# zerolan-data **Repository Path**: CrazyToffy/zerolan-data ## Basic Information - **Project Name**: zerolan-data - **Description**: No description available - **Primary Language**: Unknown - **License**: MIT - **Default Branch**: main - **Homepage**: None - **GVP Project**: No ## Statistics - **Stars**: 0 - **Forks**: 0 - **Created**: 2025-12-25 - **Last Updated**: 2025-12-25 ## Categories & Tags **Categories**: Uncategorized **Tags**: None ## README # ZerolanData ![Static Badge](https://img.shields.io/badge/Python-3.1x-blue) ![Static Badge](https://img.shields.io/badge/License-MIT-orange) ![Static Badge](https://img.shields.io/badge/ver-1.5.0-green) Define data classes used in [**ZerolanLiveRobot**](https://github.com/AkagawaTsurunaki/ZerolanLiveRobot) and [**ZerolanCore**](https://github.com/AkagawaTsurunaki/zerolan-core). All data classes inherits `pydantic.BaseModel` with strict schema validation. See documentation [here](docs/doc_en.md). The documentation is automatically generated and is consistent with the comments and annotations in the code. The project structure is as follows: ``` docs └─ doc_en.md # Documentation for zerolan-data. src └─ zerolan └─ data ├─ __init__.py ├─ protocol │ ├─ protocol.py # JSON+WebSocket message object │ ├─ __init__.py ├─ pipeline │ ├─ abs_data.py # Abstract pipeline query and prediction │ ├─ asr.py # Automatic speech recognition │ ├─ img_cap.py # Image capitioning │ ├─ llm.py # Large language model │ ├─ milvus.py # Vector database (Milvus) │ ├─ ocr.py # Optical character recognition │ ├─ tts.py # Text to speech │ ├─ vid_cap.py # Video capitioning │ ├─ vla.py # Vision language action model │ └─ __init__.py └─ data ├─ danmaku.py # Live-streaming data for Bilibili, YouTube and Twitch ├─ prompt.py # TTS prompt ├─ state.py # Service state └─ __init__.py ``` **How to generate documentation?** Run the following commands: ```shell cd src/zerolan/data/generator python doc_gen.py ```