awoooi/apps/api/src/routes/agent.py

"""
Agent (OpenClaw) Endpoints
ADR-005: BFF 架構 - 所有 AI 調用經過 BFF
Phase 1.2: 真實 Ollama 串接
"""

import json
import logging
from datetime import datetime
from typing import Literal
from uuid import UUID, uuid4

import httpx
from fastapi import APIRouter, Query
from fastapi.responses import StreamingResponse
from pydantic import BaseModel

router = APIRouter()
logger = logging.getLogger(__name__)

# ==================== Ollama Config ====================
OLLAMA_BASE_URL = "http://192.168.0.188:11434"
OLLAMA_MODEL = "llama3.2:latest"  # 可根據實際部署調整
OLLAMA_TIMEOUT = 120.0  # 串流超時


class ChatRequest(BaseModel):
    message: str
    conversation_id: UUID | None = None
    context: dict | None = None


class SuggestedAction(BaseModel):
    id: str
    label: str
    description: str | None = None
    risk_level: Literal["low", "medium", "high", "critical"]


class ChatResponse(BaseModel):
    message: str
    conversation_id: UUID
    actions: list[SuggestedAction] | None = None
    requires_approval: bool = False
    approval_id: UUID | None = None


class AgentStatus(BaseModel):
    status: Literal["idle", "thinking", "executing", "waiting_approval"]
    active_conversations: int
    current_task: str | None = None
    last_activity: datetime | None = None


@router.post("/chat", response_model=ChatResponse)
async def chat_with_agent(request: ChatRequest) -> ChatResponse:
    """與 OpenClaw 對話"""
    conversation_id = request.conversation_id or uuid4()

    # TODO: 實際調用 OpenClaw
    return ChatResponse(
        message=f"收到訊息: {request.message}",
        conversation_id=conversation_id,
        requires_approval=False,
    )


@router.post("/chat/stream")
async def chat_with_agent_stream(request: ChatRequest) -> StreamingResponse:
    """與 OpenClaw 對話 (SSE 串流)"""

    async def generate():
        # TODO: 實際串流
        yield "data: Hello from OpenClaw\n\n"
        yield "data: [DONE]\n\n"

    return StreamingResponse(
        generate(),
        media_type="text/event-stream",
    )


@router.get("/status", response_model=AgentStatus)
async def get_agent_status() -> AgentStatus:
    """OpenClaw 狀態"""
    return AgentStatus(
        status="idle",
        active_conversations=0,
        current_task=None,
        last_activity=datetime.utcnow(),
    )


@router.get("/thinking")
async def get_agent_thinking(
    prompt: str = Query(
        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。",
        description="發送給 AI 的提示詞",
    ),
    model: str = Query(default=OLLAMA_MODEL, description="Ollama 模型名稱"),
) -> StreamingResponse:
    """
    OpenClaw 思考軌跡 (SSE 串流)
    Phase 1.2: 真實串接 Ollama at 192.168.0.188:11434
    """

    async def generate_thinking_stream():
        """串接 Ollama 並轉換為 SSE 格式"""
        # 1. 開始思考
        yield f"data: {json.dumps({'type': 'thinking', 'content': '正在連接 AI 模型...'}, ensure_ascii=False)}\n\n"

        try:
            async with httpx.AsyncClient(timeout=OLLAMA_TIMEOUT) as client:
                # 2. 發送請求到 Ollama
                yield f"data: {json.dumps({'type': 'thinking', 'content': f'模型: {model}'}, ensure_ascii=False)}\n\n"

                async with client.stream(
                    "POST",
                    f"{OLLAMA_BASE_URL}/api/generate",
                    json={
                        "model": model,
                        "prompt": prompt,
                        "stream": True,
                    },
                ) as response:
                    if response.status_code != 200:
                        yield f"data: {json.dumps({'type': 'error', 'content': f'Ollama 錯誤: HTTP {response.status_code}'}, ensure_ascii=False)}\n\n"
                        yield "data: [DONE]\n\n"
                        return

                    yield f"data: {json.dumps({'type': 'thinking', 'content': '開始接收 AI 回應...'}, ensure_ascii=False)}\n\n"

                    # 3. 串流讀取 Ollama 回應
                    buffer = ""
                    async for line in response.aiter_lines():
                        if not line:
                            continue

                        try:
                            chunk = json.loads(line)
                            token = chunk.get("response", "")
                            done = chunk.get("done", False)

                            if token:
                                # 累積 token，每 10 字符或遇到標點符號時發送
                                buffer += token
                                if len(buffer) >= 10 or any(p in buffer for p in "。！？，、\n"):
                                    yield f"data: {json.dumps({'type': 'thinking', 'content': buffer}, ensure_ascii=False)}\n\n"
                                    buffer = ""

                            if done:
                                # 發送剩餘 buffer
                                if buffer:
                                    yield f"data: {json.dumps({'type': 'thinking', 'content': buffer}, ensure_ascii=False)}\n\n"
                                # 發送完成訊息
                                yield f"data: {json.dumps({'type': 'result', 'content': '分析完成'}, ensure_ascii=False)}\n\n"
                                break

                        except json.JSONDecodeError as e:
                            logger.warning(f"JSON 解析失敗: {line[:100]}... - {e}")
                            continue

        except httpx.ConnectError as e:
            logger.error(f"無法連接 Ollama: {e}")
            yield f"data: {json.dumps({'type': 'error', 'content': f'無法連接 Ollama ({OLLAMA_BASE_URL})'}, ensure_ascii=False)}\n\n"
        except httpx.TimeoutException as e:
            logger.error(f"Ollama 超時: {e}")
            yield f"data: {json.dumps({'type': 'error', 'content': '請求超時'}, ensure_ascii=False)}\n\n"
        except Exception as e:
            logger.error(f"未知錯誤: {e}")
            yield f"data: {json.dumps({'type': 'error', 'content': f'未知錯誤: {str(e)}'}, ensure_ascii=False)}\n\n"

        # 4. 結束標記
        yield "data: [DONE]\n\n"

    return StreamingResponse(
        generate_thinking_stream(),
        media_type="text/event-stream",
        headers={
            "Cache-Control": "no-cache",
            "Connection": "keep-alive",
            "X-Accel-Buffering": "no",  # 禁用 Nginx 緩衝
        },
    )