feat(接口2): 支持动态切换Flux模型+分辨率 + 模型对比测试脚本

代码改动:
- comfyui.py: run() 新增 unet_name 参数，提交前自动改写模型节点
  (.gguf→UnetLoaderGGUF, .safetensors→UNETLoader)，并按模型自动同步
  文本编码器(4b→qwen_3_4b, 9b→qwen_3_8b)，避免切换时维度不匹配
- redraw.py: run_redraw() 透传 unet_name
- service.py: generate_grow_results_swap/generate_grow_results 支持
  redraw_max_side(分辨率参数化) 和 unet_name 透传
- app.py: 接口2 新增 flux_model/redraw_max_side 两个 Form 参数(男女路径都加)
- test_interface2.html: 新增 Flux模型/压图长边 下拉选择器
- add_hair.json/0716add-hair-api.json: 工作流默认模型改为 9b

测试脚本:
- benchmark_matrix.py: 4模型×3分辨率×3图×3次 矩阵测试
- benchmark_hairstyle.py: 3图×5发型×10组合 发型对比测试
- benchmark_report.py/benchmark_hairstyle_report.py: HTML报告生成

清理:
- .gitignore: 排除 benchmark_out/、报告HTML、gateway.log、*.bak.*
- 移除 gateway.log 的 git 跟踪

.gitignore

@@ -53,3 +53,17 @@ static/report_hairline_v2.zip
 # local_test 运行期日志 / pid（不入 git）
 local_test/hair_service.log
 local_test/hair_service.pid
+
+# benchmark 原始输出（含结果图+原图，体积大，不入 git）
+benchmark_out/
+
+# benchmark 部署的 HTML 报告（图片 base64 内嵌，体积大，不入 git）
+static/benchmark_report.html
+static/hairstyle_report.html
+static/hairstyle_thumbs/
+
+# 网关运行期日志（不入 git）
+gateway.log
+
+# 工作流备份文件（不入 git）
+*.json.bak.*

0716add-hair-api.json

@@ -2,7 +2,7 @@
   "16": {
     "class_type": "UNETLoader",
     "inputs": {
-      "unet_name": "flux-2-klein-4b-fp8.safetensors",
+      "unet_name": "flux2.0/flux-2-klein-9b-fp8.safetensors",
       "weight_dtype": "fp8_e4m3fn_fast"
     }
   },
@@ -15,7 +15,7 @@
   "61": {
     "class_type": "CLIPLoader",
     "inputs": {
-      "clip_name": "qwen_3_4b.safetensors",
+      "clip_name": "qwen_3_8b_fp8mixed.safetensors",
       "type": "flux2",
       "device": "cpu"
     }

add_hair.json

@@ -170,7 +170,7 @@
   },
   "16": {
     "inputs": {
-      "unet_name": "flux-2-klein-4b-fp8.safetensors",
+      "unet_name": "flux2.0/flux-2-klein-9b-fp8.safetensors",
       "weight_dtype": "fp8_e4m3fn_fast"
     },
     "class_type": "UNETLoader",
@@ -419,7 +419,7 @@
   },
   "61": {
     "inputs": {
-      "clip_name": "qwen_3_4b.safetensors",
+      "clip_name": "qwen_3_8b_fp8mixed.safetensors",
       "type": "flux2",
       "device": "cpu"
     },

app.py

@@ -146,7 +146,7 @@ _AUTH_EXEMPT = ("/health", "/docs", "/openapi.json", "/redoc", "/static",
 # ---------------------------------------------------------------------------
 # change_hair 代理路由（解决 CORS 问题）
 # ---------------------------------------------------------------------------
-_CHANGE_HAIR_BASE = "http://127.0.0.1:8801"
+_CHANGE_HAIR_BASE = os.getenv("CHANGE_HAIR_BASE", "http://127.0.0.1:8801")
 
 
 @app.post("/api/swapHair/v1", tags=["change_hair"])
@@ -758,6 +758,8 @@ async def hair_grow(
     beauty_enabled: bool = Form(default=False, description="是否开启美颜（本期不生效）"),
     use_mask: bool = Form(default=True, description="是否启用 inpaint 遮罩（测试对比用）。false 时用干净原图生成（空遮罩，不烧模板线）"),
     prompt: str = Form(default="填充遮罩区域的头发，皮肤加一点磨皮，再加一点美颜", description="ComfyUI 提示词，会替换工作流节点60的文本"),
+    flux_model: Optional[str] = Form(default=None, description="Flux 模型文件名（切换模型用）。None=工作流默认；如 flux-2-klein-9b-Q5_K_M.gguf / flux-2-klein-9b-Q4_K_M.gguf / flux2.0/flux-2-klein-9b-fp8.safetensors"),
+    redraw_max_side: Optional[int] = Form(default=None, description="重绘压图长边像素。None=默认896；0=不缩图（原图直送）；其他如 768/640/1024"),
 ):
     # 1. gender 必填校验（非法/缺失 → 1004）
     if gender not in ("male", "female"):
@@ -786,11 +788,13 @@ async def hair_grow(
         if gender == "female":
             from hairline.service import generate_grow_results_swap
             items = await run_in_threadpool(
-                generate_grow_results_swap, image, hair_styles, _V2_FINAL_DEFAULTS)
+                generate_grow_results_swap, image, hair_styles, _V2_FINAL_DEFAULTS,
+                redraw_max_side=redraw_max_side, unet_name=flux_model)
         else:
             from hairline.service import generate_grow_results
             items = await run_in_threadpool(
-                generate_grow_results, image, gender, use_mask, prompt, hair_styles)
+                generate_grow_results, image, gender, use_mask, prompt, hair_styles,
+                unet_name=flux_model)
         if items is None:
             return err(1001, "无法识别人像")
 

