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The Backend Server is the central nervous system of the DataDot application. Built on FastAPI, it orchestrates the interaction between users, data, and AI models.

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Core Responsibilities

The server handles a wide range of critical functions:

Authentication

Manages user sessions, JWT-based authentication, and supports multi-user environments.

LLM Orchestration

Provides a unified interface for interacting with various LLM providers (OpenAI, Anthropic, Gemini, etc.).

RAG Pipeline

Handles document ingestion, embedding generation, and semantic search for Retrieval-Augmented Generation.

Workspace Management

Organizes chats, documents, and settings into logical, isolated workspaces.

Real-time Events

Supports WebSocket and Server-Sent Events (SSE) for streaming AI responses and real-time updates.

Procotol Server

Acts as a bridge for the Model Context Protocol (MCP), enabling external tool integration.

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Project Structure

The project follows a clean, modular architecture designed for scalability and maintainability. 
server/
├── app/
│   ├── api/              # API route definitions (v1 endpoints)
│   ├── core/             # Configuration, database setup, and security
│   ├── crud/             # Database CRUD abstractions
│   ├── middleware/       # Custom middleware (CORS, Auth, Logging)
│   ├── models/           # SQLAlchemy ORM models
│   ├── schemas/          # Pydantic data schemas
│   ├── services/         # Core business logic (Chat, LLM, Embeddings)
│   ├── tasks/            # Background tasks and scheduler
│   └── utils/            # Helper utilities
├── main.py               # Application entry point
├── requirements.txt      # Python dependencies
└── Dockerfile            # Container definition

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Getting Started

To dive deeper into the server, check out the following resources:

Architecture

Understand the data flow and technical stack.

Components

Detailed breakdown of key services and providers.