Update app.py

app.py

@@ -46,42 +46,40 @@ class BasicAgent:
         print(f"Agent tools initialized: {list(self.tools.keys())}")
 
     def _call_llm(self, conversation_history: list) -> str:
-    print(f"Calling LLM. Conversation history length: {len(conversation_history)}")
-
-    # Hugging Face headers (simpler)
-    headers = {
-        "Authorization": f"Bearer {self.api_key}",  # should be your HF token
-        "Content-Type": "application/json"
-    }
-
-    # Format conversation into a single prompt string
-    # You can improve this formatting later if needed
-    prompt = ""
-    for turn in conversation_history:
-        role = turn.get("role", "user").capitalize()
-        content = turn.get("content", "")
-        prompt += f"{role}: {content}\n"
-    prompt += "Assistant:"
-
-    # Payload for Hugging Face
-    payload = {
-        "inputs": prompt,
-        "parameters": {
-            "temperature": 0.7,
-            "max_new_tokens": 512
+        print(f"Calling LLM. Conversation history length: {len(conversation_history)}")
+    
+        # Hugging Face headers (simpler)
+        headers = {
+            "Authorization": f"Bearer {self.api_key}",  # should be your HF token
+            "Content-Type": "application/json"
         }
-    }
-
-    url = "https://api-inference.huggingface.co/models/deepseek-ai/DeepSeek-V3"
-    response = requests.post(url, headers=headers, json=payload)
-
-    try:
-        return response.json()[0]["generated_text"].split("Assistant:")[-1].strip()
-    except Exception:
-        return f"Error: {response.text}"
-
-        
-
+    
+        # Format conversation into a single prompt string
+        # You can improve this formatting later if needed
+        prompt = ""
+        for turn in conversation_history:
+            role = turn.get("role", "user").capitalize()
+            content = turn.get("content", "")
+            prompt += f"{role}: {content}\n"
+        prompt += "Assistant:"
+    
+        # Payload for Hugging Face
+        payload = {
+            "inputs": prompt,
+            "parameters": {
+                "temperature": 0.7,
+                "max_new_tokens": 512
+            }
+        }
+    
+        url = "https://api-inference.huggingface.co/models/deepseek-ai/DeepSeek-V3"
+        response = requests.post(url, headers=headers, json=payload)
+    
+        try:
+            return response.json()[0]["generated_text"].split("Assistant:")[-1].strip()
+        except Exception:
+            return f"Error: {response.text}"
+    
     def __call__(self, question_data: dict) -> str:
         task_id = question_data.get("task_id")
         question_text = question_data.get("question")