feat(image-render): main + Dockerfile + compose entry (port 18714)

ai_trade(HIGH, native python :8001) + wsl_docker(NORMAL, WSL2 Ubuntu-24.04
docker compose up). spec의 signal_v2→ai_trade, 22.04→24.04, web-ai-services
→web-ai/services 정정. sudoers NOPASSWD + 재부팅 검증 절차.
Plan-B-Infra Phase 3.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

services/docker-compose.yml

@@ -63,17 +63,60 @@ services:
       - NAS_BASE_URL=${NAS_BASE_URL:-http://192.168.45.54:18801}
       - INTERNAL_API_KEY=${INTERNAL_API_KEY:-}
       - OPENAI_API_KEY=${OPENAI_API_KEY:-}
-      - GOOGLE_PROJECT_ID=${GOOGLE_PROJECT_ID:-}
-      - GOOGLE_LOCATION=${GOOGLE_LOCATION:-us-central1}
-      - GOOGLE_GCS_BUCKET=${GOOGLE_GCS_BUCKET:-}
-      - GOOGLE_APPLICATION_CREDENTIALS=/app/keys/gcp-sa.json
-      - PIAPI_API_KEY=${PIAPI_API_KEY:-}
+      - GEMINI_API_KEY=${GEMINI_API_KEY:-}
+      - KLING_ACCESS_KEY=${KLING_ACCESS_KEY:-}
+      - KLING_SECRET_KEY=${KLING_SECRET_KEY:-}
       - SEEDANCE_API_KEY=${SEEDANCE_API_KEY:-}
       - VIDEO_MEDIA_ROOT=${VIDEO_MEDIA_ROOT:-/mnt/nas/webpage/data/video}
       - VIDEO_MEDIA_URL_PREFIX=${VIDEO_MEDIA_URL_PREFIX:-/media/video}
     volumes:
       - /mnt/nas/webpage/data/video:/mnt/nas/webpage/data/video
-      - ${GCP_SA_JSON_HOST_PATH:-/etc/webai/gcp-sa.json}:/app/keys/gcp-sa.json:ro
+    healthcheck:
+      test: ["CMD", "python", "-c", "import urllib.request; urllib.request.urlopen('http://localhost:8000/health')"]
+      interval: 60s
+      timeout: 5s
+      retries: 3
+
+  task-watcher:
+    build:
+      context: ./task-watcher
+    container_name: task-watcher
+    restart: unless-stopped
+    ports:
+      - "18713:8000"
+    environment:
+      - TZ=Asia/Seoul
+      - REDIS_URL=${REDIS_URL:-redis://192.168.45.54:6379}
+      - STOCK_BASE_URL=${STOCK_BASE_URL:-http://192.168.45.54:18500}
+      - TRADING_START=${TRADING_START:-07:00}
+      - TRADING_END=${TRADING_END:-16:30}
+    healthcheck:
+      test: ["CMD", "python", "-c", "import urllib.request; urllib.request.urlopen('http://localhost:8000/health')"]
+      interval: 60s
+      timeout: 5s
+      retries: 3
+
+  image-render:
+    build:
+      context: ./image-render
+    container_name: image-render
+    restart: unless-stopped
+    ports:
+      - "18714:8000"
+    environment:
+      - TZ=Asia/Seoul
+      - REDIS_URL=${REDIS_URL:-redis://192.168.45.54:6379}
+      - NAS_BASE_URL=${NAS_BASE_URL:-http://192.168.45.54:18802}
+      - INTERNAL_API_KEY=${INTERNAL_API_KEY:-}
+      - OPENAI_API_KEY=${OPENAI_API_KEY:-}
+      - GEMINI_API_KEY=${GEMINI_API_KEY:-}
+      - COMFYUI_URL=${COMFYUI_URL:-http://host.docker.internal:8188}
+      - FLUX_BLOCK_TRADING_HOURS=${FLUX_BLOCK_TRADING_HOURS:-1}
+      - IMAGE_MEDIA_ROOT=${IMAGE_MEDIA_ROOT:-/mnt/nas/webpage/data/image}
+    extra_hosts:
+      - "host.docker.internal:host-gateway"
+    volumes:
+      - /mnt/nas/webpage/data/image:/mnt/nas/webpage/data/image
     healthcheck:
       test: ["CMD", "python", "-c", "import urllib.request; urllib.request.urlopen('http://localhost:8000/health')"]
       interval: 60s

services/image-render/Dockerfile

@@ -0,0 +1,16 @@
+FROM python:3.12-slim-bookworm
+ENV PYTHONUNBUFFERED=1
+
+WORKDIR /app
+
+RUN apt-get update && apt-get install -y --no-install-recommends \
+    ca-certificates \
+ && rm -rf /var/lib/apt/lists/*
+
+COPY requirements.txt .
+RUN pip install --no-cache-dir --timeout 600 --retries 5 -r requirements.txt
+
+COPY . .
+
+EXPOSE 8000
+CMD ["python", "-m", "uvicorn", "main:app", "--host", "0.0.0.0", "--port", "8000", "--workers", "1"]

services/image-render/env.example

@@ -0,0 +1,18 @@
+# Redis (NAS)
+REDIS_URL=redis://192.168.45.54:6379
+
+# NAS image-lab webhook
+NAS_BASE_URL=http://192.168.45.54:18802
+INTERNAL_API_KEY=replace-me
+
+# API provider keys (worker reports failed if missing)
+OPENAI_API_KEY=
+GEMINI_API_KEY=
+# Seedance key not used by image-render
+
+# FLUX local
+COMFYUI_URL=http://host.docker.internal:8188
+FLUX_BLOCK_TRADING_HOURS=1
+
+# NAS SMB mount target (image-render writes to this, NAS reads via /media/image/)
+IMAGE_MEDIA_ROOT=/mnt/nas/webpage/data/image

services/image-render/main.py

@@ -0,0 +1,36 @@
+"""image-render FastAPI entry — health + lifespan (worker loop spawn)."""
+from __future__ import annotations
+
+import asyncio
+import logging
+from contextlib import asynccontextmanager
+
+from fastapi import FastAPI
+
+import worker
+
+logging.basicConfig(level=logging.INFO, format="%(asctime)s %(name)s %(levelname)s %(message)s")
+logger = logging.getLogger(__name__)
+
+
+@asynccontextmanager
+async def lifespan(app: FastAPI):
+    worker_task = asyncio.create_task(worker.worker_loop())
+    logger.info("image-render lifespan 시작")
+    try:
+        yield
+    finally:
+        worker_task.cancel()
+        try:
+            await worker_task
+        except asyncio.CancelledError:
+            pass
+        logger.info("image-render lifespan 종료")
+
+
+app = FastAPI(lifespan=lifespan)
+
+
+@app.get("/health")
+def health():
+    return {"ok": True, "service": "image-render"}

services/image-render/nas_client.py

@@ -0,0 +1,54 @@
+"""NAS webhook 어댑터 — Windows worker → NAS image-lab HTTP 위임.
+
+video-render nas_client 복제 (call-time os.getenv으로 테스트 격리).
+"""
+from __future__ import annotations
+
+import logging
+import os
+from typing import Any, Dict, Optional
+
+import httpx
+
+logger = logging.getLogger(__name__)
+
+_TIMEOUT = 10.0
+
+
+def _post(payload: Dict[str, Any]) -> None:
+    nas_base_url = os.getenv("NAS_BASE_URL", "http://192.168.45.54:18802")
+    internal_api_key = os.getenv("INTERNAL_API_KEY", "")
+    url = f"{nas_base_url}/api/internal/image/update"
+    try:
+        r = httpx.post(
+            url,
+            headers={"X-Internal-Key": internal_api_key},
+            json=payload,
+            timeout=_TIMEOUT,
+        )
+        if r.status_code != 200:
+            logger.error("webhook %s returned %d: %s",
+                         payload.get("task_id"), r.status_code, r.text[:200])
+    except Exception:
+        logger.exception("webhook %s 호출 실패", payload.get("task_id"))
+
+
+def webhook_update_task(
+    task_id: str,
+    status: str,
+    progress: int,
+    message: str = "",
+    image_url: Optional[str] = None,
+    error: Optional[str] = None,
+) -> None:
+    payload: Dict[str, Any] = {
+        "task_id": task_id,
+        "status": status,
+        "progress": progress,
+        "message": message,
+    }
+    if image_url is not None:
+        payload["image_url"] = image_url
+    if error is not None:
+        payload["error"] = error
+    _post(payload)

