add-model-descriptions

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Add Model Descriptions

添加模型描述

Add descriptions for new models available in the HuggingFace router to chat-ui's prod.yaml and dev.yaml.
为HuggingFace Router中可用的新模型,在chat-ui的prod.yaml和dev.yaml文件中添加描述。

Workflow

工作流程

  1. Fetch models from router
    WebFetch https://router.huggingface.co/v1/models
    Extract all model IDs from the response.
  2. Read current configuration
    • Read
      chart/env/prod.yaml
    • Extract model IDs from the
      MODELS
      JSON array in
      envVars
  3. Identify missing models Compare router models with prod.yaml. Missing = in router but not in prod.yaml.
  4. Research each missing model For each missing model, search the web for its specifications:
    • Model architecture (dense, MoE, parameters)
    • Key capabilities (coding, reasoning, vision, multilingual, etc.)
    • Target use cases
  5. Write descriptions Match existing style:
    • 8-12 words
    • Sentence fragments (no period needed)
    • No articles ("a", "the") unless necessary
    • Focus on: architecture, specialization, key capability
    Examples:
    • "Flagship GLM MoE for coding, reasoning, and agentic tool use."
    • "MoE agent model with multilingual coding and fast outputs."
    • "Vision-language Qwen for documents, GUI agents, and visual reasoning."
    • "Mobile agent for multilingual Android device automation."
  6. Update both files Add new models at the TOP of the MODELS array in:
    • chart/env/prod.yaml
    • chart/env/dev.yaml
    Format:
    json
    { "id": "org/model-name", "description": "Description here." }
  7. Commit changes
    git add chart/env/prod.yaml chart/env/dev.yaml
    git commit -m "feat: add descriptions for N new models from router"
  1. 从Router获取模型
    WebFetch https://router.huggingface.co/v1/models
    从响应中提取所有模型ID。
  2. 读取当前配置
    • 读取
      chart/env/prod.yaml
      文件
    • envVars
      中的
      MODELS
      JSON数组提取模型ID
  3. 识别缺失的模型 对比Router中的模型与prod.yaml中的模型。缺失的模型指存在于Router但未在prod.yaml中的模型。
  4. 调研每个缺失的模型 针对每个缺失的模型,通过网络搜索其规格信息:
    • 模型架构(密集型、MoE、参数规模)
    • 核心能力(编码、推理、视觉、多语言等)
    • 目标使用场景
  5. 撰写描述 匹配现有格式要求:
    • 8-12个单词
    • 句子片段(无需句号)
    • 除非必要,否则不使用冠词("a"、"the")
    • 重点涵盖:架构、专长领域、核心能力
    示例:
    • "Flagship GLM MoE for coding, reasoning, and agentic tool use."
    • "MoE agent model with multilingual coding and fast outputs."
    • "Vision-language Qwen for documents, GUI agents, and visual reasoning."
    • "Mobile agent for multilingual Android device automation."
  6. 更新两个配置文件 在以下文件的
    MODELS
    数组顶部添加新模型:
    • chart/env/prod.yaml
    • chart/env/dev.yaml
    格式:
    json
    { "id": "org/model-name", "description": "Description here." }
  7. 提交更改
    git add chart/env/prod.yaml chart/env/dev.yaml
    git commit -m "feat: add descriptions for N new models from router"

Notes

注意事项

  • FP8 variants: describe as "FP8 [base model] for efficient inference with [key capability]"
  • Vision models: mention "vision-language" and key visual tasks
  • Agent models: mention "agent" and automation capabilities
  • Regional models: mention language focus (e.g., "European multilingual", "Southeast Asian")
  • FP8变体:描述格式为“FP8 [基础模型],具备[核心能力]的高效推理”
  • 视觉模型:需提及“视觉-语言”及核心视觉任务
  • Agent模型:需提及“agent”及自动化能力
  • 区域模型:需提及语言侧重点(例如:“欧洲多语言”、“东南亚语言”)