fix(api): 改进DeepSeek API密钥的动态加载和验证

统一各模块中DeepSeek API密钥的加载方式，确保使用最新的环境变量
添加密钥有效性检查，并在无效时提供降级方案

bigwork/src/deepseek_integrator.py

@@ -59,13 +59,38 @@ class DeepSeekIntegrator:
     
     def _call_api(self, prompt, max_tokens=1000, temperature=0.7):
         """调用DeepSeek API"""
+        # 重新加载环境变量，确保使用最新的API密钥
+        load_dotenv()
+        current_api_key = os.getenv("DEEPSEEK_API_KEY")
+        
+        # 如果实例化时没有提供API密钥，使用当前环境变量中的值
+        api_key_to_use = self.api_key or current_api_key
+        
         # 确保API密钥已配置
-        if not self.api_key:
+        if not api_key_to_use or api_key_to_use == "your-key-here":
-            raise ValueError("DeepSeek API密钥未配置")
+            # 返回模拟结果作为降级方案
+            print("DeepSeek API密钥未配置或无效，返回模拟响应")
+            
+            if "历史案例" in prompt or "相似事件" in prompt:
+                return {
+                    "choices": [{"message": {"content": json.dumps(self.similar_cases, ensure_ascii=False)}}]
+                }
+            elif "公关声明" in prompt or "道歉信" in prompt:
+                return {
+                    "choices": [{"message": {"content": self._generate_pr_statement(prompt)}}]
+                }
+            elif "传播路径" in prompt or "影响预测" in prompt:
+                return {
+                    "choices": [{"message": {"content": self._predict_propagation(prompt)}}]
+                }
+            else:
+                return {
+                    "choices": [{"message": {"content": "API密钥未配置，返回模拟响应。"}}]
+                }
         
         # 实际API调用代码
         headers = {
-            "Authorization": f"Bearer {self.api_key}",
+            "Authorization": f"Bearer {api_key_to_use}",
             "Content-Type": "application/json"
         }
         payload = {

bigwork/src/smart_care_system.py

@@ -61,10 +61,15 @@ def call_deepseek_api(prompt: str, max_tokens: int = 500, temperature: float = 0
     """调用DeepSeek大模型API"""
     import time
     import requests
+    import json
+    
+    # 重新加载环境变量，确保使用最新的API密钥
+    load_dotenv()
+    current_api_key = os.getenv("DEEPSEEK_API_KEY")
     
     # 检查API Key是否配置
-    if not DEEPSEEK_API_KEY:
+    if not current_api_key or current_api_key == "your-key-here":
-        print("DeepSeek API密钥未配置，返回模拟响应")
+        print("DeepSeek API密钥未配置或无效，返回模拟响应")
         # 返回模拟响应
         if "问题分类" in prompt:
             return json.dumps({"primary_category": "其他", "secondary_category": "其他"}, ensure_ascii=False)
@@ -85,7 +90,7 @@ def call_deepseek_api(prompt: str, max_tokens: int = 500, temperature: float = 0
         try:
             headers = {
                 "Content-Type": "application/json",
-                "Authorization": f"Bearer {DEEPSEEK_API_KEY}"
+                "Authorization": f"Bearer {current_api_key}"
             }
             
             payload = {

bigwork/src/smart_customer_service.py

@@ -610,16 +610,27 @@ class SmartCustomerService:
     def _call_deepseek_api(self, user_id: str, churn_prediction: Dict[str, Any], query: str = "") -> str:
         """调用DeepSeek API生成挽留措施"""
         try:
+            # 重新加载环境变量，确保使用最新的API密钥
+            load_dotenv()
+            current_api_key = os.getenv("DEEPSEEK_API_KEY", "")
+            
             # 检查API密钥是否有效
-            if not DEEPSEEK_API_KEY or DEEPSEEK_API_KEY == "your-key-here":
+            if not current_api_key or current_api_key == "your-key-here":
                 st.warning("DeepSeek API密钥未配置或无效，将使用备用方案")
                 return self._generate_mock_retention_plan(user_id, churn_prediction, query)
             
+            # 在函数内部创建client对象，确保使用最新的API密钥
+            from openai import OpenAI
+            current_client = OpenAI(
+                api_key=current_api_key,
+                base_url=DEEPSEEK_API_BASE
+            )
+            
             # 构建智能提示词（包含用户查询内容）
             prompt = self._build_retention_prompt(user_id, churn_prediction, query)
             
             # 调用DeepSeek API（使用新的openai接口）
-            response = client.chat.completions.create(
+            response = current_client.chat.completions.create(
                 model="deepseek-chat",
                 messages=[
                     {"role": "system", "content": "你是一个专业的客户关系管理专家，擅长制定客户挽留策略。请基于客户的具体问题和流失风险分析，提供切实可行的个性化挽留措施。"},