Fastapi

What it does

This FastAPI skill provides a high-performance backend interface for the srbhr/resume-matcher AI agent. It enables rapid deployment of resume analysis workflows by exposing optimized API endpoints for document processing and candidate evaluation.

When to use it

• Deploying a production-grade resume screening service requiring low-latency responses.
• Integrating an existing resume matching model into a custom web application or mobile backend.
• Building scalable microservices that need automatic dependency injection and validation.
• Prototyping AI-driven HR tools with minimal boilerplate code.

Key capabilities

• Automatic OpenAPI documentation generation for seamless API discovery.
• Built-in support for Pydantic models ensuring robust data validation.
• Native async/await support for handling concurrent resume uploads efficiently.
• Easy integration with standard Python web frameworks and database adapters.

Example prompts

• "Deploy the resume matcher using FastAPI with a custom Docker container."
• "Create an API endpoint that accepts PDF resumes and returns match scores."
• "Integrate the srbhr/resume-matcher skill into my existing FastAPI project for candidate filtering."

Tips & gotchas

Ensure you have Python 3.8+ installed before initializing the environment, as older versions may lack required async features. While the framework handles validation automatically, complex resume parsing logic should be tested with diverse file formats to avoid runtime errors on edge cases like scanned images or corrupted PDFs.