Add system memory monitoring, Bedrock support, and Discord integrations
- Add CPU/GPU memory monitoring endpoint and frontend widget - Add Amazon Bedrock model support (API key / inference profiles) plus model selector entries - Add Discord weather/laundry notification job (JMA forecast + LLM-generated message) - Add Discord bot that replies to mentions via the configured LLM, with weather-aware context - Add scheduled "useless tips" job with separate webhook and quiet-hours skip - Switch FastAPI startup to lifespan handler, log viewer, markdown rendering, and toast UI additions Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
This commit is contained in:
Claude Sonnet 4.6
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from . import chat, memory, logs, system
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+48
-14
@@ -30,11 +30,29 @@ class SessionResponse(BaseModel):
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from_attributes = True
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class MessageResponse(BaseModel):
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id: int
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role: str
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content: str
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created_at: datetime
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class Config:
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from_attributes = True
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@router.get("/sessions", response_model=list[SessionResponse])
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def list_sessions(db: DBSession = Depends(get_db)):
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return db.query(Session).order_by(Session.updated_at.desc()).all()
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@router.get("/sessions/{session_id}/messages", response_model=list[MessageResponse])
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def get_messages(session_id: str, db: DBSession = Depends(get_db)):
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session = db.get(Session, session_id)
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if not session:
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raise HTTPException(status_code=404, detail="Session not found")
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return session.messages
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@router.delete("/sessions/{session_id}", status_code=204)
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def delete_session(session_id: str, db: DBSession = Depends(get_db)):
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session = db.get(Session, session_id)
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@@ -68,24 +86,40 @@ async def stream_chat(req: ChatRequest, db: DBSession = Depends(get_db)):
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context = mem.get_context_messages(db, session.id)
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async def generate():
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import json as _json
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def sse(payload: dict) -> str:
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return f"data: {_json.dumps(payload, ensure_ascii=False)}\n\n"
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# セッションIDをまず返す（新規セッション時にフロントへ通知）
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yield f"data: {{\"type\":\"session_id\",\"value\":\"{session.id}\"}}\n\n"
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yield sse({"type": "session_id", "value": session.id})
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full_response = []
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async for chunk in llm.stream_chat(context, model=req.model or session.model):
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full_response.append(chunk)
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escaped = chunk.replace('"', '\\"').replace('\n', '\\n')
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yield f"data: {{\"type\":\"chunk\",\"value\":\"{escaped}\"}}\n\n"
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try:
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async for chunk in llm.stream_chat(context, model=req.model or session.model, session_id=session.id):
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full_response.append(chunk)
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yield sse({"type": "chunk", "value": chunk})
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# アシスタントメッセージを保存
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assistant_content = "".join(full_response)
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db.add(Message(session_id=session.id, role="assistant", content=assistant_content))
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session.updated_at = datetime.now(timezone.utc)
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db.commit()
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# アシスタントメッセージを保存
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assistant_content = "".join(full_response)
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db.add(Message(session_id=session.id, role="assistant", content=assistant_content))
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session.updated_at = datetime.now(timezone.utc)
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db.commit()
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# メモリ要約チェック
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await mem.maybe_summarize(db, session)
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# メモリ要約チェック
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await mem.maybe_summarize(db, session)
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yield "data: {\"type\":\"done\"}\n\n"
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yield sse({"type": "done"})
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return StreamingResponse(generate(), media_type="text/event-stream")
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except Exception as e:
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yield sse({"type": "error", "value": str(e)})
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return StreamingResponse(
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generate(),
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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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"X-Accel-Buffering": "no",
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"Connection": "keep-alive",
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},
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)
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from datetime import datetime
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from fastapi import APIRouter, Depends, Query
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from pydantic import BaseModel
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from sqlalchemy.orm import Session as DBSession
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from sqlalchemy import desc
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from app.db.database import get_db
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from app.db.models import ApiLog
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router = APIRouter(prefix="/logs", tags=["logs"])
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class LogResponse(BaseModel):
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id: int
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session_id: str | None
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model: str
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request_json: str
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response_text: str | None
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error: str | None
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latency_ms: float | None
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created_at: datetime
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class Config:
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from_attributes = True
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@router.get("", response_model=list[LogResponse])
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def list_logs(
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session_id: str | None = Query(None),
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status: str | None = Query(None, description="'ok' または 'error'"),
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limit: int = Query(100, le=500),
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offset: int = Query(0),
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db: DBSession = Depends(get_db),
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):
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q = db.query(ApiLog)
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if session_id:
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q = q.filter(ApiLog.session_id == session_id)
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if status == "ok":
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q = q.filter(ApiLog.error.is_(None))
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elif status == "error":
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q = q.filter(ApiLog.error.isnot(None))
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return q.order_by(desc(ApiLog.created_at)).offset(offset).limit(limit).all()
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@router.delete("/{log_id}", status_code=204)
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def delete_log(log_id: int, db: DBSession = Depends(get_db)):
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log = db.get(ApiLog, log_id)
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if log:
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db.delete(log)
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db.commit()
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@@ -0,0 +1,63 @@
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from fastapi import APIRouter
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import psutil
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from pydantic import BaseModel
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from app.core.scheduler import send_useless_tip, send_weather_laundry_notification
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router = APIRouter(prefix="/api/system", tags=["system"])
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class MemoryStats(BaseModel):
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cpu_percent: float
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memory_percent: float
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memory_used_mb: float
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memory_total_mb: float
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gpu_memory_used_mb: float | None = None
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gpu_memory_total_mb: float | None = None
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gpu_memory_percent: float | None = None
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@router.get("/memory", response_model=MemoryStats)
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async def get_memory_stats():
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"""CPU と GPU のメモリ使用状況を返す"""
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# CPU/メモリ情報
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cpu_percent = psutil.cpu_percent(interval=0.1)
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memory = psutil.virtual_memory()
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stats = {
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"cpu_percent": cpu_percent,
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"memory_percent": memory.percent,
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"memory_used_mb": memory.used / (1024 * 1024),
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"memory_total_mb": memory.total / (1024 * 1024),
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}
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# GPU 情報（オプション）
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try:
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import pynvml
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pynvml.nvmlInit()
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device_count = pynvml.nvmlDeviceGetCount()
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if device_count > 0:
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handle = pynvml.nvmlDeviceGetHandleByIndex(0)
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mem_info = pynvml.nvmlDeviceGetMemoryInfo(handle)
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stats["gpu_memory_used_mb"] = mem_info.used / (1024 * 1024)
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stats["gpu_memory_total_mb"] = mem_info.total / (1024 * 1024)
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stats["gpu_memory_percent"] = (mem_info.used / mem_info.total) * 100
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pynvml.nvmlShutdown()
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except Exception:
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pass
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return MemoryStats(**stats)
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@router.post("/weather-notify/test")
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async def test_weather_notify():
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"""天気予報→Discord通知を手動で即時実行する（動作確認用）"""
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await send_weather_laundry_notification()
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return {"status": "sent"}
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@router.post("/useless-tip/test")
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async def test_useless_tip():
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"""どうでもいいtips→Discord通知を手動で即時実行する（動作確認用）"""
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await send_useless_tip()
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return {"status": "sent"}
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