Prompt Keyword Analyzer This Python project analyzes user prompts using fuzzy keyword matching to detect relevant tokens, brand terms, and keyword frequencies. It uses RapidFuzz for approximate string matching, nltk for multilingual stopword filtering, and supports both Markdown console output and structured JSON file export. --- ## 🔍 Features - Fuzzy matching using RapidFuzz - Multilingual stopword removal (English and German, configurable) - Token classification into brand and generic types - Flexible output format: markdown (printed to console) or json (saved to file) - Fully local, no Apify SDK required --- ## 📥 Example: Adidas Prompt Analysis Here's a realistic input scenario for analyzing prompts that mention Adidas, including spelling variations and discount-related terms: ### input.json json { "prompts": [ "adidas sneaker sale today", "white running shoes from addidas", "Addidas Rabattcode gesucht", "neue sportschuhe im angebot", "discount für adidas laufschuhe", "adidas schuhe im trend", "sale bei addddidas online store", "welche adidas modelle sind beliebt", "adidass running collection deals" ], "target_keywords": ["adidas", "sale", "rabattcode", "angebot", "discount", "schuhe", "sneaker"], "brand_keywords": ["adidas", "addidas", "adidass", "addddidas"], "threshold": 65, "output_format": "markdown" } ## Sample Markdown Output: | token | matched_keyword | score | frequency | type | |-----------|-----------------|-------|-----------|---------| | adidas | adidas | 100 | 4 | brand | | addidas | adidas | 91 | 1 | brand | | adidass | adidas | 91 | 1 | brand | | rabattcode| rabattcode | 100 | 1 | generic | | angebot | angebot | 100 | 1 | generic | | discount | discount | 100 | 1 | generic | | schuhe | schuhe | 100 | 2 | generic | | sneaker | sneaker | 100 | 1 | generic | * threshold: Minimum match score (0–100) * output_format: "markdown" (console) or "json" (file) --- ## ⚙️ Setup 1. Install dependencies: bash pip install -r requirements.txt python -m nltk.downloader punkt stopwords 2. Run the analyzer: bash python -m src By default, it loads input.json and saves to output.json (if format is "json"). You can also specify custom paths using environment variables: bash APIFY_INPUT_PATH=custom_input.json OUTPUT_PATH=results.json python -m src --- ## 🧪 Output (Markdown Example) | token | matched_keyword | score | frequency | type | |----------|-----------------|-------|-----------|---------| | purelei | purelei | 100 | 3 | brand | | rabatt | rabattcode | 86 | 2 | generic | | discount | discount | 100 | 1 | generic | --- ## 📝 Notes * Custom stopwords can be extended. please let me know via info@antonioblago.com * Compatible with Python 3.10+ or 3.11+ --- ## 📚 Resources * Developer Contact * SEO ---