix and match models (local, hosted, or API) through a single contract without rewriting downstream apps.
• Production-ready RAG with adapters for SQL, vector databases, and pipelines that keep context fresh.
• Dev-friendly tooling including a CLI, SDKs, React widget, and language clients maintained in this repo.

• Platform & infra teams who need a stable control plane for LLM workloads.
• Product teams shipping AI copilots that depend on reliable retrieval and guardrails.
• Researchers & tinkerers exploring local-first stacks or evaluating different foundation models.

Have a story or feature request? Open an issue or add it to the Roadmap.

ORBIT uses a flexible adapter architecture to connect your data to AI models. An API key is tied to a specific adapter, effectively creating a specialized "agent" for a certain task. Here are a few examples:

Provide instant, semantically-aware answers from a knowledge base. Perfect for customer support or internal documentation.

Sample Questions:

• "What are the summer camp programs for kids?"
• "How do I register for the contemporary dance class?"

NOTE: You need an instance of MongoDB to enable adapters

Here's the Sample Q/A datasets for this example. The knowledge base corresponds to a municipal services assistant.

#Login as admin first. Default password is admin123. You should change after installing ORBIT.
./bin/orbit.sh login

# Set up SQLite database with Q&A data
./examples/sample-db-setup.sh sqlite

# Test using node client
cd clients/node-api
npm install
npm run build
npm run test-query-from-pairs ../../examples/city-qa-pairs.json "http://localhost:3000" "your-api-key" 5 134444

Ask questions about your data in natural language and get answers without writing SQL.

Sample Questions:

• "Show me all orders from John Smith"
• "What are the top 10 customers by order value?"

# Set up PostgreSQL with a sample schema and data
cd examples/postgres

# Update with  your connection parameters
cp env.example .env

# Test connection
python test_connection.py

# Create the DB
python setup_schema.py

# Install faker to generate synthetic data
pip install faker

# Add sample data
python customer-order.py --action insert --clean --customers 100 --orders 1000

# Create an API key for the SQL intent adapter.
# Make sure you are logged in as admin if auth is enabled in `/config/config.yaml`.
python bin/orbit.py key create \
  --adapter intent-sql-postgres \
  --name "Order Management Assistant" \
  --prompt-file examples/postgres/prompts/customer-assistant-enhanced-prompt.txt

#make sure the sample SQL intent adapter is enabled in `/config/adapters.yaml`
- name: "intent-sql-postgres"
    enabled: false
    type: "retriever"
    datasource: "postgres"
    adapter: "intent"
    implementation: "retrievers.implementations.intent.IntentPostgreSQLRetriever"
    inference_provider: "ollama"

# Start or restart the server
./bin/orbit.sh start --delete-logs

# Start chatting with your new key
orbit-chat --url http://localhost:3000 --api-key YOUR_API_KEY

Looking for more samples? Browse the examples/ directory for data loaders, prompts, and client integrations you can adapt.

Your support keeps ORBIT independent and focused on open-source innovation.

• ⭐ Star the repo to signal that ORBIT matters to you.
• 📣 Share a demo, blog, or tweet so other builders discover it.
• 🐛 Open issues and PRs—your feedback directly shapes the roadmap.

For more detailed information, please refer to the official documentation.

• Installation Guide
• Configuration
• Authentication
• RAG & Adapters
• Development Roadmap
• Contributing Guide

• Questions? Open an issue
• Updates: Check the changelog
• Commercial Support: Contact schmitech.ai
• Maintained by: Remsy Schmilinsky

Apache 2.0 - See LICENSE for details.