services/image-render/providers/_media.py

@@ -0,0 +1,18 @@
+"""b64 이미지 → NAS SMB 경로 저장 → /media/image URL 반환."""
+from __future__ import annotations
+
+import base64
+import os
+import uuid
+
+IMAGE_MEDIA_ROOT = os.getenv("IMAGE_MEDIA_ROOT", "/mnt/nas/webpage/data/image")
+IMAGE_MEDIA_URL_PREFIX = os.getenv("IMAGE_MEDIA_URL_PREFIX", "/media/image")
+
+
+def save_b64_png(task_id: str, b64_data: str) -> str:
+    os.makedirs(IMAGE_MEDIA_ROOT, exist_ok=True)
+    fname = f"{task_id}-{uuid.uuid4().hex[:8]}.png"
+    path = os.path.join(IMAGE_MEDIA_ROOT, fname)
+    with open(path, "wb") as f:
+        f.write(base64.b64decode(b64_data))
+    return f"{IMAGE_MEDIA_URL_PREFIX}/{fname}"

services/image-render/providers/flux.py

@@ -0,0 +1,79 @@
+"""FLUX 로컬 — ComfyUI HTTP API.
+
+POST {COMFYUI_URL}/prompt  (workflow JSON) → prompt_id
+GET  {COMFYUI_URL}/history/{prompt_id} → outputs → image filename
+GET  {COMFYUI_URL}/view?filename=... → PNG bytes → b64
+
+워크플로우 JSON은 `flux_workflow.json` (ComfyUI UI에서 "Save (API Format)"로 export, CLIPTextEncode 노드 text를 "%PROMPT%"로 수동 치환). 박재오 산출물.
+"""
+from __future__ import annotations
+
+import base64, json, logging, os, time
+from datetime import datetime, timezone, timedelta
+import requests
+
+from nas_client import webhook_update_task
+from providers._media import save_b64_png
+
+logger = logging.getLogger(__name__)
+COMFYUI_URL = os.getenv("COMFYUI_URL", "http://127.0.0.1:8188")
+WORKFLOW_PATH = os.path.join(os.path.dirname(__file__), "flux_workflow.json")
+POLL_INTERVAL = 2
+POLL_MAX = 120
+
+
+def _is_trading_hours() -> bool:
+    kst = timezone(timedelta(hours=9))
+    now = datetime.now(kst)
+    if now.weekday() >= 5:
+        return False
+    return (now.hour, now.minute) >= (9, 0) and (now.hour, now.minute) <= (15, 30)
+
+
+def _load_workflow(prompt: str, size: str) -> dict:
+    with open(WORKFLOW_PATH, encoding="utf-8") as f:
+        wf = json.load(f)
+    # CLIPTextEncode 노드의 text를 prompt로 치환 (workflow에 "%PROMPT%" placeholder 사용)
+    raw = json.dumps(wf).replace("%PROMPT%", prompt.replace('"', "'"))
+    return json.loads(raw)
+
+
+def _submit_prompt(workflow: dict) -> str:
+    r = requests.post(f"{COMFYUI_URL}/prompt", json={"prompt": workflow}, timeout=30)
+    r.raise_for_status()
+    return r.json()["prompt_id"]
+
+
+def _poll_image_b64(prompt_id: str):
+    for _ in range(POLL_MAX):
+        h = requests.get(f"{COMFYUI_URL}/history/{prompt_id}", timeout=10)
+        data = h.json().get(prompt_id)
+        if data and data.get("outputs"):
+            for node_out in data["outputs"].values():
+                for img in node_out.get("images", []):
+                    view = requests.get(f"{COMFYUI_URL}/view",
+                                        params={"filename": img["filename"], "subfolder": img.get("subfolder", ""), "type": img.get("type", "output")},
+                                        timeout=30)
+                    view.raise_for_status()
+                    return base64.b64encode(view.content).decode()
+        time.sleep(POLL_INTERVAL)
+    return None
+
+
+def run_flux_generation(task_id: str, params: dict) -> None:
+    try:
+        if os.getenv("FLUX_BLOCK_TRADING_HOURS") == "1" and _is_trading_hours():
+            webhook_update_task(task_id, "failed", 0, "", error="장중 GPU 보호 — FLUX 거부 (API provider 사용 권장)")
+            return
+        webhook_update_task(task_id, "processing", 10, "FLUX (ComfyUI) 생성 중...")
+        wf = _load_workflow(params["prompt"], params.get("size") or "1024x1024")
+        pid = _submit_prompt(wf)
+        b64 = _poll_image_b64(pid)
+        if not b64:
+            webhook_update_task(task_id, "failed", 0, "", error="ComfyUI 타임아웃 또는 출력 없음")
+            return
+        url = save_b64_png(task_id, b64)
+        webhook_update_task(task_id, "succeeded", 100, "완료", image_url=url)
+    except Exception as e:
+        logger.exception("flux task=%s 실패", task_id)
+        webhook_update_task(task_id, "failed", 0, "", error=str(e))

services/image-render/providers/gpt_image.py

@@ -0,0 +1,47 @@
+"""GPT Image 2.0 — OpenAI Images API.
+
+POST https://api.openai.com/v1/images/generations
+body {model:"gpt-image-1", prompt, size, n:1} → data[0].b64_json
+"""
+from __future__ import annotations
+
+import logging
+import os
+
+import requests
+
+from nas_client import webhook_update_task
+from providers._media import save_b64_png
+
+logger = logging.getLogger(__name__)
+OPENAI_URL = "https://api.openai.com/v1/images/generations"
+DEFAULT_MODEL = "gpt-image-1"
+
+
+def run_gpt_image_generation(task_id: str, params: dict) -> None:
+    try:
+        if not os.getenv("OPENAI_API_KEY"):
+            webhook_update_task(task_id, "failed", 0, "", error="OPENAI_API_KEY 미설정 (Windows .env)")
+            return
+        webhook_update_task(task_id, "processing", 10, "GPT Image 호출 중...")
+        body = {
+            "model": params.get("model") or DEFAULT_MODEL,
+            "prompt": params["prompt"],
+            "size": params.get("size") or "1024x1024",
+            "n": 1,
+        }
+        resp = requests.post(
+            OPENAI_URL,
+            headers={"Authorization": f"Bearer {os.getenv('OPENAI_API_KEY')}", "Content-Type": "application/json"},
+            json=body,
+            timeout=120,
+        )
+        if resp.status_code != 200:
+            webhook_update_task(task_id, "failed", 0, "", error=f"OpenAI {resp.status_code}: {resp.text[:200]}")
+            return
+        b64 = resp.json()["data"][0]["b64_json"]
+        url = save_b64_png(task_id, b64)
+        webhook_update_task(task_id, "succeeded", 100, "완료", image_url=url)
+    except Exception as e:
+        logger.exception("gpt_image task=%s 실패", task_id)
+        webhook_update_task(task_id, "failed", 0, "", error=str(e))

