Search Results for "fastapi"
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Showing 58 open source projects for "fastapi"
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FastAPI
FastAPI framework, high performance, easy to learn, fast to code
FastAPI is a modern, fast (high-performance), web framework for building APIs with Python 3.6+ based on standard Python type hints. Great editor support. Completion everywhere. Less time debugging. Designed to be easy to use and learn. Less time reading docs. Minimize code duplication. Multiple features from each parameter declaration. -
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FastAPI-MCP
Expose your FastAPI endpoints as Model Context Protocol (MCP) tools
fastapi_mcp lets you expose existing FastAPI endpoints as Model Context Protocol (MCP) tools with minimal setup, so AI agents can call your app as first-class tools. Rather than acting as a thin converter, it’s built as a native FastAPI extension that understands dependency injection, so you can reuse Depends() for authentication and authorization across your MCP tools. The server speaks directly to your app over its ASGI interface, avoiding extra HTTP hops between the MCP layer and your API, which reduces latency and simplifies deployment. ... -
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FastAPI Python
FastAPI framework, high performance, easy to learn, fast to code
FastAPI framework, high performance, easy to learn, fast to code, ready for production. FastAPI is a modern, fast (high-performance), web framework for building APIs with Python based on standard Python type hints. -
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Full Stack FastAPI and PostgreSQL
Full stack, modern web application generator
Generate a backend and frontend stack using Python, including interactive API documentation. Production ready Python web server using Uvicorn and Gunicorn. Very high performance, on par with NodeJS and Go (thanks to Starlette and Pydantic). Great editor support. Completion everywhere. Less time debugging. Designed to be easy to use and learn. Less time reading docs. Minimize code duplication. Multiple features from each parameter declaration. Get production-ready code. With automatic... -
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FastUI
Build better UIs faster
FastUI is a library that lets developers build interactive user interfaces for FastAPI applications using Pydantic models. It automatically generates frontend components based on data schemas and endpoint logic, reducing the need for manual UI development. Designed to be type-safe, reactive, and fast, FastUI streamlines the creation of web dashboards, admin panels, and internal tools within a FastAPI backend. -
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Procrastinate
PostgreSQL-based Task Queue for Python
Procrastinate is a powerful PostgreSQL-based task queue for Python, built to integrate seamlessly with Django and FastAPI. It allows you to schedule and execute background jobs using your existing database infrastructure, avoiding the need for additional queueing systems like Redis. Procrastinate is designed with simplicity, reliability, and observability in mind. -
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FastKoko
Dockerized FastAPI wrapper for Kokoro-82M text-to-speech model
FastKoko is a self-hosted text-to-speech server built around the Kokoro-82M model and exposed through a FastAPI backend. It is designed to be easy to deploy via Docker, with separate CPU and GPU images so that users can choose between pure CPU inference and NVIDIA GPU acceleration. The project exposes an OpenAI-compatible speech endpoint, which means existing code that talks to the OpenAI audio API can often be pointed at a Kokoro-FastAPI instance with minimal changes. ... -
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LitServe
Minimal Python framework for scalable AI inference servers fast
...Unlike traditional serving tools that enforce rigid abstractions, LitServe focuses on flexibility by letting users control request handling, batching strategies, and output processing directly in Python. LitServe is built on top of FastAPI and extends it with AI-specific optimizations such as efficient multi-worker execution, which can significantly improve throughput. It includes built-in capabilities for batching, streaming responses, and automatic scaling across CPUs and GPUs, enabling high-performance deployments. -
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AutoCVE
Agent-driven automated CVE discovery platform for source code auditing
...Vulnerabilities are deduplicated and stored in a structured management system, while configurable skills extend individual agents. The platform uses a React frontend, FastAPI backend, PostgreSQL database, and Docker-based deployment. -
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Violin
Open-source Video Translation Skill
...The project is designed to keep the generated speech aligned with the original timing so the final result feels closer to a real dubbed video. It can be used from the command line, through a FastAPI web app, or as a Claude Code skill. Violin supports multilingual workflows and is useful for creators, educators, localization teams, and developers building automated video translation pipelines. It is especially practical for turning lectures, tutorials, interviews, demos, and social videos into accessible content for wider audiences. -
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supabase-py
Python Client for Supabase. Query Postgres from Flask, Django
Python Client for Supabase. Query Postgres from Flask, Django, FastAPI. Python user authentication, security policies, edge functions, file storage, and realtime data streaming. Good first issue. -
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FastHX
FastAPI server-side rendering with built-in HTMX support.
