Add comprehensive dataset card for TalkPlay-Tools Environments

README.md

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+---
+license: cc-by-nc-4.0
+task_categories:
+- audio-text-to-text
+tags:
+- music-recommendation
+- llm
+- tool-calling
+- conversational-ai
+- retrieval
+---
+
+# TalkPlay-Tools Environments
+
+This repository contains the prebuilt tool environments essential for the [TalkPlay-Tools: Conversational Music Recommendation with LLM Tool Calling](https://huggingface.co/papers/2510.01698) system.
+
+The paper proposes an LLM-based music recommendation system with tool calling that serves as a unified retrieval-reranking pipeline. These tool environments enable the system to interpret user intent, plan tool invocations, and orchestrate specialized components such as boolean filters (SQL), sparse retrieval (BM25), dense retrieval (embedding similarity), and generative retrieval (semantic IDs).
+
+*   **Paper:** [TalkPlay-Tools: Conversational Music Recommendation with LLM Tool Calling](https://huggingface.co/papers/2510.01698)
+*   **Project Page:** [https://talkpl.ai/p/talkplay_tools/index.html](https://talkpl.ai/p/talkplay_tools/index.html)
+*   **Code Repository:** [https://github.com/talkpl-ai/talkplay-tools](https://github.com/talkpl-ai/talkplay-tools)
+*   **Associated Demo Data:** [talkpl-ai/TalkPlayData-2](https://huggingface.co/datasets/talkpl-ai/TalkPlayData-2)
+
+## Dataset Structure
+
+The `tool_env.tar.gz` bundle, provided as part of this dataset, contains the following subdirectories:
+*   `cache/metadata` (test metadata files)
+*   `cache/bm25` (BM25 indices and `track_index.json`)
+*   `cache/encoder` (vector DB for embeddings)
+*   `cache/semantic_id` (RVQ indices per modality)
+*   `cache/sql` (SQLite DB for tracks)
+
+## Sample Usage (Fetching Tool Environments)
+
+Prebuilt demo indices are expected under `./cache`. You can download a prepared bundle and extract it:
+
+```bash
+wget https://huggingface.co/datasets/talkpl-ai/TalkPlayTools-Env/resolve/main/tool_env.tar.gz
+tar -xzvf tool_env.tar.gz -C ./cache
+```
+
+This will create the necessary tool environment directories in your local `./cache` folder, allowing you to use them with the [TalkPlay-Tools code](https://github.com/talkpl-ai/talkplay-tools).
+
+## Sample Usage (Quick Start)
+
+Once the tool environments are set up, you can run an example query with the provided test data (cold-start user case). This demo uses only **6,744 tracks** from the test split of [TalkPlayData-2](https://huggingface.co/datasets/talkpl-ai/TalkPlayData-2). Due to licensing constraints, the system returns Spotify links instead of direct audio files.
+
+```bash
+python run.py --user_query "I'm looking for calm and slow tempo piano music."
+```
+
+Example output:
+
+```bash
+----------------------------------------------------------------------------------------------------
+🎵 Music: https://open.spotify.com/track/00CXUMREit80f2McJsjcIz
+🤖 Assistant Response:
+I’ve found a perfect match for your request!
+**"Lieder ohne Worte (Songs without Words), Book 2, Op. 30: No. 7 in E-flat major"**
+by **Felix Mendelssohn**, performed by **Péter Nagy**.
+This classical piano piece features a **slow tempo (65.79 BPM)**, **mellow melodies**,
+and a **romantic, emotional tone** that exudes calm and introspection.
+
+The track’s **F# major key** and **instrumental, melancholic style**
+make it ideal for a relaxed, reflective mood. It’s a beautifully
+crafted piece that aligns perfectly with your request for calm and slow piano music.
+
+Would you like to explore similar tracks, or need recommendations for different moods?
+I’m here to help! 🎹
+----------------------------------------------------------------------------------------------------
+More detail results (Chain of Thought / Tool Calling / Response) are saved in ./demo/static
+```
+
+## License
+
+This project is released under the CC-BY-NC 4.0 license.