Upload bayesian_llm_assistant.py

bayesian_llm_assistant.py

@@ -243,6 +243,8 @@ Format responses with proper markdown for better readability.
             error_msg = f"❌ Error: {str(e)}\n\nPlease check your API key and try again."
             return error_msg, None
     
+
+            
     def _extract_and_render_dag(self, text):
         """
         從文字中提取 Graphviz 代碼並渲染成圖片
@@ -253,17 +255,23 @@ Format responses with proper markdown for better readability.
         Returns:
             PIL Image 或 None
         """
-        # 使用正則表達式提取 Graphviz 代碼
-        pattern = r'```graphviz\s*\n(.*?)\n```'
-        matches = re.findall(pattern, text, re.DOTALL)
+        # 方法 1: 嘗試提取 ```graphviz ... ``` 格式
+        pattern1 = r'```graphviz\s*\n(.*?)\n```'
+        matches = re.findall(pattern1, text, re.DOTALL)
         
-        if not matches:
-            return None
-        
-        try:
-            # 取第一個 Graphviz 代碼塊
+        if matches:
             dot_code = matches[0]
+        else:
+            # 方法 2: 嘗試提取 digraph ... } 格式（沒有 markdown 包裹）
+            pattern2 = r'(digraph\s+\w+\s*\{.*?\n\})'
+            matches = re.findall(pattern2, text, re.DOTALL)
             
+            if not matches:
+                return None
+            
+            dot_code = matches[0]
+        
+        try:
             # 使用 Graphviz 渲染
             graph = graphviz.Source(dot_code)
             png_bytes = graph.pipe(format='png')
@@ -275,7 +283,8 @@ Format responses with proper markdown for better readability.
             
         except Exception as e:
             print(f"Failed to render DAG: {e}")
-            return None
+            return None           
+           
     
     def _prepare_context(self, results):
         """準備分析結果的上下文資訊"""