services/image-render/providers/nano_banana.py

@@ -0,0 +1,52 @@
+"""Nano Banana — Gemini 2.5 Flash Image (generativelanguage API).
+
+POST /v1beta/models/{MODEL}:generateContent
+→ candidates[0].content.parts[*].inlineData.data (b64 png)
+"""
+from __future__ import annotations
+
+import logging, os
+import requests
+
+from nas_client import webhook_update_task
+from providers._media import save_b64_png
+
+logger = logging.getLogger(__name__)
+GEMINI_BASE = "https://generativelanguage.googleapis.com/v1beta"
+DEFAULT_MODEL = "gemini-2.5-flash-image"
+
+
+def _extract_b64(data: dict):
+    for cand in data.get("candidates", []):
+        for part in cand.get("content", {}).get("parts", []):
+            inline = part.get("inlineData") or part.get("inline_data")
+            if inline and inline.get("data"):
+                return inline["data"]
+    return None
+
+
+def run_nano_banana_generation(task_id: str, params: dict) -> None:
+    try:
+        if not os.getenv("GEMINI_API_KEY"):
+            webhook_update_task(task_id, "failed", 0, "", error="GEMINI_API_KEY 미설정 (Windows .env)")
+            return
+        webhook_update_task(task_id, "processing", 10, "Nano Banana (Gemini) 호출 중...")
+        model_id = params.get("model") or DEFAULT_MODEL
+        body = {"contents": [{"parts": [{"text": params["prompt"]}]}]}
+        resp = requests.post(
+            f"{GEMINI_BASE}/models/{model_id}:generateContent",
+            headers={"x-goog-api-key": os.getenv("GEMINI_API_KEY"), "Content-Type": "application/json"},
+            json=body, timeout=120,
+        )
+        if resp.status_code != 200:
+            webhook_update_task(task_id, "failed", 0, "", error=f"Gemini {resp.status_code}: {resp.text[:200]}")
+            return
+        b64 = _extract_b64(resp.json())
+        if not b64:
+            webhook_update_task(task_id, "failed", 0, "", error="Gemini 응답에 이미지 없음")
+            return
+        url = save_b64_png(task_id, b64)
+        webhook_update_task(task_id, "succeeded", 100, "완료", image_url=url)
+    except Exception as e:
+        logger.exception("nano_banana task=%s 실패", task_id)
+        webhook_update_task(task_id, "failed", 0, "", error=str(e))

services/image-render/requirements.txt

@@ -0,0 +1,9 @@
+fastapi==0.115.6
+uvicorn[standard]==0.34.0
+requests==2.32.3
+redis>=5.0
+httpx>=0.27
+openai>=1.50.0
+pytest>=8.0
+pytest-asyncio>=0.24
+respx>=0.21

services/image-render/tests/test_flux.py

@@ -0,0 +1,21 @@
+import providers.flux as fx
+
+def test_blocked_during_trading_hours(monkeypatch):
+    monkeypatch.setenv("FLUX_BLOCK_TRADING_HOURS", "1")
+    monkeypatch.setattr(fx, "_is_trading_hours", lambda: True)
+    calls = []
+    monkeypatch.setattr(fx, "webhook_update_task", lambda *a, **k: calls.append((a, k)))
+    fx.run_flux_generation("t1", {"prompt": "a cat"})
+    assert calls[-1][0][1] == "failed"
+    assert "장중" in calls[-1][1]["error"]
+
+def test_success_polls_history_and_saves(monkeypatch):
+    monkeypatch.setattr(fx, "_is_trading_hours", lambda: False)
+    calls = []
+    monkeypatch.setattr(fx, "webhook_update_task", lambda *a, **k: calls.append((a, k)))
+    monkeypatch.setattr(fx, "_load_workflow", lambda prompt, size: {"3": {}})
+    monkeypatch.setattr(fx, "_submit_prompt", lambda wf: "pid-1")
+    monkeypatch.setattr(fx, "_poll_image_b64", lambda pid: "ZmFrZQ==")
+    monkeypatch.setattr(fx, "save_b64_png", lambda tid, b64: "/media/image/t1.png")
+    fx.run_flux_generation("t1", {"prompt": "a cat"})
+    assert [c for c in calls if c[0][1] == "succeeded"]

services/image-render/tests/test_gpt_image.py

@@ -0,0 +1,32 @@
+import providers.gpt_image as gi
+
+
+def test_missing_key_reports_failed(monkeypatch):
+    monkeypatch.delenv("OPENAI_API_KEY", raising=False)
+    calls = []
+    monkeypatch.setattr(gi, "webhook_update_task", lambda *a, **k: calls.append((a, k)))
+    gi.run_gpt_image_generation("t1", {"prompt": "a cat"})
+    # 마지막 호출이 failed
+    assert calls[-1][0][1] == "failed"
+
+
+def test_success_saves_and_reports_url(monkeypatch):
+    monkeypatch.setenv("OPENAI_API_KEY", "sk-test")
+    calls = []
+    monkeypatch.setattr(gi, "webhook_update_task", lambda *a, **k: calls.append((a, k)))
+    monkeypatch.setattr(gi, "save_b64_png", lambda tid, b64: "/media/image/t1.png")
+
+    class FakeResp:
+        status_code = 200
+
+        def json(self):
+            return {"data": [{"b64_json": "ZmFrZQ=="}]}
+
+        def raise_for_status(self):
+            pass
+
+    monkeypatch.setattr(gi.requests, "post", lambda *a, **k: FakeResp())
+
+    gi.run_gpt_image_generation("t1", {"prompt": "a cat"})
+    succeeded = [c for c in calls if c[0][1] == "succeeded"]
+    assert succeeded and succeeded[-1][1]["image_url"] == "/media/image/t1.png"

services/image-render/tests/test_nano_banana.py

@@ -0,0 +1,25 @@
+import providers.nano_banana as nb
+
+def test_missing_key_reports_failed(monkeypatch):
+    monkeypatch.delenv("GEMINI_API_KEY", raising=False)
+    calls = []
+    monkeypatch.setattr(nb, "webhook_update_task", lambda *a, **k: calls.append((a, k)))
+    nb.run_nano_banana_generation("t1", {"prompt": "a cat"})
+    assert calls[-1][0][1] == "failed"
+
+def test_success_extracts_inline_data(monkeypatch):
+    monkeypatch.setenv("GEMINI_API_KEY", "g-test")
+    calls = []
+    monkeypatch.setattr(nb, "webhook_update_task", lambda *a, **k: calls.append((a, k)))
+    monkeypatch.setattr(nb, "save_b64_png", lambda tid, b64: "/media/image/t1.png")
+
+    class FakeResp:
+        status_code = 200
+        def json(self):
+            return {"candidates": [{"content": {"parts": [
+                {"inlineData": {"mimeType": "image/png", "data": "ZmFrZQ=="}}
+            ]}}]}
+    monkeypatch.setattr(nb.requests, "post", lambda *a, **k: FakeResp())
+
+    nb.run_nano_banana_generation("t1", {"prompt": "a cat"})
+    assert [c for c in calls if c[0][1] == "succeeded"]

services/image-render/tests/test_nas_client.py

@@ -0,0 +1,20 @@
+import nas_client
+
+
+def test_webhook_includes_image_url(monkeypatch):
+    captured = {}
+
+    def fake_post(payload):
+        captured.update(payload)
+
+    monkeypatch.setattr(nas_client, "_post", fake_post)
+    nas_client.webhook_update_task("t1", "succeeded", 100, "done", image_url="/media/image/t1.png")
+    assert captured["task_id"] == "t1"
+    assert captured["image_url"] == "/media/image/t1.png"
+
+
+def test_webhook_omits_none_fields(monkeypatch):
+    captured = {}
+    monkeypatch.setattr(nas_client, "_post", lambda p: captured.update(p))
+    nas_client.webhook_update_task("t2", "processing", 10, "working")
+    assert "image_url" not in captured and "error" not in captured

