Init: 导入NaviGlassServer源码

qwen_extractor.py

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+# qwen_extractor.py
+# -*- coding: utf-8 -*-
+from typing import List, Tuple
+import os
+from openai import OpenAI
+
+# —— 本地优先映射（可随时扩充/改名）——
+LOCAL_CN2EN = {
+    "红牛": "Red_Bull",
+    "ad钙奶": "AD_milk",
+    "ad 钙奶": "AD_milk",
+    "ad": "AD_milk",
+    "钙奶": "AD_milk",
+    "矿泉水": "bottle",
+    "水瓶": "bottle",
+    "可乐": "coke",
+    "雪碧": "sprite",
+}
+
+def _make_client() -> OpenAI:
+    # 复用你百炼兼容端点；支持从环境变量读取
+    base_url = os.getenv("DASHSCOPE_COMPAT_BASE", "https://dashscope.aliyuncs.com/compatible-mode/v1")
+    api_key  = "sk-a9440db694924559ae4ebdc2023d2b9a"
+    return OpenAI(api_key=api_key, base_url=base_url)
+
+PROMPT_SYS = (
+    "You are a label normalizer. Convert the given Chinese object "
+    "description into a short, lowercase English YOLO/vision class name "
+    "(1~3 words). If multiple are given, return the single most likely one. "
+    "Output ONLY the label, no punctuation."
+)
+
+def extract_english_label(query_cn: str) -> Tuple[str, str]:
+    """
+    返回 (label_en, source)；source ∈ {'local', 'qwen', 'fallback'}
+    """
+    q = (query_cn or "").strip().lower()
+    if q in LOCAL_CN2EN:
+        return LOCAL_CN2EN[q], "local"
+
+    # 简单规则：去掉前缀修饰词
+    for k, v in LOCAL_CN2EN.items():
+        if k in q:
+            return v, "local"
+
+    # 调用 Qwen Turbo（兼容 Chat Completions）
+    try:
+        client = _make_client()
+        msgs = [
+            {"role": "system", "content": PROMPT_SYS},
+            {"role": "user",   "content": query_cn.strip()},
+        ]
+        rsp = client.chat.completions.create(
+            model=os.getenv("QWEN_MODEL", "qwen-turbo"),
+            messages=msgs,
+            stream=False
+        )
+        label = (rsp.choices[0].message.content or "").strip()
+        # 清洗一下
+        label = label.replace(".", "").replace(",", "").replace("  ", " ").strip()
+        # 兜底：空就回 'bottle'
+        return (label or "bottle"), "qwen"
+    except Exception:
+        return "bottle", "fallback"