AISOS 技术文档

version: "3.8"
services:
  ollama:
    image: ollama/ollama:latest
    ports: ["11434:11434"]
    volumes: ["./ollama:/root/.ollama"]
    deploy:
      resources:
        reservations:
          devices:
            - capabilities: [gpu]

  qdrant:
    image: qdrant/qdrant:latest
    ports: ["6333:6333"]
    volumes: ["./qdrant:/qdrant/storage"]

  dify:
    image: langgenius/dify:latest
    ports: ["3000:3000"]
    environment:
      OLLAMA_API_BASE: "http://ollama:11434"

  openclaw:
    image: aisos/openclaw-enterprise:latest
    ports: ["8080:8080"]
    environment:
      OLLAMA_URL: "http://ollama:11434"
      QDRANT_URL: "http://qdrant:6333"
      DIFY_URL: "http://dify:3000"
      WECHAT_WORK_TOKEN: "${WECHAT_TOKEN}"

# 启动全部服务
docker-compose up -d

# 拉取 DeepSeek-r1 模型
docker exec ollama ollama pull deepseek-r1

# 拉取 Qwen 备用模型
docker exec ollama ollama pull qwen2.5

# 导入知识库
python scripts/import_knowledge.py \
  --qdrant-url http://localhost:6333 \
  --docs-dir ./knowledge/compliance/ \
  --collection "aisos-compliance"

# 验证 Agent
curl http://localhost:8080/api/health

# Agent 执行流程示例
while not task.completed:
    # 1. 思考：分析当前状态和目标
    thought = agent.reason(context, task)

    # 2. 行动：选择并执行工具/Skill
    action = agent.select_action(thought)
    result = agent.execute(action)

    # 3. 观察：评估执行结果
    observation = agent.observe(result)

    # 4. 更新上下文记忆
    context.update(thought, action, observation)

# heartbeat.yml - 安全巡检 Agent 定时任务
heartbeats:
  - name: "daily-compliance-check"
    cron: "0 2 * * *"  # 每日凌晨 2 点
    agent: "security-compliance"
    task: "执行等保 2.0 全量合规检查并生成报告"
    notify:
      channel: "wechat-work"
      target: "security-team"

  - name: "threat-intel-digest"
    cron: "0 8 * * *"  # 每日早 8 点
    agent: "threat-analyst"
    task: "采集过去 24 小时威胁情报，生成安全简报"

from openclaw.skill import BaseSkill, skill_config

@skill_config(
    name="cve-hunter",
    description="查询 CVE/CNVD 漏洞数据库，评估影响",
    version="1.0.0",
    author="AISOS"
)
class CVEHunterSkill(BaseSkill):

    async def execute(self, params):
        # 1. 查询 CVE 数据库
        cve_id = params.get("cve_id")
        cve_data = await self.query_cve(cve_id)

        # 2. 关联资产清单
        affected = await self.match_assets(
            cve_data.affected_products
        )

        # 3. RAG 增强分析
        analysis = await self.rag.query(
            collection="aisos-compliance",
            query=f"漏洞 {cve_id} 的影响和修复建议"
        )

        return {
            "cve": cve_data,
            "affected_assets": affected,
            "recommendation": analysis
        }

from aisos.knowledge import KnowledgeBase

kb = KnowledgeBase(
    qdrant_url="http://localhost:6333",
    collection="aisos-compliance"
)

# 导入等保 2.0 文档
kb.import_documents(
    path="./knowledge/compliance/",
    formats=["pdf", "docx", "md"],
    chunk_size=512,
    overlap=50
)

# RAG 检索
results = kb.search(
    query="等保 2.0 三级要求中关于访问控制的条款",
    top_k=5
)
# → 返回 5 条最相关的知识片段