AI Agent 市场：从 ClawHub 到 Hugging Face Spaces

┌────────────────────────────────────────────────────────────┐
│                  AI Agent 市场生态                          │
├────────────────┬────────────────┬───────────────────────────┤
│   开源生态型    │   平台型       │   垂直场景型              │
├────────────────┼────────────────┼───────────────────────────┤
│ Hugging Face   │ Coze (字节)    │ ClawHub (Agent分发)       │
│ Spaces         │ Dify Marketplace│ AutoGPT Store            │
│ GitHub Topics  │ FastGPT App库  │ AgentGPT                  │
│ CrewAI Hub     │ 千帆 AppBuilder │ SuperAGI                 │
└────────────────┴────────────────┴───────────────────────────┘

# app.py — Gradio Agent 示例
import gradio as gr
from openai import OpenAI

client = OpenAI(
    base_url="https://your-inference-endpoint/v1",
    api_key="hf_xxx",
)

def chat(message, history):
    messages = [{"role": "system", "content": "你是一个有用的助手。"}]
    for h in history:
        messages.append({"role": "user", "content": h[0]})
        messages.append({"role": "assistant", "content": h[1]})
    messages.append({"role": "user", "content": message})
    
    response = client.chat.completions.create(
        model="meta-llama/Llama-3.3-70B-Instruct",
        messages=messages,
        stream=True,
    )
    
    partial = ""
    for chunk in response:
        if chunk.choices[0].delta.content:
            partial += chunk.choices[0].delta.content
            yield partial

demo = gr.ChatInterface(chat, title="我的 AI Agent")
demo.launch()

# README.md 中的 frontmatter
---
title: "AI Research Agent"
emoji: "🔬"
colorFrom: "blue"
colorTo: "purple"
sdk: "gradio"
sdk_version: "5.0.0"
app_file: "app.py"
pinned: true
license: "mit"
models:
  - "meta-llama/Llama-3.3-70B-Instruct"
tags:
  - "agent"
  - "research"
  - "rag"
---

# agent.yaml — ClawHub Agent 定义文件
name: "code-reviewer"
version: "1.2.0"
description: "自动化代码审查 Agent"
author: "developer-name"
license: "MIT"

# Agent 配置
agent:
  model: "gpt-4o"
  system_prompt: |
    你是一位资深代码审查专家。
    请从安全性、性能、可读性三个维度审查代码。
  tools:
    - github-read
    - github-comment
  parameters:
    temperature: 0.3
    max_tokens: 4096

# 依赖
dependencies:
  - "openai>=1.0"
  - "pygithub>=2.0"

# 运行时要求
runtime:
  memory: "512MB"
  timeout: 60

# 安装 ClawHub CLI
pip install clawhub

# 登录
clawhub login

# 初始化 Agent 项目
clawhub init my-agent
# → 生成 agent.yaml 模板

# 本地测试
clawhub run

# 发布到市场
clawhub publish

# 版本管理
clawhub version bump patch  # 1.0.0 → 1.0.1
clawhub publish

┌─────────────────────────────────────┐
│            Coze 平台架构             │
├─────────────────────────────────────┤
│  ┌───────────┐  ┌───────────────┐  │
│  │ 可视化编辑 │  │ 插件市场       │  │
│  │ (拖拽式)   │  │ (60+ 内置)    │  │
│  └─────┬─────┘  └───────┬───────┘  │
│        │                 │          │
│  ┌─────┴─────────────────┴──────┐  │
│  │       Agent 运行时引擎        │  │
│  └─────┬─────────────────┬──────┘  │
│        │                 │          │
│  ┌─────┴─────┐  ┌────────┴──────┐  │
│  │ 知识库     │  │ 发布渠道       │  │
│  │ (RAG)     │  │ (飞书/微信/...)│  │
│  └───────────┘  └───────────────┘  │
└─────────────────────────────────────┘

// Coze Bot 配置（JSON 导出）
{
  "bot_id": "code-assistant",
  "name": "代码助手",
  "description": "智能代码审查和优化建议",
  "model": "doubao-pro-32k",
  "system_prompt": "你是一个专业的代码助手...",
  "plugins": [
    "github_search",
    "code_runner",
    "stackoverflow_search"
  ],
  "knowledge_base": {
    "datasets": ["python_best_practices"],
    "top_k": 5
  },
  "workflow": {
    "nodes": [
      {"type": "intent_classify", "categories": ["审查", "优化", "解释"]},
      {"type": "conditional", "branches": [...]},
      {"type": "llm_generate", "model": "doubao-pro-32k"}
    ]
  },
  "publish_channels": ["feishu", "wechat", "web"]
}

# Dify 应用模板
app:
  name: "智能客服"
  mode: "advanced-chat"
  description: "基于知识库的智能客服系统"
  
  model_config:
    model:
      provider: "openai"
      name: "gpt-4o"
      mode: "chat"
    completion_params:
      temperature: 0.3
      max_tokens: 2048
  
  dataset_configs:
    datasets:
      - dataset_id: "faq_knowledge_base"
        retriever:
          type: "hybrid"
          top_k: 5
          score_threshold: 0.5
          rerank: true
  
  workflow:
    nodes:
      - id: "start"
        type: "start"
      - id: "intent"
        type: "question-classifier"
        categories:
          - "产品咨询 → product_search"
          - "售后问题 → after_sale"
          - "其他 → general_chat"
      - id: "product_search"
        type: "knowledge-retrieval"
        dataset_id: "product_info"
      - id: "generate"
        type: "llm"
        template: "基于以下信息回答用户问题：\n{context}\n\n问题：{query}"

# CrewAI Hub 模板导入
from crewai import Crew

# 从 Hub 导入预定义的 Crew 模板
crew = Crew.from_hub(
    "research-team-template",
    agents_config="agents.yaml",
    tasks_config="tasks.yaml",
)

# 自定义并运行
crew.agents[0].llm = "gpt-4o"  # 替换模型
result = crew.kickoff(inputs={"topic": "AI Agent 市场分析"})

# agents.yaml — 可共享的 Agent 配置
researcher:
  role: "研究员"
  goal: "收集和分析信息"
  backstory: "你是经验丰富的研究员"
  tools:
    - "serper_search"
    - "web_scraper"

analyst:
  role: "分析师"
  goal: "从数据中提取洞察"
  backstory: "你是数据驱动的分析师"
  tools:
    - "python_executor"
    - "data_visualizer"

writer:
  role: "撰稿人"
  goal: "将分析结果转化为报告"
  backstory: "你是技术写作专家"