services/image-render/tests/test_worker.py

@@ -0,0 +1,15 @@
+import worker
+
+
+def test_dispatch_routes_to_provider(monkeypatch):
+    called = {}
+    monkeypatch.setattr(worker, "run_gpt_image_generation", lambda tid, p: called.setdefault("gpt", (tid, p)))
+    worker._dispatch({"job_type": "gpt_image_generation", "task_id": "t1", "params": {"prompt": "x"}})
+    assert called["gpt"][0] == "t1"
+
+
+def test_dispatch_unknown_job_type_reports_failed(monkeypatch):
+    calls = []
+    monkeypatch.setattr(worker, "webhook_update_task", lambda *a, **k: calls.append((a, k)))
+    worker._dispatch({"job_type": "midjourney_generation", "task_id": "t9", "params": {}})
+    assert calls[-1][0][1] == "failed"

services/image-render/worker.py

@@ -0,0 +1,84 @@
+"""Redis BLPOP worker — queue:image-render → job_type dispatch → NAS webhook.
+
+queue:paused 가 set이면 대기 (task-watcher가 박재오 활동 감지 시 set).
+video-render worker.py 패턴 — string-based dispatch + getattr (테스트 patch 호환).
+"""
+from __future__ import annotations
+
+import asyncio
+import json
+import logging
+import os
+import sys
+
+import redis.asyncio as aioredis
+
+from nas_client import webhook_update_task
+from providers.gpt_image import run_gpt_image_generation
+from providers.nano_banana import run_nano_banana_generation
+from providers.flux import run_flux_generation
+
+logger = logging.getLogger(__name__)
+
+REDIS_URL = os.getenv("REDIS_URL", "redis://192.168.45.54:6379")
+QUEUE_KEY = "queue:image-render"
+PAUSED_KEY = "queue:paused"
+
+# string names so `unittest.mock.patch` / `monkeypatch.setattr` on `worker.<name>`
+# is correctly intercepted by getattr(sys.modules[__name__], ...)
+_DISPATCH_TABLE = {
+    "gpt_image_generation":   "run_gpt_image_generation",
+    "nano_banana_generation": "run_nano_banana_generation",
+    "flux_generation":        "run_flux_generation",
+}
+
+
+def _dispatch(payload: dict) -> None:
+    """payload[job_type] → provider 함수 호출 (sync, worker_loop에서 asyncio.to_thread로 wrap)."""
+    job_type = payload.get("job_type", "")
+    task_id = payload.get("task_id", "")
+    params = payload.get("params", {})
+    fn_name = _DISPATCH_TABLE.get(job_type)
+    if fn_name is None:
+        logger.error("unknown job_type=%s task=%s", job_type, task_id)
+        webhook_update_task(task_id, "failed", 0, "", error=f"unknown job_type: {job_type}")
+        return
+    try:
+        fn = getattr(sys.modules[__name__], fn_name)
+    except AttributeError:
+        logger.error("dispatch table typo for job_type=%s name=%s task=%s", job_type, fn_name, task_id)
+        webhook_update_task(task_id, "failed", 0, "", error=f"internal dispatch error: {fn_name}")
+        return
+    fn(task_id, params)
+
+
+async def worker_loop():
+    redis = aioredis.from_url(REDIS_URL, decode_responses=False)
+    logger.info("image-render worker started (queue=%s)", QUEUE_KEY)
+    while True:
+        try:
+            paused = await redis.get(PAUSED_KEY)
+            if paused == b"1":
+                await asyncio.sleep(10)
+                continue
+            item = await redis.blpop(QUEUE_KEY, timeout=5)
+            if item is None:
+                continue
+            _, raw = item
+            try:
+                payload = json.loads(raw)
+            except json.JSONDecodeError:
+                logger.error("invalid queue payload: %r", raw[:200])
+                continue
+            await asyncio.to_thread(_dispatch, payload)
+        except asyncio.CancelledError:
+            logger.info("worker_loop cancelled")
+            raise
+        except Exception:
+            logger.exception("worker_loop iteration 실패, 5초 후 재시도")
+            await asyncio.sleep(5)
+
+
+if __name__ == "__main__":
+    logging.basicConfig(level=logging.INFO)
+    asyncio.run(worker_loop())

services/task-watcher/.env.example

@@ -0,0 +1,11 @@
+# Plan-B-Infra — task-watcher
+
+# NAS Redis
+REDIS_URL=redis://192.168.45.54:6379
+
+# NAS stock holidays endpoint
+STOCK_BASE_URL=http://192.168.45.54:18500
+
+# 트레이딩 윈도우 (KST, HH:MM) — 이 시간대에만 queue:paused
+TRADING_START=07:00
+TRADING_END=16:30

services/task-watcher/Dockerfile

@@ -0,0 +1,16 @@
+FROM python:3.12-slim-bookworm
+ENV PYTHONUNBUFFERED=1
+
+WORKDIR /app
+
+RUN apt-get update && apt-get install -y --no-install-recommends \
+    ca-certificates tzdata \
+ && rm -rf /var/lib/apt/lists/*
+
+COPY requirements.txt .
+RUN pip install --no-cache-dir --timeout 600 --retries 5 -r requirements.txt
+
+COPY . .
+
+EXPOSE 8000
+CMD ["python", "-m", "uvicorn", "main:app", "--host", "0.0.0.0", "--port", "8000", "--workers", "1"]

services/task-watcher/NSSM_SETUP.md

@@ -0,0 +1,83 @@
+# NSSM 자동 시작 설정 (SP-9)
+
+Windows AI 머신 부팅 시 ai_trade(트레이딩) + WSL2 Docker(render workers + task-watcher) 자동 시작.
+
+## 1. NSSM 다운로드
+
+https://nssm.cc/download → nssm-2.24.zip → `C:\nssm\nssm.exe` 배치 (또는 PATH 등록).
+
+## 2. ai_trade (Native Python, HIGH priority)
+
+⚠️ spec의 signal_v2는 ai_trade로 rename됨. 경로/포트 확인.
+
+```powershell
+# 관리자 PowerShell
+C:\nssm\nssm.exe install ai_trade "C:\Python312\python.exe" "-m uvicorn main:app --host 0.0.0.0 --port 8001"
+C:\nssm\nssm.exe set ai_trade AppDirectory "C:\Users\jaeoh\Desktop\workspace\web-ai\ai_trade"
+C:\nssm\nssm.exe set ai_trade Priority HIGH_PRIORITY_CLASS
+C:\nssm\nssm.exe set ai_trade Start SERVICE_AUTO_START
+C:\nssm\nssm.exe set ai_trade AppStdout "C:\Users\jaeoh\nssm-logs\ai_trade.log"
+C:\nssm\nssm.exe set ai_trade AppStderr "C:\Users\jaeoh\nssm-logs\ai_trade.log"
+```
+
+(ai_trade의 실제 진입점이 main:app + port 8001인지 확인. 다르면 조정.)
+
+## 3. WSL2 Docker (NORMAL priority — render workers + task-watcher)
+
+```powershell
+C:\nssm\nssm.exe install wsl_docker "C:\Windows\System32\wsl.exe" "-d Ubuntu-24.04 -- sh -c 'sudo service docker start && cd /workspace/web-ai/services && docker compose up -d'"
+C:\nssm\nssm.exe set wsl_docker Priority NORMAL_PRIORITY_CLASS
+C:\nssm\nssm.exe set wsl_docker Start SERVICE_AUTO_START
+C:\nssm\nssm.exe set wsl_docker AppStdout "C:\Users\jaeoh\nssm-logs\wsl_docker.log"
+```
+
+⚠️ 변경점: Ubuntu-22.04 → **Ubuntu-24.04**, web-ai-services → **web-ai/services**. WSL 경로는 박재오 WSL 마운트 기준 (`/workspace`가 web-ai에 매핑되어 있으면 그대로, 아니면 `/mnt/c/Users/jaeoh/Desktop/workspace/web-ai/services`).
+
+`sudo service docker start`가 비밀번호 요구하면 sudoers에 NOPASSWD 추가:
+```bash
+# WSL2 안
+echo "$USER ALL=(ALL) NOPASSWD: /usr/sbin/service docker start" | sudo tee /etc/sudoers.d/docker-start
+```
+
+## 4. 서비스 시작 + 확인
+
+```powershell
+C:\nssm\nssm.exe start ai_trade
+C:\nssm\nssm.exe start wsl_docker
+
+# 상태 확인
+C:\nssm\nssm.exe status ai_trade
+C:\nssm\nssm.exe status wsl_docker
+sc query ai_trade
+```
+
+## 5. 검증
+
+```powershell
+# ai_trade
+curl http://localhost:8001/health   # 또는 ai_trade의 실제 health endpoint
+
+# WSL2 docker 컨테이너 (재부팅 후 자동 시작 확인)
+wsl -d Ubuntu-24.04 -- docker ps
+# insta-render, music-render, video-render, task-watcher 4개 Up 확인
+```
+
+## 6. 재부팅 테스트
+
+Windows 재부팅 → 로그인 → 수동 조작 없이:
+- ai_trade 서비스 자동 시작 (HIGH priority)
+- WSL2 + Docker + 4 컨테이너 자동 시작 (NORMAL priority)
+- task-watcher가 trading window에 queue:paused 토글 시작
+
+## task-watcher 동작 확인
+
+```bash
+# WSL2
+docker logs task-watcher --tail 20
+# 기대: "task-watcher started" + mode 전환 로그 (trading/free)
+
+# Redis 큐 상태 (NAS 또는 LAN)
+docker exec redis redis-cli GET queue:paused
+# 트레이딩 시간대(평일 07:00-16:30): "1"
+# 그 외: (nil)
+```

