encoder-010/infotact-project1-grievance-nlp

An AI-powered system for automated analysis of citizen complaints: it classifies which government department should handle a complaint, detects sentiment (Critical/Negative/Neutral/Positive), assigns an urgency score (0–100), and recommends priority actions. Intended users include municipal/government grievance teams, civic-tech developers, and evaluators of NLP solutions. Key features: - Models: TF-IDF vectorization with Random Forest for department classification and SVM for sentiment. - Tech stack: Python, NLTK, scikit-learn, FastAPI (REST endpoints: GET /, GET /health, POST /analyze). - Performance: department accuracy 53.33%, sentiment 66.11%, macro F1 53.33%. - Run: pip install -r requirements.txt; uvicorn main:app --reload. - Organized week-wise development and documented commits.

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