Build AI Apps with Python: Test Your AI Agent — Keyword Matching Eval Framework | Episode 22

How do you know your agent works? Test it. Define expected answers, run the agent, check the results. A score report tells you exactly what passed and what broke. We build an evaluation framework from scratch. Five test cases with expected keywords — capital of France expects "Paris", Django language expects "Python", Linux creator expects "Linus" and "Torvalds". The evaluate function runs the agent against each case, checks keyword matches case-insensitively, and produces a pass/fail report with a percentage score. Run it after every change to catch regressions before deploying. Student code: https://github.com/GoCelesteAI/build-ai-apps-python/tree/main/episode22 Every keystroke is shown on screen with 3-second pauses so you can follow along at your own pace. What You'll Learn: • Test cases with expected keywords • Running agents against test suites • Case-insensitive keyword matching • Tracking found and missing keywords • Pass/fail determination per test • Score calculation with percentage • Regression testing for agents Key Takeaways: 1. Test cases define expected keywords — simple to write, easy to extend 2. Keyword matching is reliable — case-insensitive search tracks found and missing 3. The score catches regressions — run after every change, fix drops before deploying This is Episode 22 of Build AI Apps with Python in Neovim — Phase 4 (AI Agents). Taught by CelesteAI. Like & subscribe for more tutorials! #python #ai #evaluation #testing #agenteval #claudeapi #anthropic #neovim #programming #tutorial #machinelearning #artificialintelligence #coding #pythontutorial #buildaiapps #llm #genai #regressiontesting