FastAPI backend

Handles API requests, manages business logic, connects to data services, and serves the frontend for DataLens, using FastAPI routes and dependencies as its interface. DataLens Platform uses a FastAPI app backend to provide API endpoints and services. The FastAPI backend in the DataLens Project uses SQLAlchemy ORM for data access. The FastAPI backend uses DS-STAR FileAnalyzer for AI cataloging of uploaded files. The FastAPI backend integrates with DuckDB for data extraction storage and querying. The FastAPI backend exposes a Text-to-SQL query API for natural language queries. The SvelteKit frontend communicates with the FastAPI backend via API endpoints. The FastAPI backend uses PostgreSQL database for multi-tenant metadata storage. The FastAPI backend provides a production-ready Dockerfile for deployment. The FastAPI backend uses AI cataloging to automatically discover table structures on file upload. FastAPI backend runs on theo server and orchestrates file extraction, query execution, and database storage. The DataLens Platform is built with a FastAPI app backend that passes all 13 tests. pytest is used to execute tests that cover the FastAPI app components of the DataLens Platform. httpx is used as part of tests covering the FastAPI app implementation of the DataLens Platform. Project 13 uses the FastAPI backend for file extraction and DuckDB storage as part of its data platform. theo hosts the FastAPI backend which runs file extraction, DuckDB storage, and uses SQLCoder-7B for query processing. The RQ worker is used by the FastAPI backend to handle asynchronous jobs such as embeddings and summary generation.