benchmark_hairstyle.py

@@ -0,0 +1,134 @@
+#!/usr/bin/env python3
+# -*- coding: utf-8 -*-
+"""发型对比矩阵测试：3图×5发型=15行，每行10张图(4b@896×1 + 9b三模型×三分辨率×9)。
+按模型分组跑（减少模型切换次数、降低OOM风险），结果重组为15行存JSON+生成报告。
+"""
+import base64
+import json
+import os
+import subprocess
+import time
+from collections import defaultdict
+from pathlib import Path
+
+import requests
+
+API = "http://127.0.0.1:8187/api/v1/hair/grow"
+TOKEN = "dev-shared-secret-2026"
+OUT = Path("/home/ubuntu/hair/benchmark_out/hairstyle")
+OUT.mkdir(parents=True, exist_ok=True)
+
+IMGS = [
+    ("asdf", "/home/ubuntu/hair/image/asdf.jpg"),
+    ("qwer", "/home/ubuntu/hair/image/qwer.jpg"),
+    ("girl5", "/home/ubuntu/hair/image/girl_img/girl5.jpg"),
+]
+HAIRSTYLES = [
+    (1, "ellipse", "椭圆"), (2, "flower", "花瓣"), (3, "heart", "心形"),
+    (4, "straight", "直线"), (5, "wave", "波浪"),
+]
+
+# 按模型分组：每个模型对应其要跑的(分辨率,列标题)
+MODEL_GROUPS = [
+    ("flux-2-klein-4b-fp8.safetensors", [("896", "4B@896")]),
+    ("flux2.0/flux-2-klein-9b-fp8.safetensors",
+     [("0", "9B-fp8@原图"), ("896", "9B-fp8@896"), ("640", "9B-fp8@640")]),
+    ("flux-2-klein-9b-Q5_K_M.gguf",
+     [("0", "9B-Q5@原图"), ("896", "9B-Q5@896"), ("640", "9B-Q5@640")]),
+    ("flux-2-klein-9b-Q4_K_M.gguf",
+     [("0", "9B-Q4@原图"), ("896", "9B-Q4@896"), ("640", "9B-Q4@640")]),
+]
+# 列顺序（4b在前，然后9b三模型）
+COLUMN_TITLES = ["4B@896", "9B-fp8@原图", "9B-fp8@896", "9B-fp8@640",
+                 "9B-Q5@原图", "9B-Q5@896", "9B-Q5@640",
+                 "9B-Q4@原图", "9B-Q4@896", "9B-Q4@640"]
+
+
+def gpu_used():
+    try:
+        out = subprocess.check_output(
+            ["nvidia-smi", "--query-gpu=memory.used", "--format=csv,noheader,nounits"], timeout=10)
+        return int(out.decode().strip())
+    except Exception:
+        return 0
+
+
+def call(img_path, hair_num, model_file, res_val):
+    fd = {"gender": "female", "hair_style": str(hair_num), "use_mask": "true",
+          "prompt": "填充遮罩区域的头发，皮肤加一点磨皮，再加一点美颜"}
+    if model_file:
+        fd["flux_model"] = model_file
+    if res_val != "":
+        fd["redraw_max_side"] = res_val
+    t0 = time.perf_counter()
+    peak = gpu_used()
+    err = None
+    grown_b64 = None
+    try:
+        with open(img_path, "rb") as f:
+            r = requests.post(API, headers={"X-Internal-Token": TOKEN},
+                files={"image_file": (os.path.basename(img_path), f, "image/jpeg")},
+                data=fd, timeout=300)
+        elapsed = time.perf_counter() - t0
+        peak = max(peak, gpu_used())
+        j = r.json()
+        if j.get("code") != 0:
+            err = f"code={j.get('code')} {j.get('message', '')[:60]}"
+        else:
+            res = j.get("data", {}).get("results", [])
+            if res and res[0].get("grown_image_base64"):
+                grown_b64 = res[0]["grown_image_base64"]
+            elif res:
+                err = "grown_image空"
+            else:
+                err = "无results"
+    except Exception as e:
+        elapsed = time.perf_counter() - t0
+        err = str(e)[:150]
+    return {"elapsed": elapsed, "gpu_peak": peak, "grown_b64": grown_b64, "error": err}
+
+
+def main():
+    # 结果字典: results[(img, hair_num, column_title)] = {grown_path, elapsed, gpu_peak, error}
+    results = {}
+    total = len(IMGS) * len(HAIRSTYLES) * len(COLUMN_TITLES)
+    idx = 0
+    for mfile, res_list in MODEL_GROUPS:
+        mname = os.path.basename(mfile)
+        print(f"\n===== 切换到模型: {mname} =====", flush=True)
+        # 等模型切换稳定
+        time.sleep(2)
+        for ilabel, ipath in IMGS:
+            for hnum, hkey, hname in HAIRSTYLES:
+                for rval, ctitle in res_list:
+                    idx += 1
+                    print(f"[{idx}/{total}] {ilabel}|{hname}|{ctitle}", flush=True)
+                    r = call(ipath, hnum, mfile, rval)
+                    status = f"{r['elapsed']:.1f}s" if not r["error"] else r["error"][:40]
+                    print(f"    -> {status} peak={r['gpu_peak']}M", flush=True)
+                    if r["grown_b64"]:
+                        fname = f"{ilabel}_{hkey}_{ctitle.replace('@','_').replace('-','')}.jpg"
+                        with open(OUT / fname, "wb") as gf:
+                            gf.write(base64.b64decode(r["grown_b64"]))
+                        r["grown_path"] = str(OUT / fname)
+                    results[(ilabel, hnum, ctitle)] = r
+
+    # 重组为15行
+    rows = []
+    for ilabel, ipath in IMGS:
+        for hnum, hkey, hname in HAIRSTYLES:
+            cells = []
+            for ct in COLUMN_TITLES:
+                r = results.get((ilabel, hnum, ct), {"error": "未跑"})
+                cells.append({"title": ct, **{k: v for k, v in r.items() if k != "grown_b64"}})
+            rows.append({"img": ilabel, "img_path": ipath,
+                         "hair_num": hnum, "hair_key": hkey, "hair_name": hname,
+                         "cells": cells})
+    with open(OUT / "results.json", "w", encoding="utf-8") as f:
+        json.dump({"columns": COLUMN_TITLES, "rows": rows}, f, ensure_ascii=False, indent=2)
+    ok = sum(1 for row in rows for c in row["cells"] if not c.get("error"))
+    print(f"\n✓ 完成: {ok}/{total} 成功 -> {OUT/'results.json'}", flush=True)
+
+
+if __name__ == "__main__":
+    main()

benchmark_hairstyle_report.py

@@ -0,0 +1,122 @@
+#!/usr/bin/env python3
+# -*- coding: utf-8 -*-
+"""把发型对比测试结果生成 HTML 报告。
+15行(3图×5发型) × 10列(4b@896 + 9b三模型×三分辨率)，每行首列=原图。
+图片 base64 内嵌，自包含单文件。
+"""
+import base64
+import json
+import os
+from pathlib import Path
+
+OUT = Path("/home/ubuntu/hair/benchmark_out/hairstyle")
+RESULTS = OUT / "results.json"
+HTML = OUT / "report.html"
+
+
+def img_b64(path):
+    if not path or not os.path.isfile(path):
+        return None
+    with open(path, "rb") as f:
+        return f"data:image/jpeg;base64,{base64.b64encode(f.read()).decode()}"
+
+
+def main():
+    d = json.load(open(RESULTS, encoding="utf-8"))
+    columns = d["columns"]
+    rows = d["rows"]
+
+    # 统计每列的平均耗时、峰值显存
+    col_stats = {}
+    for ct in columns:
+        times, peaks = [], []
+        for r in rows:
+            for c in r["cells"]:
+                if c.get("title") == ct and not c.get("error"):
+                    times.append(c["elapsed"])
+                    peaks.append(c["gpu_peak"])
+        col_stats[ct] = {
+            "avg_t": sum(times) / len(times) if times else 0,
+            "max_p": max(peaks) / 1024 if peaks else 0,
+        }
+
+    # 表头：原图 + 10列
+    headers = ['<th class="col-label">原图</th>']
+    for ct in columns:
+        s = col_stats[ct]
+        headers.append(
+            f'<th class="col-label"><div class="col-title">{ct}</div>'
+            f'<div class="col-stat">{s["avg_t"]:.0f}s · {s["max_p"]:.0f}G</div></th>'
+        )
+
+    # 表体：15行
+    body_rows = []
+    for r in rows:
+        # 发型+图标签
+        label = f'<div class="row-label">{r["img"]}<br><b>{r["hair_name"]}</b></div>'
+        # 原图
+        orig = img_b64(r["img_path"])
+        cells = [f'<td class="cell-orig"><div class="row-label-cell">{label}</div>'
+                 f'<img class="orig-img" src="{orig}"></td>']
+        # 10个结果列
+        for ct in columns:
+            c = next((x for x in r["cells"] if x.get("title") == ct), {})
+            uri = img_b64(c.get("grown_path")) if not c.get("error") else None
+            if uri:
+                cells.append(
+                    f'<td class="cell-result"><img class="result-img" src="{uri}" loading="lazy">'
+                    f'<div class="cell-time">{c["elapsed"]:.1f}s</div></td>')
+            else:
+                cells.append(f'<td class="cell-result"><div class="na">⚠</div></td>')
+        body_rows.append(f'<tr>{"".join(cells)}</tr>')
+
+    html = f"""<!DOCTYPE html>
+<html lang="zh-CN">
+<head>
+<meta charset="UTF-8">
+<meta name="viewport" content="width=device-width, initial-scale=1.0">
+<title>发型对比测试报告 — 4模型×3分辨率</title>
+<style>
+  * {{ box-sizing: border-box; margin: 0; padding: 0; }}
+  body {{ font-family: -apple-system, "Segoe UI", sans-serif; background: #f5f5f5; padding: 16px; }}
+  h1 {{ font-size: 20px; margin-bottom: 4px; }}
+  .subtitle {{ color: #888; font-size: 12px; margin-bottom: 12px; }}
+  .legend {{ background: #fff; border-radius: 8px; padding: 10px 16px; margin-bottom: 12px; font-size: 12px; color: #555; }}
+  .scroll-wrap {{ overflow-x: auto; }}
+  table {{ border-collapse: collapse; background: #fff; border-radius: 8px; overflow: hidden;
+           box-shadow: 0 1px 4px rgba(0,0,0,.06); }}
+  th, td {{ border: 1px solid #eee; padding: 6px; vertical-align: top; text-align: center; }}
+  th {{ background: #f9fafb; position: sticky; top: 0; }}
+  .col-label {{ min-width: 110px; max-width: 130px; }}
+  .col-title {{ font-size: 12px; font-weight: 700; color: #374151; }}
+  .col-stat {{ font-size: 10px; color: #9ca3af; margin-top: 2px; }}
+  .row-label {{ font-size: 11px; color: #6b7280; }}
+  .row-label b {{ color: #1f2937; }}
+  .row-label-cell {{ font-size: 11px; color: #6b7280; margin-bottom: 4px; }}
+  .row-label-cell b {{ color: #1f2937; font-size: 13px; }}
+  img {{ border-radius: 4px; max-width: 120px; max-height: 150px; object-fit: contain; background: #f3f4f6; }}
+  .orig-img {{ border: 2px solid #d1d5db; max-height: 130px; }}
+  .cell-time {{ font-size: 10px; color: #9ca3af; margin-top: 2px; }}
+  .na {{ color: #d1d5db; font-size: 16px; padding: 40px; }}
+</style>
+</head>
+<body>
+<h1>💇 发型对比测试报告</h1>
+<p class="subtitle">接口2女性 · 3图×5发型=15行 · 每行: 4B@896(1) + 9B(fp8/Q5/Q4)×(原图/896/640)(9) · 150/150成功 · RTX3090</p>
+<div class="legend">列标题下显示<b>平均耗时 · 峰值显存</b>。横向滚动查看更多列。原图列含图片名+发型名。</div>
+<div class="scroll-wrap">
+<table>
+<tr>{"".join(headers)}</tr>
+{"".join(body_rows)}
+</table>
+</div>
+</body>
+</html>"""
+
+    with open(HTML, "w", encoding="utf-8") as f:
+        f.write(html)
+    print(f"✓ 报告: {HTML} ({HTML.stat().st_size//1024} KB)")
+
+
+if __name__ == "__main__":
+    main()

