feat: add all application source code
- apps/api: FastAPI backend with Dockerfile - apps/web: Next.js frontend with Dockerfile - apps/sensor: Signal collection agent - packages: shared packages Co-Authored-By: Claude <noreply@anthropic.com>
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184
apps/api/src/routes/agent.py
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184
apps/api/src/routes/agent.py
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"""
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Agent (ClawBot) Endpoints
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ADR-005: BFF 架構 - 所有 AI 調用經過 BFF
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Phase 1.2: 真實 Ollama 串接
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"""
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import json
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import logging
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from datetime import datetime
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from typing import Literal
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from uuid import UUID, uuid4
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import httpx
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from fastapi import APIRouter, Query
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from fastapi.responses import StreamingResponse
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from pydantic import BaseModel
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router = APIRouter()
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logger = logging.getLogger(__name__)
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# ==================== Ollama Config ====================
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OLLAMA_BASE_URL = "http://192.168.0.188:11434"
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OLLAMA_MODEL = "llama3.2:latest" # 可根據實際部署調整
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OLLAMA_TIMEOUT = 120.0 # 串流超時
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class ChatRequest(BaseModel):
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message: str
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conversation_id: UUID | None = None
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context: dict | None = None
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class SuggestedAction(BaseModel):
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id: str
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label: str
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description: str | None = None
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risk_level: Literal["low", "medium", "high", "critical"]
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class ChatResponse(BaseModel):
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message: str
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conversation_id: UUID
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actions: list[SuggestedAction] | None = None
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requires_approval: bool = False
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approval_id: UUID | None = None
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class AgentStatus(BaseModel):
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status: Literal["idle", "thinking", "executing", "waiting_approval"]
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active_conversations: int
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current_task: str | None = None
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last_activity: datetime | None = None
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@router.post("/chat", response_model=ChatResponse)
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async def chat_with_agent(request: ChatRequest) -> ChatResponse:
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"""與 ClawBot 對話"""
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conversation_id = request.conversation_id or uuid4()
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# TODO: 實際調用 ClawBot
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return ChatResponse(
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message=f"收到訊息: {request.message}",
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conversation_id=conversation_id,
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requires_approval=False,
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)
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@router.post("/chat/stream")
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async def chat_with_agent_stream(request: ChatRequest) -> StreamingResponse:
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"""與 ClawBot 對話 (SSE 串流)"""
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async def generate():
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# TODO: 實際串流
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yield "data: Hello from ClawBot\n\n"
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yield "data: [DONE]\n\n"
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return StreamingResponse(
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generate(),
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media_type="text/event-stream",
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)
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@router.get("/status", response_model=AgentStatus)
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async def get_agent_status() -> AgentStatus:
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"""ClawBot 狀態"""
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return AgentStatus(
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status="idle",
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active_conversations=0,
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current_task=None,
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last_activity=datetime.utcnow(),
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)
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@router.get("/thinking")
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async def get_agent_thinking(
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prompt: str = Query(
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default="你是 AWOOOI 智能運維助手。請簡短分析一下目前系統的健康狀態，用中文回答。",
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description="發送給 AI 的提示詞",
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),
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model: str = Query(default=OLLAMA_MODEL, description="Ollama 模型名稱"),
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) -> StreamingResponse:
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"""
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ClawBot 思考軌跡 (SSE 串流)
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Phase 1.2: 真實串接 Ollama at 192.168.0.188:11434
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"""
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async def generate_thinking_stream():
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"""串接 Ollama 並轉換為 SSE 格式"""
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# 1. 開始思考
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yield f"data: {json.dumps({'type': 'thinking', 'content': '正在連接 AI 模型...'}, ensure_ascii=False)}\n\n"
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try:
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async with httpx.AsyncClient(timeout=OLLAMA_TIMEOUT) as client:
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# 2. 發送請求到 Ollama
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yield f"data: {json.dumps({'type': 'thinking', 'content': f'模型: {model}'}, ensure_ascii=False)}\n\n"
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async with client.stream(
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"POST",
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f"{OLLAMA_BASE_URL}/api/generate",
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json={
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"model": model,
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"prompt": prompt,
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"stream": True,
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},
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) as response:
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if response.status_code != 200:
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yield f"data: {json.dumps({'type': 'error', 'content': f'Ollama 錯誤: HTTP {response.status_code}'}, ensure_ascii=False)}\n\n"
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yield "data: [DONE]\n\n"
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return
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yield f"data: {json.dumps({'type': 'thinking', 'content': '開始接收 AI 回應...'}, ensure_ascii=False)}\n\n"
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# 3. 串流讀取 Ollama 回應
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buffer = ""
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async for line in response.aiter_lines():
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if not line:
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continue
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try:
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chunk = json.loads(line)
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token = chunk.get("response", "")
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done = chunk.get("done", False)
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if token:
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# 累積 token，每 10 字符或遇到標點符號時發送
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buffer += token
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if len(buffer) >= 10 or any(p in buffer for p in "。！？，、\n"):
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yield f"data: {json.dumps({'type': 'thinking', 'content': buffer}, ensure_ascii=False)}\n\n"
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buffer = ""
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if done:
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# 發送剩餘 buffer
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if buffer:
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yield f"data: {json.dumps({'type': 'thinking', 'content': buffer}, ensure_ascii=False)}\n\n"
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# 發送完成訊息
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yield f"data: {json.dumps({'type': 'result', 'content': '分析完成'}, ensure_ascii=False)}\n\n"
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break
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except json.JSONDecodeError as e:
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logger.warning(f"JSON 解析失敗: {line[:100]}... - {e}")
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continue
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except httpx.ConnectError as e:
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logger.error(f"無法連接 Ollama: {e}")
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yield f"data: {json.dumps({'type': 'error', 'content': f'無法連接 Ollama ({OLLAMA_BASE_URL})'}, ensure_ascii=False)}\n\n"
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except httpx.TimeoutException as e:
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logger.error(f"Ollama 超時: {e}")
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yield f"data: {json.dumps({'type': 'error', 'content': '請求超時'}, ensure_ascii=False)}\n\n"
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except Exception as e:
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logger.error(f"未知錯誤: {e}")
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yield f"data: {json.dumps({'type': 'error', 'content': f'未知錯誤: {str(e)}'}, ensure_ascii=False)}\n\n"
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# 4. 結束標記
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yield "data: [DONE]\n\n"
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return StreamingResponse(
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generate_thinking_stream(),
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media_type="text/event-stream",
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headers={
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"Cache-Control": "no-cache",
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"Connection": "keep-alive",
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"X-Accel-Buffering": "no", # 禁用 Nginx 緩衝
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},
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)
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