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agent api

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Basic Information

This repository provides a minimal open source foundation for serving agent-based applications using FastAPI and PostgreSQL. It is intended as a lightweight, developer-friendly starting point for building APIs that manage and operate agents. The README documents prerequisites such as Python 3.7 or higher and PostgreSQL, explains how to configure the DATABASE_URL in an environment file, and shows how to run database migrations with alembic. The project demonstrates running a local FastAPI server with uvicorn and exposes interactive API documentation. The package installation is handled via a requirements file and the repository includes an example POST to an /agents endpoint and a sample response to illustrate basic CRUD behavior. Overall the repo aims to make it straightforward to deploy and extend agent services while keeping configuration and code simple.

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App URL
https://github.com/HackerGCLASS/agent-api
Github Repository
https://github.com/HackerGCLASS/agent-api/blob/main/README.md

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App Details

Features
The project centers on a small set of clear features: a FastAPI application for building HTTP APIs, PostgreSQL for persistence, and alembic for database migrations. It emphasizes a minimal setup with a requirements.txt for dependency installation and simple commands to run the server via uvicorn. The README highlights developer ergonomics with interactive API docs available at the FastAPI docs route and usage examples for creating agents through a POST to /agents. It also documents environment configuration for DATABASE_URL and includes guidance on running migrations and starting the app locally. The repository includes a releases section and basic contribution guidance to encourage improvements and community involvement.
Use Cases
This repo is useful for developers who need a fast, opinionated starting point to build and experiment with agent-backed services. By combining FastAPI for rapid API development and PostgreSQL for reliable data storage, it lets teams prototype agent creation and management quickly while maintaining a production-capable stack. Clear setup instructions, an example request/response pair, and interactive API documentation reduce onboarding time and make testing with tools like curl or Postman straightforward. The inclusion of alembic migrations and environment-driven configuration supports reproducible deployments and local development. The minimal, documented codebase makes it easy to extend agent models, add endpoints, and integrate additional services without heavy initial complexity.

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