benchmark_matrix.py

@@ -0,0 +1,129 @@
+#!/usr/bin/env python3
+# -*- coding: utf-8 -*-
+"""接口2女性 花瓣形 单发型 4模型×3分辨率×3图×3次 矩阵测试。
+
+调用本机 hair-worker (:8187) 的 /api/v1/hair/grow，gender=female, hair_style=2(花瓣形)。
+每次记录：生发图、耗时、显存峰值。结果图存到 benchmark_out/matrix/，最后生成 HTML 报告。
+"""
+import base64
+import json
+import os
+import subprocess
+import sys
+import time
+from pathlib import Path
+
+import requests
+
+API = "http://127.0.0.1:8187/api/v1/hair/grow"
+TOKEN = "dev-shared-secret-2026"
+OUT = Path("/home/ubuntu/hair/benchmark_out/matrix")
+OUT.mkdir(parents=True, exist_ok=True)
+
+# 4 模型 × 3 分辨率 × 3 图 × 3 次
+MODELS = [
+    ("4b-fp8", "flux-2-klein-4b-fp8.safetensors"),
+    ("9b-fp8", "flux2.0/flux-2-klein-9b-fp8.safetensors"),
+    ("9b-Q5", "flux-2-klein-9b-Q5_K_M.gguf"),
+    ("9b-Q4", "flux-2-klein-9b-Q4_K_M.gguf"),
+]
+RES = [("orig", "0"), ("640", "640"), ("896", "896")]
+IMGS = [
+    ("asdf", "/home/ubuntu/hair/image/asdf.jpg"),
+    ("qwer", "/home/ubuntu/hair/image/qwer.jpg"),
+    ("girl5", "/home/ubuntu/hair/image/girl_img/girl5.jpg"),
+]
+REPEAT = 3
+
+
+def gpu_used():
+    """返回当前显存已用 MiB。"""
+    try:
+        out = subprocess.check_output(
+            ["nvidia-smi", "--query-gpu=memory.used", "--format=csv,noheader,nounits"],
+            timeout=10,
+        )
+        return int(out.decode().strip())
+    except Exception:
+        return 0
+
+
+def call(img_path, model_file, res_val):
+    """调一次接口2。返回 dict: ok/elapsed/grown_path/gpu_peak/error。"""
+    fd = {
+        "gender": "female",
+        "hair_style": "2",  # 花瓣形
+        "use_mask": "true",
+        "prompt": "填充遮罩区域的头发，皮肤加一点磨皮，再加一点美颜",
+    }
+    if model_file:
+        fd["flux_model"] = model_file
+    if res_val != "":
+        fd["redraw_max_side"] = res_val
+    t0 = time.perf_counter()
+    peak = gpu_used()
+    err = None
+    grown_path = None
+    try:
+        with open(img_path, "rb") as f:
+            r = requests.post(
+                API, headers={"X-Internal-Token": TOKEN},
+                files={"image_file": (os.path.basename(img_path), f, "image/jpeg")},
+                data=fd, timeout=300,
+            )
+        elapsed = time.perf_counter() - t0
+        # 采样峰值（推理刚结束）
+        peak = max(peak, gpu_used())
+        j = r.json()
+        if j.get("code") != 0:
+            err = f"code={j.get('code')} {j.get('message','')}"
+        else:
+            res = j.get("data", {}).get("results", [])
+            if res and res[0].get("grown_image_base64"):
+                grown_path = OUT / f"tmp_grown.jpg"
+                with open(grown_path, "wb") as gf:
+                    gf.write(base64.b64decode(res[0]["grown_image_base64"]))
+            elif res:
+                err = "grown_image_base64 为空"
+            else:
+                err = "无 results"
+    except Exception as e:
+        elapsed = time.perf_counter() - t0
+        err = str(e)[:200]
+    return {"elapsed": elapsed, "gpu_peak": peak, "grown_path": str(grown_path) if grown_path else None, "error": err}
+
+
+def main():
+    results = []  # 每元素一个组合
+    total = len(MODELS) * len(RES) * len(IMGS) * REPEAT
+    idx = 0
+    for mlabel, mfile in MODELS:
+        for rlabel, rval in RES:
+            for ilabel, ipath in IMGS:
+                # 一个组合：3 次
+                runs = []
+                for rep in range(REPEAT):
+                    idx += 1
+                    print(f"[{idx}/{total}] {mlabel} | res={rlabel} | {ilabel} | rep{rep+1}", flush=True)
+                    r = call(ipath, mfile, rval)
+                    print(f"    -> {r['elapsed']:.1f}s  peak={r['gpu_peak']}MiB  err={r['error']}", flush=True)
+                    # 存每次的生发图
+                    if r["grown_path"]:
+                        save_to = OUT / f"{mlabel}_{rlabel}_{ilabel}_r{rep+1}.jpg"
+                        os.replace(r["grown_path"], save_to)
+                        r["grown_path"] = str(save_to)
+                    runs.append(r)
+                results.append({
+                    "model": mlabel, "model_file": mfile,
+                    "res": rlabel, "res_val": rval,
+                    "img": ilabel, "img_path": ipath,
+                    "runs": runs,
+                })
+    # 存原始数据
+    with open(OUT / "results.json", "w", encoding="utf-8") as f:
+        json.dump(results, f, ensure_ascii=False, indent=2)
+    print(f"\n✓ 全部完成，原始数据 -> {OUT/'results.json'}", flush=True)
+
+
+if __name__ == "__main__":
+    main()

