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Basic Information

Unbody is an open-source backend platform for developers building AI-native applications, positioned as the Supabase of the AI era. It centralizes the fragmented process of adding AI features by providing tooling for data ingestion, indexing, orchestration and local deployment. The repository contains a Node.js application that runs with Docker and Docker Compose, requires an OpenAI API key, and includes a CLI to add data sources and connect example storage. It is intended for developers to set up a demo project, monitor file indexing with a Temporal dashboard running locally, and iterate on knowledge-focused features rather than static data. The project is in early development and maintained publicly to encourage contributions and community feedback.

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Features
Key features documented in the README include a modular Node.js backend, Docker Compose configuration to start required services locally, and a CLI workflow for adding data sources from the provided examples. The stack integrates with OpenAI via an API key for model access and uses Temporal to power indexing and workflow monitoring. The repository supplies example projects and a storage directory to bootstrap ingestion, environment templates for quick setup, and commands to start the application and observe indexing progress. The README provides step-by-step installation, environment setup, and running instructions aimed at accelerating local development and prototyping.
Use Cases
Unbody lowers engineering overhead when adding AI capabilities by offering a ready backend that handles ingestion, indexing and orchestration so teams can focus on application logic. Example projects and a CLI speed onboarding and make it easy to add file-based data sources for search and retrieval. Local development with Docker Compose and a Temporal dashboard makes indexing pipelines visible and debuggable. Built-in OpenAI integration enables rapid prototyping of model-driven features without wiring low-level services. By focusing on knowledge-centric indexing rather than static data, the platform supports retrieval-augmented workflows and searchable content systems. Documentation and community channels are available to support early adopters as the project matures.

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