FastHX is a high-performance HTTP and WebSocket server framework designed for Haxe, enabling fast and scalable web application development. -
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Habit Tracker
Habit Tracker for the AI Coding Workshop
Habit Tracker is a personal habit-tracking web application designed to help users build and maintain daily habits through intuitive UI and analytics that visualize progress over time. It runs locally with a FastAPI backend (Python) and a React frontend, storing all data in a lightweight SQLite database so there’s no need for user accounts or cloud storage, which keeps habit data fully private and self-contained. The app provides streak tracking and completion rates for each habit, giving users feedback on consistency and motivation by showing how often habits are completed and where they may be lagging. ... -
14
Mangum
AWS Lambda support for ASGI applications
...Event handlers for API Gateway HTTP and REST APIs, Application Load Balancer, Function URLs, and CloudFront Lambda@Edge. Compatibility with ASGI application frameworks, such as Starlette, FastAPI, Quart and Django. Support for binary media types and payload compression in API Gateway using GZip or Brotli. Works with existing deployment and configuration tools, including Serverless Framework and AWS SAM. The heart of Mangum is the adapter class. It is a configurable wrapper that allows any ASGI application (or framework) to run in an AWS Lambda deployment. ... -
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MLX-Audio
A text-to-speech, speech-to-text and speech-to-speech library
...It includes examples such as audiobook generation to demonstrate long-form synthesis and joined audio segments. On top of that, MLX-Audio offers a modern web interface powered by FastAPI, with real-time waveform and 3D visualizations, file upload, and audio management. -
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ODMantic
Sync and Async ODM (Object Document Mapper) for MongoDB
Odmantic is an Object-Document Mapper (ODM) for MongoDB, designed for Python applications using Pydantic models, providing a seamless integration with type safety and validation. -
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OAGI Python SDK
Python SDK for the Computer Use model Lux, developed by OpenAGI
...It provides high-level asynchronous agents (like AsyncDefaultAgent and AsyncActor) that encapsulate the loop of capturing screenshots, sending them to Lux, interpreting responses, and executing UI actions with PyAutoGUI. Multiple installation flavors let you choose between a minimal oagi-core package or variants that bundle desktop automation and FastAPI/Socket.IO server capabilities. -
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OpenMed
Open source healthcare AI
...The project includes a curated registry of more than a dozen medical NER models focused on areas such as diseases, drugs, anatomy, genes, and protected health information, and it is built to support both research and deployment scenarios. OpenMed can be used in three main ways: as a simple Python API for scripts and notebooks, as a Docker-friendly FastAPI service for backend integration, and as a batch-processing system for multi-document workflows. -
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LLaMA Efficient Tuning
Easy-to-use LLM fine-tuning framework (LLaMA-2, BLOOM, Falcon
Easy-to-use LLM fine-tuning framework (LLaMA-2, BLOOM, Falcon, Baichuan, Qwen, ChatGLM2) -
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RAG API
ID-based RAG FastAPI: Integration with Langchain and PostgreSQL
rag_api is an open-source REST API for building Retrieval-Augmented Generation (RAG) systems using LLMs like GPT. It lets users index documents, search semantically, and retrieve relevant content for use in generative AI workflows. Designed for rapid prototyping, it is ideal for chatbot development, document assistants, and knowledge-based LLM apps. -
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NiceGUI
Create web-based user interfaces with Python
NiceGUI is a Python-based UI framework that enables developers to create interactive web applications using only Python code. It abstracts away the complexities of HTML, CSS, and JavaScript, allowing for rapid development of web interfaces directly from Python scripts. NiceGUI is suitable for building dashboards, control panels, and other web-based tools, especially in contexts like robotics and data visualization. -
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Local-NotebookLM
Googles NotebookLM but local
Local-NotebookLM is a local AI tool for turning PDF documents into generated audio content. It works like a self-hosted alternative to NotebookLM-style document-to-audio workflows. The system extracts and processes PDF text, sends the content through an LLM, and converts the result into speech with configurable voices. Users can generate podcasts, summaries, interviews, lectures, debates, tutorials, news reports, executive briefs, and other formats. It supports multiple LLM providers,... -
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ReactPy
It's React, but in Python
ReactPy provides a React-style component model for Python developers to build web frontends without JavaScript. Components and hooks create declarative, reactive UIs, working across frameworks like Flask, Django, Jupyter, and more. With WebAssembly support for performance, ReactPy aims to empower Python-native frontend development. -
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Hamilton DAGWorks
Helps scientists define testable, modular, self-documenting dataflow
Hamilton is a lightweight Python library for directed acyclic graphs (DAGs) of data transformations. Your DAG is portable; it runs anywhere Python runs, whether it's a script, notebook, Airflow pipeline, FastAPI server, etc. Your DAG is expressive; Hamilton has extensive features to define and modify the execution of a DAG (e.g., data validation, experiment tracking, remote execution). To create a DAG, write regular Python functions that specify their dependencies with their parameters. As shown below, it results in readable code that can always be visualized. ... -
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Typer
Typer, build great CLIs, based on Python type hints
...Grow in complexity as much as you want, create arbitrarily complex trees of commands and groups of subcommands, with options and arguments. And it's intended to be the FastAPI of CLIs. Typer stands on the shoulders of a giant. Its only internal dependency is Click.