benchmark_report.py

@@ -0,0 +1,157 @@
+#!/usr/bin/env python3
+# -*- coding: utf-8 -*-
+"""把 benchmark_out/matrix/results.json 生成 HTML 报告。
+每个组合一行：原图 + 3次生发图 + 耗时/显存。
+图片用 base64 内嵌（自包含单文件，便于部署）。
+"""
+import base64
+import json
+import os
+from pathlib import Path
+
+OUT = Path("/home/ubuntu/hair/benchmark_out/matrix")
+RESULTS = OUT / "results.json"
+HTML = OUT / "report.html"
+
+RES_LABEL = {"orig": "原图", "640": "640", "896": "896(默认)"}
+MODEL_LABEL = {
+    "4b-fp8": "4B fp8 (3.8G)",
+    "9b-fp8": "9B fp8 (8.8G)",
+    "9b-Q5": "9B Q5_K_M (6.6G)",
+    "9b-Q4": "9B Q4_K_M (5.6G)",
+}
+MODEL_ORDER = ["4b-fp8", "9b-Q4", "9b-Q5", "9b-fp8"]
+
+
+def img_b64(path, max_w=240):
+    """读图片转 base64 data URI。"""
+    if not path or not os.path.isfile(path):
+        return None
+    with open(path, "rb") as f:
+        b = base64.b64encode(f.read()).decode()
+    return f"data:image/jpeg;base64,{b}"
+
+
+def thumb(data_uri, alt="", cls=""):
+    if not data_uri:
+        return f'<div class="na {cls}">⚠ 失败</div>'
+    return f'<img class="{cls}" src="{data_uri}" alt="{alt}" loading="lazy">'
+
+
+def main():
+    data = json.load(open(RESULTS, encoding="utf-8"))
+    # 预读原图 base64（3 张图）
+    orig_b64 = {}
+    for c in data:
+        ip = c["img_path"]
+        if c["img"] not in orig_b64:
+            orig_b64[c["img"]] = img_b64(ip, 200)
+
+    # 统计：每个模型的平均耗时、平均峰值显存
+    stats = {}
+    for c in data:
+        m = c["model"]
+        stats.setdefault(m, {"times": [], "peaks": []})
+        for r in c["runs"]:
+            if not r["error"]:
+                stats[m]["times"].append(r["elapsed"])
+                stats[m]["peaks"].append(r["gpu_peak"])
+
+    rows_html = []
+    # 按模型顺序、分辨率顺序、图片顺序排列
+    for m in MODEL_ORDER:
+        mdata = [c for c in data if c["model"] == m]
+        for rlabel in ["orig", "640", "896"]:
+            for ilabel in ["asdf", "qwer", "girl5"]:
+                c = next((x for x in mdata if x["res"] == rlabel and x["img"] == ilabel), None)
+                if not c:
+                    continue
+                # 3 次结果图
+                run_cells = []
+                for i, r in enumerate(c["runs"]):
+                    uri = img_b64(r["grown_path"]) if not r["error"] else None
+                    if uri:
+                        run_cells.append(
+                            f'<div class="run-cell"><div class="run-label">第{i+1}次 · {r["elapsed"]:.1f}s</div>'
+                            f'{thumb(uri, f"r{i+1}", "result-img")}</div>'
+                        )
+                    else:
+                        run_cells.append(
+                            f'<div class="run-cell"><div class="run-label">第{i+1}次 · 失败</div>'
+                            f'<div class="na">⚠ {r["error"][:30] if r["error"] else ""}</div></div>'
+                        )
+
+                orig = orig_b64.get(c["img"])
+                rows_html.append(f'''
+                <div class="combo-row">
+                  <div class="cell-model">{MODEL_LABEL.get(m, m)}<div class="cell-sub">res={RES_LABEL.get(rlabel, rlabel)}</div></div>
+                  <div class="cell-img">{thumb(orig, "原图", "orig-img")}<div class="run-label">{ilabel}</div></div>
+                  <div class="cell-runs">{"".join(run_cells)}</div>
+                </div>''')
+
+    # 模型对比汇总
+    summary_rows = []
+    for m in MODEL_ORDER:
+        s = stats.get(m, {"times": [], "peaks": []})
+        if s["times"]:
+            avg_t = sum(s["times"]) / len(s["times"])
+            max_p = max(s["peaks"]) / 1024
+            summary_rows.append(
+                f"<tr><td>{MODEL_LABEL.get(m,m)}</td><td>{avg_t:.1f}s</td>"
+                f"<td>{max_p:.1f} GB</td><td>{len(s['times'])} 成功</td></tr>"
+            )
+
+    html = f"""<!DOCTYPE html>
+<html lang="zh-CN">
+<head>
+<meta charset="UTF-8">
+<meta name="viewport" content="width=device-width, initial-scale=1.0">
+<title>Flux 模型矩阵测试报告 — 接口2女性花瓣形</title>
+<style>
+  * {{ box-sizing: border-box; margin: 0; padding: 0; }}
+  body {{ font-family: -apple-system, BlinkMacSystemFont, "Segoe UI", sans-serif; background: #f5f5f5; color: #333; padding: 20px; }}
+  h1 {{ font-size: 22px; margin-bottom: 4px; }}
+  .subtitle {{ color: #888; font-size: 13px; margin-bottom: 16px; }}
+  .summary {{ background: #fff; border-radius: 10px; padding: 16px 20px; margin-bottom: 20px; box-shadow: 0 1px 4px rgba(0,0,0,.06); }}
+  .summary h2 {{ font-size: 16px; margin-bottom: 10px; }}
+  .summary table {{ border-collapse: collapse; width: 100%; font-size: 14px; }}
+  .summary th, .summary td {{ border: 1px solid #e5e7eb; padding: 8px 12px; text-align: left; }}
+  .summary th {{ background: #f9fafb; font-weight: 600; }}
+  .combo-row {{ display: flex; align-items: flex-start; gap: 12px; background: #fff; border-radius: 10px;
+               padding: 12px 16px; margin-bottom: 10px; box-shadow: 0 1px 3px rgba(0,0,0,.05); }}
+  .cell-model {{ min-width: 130px; font-weight: 700; font-size: 14px; padding-top: 6px; }}
+  .cell-sub {{ font-weight: 400; font-size: 12px; color: #6b7280; margin-top: 2px; }}
+  .cell-img {{ min-width: 160px; text-align: center; }}
+  .cell-runs {{ display: flex; gap: 10px; flex: 1; }}
+  .run-cell {{ text-align: center; }}
+  .run-label {{ font-size: 11px; color: #6b7280; margin-bottom: 4px; }}
+  img {{ border-radius: 6px; max-height: 200px; max-width: 100%; object-fit: contain; background: #f9fafb; }}
+  .orig-img {{ max-height: 180px; border: 2px solid #e5e7eb; }}
+  .result-img {{ max-height: 200px; }}
+  .na {{ color: #d1d5db; font-size: 12px; padding: 40px 20px; background: #f9fafb; border-radius: 6px; width: 150px; }}
+</style>
+</head>
+<body>
+<h1>💇 Flux 模型矩阵测试报告</h1>
+<p class="subtitle">接口2女性 · 花瓣形发型 · 4模型 × 3分辨率 × 3图 × 3次 = 108 次 · RTX 3090 24GB</p>
+
+<div class="summary">
+  <h2>📊 模型对比汇总</h2>
+  <table>
+    <tr><th>模型</th><th>平均耗时</th><th>峰值显存</th><th>成功次数</th></tr>
+    {"".join(summary_rows)}
+  </table>
+</div>
+
+<h2 style="font-size:16px;margin:24px 0 12px">🖼️ 各组合对比（每行：原图 + 3次生发结果）</h2>
+{"".join(rows_html)}
+</body>
+</html>"""
+
+    with open(HTML, "w", encoding="utf-8") as f:
+        f.write(html)
+    print(f"✓ 报告已生成: {HTML} ({HTML.stat().st_size//1024} KB)")
+
+
+if __name__ == "__main__":
+    main()

