cnbugs
d5d7e45ded
- 后端: FastAPI + kubectl 9大检查项(Pod/Node/Event/Deploy/Service/PVC/资源/网络) - AI Agent: OpenAI兼容接口自动分析故障根因+多轮追问对话 - 前端: Vue3 + Element Plus 仪表盘, 健康评分, 问题列表, 资源监控 - 一键启动脚本 start.sh
81 lines
3.6 KiB
Python
81 lines
3.6 KiB
Python
"""AI Agent 分析模块 - 调用 OpenAI 兼容接口分析诊断结果"""
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import httpx
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from backend.config import AI_API_BASE, AI_API_KEY, AI_MODEL
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SYSTEM_PROMPT = """你是一位资深的 Kubernetes 运维专家和 SRE 工程师。你的任务是分析 K8S 集群诊断报告，找出根本原因并给出修复建议。
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分析要求：
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1. **问题定位**：明确指出每个问题的根本原因（Root Cause），不要只描述表面现象
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2. **影响评估**：说明每个问题对业务的潜在影响
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3. **修复方案**：给出具体的修复命令或操作步骤（kubectl 命令、YAML 修改等）
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4. **优先级排序**：按紧急程度排序，先处理影响最大的问题
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5. **预防建议**：给出避免类似问题再次发生的建议
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输出格式：使用清晰的 Markdown，包含标题、列表、代码块。语言使用中文。"""
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async def analyze_with_ai(report: str, question: str = "") -> dict:
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"""调用 AI 分析诊断报告"""
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user_msg = f"以下是 K8S 集群诊断报告，请进行详细分析：\n\n{report}"
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if question:
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user_msg += f"\n\n用户额外问题：{question}"
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try:
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async with httpx.AsyncClient(timeout=120) as client:
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resp = await client.post(
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f"{AI_API_BASE}/chat/completions",
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headers={
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"Authorization": f"Bearer {AI_API_KEY}",
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"Content-Type": "application/json",
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},
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json={
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"model": AI_MODEL,
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"messages": [
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{"role": "system", "content": SYSTEM_PROMPT},
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{"role": "user", "content": user_msg},
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],
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"temperature": 0.3,
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"max_tokens": 4096,
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},
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)
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resp.raise_for_status()
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data = resp.json()
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content = data["choices"][0]["message"]["content"]
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return {"success": True, "analysis": content, "model": AI_MODEL}
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except httpx.HTTPStatusError as e:
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return {"success": False, "analysis": f"AI 接口返回错误: {e.response.status_code} - {e.response.text[:500]}", "model": AI_MODEL}
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except httpx.ConnectError:
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return {"success": False, "analysis": f"无法连接 AI 服务 ({AI_API_BASE})，请检查配置", "model": AI_MODEL}
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except Exception as e:
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return {"success": False, "analysis": f"AI 分析失败: {str(e)}", "model": AI_MODEL}
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async def chat_with_ai(messages: list[dict], context: str = "") -> dict:
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"""多轮对话 - 基于诊断上下文追问"""
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msgs = [{"role": "system", "content": SYSTEM_PROMPT}]
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if context:
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msgs.append({"role": "system", "content": f"当前诊断上下文：\n{context}"})
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msgs.extend(messages)
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try:
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async with httpx.AsyncClient(timeout=120) as client:
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resp = await client.post(
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f"{AI_API_BASE}/chat/completions",
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headers={
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"Authorization": f"Bearer {AI_API_KEY}",
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"Content-Type": "application/json",
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},
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json={
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"model": AI_MODEL,
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"messages": msgs,
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"temperature": 0.3,
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"max_tokens": 4096,
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},
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)
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resp.raise_for_status()
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data = resp.json()
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content = data["choices"][0]["message"]["content"]
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return {"success": True, "reply": content}
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except Exception as e:
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return {"success": False, "reply": f"AI 对话失败: {str(e)}"}
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