services/task-watcher/main.py

@@ -0,0 +1,36 @@
+"""task-watcher FastAPI entry — health + lifespan (watcher loop spawn)."""
+from __future__ import annotations
+
+import asyncio
+import logging
+from contextlib import asynccontextmanager
+
+from fastapi import FastAPI
+
+import watcher
+
+logging.basicConfig(level=logging.INFO, format="%(asctime)s %(name)s %(levelname)s %(message)s")
+logger = logging.getLogger(__name__)
+
+
+@asynccontextmanager
+async def lifespan(app: FastAPI):
+    watcher_task = asyncio.create_task(watcher.watcher_loop())
+    logger.info("task-watcher lifespan 시작")
+    try:
+        yield
+    finally:
+        watcher_task.cancel()
+        try:
+            await watcher_task
+        except asyncio.CancelledError:
+            pass
+        logger.info("task-watcher lifespan 종료")
+
+
+app = FastAPI(lifespan=lifespan)
+
+
+@app.get("/health")
+def health():
+    return {"ok": True, "service": "task-watcher"}

services/task-watcher/mode.py

@@ -0,0 +1,57 @@
+"""시간대 + 휴장일 기반 모드 판정 (idle 감지 생략 — 박재오 결정 2026-05-22).
+
+trading: 비휴장 평일 07:00–16:30 (장중) → queue:paused SET
+free:    그 외 (장 전/후, 주말, 휴장) → queue:paused DEL
+"""
+from __future__ import annotations
+
+import datetime as dt
+import logging
+import os
+from typing import Set
+from zoneinfo import ZoneInfo
+
+import httpx
+
+logger = logging.getLogger(__name__)
+
+KST = ZoneInfo("Asia/Seoul")
+STOCK_BASE_URL = os.getenv("STOCK_BASE_URL", "http://192.168.45.54:18500")
+
+# 트레이딩 윈도우 (HH:MM, KST). .env로 조정 가능.
+TRADING_START = os.getenv("TRADING_START", "07:00")
+TRADING_END = os.getenv("TRADING_END", "16:30")
+
+
+def _parse_hhmm(s: str) -> dt.time:
+    hh, mm = s.split(":")
+    return dt.time(int(hh), int(mm))
+
+
+def current_mode(now: dt.datetime, holidays: Set[str]) -> str:
+    """now(KST aware) + holidays(ISO date set) → 'trading' | 'free'."""
+    # 주말 (토=5, 일=6)
+    if now.weekday() >= 5:
+        return "free"
+    # 휴장일
+    if now.date().isoformat() in holidays:
+        return "free"
+    # 트레이딩 윈도우 [start, end)
+    start = _parse_hhmm(TRADING_START)
+    end = _parse_hhmm(TRADING_END)
+    t = now.timetz().replace(tzinfo=None)
+    if start <= t < end:
+        return "trading"
+    return "free"
+
+
+def fetch_holidays() -> Set[str]:
+    """NAS stock /api/stock/holidays 조회. 실패 시 빈 set (안전 — free로 판정)."""
+    try:
+        r = httpx.get(f"{STOCK_BASE_URL}/api/stock/holidays", timeout=10.0)
+        if r.status_code == 200:
+            return set(r.json().get("holidays", []))
+        logger.warning("holidays fetch returned %d", r.status_code)
+    except Exception:
+        logger.exception("holidays fetch 실패")
+    return set()

services/task-watcher/requirements.txt

@@ -0,0 +1,5 @@
+fastapi==0.115.6
+uvicorn[standard]==0.34.0
+redis>=5.0
+httpx>=0.27
+pytest>=8.0

services/task-watcher/tests/test_mode.py

@@ -0,0 +1,44 @@
+"""current_mode — 시간대 + 휴장일 판정 (순수 함수)."""
+import datetime as dt
+from zoneinfo import ZoneInfo
+
+from mode import current_mode
+
+KST = ZoneInfo("Asia/Seoul")
+HOLIDAYS = {"2026-05-25"}  # 가상 휴장일 (월요일)
+
+
+def _kst(y, m, d, hh, mm):
+    return dt.datetime(y, m, d, hh, mm, tzinfo=KST)
+
+
+def test_weekday_trading_hours_is_trading():
+    # 2026-05-22 금요일 10:00 — 트레이딩 시간대
+    assert current_mode(_kst(2026, 5, 22, 10, 0), HOLIDAYS) == "trading"
+
+
+def test_weekday_before_open_is_free():
+    # 평일 06:00 — 장 전
+    assert current_mode(_kst(2026, 5, 22, 6, 0), HOLIDAYS) == "free"
+
+
+def test_weekday_after_close_is_free():
+    # 평일 17:00 — 장 마감 후
+    assert current_mode(_kst(2026, 5, 22, 17, 0), HOLIDAYS) == "free"
+
+
+def test_weekend_is_free():
+    # 2026-05-23 토요일 10:00
+    assert current_mode(_kst(2026, 5, 23, 10, 0), HOLIDAYS) == "free"
+
+
+def test_holiday_weekday_is_free():
+    # 2026-05-25 월요일이지만 휴장일 → 트레이딩 시간대라도 free
+    assert current_mode(_kst(2026, 5, 25, 10, 0), HOLIDAYS) == "free"
+
+
+def test_trading_boundary_inclusive_start_exclusive_end():
+    # 07:00 정각 = 트레이딩 시작, 16:30 정각 = 마감 (16:30은 free)
+    assert current_mode(_kst(2026, 5, 22, 7, 0), HOLIDAYS) == "trading"
+    assert current_mode(_kst(2026, 5, 22, 16, 29), HOLIDAYS) == "trading"
+    assert current_mode(_kst(2026, 5, 22, 16, 30), HOLIDAYS) == "free"