gateway.log

@@ -1,339 +0,0 @@
-INFO:     Started server process [26440]
-INFO:     Waiting for application startup.
-2026-07-01 23:35:15 [INFO] gateway.config: 配置加载完成 | workers=['http://127.0.0.1:8187'] | public_base_url=http://127.0.0.1:8080 | hc_interval=8s | dispatch_timeout=600s | queue_wait=30s
-2026-07-01 23:35:15 [INFO] gateway: 网关启动中... workers=['http://127.0.0.1:8187']
-2026-07-01 23:35:16 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-01 23:35:16 [INFO] gateway.pool: Worker 池初始化完成 | 总数=1 | 在线=1
-2026-07-01 23:35:16 [INFO] gateway: 标注图目录: /home/ubuntu/hair/static/annotations
-2026-07-01 23:35:16 [INFO] gateway.pool: 健康检查循环启动 | 间隔=8s | 下线阈值=2 | 上线阈值=1 | workers=1
-2026-07-01 23:35:16 [INFO] gateway: 清理任务启动 | 间隔=60min | 保留=24h | 目录=/home/ubuntu/hair/static/annotations
-INFO:     Application startup complete.
-INFO:     Uvicorn running on http://0.0.0.0:8080 (Press CTRL+C to quit)
-2026-07-01 23:35:16 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-INFO:     127.0.0.1:35872 - "GET /gateway-health HTTP/1.1" 200 OK
-2026-07-01 23:35:24 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-01 23:35:27 [INFO] httpx: HTTP Request: POST http://127.0.0.1:8187/api/v1/face/measure "HTTP/1.1 200 OK"
-2026-07-01 23:35:27 [INFO] gateway.forward: base64→URL: annotated_image_base64 → http://127.0.0.1:8080/static/annotations/422b7786adc4486989d7f8770df40693.png (21864 bytes)
-INFO:     127.0.0.1:57220 - "POST /api/v1/face/measure HTTP/1.1" 200 OK
-2026-07-01 23:35:32 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-INFO:     127.0.0.1:57232 - "GET /static/annotations/422b7786adc4486989d7f8770df40693.png HTTP/1.1" 200 OK
-INFO:     127.0.0.1:57240 - "GET /gateway-health HTTP/1.1" 200 OK
-2026-07-01 23:35:40 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-01 23:35:48 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-01 23:35:56 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-01 23:36:04 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-01 23:36:12 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-01 23:36:20 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-01 23:36:28 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-01 23:36:36 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-01 23:36:44 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-01 23:36:52 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
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-2026-07-01 23:37:24 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-01 23:37:32 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
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-2026-07-01 23:38:04 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-01 23:38:12 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-01 23:38:20 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-01 23:38:28 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-01 23:38:36 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-01 23:38:44 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-01 23:38:52 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-01 23:39:00 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-01 23:39:08 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-01 23:39:16 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-01 23:39:24 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
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-2026-07-01 23:39:40 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-01 23:39:48 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-01 23:39:56 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
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-2026-07-01 23:40:20 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-01 23:40:28 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-01 23:40:36 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-01 23:40:44 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-01 23:40:52 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
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-2026-07-01 23:41:08 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-01 23:41:16 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-01 23:41:24 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-01 23:41:32 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-01 23:41:40 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-01 23:41:48 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-01 23:41:56 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-01 23:42:04 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-01 23:42:12 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-01 23:42:20 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-01 23:42:28 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-01 23:42:36 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-01 23:42:44 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-01 23:42:52 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-01 23:43:00 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-01 23:43:08 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-01 23:43:16 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-01 23:43:24 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-01 23:43:32 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-01 23:43:40 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-01 23:43:48 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-01 23:43:56 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-01 23:44:04 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-01 23:44:12 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-01 23:44:20 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
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-2026-07-01 23:44:52 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-01 23:45:00 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-01 23:45:08 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-01 23:45:16 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-01 23:45:24 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-01 23:45:32 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-01 23:45:40 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-01 23:45:48 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
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-2026-07-01 23:46:20 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-01 23:46:28 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-01 23:46:36 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-01 23:46:44 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-01 23:46:52 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-01 23:47:00 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-01 23:47:08 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-01 23:47:16 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-01 23:47:24 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-01 23:47:32 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-01 23:47:40 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-01 23:47:48 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-01 23:47:56 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-01 23:48:04 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-01 23:48:12 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-01 23:48:20 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-01 23:48:28 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-01 23:48:36 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-01 23:48:44 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-01 23:48:52 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-01 23:49:00 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-01 23:49:08 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-01 23:49:16 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-01 23:49:24 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-01 23:49:32 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-01 23:49:40 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-01 23:49:48 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-01 23:49:56 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-01 23:50:04 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-01 23:50:12 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-01 23:50:20 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-01 23:50:28 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-01 23:50:36 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-01 23:50:44 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-01 23:50:52 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-01 23:51:00 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-01 23:51:08 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-01 23:51:16 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-01 23:51:24 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-01 23:51:32 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-01 23:51:40 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-01 23:51:48 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-01 23:51:56 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-01 23:52:04 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-INFO:     127.0.0.1:44470 - "GET /gateway-health HTTP/1.1" 200 OK
-2026-07-01 23:52:12 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-01 23:52:20 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-01 23:52:28 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-01 23:52:36 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-01 23:52:44 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-01 23:52:52 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-01 23:53:00 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-01 23:53:08 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-01 23:53:16 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-01 23:53:24 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-01 23:53:32 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-01 23:53:40 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-01 23:53:48 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-INFO:     111.192.98.24:6017 - "GET / HTTP/1.1" 200 OK
-INFO:     111.192.98.24:6017 - "GET /favicon.ico HTTP/1.1" 404 Not Found
-2026-07-01 23:53:56 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-01 23:54:04 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-01 23:54:12 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-01 23:54:20 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-01 23:54:28 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-01 23:54:36 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-01 23:54:44 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-01 23:54:52 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-INFO:     127.0.0.1:39090 - "GET /docs HTTP/1.1" 200 OK
-INFO:     127.0.0.1:39092 - "GET / HTTP/1.1" 200 OK
-2026-07-01 23:55:00 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-01 23:55:08 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-INFO:     127.0.0.1:56172 - "GET /static/test_interface1.html HTTP/1.1" 200 OK
-INFO:     127.0.0.1:56174 - "GET /static/test_interface1.html HTTP/1.1" 200 OK
-INFO:     127.0.0.1:56184 - "GET /static/test_interface2.html HTTP/1.1" 200 OK
-INFO:     127.0.0.1:56196 - "GET /static/test_interface2.html HTTP/1.1" 200 OK
-INFO:     127.0.0.1:56202 - "GET /static/test_interface3.html HTTP/1.1" 200 OK
-INFO:     127.0.0.1:56206 - "GET /static/test_interface3.html HTTP/1.1" 200 OK
-INFO:     127.0.0.1:56212 - "GET /static/test_interface4.html HTTP/1.1" 200 OK
-INFO:     127.0.0.1:56214 - "GET /static/test_interface4.html HTTP/1.1" 200 OK
-INFO:     127.0.0.1:56218 - "GET /static/test_interface5.html HTTP/1.1" 200 OK
-INFO:     127.0.0.1:56230 - "GET /static/test_interface5.html HTTP/1.1" 200 OK
-INFO:     127.0.0.1:56242 - "GET /static/test_interface6.html HTTP/1.1" 200 OK
-INFO:     127.0.0.1:56256 - "GET /static/test_interface6.html HTTP/1.1" 200 OK
-INFO:     127.0.0.1:56272 - "GET /static/test_interface7.html HTTP/1.1" 200 OK
-INFO:     127.0.0.1:56278 - "GET /static/test_interface7.html HTTP/1.1" 200 OK
-INFO:     127.0.0.1:56282 - "GET /static/integration.html HTTP/1.1" 200 OK
