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Runs the FastAPI backend server with hot-reloading for automatic code changes during development.

Implements custom chat API backends with FastAPI, supporting SSE streaming, conversation persistence, and multi-model integration via LiteLLM.

Automatically refactors FastAPI code to improve performance, simplify async handling, optimize Pydantic models, and resolve common architectural inefficiencies.

Builds scalable web applications with Next.js frontend and FastAPI backend, handling authentication, database integration, and deployment workflows.

Generates Django Ninja API boilerplate, configures project structure, and provides automated setup for REST API development with Django and FastAPI Ninja.

Creates a FastAPI-based AI service endpoint for handling machine learning or AI-related tasks using Python.

Provides expert guidelines and best practices for developing robust, performant FastAPI applications in Python, focusing on API design, error handling, and project structure.

Provides expert guidelines and best practices for building scalable, serverless microservices using FastAPI and cloud-native deployment strategies.

Automatically diagnoses and provides targeted solutions for common FastAPI development issues like async/await errors, validation problems, and CORS configuration challenges.

Serves interior design recommendations and context-aware suggestions using machine learning models and FastAPI, enabling personalized home decor and layout planning.

Implements a Server-Sent Events (SSE) web server using FastAPI that enables AI models to dynamically access external tools, data sources, and context through a standardized Model Context Protocol (...

Analyzes financial data and generates research insights using a Model Context Protocol server with FastAPI integration for streamlined financial information processing.

Enable advanced scientific reasoning by leveraging graph structures and dynamic confidence scoring to process complex queries. Connect to external databases for real-time evidence gathering and integrate seamlessly with AI clients via the Model Context Protocol. Deploy easily with Docker and benefit from a modular, high-performance Python and FastAPI-based framework.