services/task-watcher/watcher.py

@@ -0,0 +1,59 @@
+"""30초마다 current_mode 판정 → queue:paused 토글.
+
+trading → SET queue:paused 1 EX 600 (10분 TTL — watcher 죽어도 자동 해제)
+free    → DEL queue:paused
+holidays는 1시간마다 refresh (매 loop fetch 부하 회피).
+"""
+from __future__ import annotations
+
+import asyncio
+import datetime as dt
+import logging
+import os
+from zoneinfo import ZoneInfo
+
+import redis.asyncio as aioredis
+
+from mode import current_mode, fetch_holidays, KST
+
+logger = logging.getLogger(__name__)
+
+REDIS_URL = os.getenv("REDIS_URL", "redis://192.168.45.54:6379")
+PAUSED_KEY = "queue:paused"
+LOOP_INTERVAL = 30          # 초
+HOLIDAYS_REFRESH = 3600     # 1시간
+PAUSED_TTL = 600            # 10분 (watcher 죽어도 자동 해제)
+
+
+async def watcher_loop():
+    redis = aioredis.from_url(REDIS_URL, decode_responses=False)
+    holidays = fetch_holidays()
+    last_holiday_refresh = dt.datetime.now(KST)
+    last_mode = None
+    logger.info("task-watcher started (trading window 토글)")
+
+    while True:
+        try:
+            now = dt.datetime.now(KST)
+            # holidays 주기적 refresh
+            if (now - last_holiday_refresh).total_seconds() >= HOLIDAYS_REFRESH:
+                holidays = fetch_holidays()
+                last_holiday_refresh = now
+
+            mode = current_mode(now, holidays)
+            if mode == "trading":
+                await redis.set(PAUSED_KEY, b"1", ex=PAUSED_TTL)
+            else:
+                await redis.delete(PAUSED_KEY)
+
+            if mode != last_mode:
+                logger.info("mode 전환: %s → %s (paused=%s)", last_mode, mode, mode == "trading")
+                last_mode = mode
+
+            await asyncio.sleep(LOOP_INTERVAL)
+        except asyncio.CancelledError:
+            logger.info("watcher_loop cancelled")
+            raise
+        except Exception:
+            logger.exception("watcher_loop iteration 실패, 30초 후 재시도")
+            await asyncio.sleep(LOOP_INTERVAL)

services/video-render/.env.example

@@ -10,14 +10,12 @@ INTERNAL_API_KEY=__copy_from_nas_dotenv__
 # Sora 2 (OpenAI)
 OPENAI_API_KEY=__paste_openai_key__
 
-# Veo 3.1 (Google Vertex AI)
-GOOGLE_PROJECT_ID=__paste_gcp_project_id__
-GOOGLE_LOCATION=us-central1
-GOOGLE_GCS_BUCKET=__paste_gcs_bucket_name__
-GOOGLE_APPLICATION_CREDENTIALS=/app/keys/gcp-sa.json
+# Veo (Google Gemini API — ai.google.dev. Vertex AI 경로 아님, GCS bucket 불필요)
+GEMINI_API_KEY=__paste_gemini_key__
 
-# Kling (PiAPI gateway)
-PIAPI_API_KEY=__paste_piapi_key__
+# Kling (Native KlingAI — JWT auth with Access Key + Secret Key)
+KLING_ACCESS_KEY=__paste_kling_access_key__
+KLING_SECRET_KEY=__paste_kling_secret_key__
 
 # Seedance 2.0 (BytePlus)
 SEEDANCE_API_KEY=__paste_seedance_key__

services/video-render/providers/kling.py

@@ -1,6 +1,7 @@
-"""Kling AI video generation — PiAPI gateway 경유.
+"""Kling AI video generation — Native KlingAI API (api.klingai.com).
 
-POST https://api.piapi.ai/api/v1/task → GET /api/v1/task/{id} 폴링 → data.output.video_url 다운로드.
+JWT auth: HS256, payload {iss: ACCESS_KEY, exp: now+1800, nbf: now-5}.
+POST /v1/videos/text2video → GET /v1/videos/text2video/{task_id} → task_result.videos[0].url 다운로드.
 """
 from __future__ import annotations
 
@@ -9,26 +10,41 @@ import os
 import time
 from typing import Optional
 
+import jwt as pyjwt
 import requests
 
 from nas_client import webhook_update_task
 
 logger = logging.getLogger(__name__)
 
-PIAPI_BASE_URL = "https://api.piapi.ai/api/v1"
+KLING_BASE_URL = "https://api.klingai.com"
 VIDEO_MEDIA_ROOT = os.getenv("VIDEO_MEDIA_ROOT", "/mnt/nas/webpage/data/video")
 VIDEO_MEDIA_URL_PREFIX = os.getenv("VIDEO_MEDIA_URL_PREFIX", "/media/video")
 
-POLL_INTERVAL = 10   # Kling은 30~180초
-POLL_MAX_ATTEMPTS = 60   # 최대 10분
+POLL_INTERVAL = 10
+POLL_MAX_ATTEMPTS = 60   # 최대 ~10분
 
-DEFAULT_VERSION = "2.6"
+DEFAULT_MODEL = "kling-v1-6"
+
+JWT_EXP_SECONDS = 1800   # 30분
+JWT_NBF_OFFSET = -5      # 5초 뒤로
+
+
+def _generate_jwt() -> Optional[str]:
+    access_key = os.getenv("KLING_ACCESS_KEY", "")
+    secret_key = os.getenv("KLING_SECRET_KEY", "")
+    if not access_key or not secret_key:
+        return None
+    now = int(time.time())
+    headers = {"alg": "HS256", "typ": "JWT"}
+    payload = {"iss": access_key, "exp": now + JWT_EXP_SECONDS, "nbf": now + JWT_NBF_OFFSET}
+    return pyjwt.encode(payload, secret_key, algorithm="HS256", headers=headers)
 
 
 def _headers() -> dict:
-    api_key = os.getenv("PIAPI_API_KEY", "")
+    token = _generate_jwt()
     return {
-        "x-api-key": api_key,
+        "Authorization": f"Bearer {token}" if token else "",
         "Content-Type": "application/json",
     }
 
@@ -36,80 +52,83 @@ def _headers() -> dict:
 def run_kling_generation(task_id: str, params: dict) -> None:
     """Kling으로 영상 생성 → mp4 → NAS SMB → webhook."""
     try:
-        if not os.getenv("PIAPI_API_KEY"):
-            webhook_update_task(task_id, "failed", 0, "", error="PIAPI_API_KEY 미설정")
+        if not os.getenv("KLING_ACCESS_KEY") or not os.getenv("KLING_SECRET_KEY"):
+            webhook_update_task(task_id, "failed", 0, "",
+                                error="KLING_ACCESS_KEY 또는 KLING_SECRET_KEY 미설정")
             return
 
         webhook_update_task(task_id, "processing", 5, "Kling API 호출 중...")
 
-        input_obj = {
-            "prompt": params["prompt"][:2500],
-            "duration": params.get("duration", 5),
-            "aspect_ratio": params.get("aspect_ratio", "16:9"),
-            "mode": params.get("mode", "std"),
-            "version": params.get("model") or DEFAULT_VERSION,
-        }
-        if params.get("negative_prompt"):
-            input_obj["negative_prompt"] = params["negative_prompt"][:2500]
-        if params.get("cfg_scale") is not None:
-            input_obj["cfg_scale"] = str(params["cfg_scale"])
-        if params.get("image_url"):
-            input_obj["image_url"] = params["image_url"]
+        # image_url 있으면 image2video, 없으면 text2video
+        is_image2video = bool(params.get("image_url"))
+        endpoint_path = "/v1/videos/image2video" if is_image2video else "/v1/videos/text2video"
 
         body = {
-            "model": "kling",
-            "task_type": "video_generation",
-            "input": input_obj,
-            "config": {"service_mode": "public"},
+            "model_name": params.get("model") or DEFAULT_MODEL,
+            "prompt": params["prompt"][:2500],
+            "duration": str(params.get("duration", 5)),
+            "aspect_ratio": params.get("aspect_ratio", "16:9"),
+            "mode": params.get("mode", "std"),
         }
+        if params.get("negative_prompt"):
+            body["negative_prompt"] = params["negative_prompt"][:2500]
+        if params.get("cfg_scale") is not None:
+            body["cfg_scale"] = float(params["cfg_scale"])
+        if is_image2video:
+            body["image"] = params["image_url"]
 