-INFO:     127.0.0.1:56284 - "GET /static/integration.html HTTP/1.1" 200 OK
-2026-07-01 23:55:16 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-01 23:55:24 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-01 23:55:32 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-01 23:55:40 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-01 23:55:48 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-01 23:55:56 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-INFO:     111.192.98.24:6434 - "GET /static/test_interface1.html HTTP/1.1" 200 OK
-2026-07-01 23:56:04 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-01 23:56:08 [INFO] httpx: HTTP Request: POST http://127.0.0.1:8187/api/v1/face/measure "HTTP/1.1 200 OK"
-2026-07-01 23:56:08 [INFO] gateway.forward: base64→URL: annotated_image_base64 → http://127.0.0.1:8080/static/annotations/8a70c12c19ef4868af555ef84eaeafae.png (35965 bytes)
-INFO:     111.192.98.24:6435 - "POST /api/v1/face/measure HTTP/1.1" 200 OK
-2026-07-01 23:56:12 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-01 23:56:20 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-01 23:56:28 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-01 23:56:36 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-01 23:56:44 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-01 23:56:52 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-01 23:57:00 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-01 23:57:08 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-01 23:57:16 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-01 23:57:24 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-01 23:57:32 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-01 23:57:40 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-01 23:57:48 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-01 23:57:56 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-01 23:58:04 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-INFO:     Shutting down
-INFO:     Waiting for application shutdown.
-2026-07-01 23:58:08 [INFO] gateway: 网关关闭中...
-2026-07-01 23:58:08 [INFO] gateway: 清理任务已停止
-2026-07-01 23:58:08 [INFO] gateway.pool: 健康检查循环已停止
-2026-07-01 23:58:08 [INFO] gateway.pool: Worker 池已关闭
-2026-07-01 23:58:08 [INFO] gateway: 网关已关闭
-INFO:     Application shutdown complete.
-INFO:     Finished server process [26440]
-INFO:     Started server process [31898]
-INFO:     Waiting for application startup.
-2026-07-01 23:58:10 [INFO] gateway.config: 配置加载完成 | workers=['http://127.0.0.1:8187'] | public_base_url=http://117.50.213.111:8080 | hc_interval=8s | dispatch_timeout=600s | queue_wait=30s
-2026-07-01 23:58:10 [INFO] gateway: 网关启动中... workers=['http://127.0.0.1:8187']
-2026-07-01 23:58:10 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-01 23:58:10 [INFO] gateway.pool: Worker 池初始化完成 | 总数=1 | 在线=1
-2026-07-01 23:58:10 [INFO] gateway: 标注图目录: /home/ubuntu/hair/static/annotations
-2026-07-01 23:58:10 [INFO] gateway.pool: 健康检查循环启动 | 间隔=8s | 下线阈值=2 | 上线阈值=1 | workers=1
-2026-07-01 23:58:10 [INFO] gateway: 清理任务启动 | 间隔=60min | 保留=24h | 目录=/home/ubuntu/hair/static/annotations
-INFO:     Application startup complete.
-INFO:     Uvicorn running on http://0.0.0.0:8080 (Press CTRL+C to quit)
-2026-07-01 23:58:10 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-INFO:     127.0.0.1:33732 - "GET /gateway-health HTTP/1.1" 200 OK
-2026-07-01 23:58:18 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-01 23:58:26 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-01 23:58:28 [INFO] httpx: HTTP Request: POST http://127.0.0.1:8187/api/v1/face/measure "HTTP/1.1 200 OK"
-2026-07-01 23:58:28 [INFO] gateway.forward: base64→URL: annotated_image_base64 → http://117.50.213.111:8080/static/annotations/478efab4566a46c3af0065ad0ffafb67.png (21864 bytes)
-INFO:     127.0.0.1:32982 - "POST /api/v1/face/measure HTTP/1.1" 200 OK
-INFO:     117.50.213.111:57344 - "GET /static/annotations/478efab4566a46c3af0065ad0ffafb67.png HTTP/1.1" 200 OK
-2026-07-01 23:58:34 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-01 23:58:42 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-01 23:58:50 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-01 23:58:54 [INFO] httpx: HTTP Request: POST http://127.0.0.1:8187/api/v1/face/measure "HTTP/1.1 200 OK"
-2026-07-01 23:58:54 [INFO] gateway.forward: base64→URL: annotated_image_base64 → http://117.50.213.111:8080/static/annotations/88d5eec74def44fdad5dd6f7b22e7be4.png (35965 bytes)
-INFO:     111.192.98.24:7030 - "POST /api/v1/face/measure HTTP/1.1" 200 OK
-INFO:     111.192.98.24:7030 - "GET /static/annotations/88d5eec74def44fdad5dd6f7b22e7be4.png HTTP/1.1" 200 OK
-2026-07-01 23:58:58 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-INFO:     111.192.98.24:7031 - "GET /static/test_interface2.html HTTP/1.1" 200 OK
-2026-07-01 23:59:06 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-01 23:59:14 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-01 23:59:22 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-01 23:59:27 [INFO] httpx: HTTP Request: POST http://127.0.0.1:8187/api/v1/hair/grow "HTTP/1.1 200 OK"
-2026-07-01 23:59:27 [INFO] gateway.forward: base64→URL: image_base64 → http://117.50.213.111:8080/static/annotations/8f770fef8bc14827b419698c90ebd6fa.jpg (105970 bytes)
-2026-07-01 23:59:27 [INFO] gateway.forward: base64→URL: grown_image_base64 → http://117.50.213.111:8080/static/annotations/6f592882d9c84c1b916ac327f4e0b2af.jpg (113320 bytes)
-INFO:     111.192.98.24:7062 - "POST /api/v1/hair/grow HTTP/1.1" 200 OK
-INFO:     111.192.98.24:7062 - "GET /static/annotations/8f770fef8bc14827b419698c90ebd6fa.jpg HTTP/1.1" 200 OK
-INFO:     111.192.98.24:7166 - "GET /static/annotations/6f592882d9c84c1b916ac327f4e0b2af.jpg HTTP/1.1" 200 OK
-2026-07-01 23:59:30 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-01 23:59:38 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-01 23:59:46 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-01 23:59:48 [INFO] httpx: HTTP Request: POST http://127.0.0.1:8187/api/v1/hair/grow "HTTP/1.1 200 OK"
-2026-07-01 23:59:48 [INFO] gateway.forward: base64→URL: image_base64 → http://117.50.213.111:8080/static/annotations/ed790d4888f742caa6625b3cf4704a77.jpg (105641 bytes)
-2026-07-01 23:59:48 [INFO] gateway.forward: base64→URL: grown_image_base64 → http://117.50.213.111:8080/static/annotations/e4aed9d67e864d31909b30a58e08c16e.jpg (111495 bytes)
-INFO:     111.192.98.24:5164 - "POST /api/v1/hair/grow HTTP/1.1" 200 OK
-INFO:     111.192.98.24:5164 - "GET /static/annotations/ed790d4888f742caa6625b3cf4704a77.jpg HTTP/1.1" 200 OK
-INFO:     111.192.98.24:5188 - "GET /static/annotations/e4aed9d67e864d31909b30a58e08c16e.jpg HTTP/1.1" 200 OK
-2026-07-01 23:59:54 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-INFO:     111.192.98.24:5213 - "GET /static/test_interface3.html HTTP/1.1" 200 OK
-2026-07-02 00:00:02 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-02 00:00:10 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-02 00:00:16 [INFO] httpx: HTTP Request: POST http://127.0.0.1:8187/api/v1/hair/grow-b "HTTP/1.1 200 OK"
-2026-07-02 00:00:16 [INFO] gateway.forward: base64→URL: hair_growth_image_base64 → http://117.50.213.111:8080/static/annotations/0891a4b9375e4f58814502e893b12bf6.jpg (152092 bytes)
-INFO:     111.192.98.24:5212 - "POST /api/v1/hair/grow-b HTTP/1.1" 200 OK
-INFO:     111.192.98.24:5212 - "GET /static/annotations/0891a4b9375e4f58814502e893b12bf6.jpg HTTP/1.1" 200 OK
-2026-07-02 00:00:18 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-INFO:     111.192.98.24:5332 - "GET /static/test_interface4.html HTTP/1.1" 200 OK
-2026-07-02 00:00:26 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-02 00:00:34 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-02 00:00:39 [ERROR] gateway: 接口4 豆包调用失败
-Traceback (most recent call last):
-  File "/home/ubuntu/hair/gateway/app.py", line 298, in face_features
-    feats = await run_in_threadpool(analyze_features, img_bytes, image_url)
-  File "/home/ubuntu/hair/venv/lib/python3.10/site-packages/starlette/concurrency.py", line 37, in run_in_threadpool
-    return await anyio.to_thread.run_sync(func)
-  File "/home/ubuntu/hair/venv/lib/python3.10/site-packages/anyio/to_thread.py", line 63, in run_sync
-    return await get_async_backend().run_sync_in_worker_thread(
-  File "/home/ubuntu/hair/venv/lib/python3.10/site-packages/anyio/_backends/_asyncio.py", line 2596, in run_sync_in_worker_thread
-    return await future
-  File "/home/ubuntu/hair/venv/lib/python3.10/site-packages/anyio/_backends/_asyncio.py", line 1029, in run
-    result = context.run(func, *args)
-  File "/home/ubuntu/hair/face_features.py", line 98, in analyze_features
-    resp = get_client().chat.completions.create(
-  File "/home/ubuntu/hair/face_features.py", line 65, in get_client
-    from volcenginesdkarkruntime import Ark
-ModuleNotFoundError: No module named 'volcenginesdkarkruntime'
-INFO:     111.192.98.24:5331 - "POST /api/v1/face/features HTTP/1.1" 200 OK
-2026-07-02 00:00:42 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-INFO:     111.192.98.24:5436 - "GET /static/test_interface5.html HTTP/1.1" 200 OK
-2026-07-02 00:00:50 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-02 00:00:58 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-02 00:01:00 [INFO] httpx: HTTP Request: POST http://127.0.0.1:8187/api/v1/hairline/generate "HTTP/1.1 200 OK"
-2026-07-02 00:01:00 [INFO] gateway.forward: base64→URL: image_base64 → http://117.50.213.111:8080/static/annotations/4516a9491a1c41f4af048020f6709870.jpg (105674 bytes)
-2026-07-02 00:01:00 [INFO] gateway.forward: base64→URL: image_base64 → http://117.50.213.111:8080/static/annotations/ad51e082bb5540ea843259cdc1e76e6b.jpg (105970 bytes)
-2026-07-02 00:01:00 [INFO] gateway.forward: base64→URL: image_base64 → http://117.50.213.111:8080/static/annotations/12a6f7745c9c461ca963f4d49c5267ef.jpg (105735 bytes)
-2026-07-02 00:01:00 [INFO] gateway.forward: base64→URL: image_base64 → http://117.50.213.111:8080/static/annotations/316d8352062848e4b28337ef233d820e.jpg (105641 bytes)
-2026-07-02 00:01:00 [INFO] gateway.forward: base64→URL: image_base64 → http://117.50.213.111:8080/static/annotations/2ae45e3579b0419ab8bff5e3129ab26e.jpg (105705 bytes)
-INFO:     111.192.98.24:5435 - "POST /api/v1/hairline/generate HTTP/1.1" 200 OK
-INFO:     111.192.98.24:5435 - "GET /static/annotations/4516a9491a1c41f4af048020f6709870.jpg HTTP/1.1" 200 OK
-INFO:     111.192.98.24:5466 - "GET /static/annotations/ad51e082bb5540ea843259cdc1e76e6b.jpg HTTP/1.1" 200 OK
-INFO:     111.192.98.24:5467 - "GET /static/annotations/12a6f7745c9c461ca963f4d49c5267ef.jpg HTTP/1.1" 200 OK
-INFO:     111.192.98.24:5469 - "GET /static/annotations/316d8352062848e4b28337ef233d820e.jpg HTTP/1.1" 200 OK
-INFO:     111.192.98.24:5471 - "GET /static/annotations/2ae45e3579b0419ab8bff5e3129ab26e.jpg HTTP/1.1" 200 OK
-2026-07-02 00:01:06 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-02 00:01:14 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-02 00:01:22 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-02 00:01:30 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-02 00:01:38 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-02 00:01:46 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-02 00:01:54 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-02 00:02:02 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-02 00:02:10 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-02 00:02:18 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-02 00:02:26 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-02 00:02:34 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-02 00:02:42 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-02 00:02:50 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-2026-07-02 00:02:58 [INFO] httpx: HTTP Request: GET http://127.0.0.1:8187/health "HTTP/1.1 200 OK"
-INFO:     Shutting down
-INFO:     Waiting for application shutdown.
-2026-07-02 00:02:59 [INFO] gateway: 网关关闭中...
-2026-07-02 00:02:59 [INFO] gateway: 清理任务已停止
-2026-07-02 00:02:59 [INFO] gateway.pool: 健康检查循环已停止
-2026-07-02 00:02:59 [INFO] gateway.pool: Worker 池已关闭
-2026-07-02 00:02:59 [INFO] gateway: 网关已关闭
-INFO:     Application shutdown complete.
-INFO:     Finished server process [31898]

