Ai resume role recommended

Inspiration# AI Resume Skill Extractor

Inspiration

The project was inspired by the difficulty of manually reviewing resumes and identifying relevant technical skills. I wanted to build a simple AI-based solution that could automatically extract useful information from a resume and help make the screening process faster.

How I Built It

I built the project using Python and FastAPI. The application accepts a resume in PDF format, extracts its text using PyMuPDF, and processes the content to identify technical skills.

The extracted skills are returned through a REST API, making the application easy to integrate with other systems. I also used Swagger UI through FastAPI's /docs endpoint to test and demonstrate the API.

The basic workflow is:

$$ \text{Resume PDF} \rightarrow \text{Text Extraction} \rightarrow \text{Skill Detection} \rightarrow \text{Structured Output} $$

What I Learned

Through this project, I learned how to:

• Build REST APIs using FastAPI
• Handle PDF file uploads and text extraction
• Process unstructured resume data
• Design and test API endpoints
• Work with JSON-based API responses
• Use Swagger/OpenAPI for API testing
• Structure a practical AI/ML-oriented application

Challenges Faced

One of the main challenges was handling different resume formats and extracting meaningful information from unstructured text. Resumes can contain different layouts, skill names, sections, and formatting styles.

I also had to make the skill extraction process reliable enough to identify relevant technical skills without incorrectly treating unrelated words as skills.

This project helped me understand how real-world AI applications combine Python, APIs, text processing, and structured data to solve practical problems.

What it does

How we built it

Challenges we ran into

Accomplishments that we're proud of

What we learned

What's next for Ai resume role recommended

Built With

• fastapi
• pymupdf
• python
• rest-api
• swagger/openapi