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README.md

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# <img src="https://avatars.githubusercontent.com/u/30185530?s=200&v=4" alt="OpenMined" width="32" align="center"> Syft Space Server
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# <a href="https://github.com/OpenMined"><img src="https://avatars.githubusercontent.com/u/30185530?s=200&v=4" alt="OpenMined" width="32" align="center"></a> Syft Space Server
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[![Python](https://img.shields.io/badge/python-3.10%2B-blue)](https://www.python.org/downloads/)
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[![Node.js](https://img.shields.io/badge/node.js-20%2B-green)](https://nodejs.org/)
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[![uv](https://img.shields.io/badge/uv-package%20manager-blueviolet)](https://github.com/astral-sh/uv)
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[![Bun](https://img.shields.io/badge/bun-runtime-f9f1e1)](https://bun.sh/)
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A friendly platform for building AI-powered search and question-answering tools. Connect your documents to language models and query them through simple API endpoints.
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A space where you can turn data and models into shareable workflows — exposing them through secure endpoints under your own rules for privacy, payments, and human oversight.
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## What This Project Does
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Syft Space Server helps you create **RAG (Retrieval-Augmented Generation) endpoints**. In plain terms, it lets you:
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Syft Space Server lets you create **secure, shareable AI endpoints**. In plain terms, it helps you:
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- **Upload documents** to a searchable database
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- **Connect language models** (like OpenAI-compatible APIs)
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- **Create endpoints** that combine your documents with AI to answer questions
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- **Connect your data** to searchable vector databases
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- **Integrate language models** (OpenAI-compatible APIs)
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- **Build endpoints** that combine data and models into queryable workflows
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- **Set your own rules** for access control, rate limiting, and usage tracking
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Think of it as a bridge between your data and AI models, wrapped in an easy-to-use interface.
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Think of it as your personal control plane for AI workflows — you decide who can access what, under what terms.
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## Why You Might Want to Use It
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- **Build AI search tools** without managing complex infrastructure
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- **Self-host your data** instead of sending everything to third-party services
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- **Create custom Q&A bots** trained on your own documents
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- **Experiment with RAG** using a visual interface
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- **Own your data** — self-host instead of sending everything to third parties
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- **Control access** — define policies for privacy, payments, and oversight
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- **Share securely** — expose endpoints without exposing raw data
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- **Stay flexible** — works with your existing models and databases
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## Prerequisites
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- **Docker** (recommended) - [Install Docker](https://docs.docker.com/get-docker/)
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Or for running from source:
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- **Python 3.10+** - [Download Python](https://www.python.org/downloads/)
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- **Bun** - [Install Bun](https://bun.sh/)
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## Quick Start
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```
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The frontend development server runs at [http://localhost:5173](http://localhost:5173).
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For detailed reference to frontend and developement instructions, see [`frontend/README.md`](frontend/README.md).
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For detailed reference to frontend and development instructions, see [`frontend/README.md`](frontend/README.md).
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## Configuration
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