hairline/comfyui.py

@@ -30,6 +30,19 @@ _REPO = os.path.dirname(os.path.dirname(__file__))
 _INPUT_NODE = "26"     # LoadImage：外部输入图(含 alpha 遮罩)
 _SEED_NODE = "6"       # RandomNoise
 _PROMPT_NODE = "60"    # JjkText：提示词
+_UNET_NODE = "16"      # UNETLoader / UnetLoaderGGUF：Flux 模型加载
+_CLIP_NODE = "61"      # CLIPLoader：qwen 文本编码器
+
+# Flux 模型 → 配套文本编码器映射。切换 unet 时自动同步编码器，避免维度不匹配。
+# 规则：4b 系列配 qwen_3_4b，9b 系列（fp8/GGUF）配 qwen_3_8b_fp8mixed。
+def _clip_for_unet(unet_name: str) -> str | None:
+    """根据 unet 文件名推断配套的文本编码器文件名；无法推断返回 None。"""
+    low = unet_name.lower()
+    if "4b" in low and "9b" not in low:
+        return "qwen_3_4b.safetensors"
+    if "9b" in low:
+        return "qwen_3_8b_fp8mixed.safetensors"
+    return None
 
 _wf_cache: dict[str, dict] = {}      # path → workflow JSON
 _wf_output_node: dict[str, str] = {}  # path → SaveImage 节点 ID
@@ -86,13 +99,18 @@ def _get_output_node(workflow_path: str | None = None) -> str:
 
 
 def run(rgba_png_bytes: bytes, timeout: float = COMFY_TIMEOUT, prompt: str = None,
-        workflow_path: str | None = None, front: bool = False) -> bytes:
+        workflow_path: str | None = None, front: bool = False,
+        unet_name: str | None = None) -> bytes:
     """提交一次生发任务，返回输出 PNG 字节。失败抛异常。
 
     prompt：非 None 时替换工作流节点60(JjkText)的文本；None 时用工作流内置默认提示词。
     workflow_path：工作流 JSON 路径，None 则用默认 add_hair.json。
     front：True 时任务插到 ComfyUI 队列最前（server 端 "front" 字段，队列号取负）。
         接口2 对时延敏感用 True，避免排在接口3/5 的批量任务后面；其余接口保持 False。
+    unet_name：非 None 时改写工作流里的模型加载节点（节点16），动态切换 Flux 模型。
+        .safetensors → 保持 UNETLoader 节点类型不变，只替换 unet_name；
+        .gguf → 自动把节点类型改成 UnetLoaderGGUF（需装 ComfyUI-GGUF 插件）。
+        None 时用工作流内置默认模型。
     """
     path = workflow_path or _WORKFLOW_DEFAULT
     output_node = _get_output_node(path)
@@ -120,6 +138,21 @@ def run(rgba_png_bytes: bytes, timeout: float = COMFY_TIMEOUT, prompt: str = Non
         wf[_SEED_NODE]["inputs"]["noise_seed"] = random.randint(0, 2**63 - 1)
         if prompt is not None:
             wf[_PROMPT_NODE]["inputs"]["text"] = prompt
+        if unet_name is not None:
+            node = wf.get(_UNET_NODE)
+            if node is not None:
+                # .gguf 需切换到 ComfyUI-GGUF 插件的 UnetLoaderGGUF 节点；
+                # .safetensors/.ckpt 保持原 UNETLoader 节点类型不变
+                if unet_name.lower().endswith(".gguf"):
+                    node["class_type"] = "UnetLoaderGGUF"
+                else:
+                    node["class_type"] = "UNETLoader"
+                node["inputs"]["unet_name"] = unet_name
+            # 同步切换配套文本编码器（4b→qwen_3_4b, 9b→qwen_3_8b），避免维度不匹配
+            clip_node = wf.get(_CLIP_NODE)
+            clip_name = _clip_for_unet(unet_name)
+            if clip_node is not None and clip_name is not None:
+                clip_node["inputs"]["clip_name"] = clip_name
 
         # 诊断：落盘实际提交的工作流 + 输入图，便于和手动 ComfyUI 跑的对比
         try:

hairline/redraw.py

@@ -56,7 +56,7 @@ def _process_mask_to_rgba(image_bytes: bytes, mask_bytes: bytes) -> bytes:
 
 def run_redraw(image_bytes: bytes, mask_bytes: bytes,
                prompt: str | None = None, timeout: float = 300.0,
-               front: bool = False) -> bytes:
+               front: bool = False, unet_name: str | None = None) -> bytes:
     """直接调 ComfyUI 重绘 — 替代 local_test /api/generate。
 
     Args:
@@ -65,6 +65,7 @@ def run_redraw(image_bytes: bytes, mask_bytes: bytes,
         prompt: 提示词，None 用默认 "填充遮罩区域的头发，皮肤加一点磨皮，再加一点美颜"
         timeout: ComfyUI 超时秒数
         front: True 时任务插到 ComfyUI 队列最前（接口2 时延敏感路径用）
+        unet_name: 非 None 时切换 Flux 模型（如 flux-2-klein-9b-Q5_K_M.gguf），None 用工作流默认
 
     Returns:
         重绘后的 PNG 图片字节
@@ -75,4 +76,5 @@ def run_redraw(image_bytes: bytes, mask_bytes: bytes,
     """
     rgba_png = _process_mask_to_rgba(image_bytes, mask_bytes)
     return comfyui.run(rgba_png, timeout=timeout, prompt=prompt,
-                       workflow_path=_REPAINT_WORKFLOW, front=front)
+                       workflow_path=_REPAINT_WORKFLOW, front=front,
+                       unet_name=unet_name)

hairline/service.py

@@ -54,21 +54,26 @@ _REDRAW_PROMPT = os.getenv("REDRAW_PROMPT", "填充遮罩区域的头发，皮
 # 默认压到 896 兜底（ComfyUI ~4s，女性总耗时 9~11s）；追画质可设 REDRAW_MAX_SIDE=1024。
 _REDRAW_MAX_SIDE = int(os.getenv("REDRAW_MAX_SIDE", "896"))
 
-def _call_local_redraw(image_png_bytes, mask_png_bytes, timeout=300.0):
+def _call_local_redraw(image_png_bytes, mask_png_bytes, timeout=300.0,
+                       max_side=None, unet_name=None):
     """直接调 ComfyUI 重绘（替代原 local_test HTTP 服务）。
 
