Build AI Apps with Python: Product Review Analyzer with JSON | Episode 5

Get real data from AI — not paragraphs! In this episode, we build a product review analyzer that returns structured JSON. Feed in any review, get back sentiment, rating, key points, and a summary in a predictable format. The secret is a detailed system prompt that defines the exact JSON structure. Combined with temperature=0.0 for consistency, every response is parseable and reliable. Three reviews — positive, negative, neutral — all return the same structured format. Student code: https://github.com/GoCelesteAI/build-ai-apps-python/tree/main/episode05 Every keystroke is shown on screen with 3-second pauses so you can follow along at your own pace. What You'll Learn: • System prompts that define JSON output format • temperature=0.0 for reliable, consistent structured output • json.loads() to parse AI responses into Python dictionaries • json.dumps(indent=2) to pretty-print structured data • Building a reusable analyze_review() function • Processing positive, negative, and neutral reviews • Why structured output matters for real applications • Running Python scripts with :!python % Timestamps: 0:00 - Introduction 0:12 - Why Structured Output? (Preview) 0:44 - Creating structured_output.py 1:00 - Imports (new: json module) 1:30 - Setup 2:00 - System prompt — defining the JSON contract 3:40 - analyze_review() function 4:20 - temperature=0.0 — why zero matters 5:30 - json.loads() — text to data 6:00 - Review 1: Positive laptop review 6:30 - First run — structured JSON output! 7:40 - Review 2: Negative headphones review 8:40 - Review 3: Neutral coffee maker review 9:40 - Run all three — comparing results 10:30 - Code review 10:50 - Recap: 3 Key Takeaways 11:22 - End Screen Key Takeaways: 1. A detailed system prompt defines the JSON structure — Claude follows it precisely 2. temperature=0.0 gives reliable, consistent output — perfect for data extraction 3. json.loads() turns text into Python data, json.dumps() makes it readable This is Episode 5 of Build AI Apps with Python in Neovim — 32 episodes from API basics to production deployment, covering tool use, RAG, AI agents, and more.