fix(kb-deep-analyzer): 子线程环境变量传递

- 在 _analyze_chunks_concurrent 中使用 _worker_env 保存环境变量
- 添加 init_worker() 初始化函数
- ThreadPoolExecutor 使用 initializer=init_worker 传递环境变量

skills/kb-deep-analyzer/deep_analyzer.py

@@ -702,6 +702,18 @@ class DeepAnalyzer:
         """
         import concurrent.futures
 
+        # 确保环境变量在子线程中可用
+        _worker_env = {
+            'AI_API_KEY': os.environ.get('AI_API_KEY', ''),
+            'AI_PROVIDER': os.environ.get('AI_PROVIDER', ''),
+            'AI_MODEL': os.environ.get('AI_MODEL', ''),
+            'AI_BASE_URL': os.environ.get('AI_BASE_URL', ''),
+        }
+        
+        def init_worker():
+            """初始化 worker 线程的环境变量"""
+            os.environ.update(_worker_env)
+        
         result = AnalysisResult()
         CHUNK_MAX_CHARS = 3000
         total_chars = len(text)
@@ -778,7 +790,7 @@ class DeepAnalyzer:
             batch_tasks = [(i, batch_chunks[j], batch_times[j][0], batch_times[j][1]) 
                           for j, i in enumerate(range(batch_idx, batch_end))]
 
-            with concurrent.futures.ThreadPoolExecutor(max_workers=batch_size) as executor:
+            with concurrent.futures.ThreadPoolExecutor(max_workers=batch_size, initializer=init_worker) as executor:
                 futures = {executor.submit(self._analyze_chunk, task[1], task[0] + 1, metadata): task[0] 
                           for task in batch_tasks}