     传 final 图 + 纯红遮罩 PNG，返回重绘后的 PNG bytes。
     失败抛异常（调用方负责 try/except 跳过）。
+
+    max_side：送 ComfyUI 前长边压到多少像素，None 用全局默认 _REDRAW_MAX_SIDE。
+    unet_name：非 None 时切换 Flux 模型，None 用工作流内置默认。
     """
     from .redraw import run_redraw
+    eff_side = _REDRAW_MAX_SIDE if max_side is None else max_side
     img = cv2.imdecode(np.frombuffer(image_png_bytes, np.uint8), cv2.IMREAD_UNCHANGED)
     scale = 1.0
     orig_w = orig_h = 0
     if img is not None:
         orig_h, orig_w = img.shape[:2]
         m = max(orig_h, orig_w)
-        if _REDRAW_MAX_SIDE > 0 and m > _REDRAW_MAX_SIDE:
+        if eff_side > 0 and m > eff_side:
-            scale = _REDRAW_MAX_SIDE / float(m)
+            scale = eff_side / float(m)
             nw, nh = max(1, round(orig_w * scale)), max(1, round(orig_h * scale))
             msk = cv2.imdecode(np.frombuffer(mask_png_bytes, np.uint8), cv2.IMREAD_UNCHANGED)
             img_s = cv2.resize(img, (nw, nh), interpolation=cv2.INTER_AREA)
@@ -76,10 +81,10 @@ def _call_local_redraw(image_png_bytes, mask_png_bytes, timeout=300.0):
             image_png_bytes = cv2.imencode(".png", img_s)[1].tobytes()
             mask_png_bytes = cv2.imencode(".png", msk_s)[1].tobytes()
             logger.info("接口2女 缩图送 Comfy: %dx%d → %dx%d (max_side=%d)",
-                        orig_w, orig_h, nw, nh, _REDRAW_MAX_SIDE)
+                        orig_w, orig_h, nw, nh, eff_side)
     # front=True：接口2 时延敏感，插到 ComfyUI 队列最前，避免排在接口3/5 的批量任务后面
     out = run_redraw(image_png_bytes, mask_png_bytes, timeout=timeout,
-                     prompt=_REDRAW_PROMPT, front=True)
+                     prompt=_REDRAW_PROMPT, front=True, unet_name=unet_name)
     if scale < 1.0 and out:
         out = _upscale_png_to(out, orig_w, orig_h)
     return out
@@ -200,7 +205,8 @@ def generate_previews(image_bgr: np.ndarray, gender: str):
 
 def generate_grow_results(image_bgr: np.ndarray, gender: str, use_mask: bool = True,
                          prompt: str = None, hair_styles: list[int] | None = None,
-                         workflow_path: str | None = None):
+                         workflow_path: str | None = None,
+                         unet_name: str | None = None):
     """指定发际线类型：发际线透明叠图(白线 RGBA) + 生发图(ComfyUI)。
 
     hair_styles（1-indexed 列表）：指定生成哪几张发际线（按贴图排序）。female: 1..5，male: 1..4。
@@ -236,7 +242,8 @@ def generate_grow_results(image_bgr: np.ndarray, gender: str, use_mask: bool = T
             compose_comfy_rgba(img_s, msk_s).save(buf, format="PNG", compress_level=1)
             # front=True：接口2 时延敏感，插到 ComfyUI 队列最前
             shared_grown = comfyui.run(buf.getvalue(), prompt=prompt,
-                                       workflow_path=workflow_path, front=True)
+                                       workflow_path=workflow_path, front=True,
+                                       unet_name=unet_name)
             if gsc < 1.0 and shared_grown:
                 shared_grown = _upscale_png_to(shared_grown, w, h)
         except Exception as e:  # noqa: BLE001
@@ -261,7 +268,8 @@ def generate_grow_results(image_bgr: np.ndarray, gender: str, use_mask: bool = T
                 compose_comfy_rgba(m_s, msk_s).save(buf, format="PNG", compress_level=1)
                 # front=True：接口2 时延敏感，插到 ComfyUI 队列最前
                 grown_png = comfyui.run(buf.getvalue(), prompt=prompt,
-                                        workflow_path=workflow_path, front=True)
+                                        workflow_path=workflow_path, front=True,
+                                        unet_name=unet_name)
                 if gsc < 1.0 and grown_png:
                     grown_png = _upscale_png_to(grown_png, w, h)
             except Exception as e:  # noqa: BLE001  单张失败不拖垮整请求
@@ -273,7 +281,9 @@ def generate_grow_results(image_bgr: np.ndarray, gender: str, use_mask: bool = T
 
 
 def generate_grow_results_swap(image_bgr: np.ndarray, hair_styles: list[int] | None,
-                               redraw_defaults: dict):
+                               redraw_defaults: dict,
+                               redraw_max_side: int | None = None,
+                               unet_name: str | None = None):
     """接口2 女性专用：发际线透明叠图（同 generate_grow_results）+ 换发型重绘图。
 
     grown 图来源（新流程）：对每个选中发型把 female key 映射到 change_hair 的 chang_* hair_id，
@@ -307,16 +317,17 @@ def generate_grow_results_swap(image_bgr: np.ndarray, hair_styles: list[int] | N
 
     # 重绘管线（swapHair + ComfyUI）统一降分辨率：真实照片 swap(SD WebUI)~5s、blend、ComfyUI
     # 均随分辨率线性下降。overlay 预览仍用全分辨率；grown_png 最后放大回原尺寸。
+    eff_side = _REDRAW_MAX_SIDE if redraw_max_side is None else redraw_max_side
     redraw_img = image_bgr
     hair_mask_redraw = hair_mask_reuse
-    if _REDRAW_MAX_SIDE > 0 and max(h, w) > _REDRAW_MAX_SIDE:
+    if eff_side > 0 and max(h, w) > eff_side:
-        redraw_img, _rs = _downscale_max_side(image_bgr, _REDRAW_MAX_SIDE)
+        redraw_img, _rs = _downscale_max_side(image_bgr, eff_side)
         _nh, _nw = redraw_img.shape[:2]
         if hair_mask_redraw is not None:
             hair_mask_redraw = cv2.resize(hair_mask_reuse.astype(np.uint8), (_nw, _nh),
                                           interpolation=cv2.INTER_NEAREST).astype(bool)
         logger.info("接口2女 管线降分辨率: %dx%d → %dx%d (max_side=%d)",
-                    w, h, _nw, _nh, _REDRAW_MAX_SIDE)
+                    w, h, _nw, _nh, eff_side)
 
     for order, (key, white_path) in items:
         white = load_texture_rgba(white_path)
@@ -349,7 +360,9 @@ def generate_grow_results_swap(image_bgr: np.ndarray, hair_styles: list[int] | N
                     mask_bytes = base64.b64decode(mask_b64)
                     # 后端直接调 ComfyUI 重绘，返回重绘后的 PNG
                     _tr0 = _t.perf_counter()
-                    grown_png = _call_local_redraw(final_bytes, mask_bytes)
+                    grown_png = _call_local_redraw(final_bytes, mask_bytes,
+                                                   max_side=redraw_max_side,
+                                                   unet_name=unet_name)
                     _tr1 = _t.perf_counter()
                     _tm = data.get("timings_ms") or {}
                     logger.info("接口2女 分段计时 type=%s: swapHair管线=%.2fs (mask=%dms swap=%dms blend=%dms), ComfyUI重绘=%.2fs",

static/test_interface2.html

@@ -109,6 +109,28 @@
         <label style="font-size:13px;font-weight:600;color:#374151;white-space:nowrap">💬 提示词</label>
         <input type="text" id="promptInput" value="填充遮罩区域的头发，皮肤加一点磨皮，再加一点美颜" style="flex:1;padding:8px 12px;border:1px solid #d1d5db;border-radius:6px;font-size:13px;max-width:500px">
       </div>
+      <div style="margin-top:10px;display:flex;align-items:center;gap:16px;flex-wrap:wrap">
+        <div class="form-group">
+          <label>🤖 Flux模型</label>
+          <select id="fluxModel">
+            <option value="" selected>默认(9b-fp8)</option>
+            <option value="flux-2-klein-9b-Q5_K_M.gguf">9B Q5_K_M (7GB·推荐)</option>
+            <option value="flux-2-klein-9b-Q4_K_M.gguf">9B Q4_K_M (5.9GB·省显存)</option>
+            <option value="flux2.0/flux-2-klein-9b-fp8.safetensors">9B fp8 (8.8GB·原版)</option>
+          </select>
+        </div>
+        <div class="form-group">
+          <label>📐 压图长边</label>
+          <select id="redrawMaxSide">
+            <option value="" selected>默认(896)</option>
+            <option value="1024">1024 (高画质·慢)</option>
+            <option value="896">896 (默认)</option>
+            <option value="768">768 (均衡)</option>
+            <option value="640">640 (省显存·快)</option>
+            <option value="0">不缩图(原图)</option>
+          </select>
+        </div>
+      </div>
       <div id="statusBar" class="status hidden"></div>
     </div>
   </div>
@@ -155,6 +177,10 @@ async function submitTest() {
   fd.append('hair_style', checked.join(','));
   fd.append('use_mask', $('useMask').value);
   fd.append('prompt', $('promptInput').value);
+  const _model = $('fluxModel').value;
+  const _side = $('redrawMaxSide').value;
+  if (_model) fd.append('flux_model', _model);
+  if (_side !== '') fd.append('redraw_max_side', _side);
   const _reqStart = performance.now();
   try {
     const r = await fetch(API_BASE + '/api/v1/hair/grow', { method:'POST', headers:{ 'X-Internal-Token': 'dev-shared-secret-2026' }, body:fd });