An AI-assisted API testing framework built with Python, pytest, and requests.
This project explores how AI can assist in API testing by:
- Generating test cases from API inputs
- Suggesting edge cases and negative scenarios
- Validating AI-generated test cases before execution
- Executing tests using pytest
- Providing clear and structured results
To bridge the gap between:
- manual API testing
- and intelligent, AI-assisted test generation
while keeping execution reliable and deterministic.
AI suggests → Framework validates → pytest executes
AI is used for assistance, not blind automation.
- Python
- pytest
- requests
- LLM (OpenAI/Claude)
🚧 Work in progress — building in public and learning step by step.
Would love feedback from QA/SDET folks on:
- framework design
- test generation approach
- real-world usability
Feel free to open issues or discussions!