Saloni Tangal@SaloniT

Nrityapath is an AI system that generates Bharatanatyam choreography notation from natural language. Users can input a movement phrase or story, and the system outputs a structured JSON sequence following a new standard: NNF (Nrityapath Notation Format). The project addresses a major gap in Indian classical dance: there is no modern, digital way to document movement, emotion, and narrative. NNF converts text into precise choreographic elements such as posture (ARA, SAM, MND), mudra (ALA, KAT, TRI, PTA), movement type (FWD, TURN_R, STATIC), beats (1B–4B), direction, rasa, and teaching notes. How It Works: 1. Gemini / Google AI Studio A strict system prompt enforces the NNF schema. Movement or story descriptions become clean, consistent JSON with 1–7 choreographic steps. 2. Opus Workflow Text input → NNF Generator (LLM agent) → Rule-based checks + agentic review → Human review for cultural accuracy and schema correctness → Audit summary for transparency → Final JSON output Public Opus Template: https://app.opus.com/app/workflow/share/30455570-d049-4e60-90f2-e1a600f6885a 3. Prototype: A lightweight UI visualizes choreography with stick-figure illustrations, posture/mudra icons, direction and beat markers, a JSON viewer, and step-by-step navigation. Why It Matters: Classical dance lacks a universal, digital, accessible notation system. Nrityapath provides structured choreography documentation for dancers, students, teachers, and archivists. It also opens pathways for animated practice tools, curriculum design, and collaborative choreography libraries. Tech Stack: Gemini 5.1 (NNF generation), Opus (validation + audit), Bolt.new / Framer (visualization), GitHub (schema + examples). Impact: Nrityapath lays the foundation for a new digital standard in Bharatanatyam notation, supporting learning, preservation, and creative innovation across global classical dance communities.

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