-        resp = requests.post(f"{PIAPI_BASE_URL}/task", headers=_headers(), json=body, timeout=30)
+        resp = requests.post(f"{KLING_BASE_URL}{endpoint_path}",
+                             headers=_headers(), json=body, timeout=30)
         if resp.status_code != 200:
             webhook_update_task(task_id, "failed", 0, "",
-                                error=f"Kling/PiAPI 오류: {resp.status_code} {resp.text[:300]}")
+                                error=f"Kling API 오류: {resp.status_code} {resp.text[:300]}")
             return
 
         body_json = resp.json()
-        if body_json.get("code") != 200:
+        if body_json.get("code") != 0:
             webhook_update_task(task_id, "failed", 0, "",
-                                error=f"Kling/PiAPI 거부: {body_json.get('message', '?')}")
+                                error=f"Kling API 거부: {body_json.get('message', '?')}")
             return
 
-        piapi_task_id = (body_json.get("data") or {}).get("task_id", "")
-        if not piapi_task_id:
-            webhook_update_task(task_id, "failed", 0, "", error="Kling/PiAPI 응답에 task_id 없음")
+        kling_task_id = (body_json.get("data") or {}).get("task_id", "")
+        if not kling_task_id:
+            webhook_update_task(task_id, "failed", 0, "", error="Kling 응답에 task_id 없음")
             return
 
         webhook_update_task(task_id, "processing", 15, "Kling 작업 등록됨")
 
-        # 폴링 — GET /task/{id}
+        # 폴링 — GET /v1/videos/{text2video|image2video}/{task_id}
         video_url = None
         for attempt in range(POLL_MAX_ATTEMPTS):
             time.sleep(POLL_INTERVAL)
-            fetch = requests.get(f"{PIAPI_BASE_URL}/task/{piapi_task_id}",
+            fetch = requests.get(f"{KLING_BASE_URL}{endpoint_path}/{kling_task_id}",
                                  headers=_headers(), timeout=30)
             if fetch.status_code != 200:
                 continue
             fd = fetch.json()
-            data = fd.get("data", {})
-            status = data.get("status", "")
+            if fd.get("code") != 0:
+                continue
+            data = fd.get("data") or {}
+            status = data.get("task_status", "")
             scaled = min(15 + int((attempt / POLL_MAX_ATTEMPTS) * 65), 79)
             webhook_update_task(task_id, "processing", scaled, f"Kling 생성 중... ({status})")
 
-            if status == "Completed":
-                video_url = (data.get("output") or {}).get("video_url", "")
+            if status == "succeed":
+                videos = ((data.get("task_result") or {}).get("videos") or [])
+                if videos:
+                    video_url = videos[0].get("url", "")
                 break
-            elif status in ("Failed", "failed"):
-                err = (data.get("error") or {}).get("message", "Kling 작업 실패")
+            elif status == "failed":
+                err = data.get("task_status_msg") or "Kling 작업 실패"
                 webhook_update_task(task_id, "failed", 0, "", error=err)
                 return
-            # Pending/Processing/Staged → 계속 폴링
+            # submitted/processing → 계속 폴링
         else:
             webhook_update_task(task_id, "failed", 0, "", error="Kling 폴링 timeout (10분)")
             return
 
         if not video_url:
-            webhook_update_task(task_id, "failed", 0, "", error="Kling 완료했으나 video_url 없음")
+            webhook_update_task(task_id, "failed", 0, "", error="Kling 완료했으나 video url 없음")
             return
 
         webhook_update_task(task_id, "processing", 85, "Kling 결과 다운로드 중...")
@@ -117,6 +136,7 @@ def run_kling_generation(task_id: str, params: dict) -> None:
         os.makedirs(VIDEO_MEDIA_ROOT, exist_ok=True)
         file_path = os.path.join(VIDEO_MEDIA_ROOT, filename)
 
+        # Kling 결과 url은 일반적으로 인증 불필요 (signed URL)
         dl = requests.get(video_url, stream=True, timeout=300)
         dl.raise_for_status()
         with open(file_path, "wb") as f:
@@ -127,7 +147,7 @@ def run_kling_generation(task_id: str, params: dict) -> None:
         webhook_update_task(task_id, "succeeded", 100, "Kling 생성 완료", video_url=local_url)
 
     except requests.Timeout:
-        webhook_update_task(task_id, "failed", 0, "", error="Kling/PiAPI 타임아웃")
+        webhook_update_task(task_id, "failed", 0, "", error="Kling API 타임아웃")
     except Exception as e:
         logger.exception("Kling generation error task=%s", task_id)
         webhook_update_task(task_id, "failed", 0, "", error=str(e))

services/video-render/providers/veo.py

@@ -1,13 +1,13 @@
-"""Veo 3.1 video generation — Google Vertex AI.
+"""Veo 3.1 video generation — Gemini API (ai.google.dev).
 
-POST .../models/{MODEL}:predictLongRunning → POST :fetchPredictOperation 폴링 →
-결과 gs://bucket/path/sample_0.mp4 → google-cloud-storage로 다운로드 → NAS SMB.
+POST https://generativelanguage.googleapis.com/v1beta/models/{MODEL}:predictLongRunning
+GET https://generativelanguage.googleapis.com/v1beta/{operation_name}
+→ done=true 시 response.generateVideoResponse.generatedSamples[0].video.uri 다운로드
 """
 from __future__ import annotations
 
 import logging
 import os
-import subprocess
 import time
 from typing import Optional
 
@@ -17,100 +17,59 @@ from nas_client import webhook_update_task
 
 logger = logging.getLogger(__name__)
 
+GEMINI_BASE_URL = "https://generativelanguage.googleapis.com/v1beta"
 VIDEO_MEDIA_ROOT = os.getenv("VIDEO_MEDIA_ROOT", "/mnt/nas/webpage/data/video")
 VIDEO_MEDIA_URL_PREFIX = os.getenv("VIDEO_MEDIA_URL_PREFIX", "/media/video")
 
-POLL_INTERVAL = 12   # Veo는 30~120초 소요
-POLL_MAX_ATTEMPTS = 50   # 최대 ~10분
+POLL_INTERVAL = 10   # Veo는 30~120초 소요
+POLL_MAX_ATTEMPTS = 60   # 최대 ~10분
 
-DEFAULT_MODEL = "veo-3.1-fast-generate-001"
+DEFAULT_MODEL = "veo-3.1-fast-generate-preview"
 
