feat(网关): 接口4 改由网关本机直接调豆包视觉模型，不再代理到 worker

- gateway/app.py: 接口4 handler 改为直接调用 face_features 模块
- face_features.py: API Key 读取支持 gateway/config.json
- gateway/config.example.json: 增加 ark_api_key 配置项

gateway/app.py

@@ -5,11 +5,17 @@
 """
 
 import asyncio
+import base64
+import json
 import logging
 import time
 from contextlib import asynccontextmanager
+from io import BytesIO
 from pathlib import Path
-from fastapi import FastAPI, Request
+from typing import Optional
+
+from fastapi import FastAPI, File, Form, Request, UploadFile
+from fastapi.responses import JSONResponse
 from fastapi.staticfiles import StaticFiles
 
 from gateway.config import load_config
@@ -217,9 +223,6 @@ _GROW_B_FORMS = {
     "marked_image_file": {"type": "file", "description": "划线图片文件"},
     "marked_image_url": {"type": "string", "description": "划线图片 URL"},
     "marked_image_base64": {"type": "string", "description": "划线图片 base64"},
-    "original_image_file": {"type": "file", "description": "原始用户照片文件"},
-    "original_image_url": {"type": "string", "description": "原始用户照片 URL"},
-    "original_image_base64": {"type": "string", "description": "原始用户照片 base64"},
 }
 
 
@@ -242,9 +245,67 @@ async def hair_grow_b(request: Request):
 
 
 @app.post("/api/v1/face/features", tags=["人脸分析"])
-async def face_features(request: Request):
-    """接口4：用户特征分析"""
-    return await _proxy(request, "/api/v1/face/features")
+async def face_features(
+    image_file: Optional[UploadFile] = File(default=None, description="上传图片文件（JPG/PNG，≤ 1 MB）"),
+    image_url: Optional[str] = Form(default=None, description="图片 URL"),
+    image_base64: Optional[str] = Form(default=None, description="图片 base64（需带前缀）"),
+):
+    """接口4：用户特征分析 — 本机直接调豆包视觉模型，不经过 worker。"""
+    import uuid as _uuid
+
+    # 三选一校验
+    provided = [x for x in (image_file, image_url, image_base64) if x]
+    if len(provided) != 1:
+        return JSONResponse(status_code=400, content={
+            "code": 1007, "message": "图片参数错误：必须且只能传 image_file / image_url / image_base64 其中一个",
+            "request_id": f"gw-{_uuid.uuid4().hex[:8]}", "data": None,
+        })
+
+    img_bytes = None
+    if image_file:
+        raw = await image_file.read()
+        if len(raw) > 1_000_000:
+            return JSONResponse(status_code=400, content={
+                "code": 1006, "message": "文件超出 1 MB 限制",
+                "request_id": f"gw-{_uuid.uuid4().hex[:8]}", "data": None,
+            })
+        img_bytes = raw
+    elif image_base64:
+        b64 = image_base64
+        if "," in b64:
+            b64 = b64.split(",", 1)[1]
+        try:
+            img_bytes = base64.b64decode(b64)
+        except Exception:
+            return JSONResponse(status_code=400, content={
+                "code": 1008, "message": "图片格式不支持（base64 解码失败）",
+                "request_id": f"gw-{_uuid.uuid4().hex[:8]}", "data": None,
+            })
+
+    from fastapi.concurrency import run_in_threadpool
+    from face_features import analyze_features, has_face
+
+    try:
+        feats = await run_in_threadpool(analyze_features, img_bytes, image_url)
+    except Exception as ex:
+        logger.exception("接口4 豆包调用失败")
+        return JSONResponse(status_code=503, content={
+            "code": 1007, "message": f"分析服务异常：{ex}",
+            "request_id": f"gw-{_uuid.uuid4().hex[:8]}", "data": None,
+        })
+
+    if not has_face(feats):
+        return JSONResponse(status_code=400, content={
+            "code": 1001, "message": "无法识别人像",
+            "request_id": f"gw-{_uuid.uuid4().hex[:8]}", "data": None,
+        })
+
+    return JSONResponse(status_code=200, content={
+        "code": 0,
+        "message": "success",
+        "request_id": f"gw-{_uuid.uuid4().hex[:8]}",
+        "data": {"features": json.dumps(feats, ensure_ascii=False)},
+    })
 
 
 @app.post("/api/v1/hairline/generate", tags=["人脸分析"])

gateway/config.example.json

@@ -13,6 +13,7 @@
     "unhealthy_threshold": 2,
     "healthy_threshold": 1
   },
+  "ark_api_key": "",
   "dispatch": {
     "per_worker_concurrency": 1,
     "queue_wait_seconds": 30,