feat: automate image pipeline and simplify gemini flow

services/service_image_analyzer.py

@@ -20,6 +20,13 @@ logger = logging.getLogger("cs_agent")
 
 
 ANALYSIS_PROMPT = """你是一个电商图片处理评估专家。
+客户需求如下：
+{customer_requirement}
+
+请结合客户需求和图片内容一起判断，不要只看图片本身。
+如果客户明确说了“找原图/找图/素材/大图”，类型优先判断为“找原图/素材提取”类；
+如果客户明确说了“修复/高清/清晰/放大”，类型优先判断为“高清修复”类。
+
 请仔细分析这张图片，输出以下字段，每行一个，不要多余内容：
 
 敏感内容: <yes|no>
@@ -101,7 +108,7 @@ class ImageAnalyzerService:
             logger.debug(f"[ImageAnalyzer] 获取尺寸失败: {e}")
             return (0, 0)
 
-    async def analyze(self, image_url: str) -> Dict[str, Any]:
+    async def analyze(self, image_url: str, customer_requirement: str = "") -> Dict[str, Any]:
         """
         异步分析图片，返回结构化结果
         
@@ -133,7 +140,8 @@ class ImageAnalyzerService:
             return self._fallback(image_url, "未配置 API Key")
 
         # 缓存检查
-        cache_key = image_url
+        customer_requirement = str(customer_requirement or "").strip()
+        cache_key = f"{image_url}|{customer_requirement}"
         now = time.monotonic()
         cached = self._analysis_cache.get(cache_key)
         if cached:
@@ -149,6 +157,9 @@ class ImageAnalyzerService:
         try:
             client = AsyncOpenAI(base_url=self.base_url, api_key=self.api_key)
             
+            prompt_text = ANALYSIS_PROMPT.format(
+                customer_requirement=customer_requirement or "未提供明确补充需求"
+            )
             response = await asyncio.wait_for(
                 client.chat.completions.create(
                     model=self.vision_model,
@@ -156,7 +167,7 @@ class ImageAnalyzerService:
                         "role": "user",
                         "content": [
                             {"type": "image_url", "image_url": {"url": image_url}},
-                            {"type": "text", "text": ANALYSIS_PROMPT}
+                            {"type": "text", "text": prompt_text}
                         ]
                     }],
                     max_tokens=500
@@ -170,6 +181,7 @@ class ImageAnalyzerService:
             elapsed = time.monotonic() - start
             
             result = self._parse_result(image_url, content)
+            result["customer_requirement"] = customer_requirement
             result["elapsed"] = round(elapsed, 2)
             
             # 获取尺寸
@@ -241,6 +253,7 @@ class ImageAnalyzerService:
             
         return {
             "url": url,
+            "customer_requirement": "",
             "complexity": complexity,
             "reason": extract("原因"),
             "subject": extract("主体"),
@@ -280,6 +293,7 @@ class ImageAnalyzerService:
         from datetime import datetime
         return {
             "url": url,
+            "customer_requirement": "",
             "complexity": "normal",
             "reason": reason,
             "subject": "",