 
-def _gcloud_access_token() -> Optional[str]:
-    """GOOGLE_APPLICATION_CREDENTIALS service account JSON으로 access token 발행.
-
-    google-auth가 컨테이너 안에서 자동 인증 — Bearer 토큰을 GCS SDK가 직접 사용.
-    REST API 호출용으로는 명시적 token이 필요 → google.auth로 발행.
-    """
-    try:
-        from google.auth import default as google_default_auth
-        from google.auth.transport.requests import Request as GoogleAuthRequest
-
-        credentials, _ = google_default_auth(
-            scopes=["https://www.googleapis.com/auth/cloud-platform"],
-        )
-        credentials.refresh(GoogleAuthRequest())
-        return credentials.token
-    except Exception:
-        logger.exception("Google credentials refresh 실패")
-        return None
-
-
-def _download_gcs(gcs_uri: str, local_path: str) -> bool:
-    """gs://bucket/path/file.mp4 → local_path 다운로드. 성공 여부 반환."""
-    try:
-        from google.cloud import storage as gcs_storage
-        if not gcs_uri.startswith("gs://"):
-            return False
-        without_scheme = gcs_uri[len("gs://"):]
-        bucket_name, blob_path = without_scheme.split("/", 1)
-        client = gcs_storage.Client(project=os.getenv("GOOGLE_PROJECT_ID"))
-        bucket = client.bucket(bucket_name)
-        blob = bucket.blob(blob_path)
-        blob.download_to_filename(local_path)
-        return True
-    except Exception:
-        logger.exception("GCS 다운로드 실패: %s", gcs_uri)
-        return False
+def _headers() -> dict:
+    api_key = os.getenv("GEMINI_API_KEY", "")
+    return {
+        "x-goog-api-key": api_key,
+        "Content-Type": "application/json",
+    }
 
 
 def run_veo_generation(task_id: str, params: dict) -> None:
-    """Veo 3.1로 영상 생성 → GCS → NAS SMB → webhook."""
+    """Veo로 영상 생성 → mp4 → NAS SMB → webhook."""
     try:
-        project_id = os.getenv("GOOGLE_PROJECT_ID", "")
-        location = os.getenv("GOOGLE_LOCATION", "us-central1")
-        gcs_bucket = os.getenv("GOOGLE_GCS_BUCKET", "")
-
-        if not project_id or not gcs_bucket:
-            webhook_update_task(task_id, "failed", 0, "",
-                                error="GOOGLE_PROJECT_ID 또는 GOOGLE_GCS_BUCKET 미설정")
+        if not os.getenv("GEMINI_API_KEY"):
+            webhook_update_task(task_id, "failed", 0, "", error="GEMINI_API_KEY 미설정 (Windows .env)")
             return
 
-        token = _gcloud_access_token()
-        if not token:
-            webhook_update_task(task_id, "failed", 0, "",
-                                error="Google access token 발행 실패 (서비스 계정 JSON 확인)")
-            return
-
-        webhook_update_task(task_id, "processing", 5, "Veo API 호출 중...")
+        webhook_update_task(task_id, "processing", 5, "Veo (Gemini API) 호출 중...")
 
         model_id = params.get("model") or DEFAULT_MODEL
-        endpoint_base = (
-            f"https://{location}-aiplatform.googleapis.com/v1/projects/{project_id}"
-            f"/locations/{location}/publishers/google/models/{model_id}"
-        )
-        headers = {
-            "Authorization": f"Bearer {token}",
-            "Content-Type": "application/json",
-        }
         body = {
             "instances": [{"prompt": params["prompt"]}],
             "parameters": {
-                "storageUri": f"gs://{gcs_bucket}/veo/{task_id}/",
-                "sampleCount": 1,
                 "aspectRatio": params.get("aspect_ratio") or "16:9",
             },
         }
+        # numberOfVideos는 일부 모델(veo-3.0-fast 등) 미지원 — 호출자 명시 시에만 추가
+        if params.get("number_of_videos"):
+            body["parameters"]["numberOfVideos"] = int(params["number_of_videos"])
         if params.get("duration"):
-            body["parameters"]["duration"] = params["duration"]
+            body["parameters"]["durationSeconds"] = int(params["duration"])
+        if params.get("resolution"):
+            body["parameters"]["resolution"] = params["resolution"]
         if params.get("negative_prompt"):
             body["parameters"]["negativePrompt"] = params["negative_prompt"]
+        if params.get("person_generation"):
+            body["parameters"]["personGeneration"] = params["person_generation"]
 
-        resp = requests.post(f"{endpoint_base}:predictLongRunning",
-                             headers=headers, json=body, timeout=30)
+        resp = requests.post(
+            f"{GEMINI_BASE_URL}/models/{model_id}:predictLongRunning",
+            headers=_headers(), json=body, timeout=30,
+        )
         if resp.status_code != 200:
             webhook_update_task(task_id, "failed", 0, "",
-                                error=f"Veo API 오류: {resp.status_code} {resp.text[:300]}")
+                                error=f"Veo Gemini API 오류: {resp.status_code} {resp.text[:300]}")
             return
 
         op_name = resp.json().get("name", "")
@@ -118,16 +77,15 @@ def run_veo_generation(task_id: str, params: dict) -> None:
             webhook_update_task(task_id, "failed", 0, "", error="Veo 응답에 operation name 없음")
             return
 
-        webhook_update_task(task_id, "processing", 15, f"Veo 작업 시작됨")
+        webhook_update_task(task_id, "processing", 15, "Veo 작업 시작됨")
 
-        # 폴링 — fetchPredictOperation
-        gcs_uri = None
+        # 폴링 — GET /v1beta/{operation_name}
+        video_uri = None
         for attempt in range(POLL_MAX_ATTEMPTS):
             time.sleep(POLL_INTERVAL)
-            fetch = requests.post(
-                f"{endpoint_base}:fetchPredictOperation",
-                headers=headers,
-                json={"operationName": op_name},
+            fetch = requests.get(
+                f"{GEMINI_BASE_URL}/{op_name}",
+                headers=_headers(),
                 timeout=30,
             )
             if fetch.status_code != 200:
@@ -142,29 +100,34 @@ def run_veo_generation(task_id: str, params: dict) -> None:
                     webhook_update_task(task_id, "failed", 0, "",
                                         error=f"Veo 작업 실패: {fd['error'].get('message','?')}")
                     return
-                videos = (fd.get("response") or {}).get("videos") or []
-                if not videos:
-                    webhook_update_task(task_id, "failed", 0, "", error="Veo 완료했으나 videos 비어 있음")
+                # response.generateVideoResponse.generatedSamples[0].video.uri
+                response = fd.get("response") or {}
+                gen = response.get("generateVideoResponse") or {}
+                samples = gen.get("generatedSamples") or []
+                if not samples:
+                    webhook_update_task(task_id, "failed", 0, "", error="Veo 완료했으나 generatedSamples 비어 있음")
                     return
-                gcs_uri = videos[0].get("gcsUri", "")
+                video_uri = (samples[0].get("video") or {}).get("uri", "")
                 break
         else:
             webhook_update_task(task_id, "failed", 0, "", error="Veo 폴링 timeout (10분)")
             return
 
-        if not gcs_uri:
-            webhook_update_task(task_id, "failed", 0, "", error="Veo 응답에 gcsUri 없음")
+        if not video_uri:
+            webhook_update_task(task_id, "failed", 0, "", error="Veo 응답에 video.uri 없음")
             return
 
-        webhook_update_task(task_id, "processing", 85, "GCS에서 mp4 다운로드 중...")
+        webhook_update_task(task_id, "processing", 85, "Veo 결과 다운로드 중...")
         filename = f"{task_id}.mp4"
         os.makedirs(VIDEO_MEDIA_ROOT, exist_ok=True)
         file_path = os.path.join(VIDEO_MEDIA_ROOT, filename)
 
-        ok = _download_gcs(gcs_uri, file_path)
-        if not ok:
-            webhook_update_task(task_id, "failed", 0, "", error=f"GCS 다운로드 실패: {gcs_uri}")
-            return
+        # 다운로드 — x-goog-api-key 헤더 그대로 사용 (Gemini API가 인증 처리)
+        dl = requests.get(video_uri, headers=_headers(), stream=True, timeout=300)
+        dl.raise_for_status()
+        with open(file_path, "wb") as f:
+            for chunk in dl.iter_content(chunk_size=8192):
+                f.write(chunk)
 
         local_url = f"{VIDEO_MEDIA_URL_PREFIX}/{filename}"
         webhook_update_task(task_id, "succeeded", 100, "Veo 생성 완료", video_url=local_url)

services/video-render/requirements.txt

@@ -4,7 +4,7 @@ requests==2.32.3
 redis>=5.0
 httpx>=0.27
 openai>=1.50.0
-google-cloud-storage>=2.18.0
+PyJWT>=2.8.0
 pytest>=8.0
 pytest-asyncio>=0.24
 respx>=0.21