Update app.py

app.py

@@ -42,40 +42,44 @@ class ArtExplorer:
         return fig
 
     def get_llm_response(self, query: str, zoom_context: dict = None) -> dict:
-        try:
-            current_zoom_states = {
-                "temporal": {"level": self.current_state["zoom_level"], "selection": ""},
-                "geographical": {"level": self.current_state["zoom_level"], "selection": ""},
-                "style": {"level": self.current_state["zoom_level"], "selection": ""},
-                "subject": {"level": self.current_state["zoom_level"], "selection": ""}
-            }
-
-            if zoom_context:
-                for key, value in zoom_context.items():
-                    if key in current_zoom_states:
-                        current_zoom_states[key]["selection"] = value
-
-            messages=[
-                {"role": "system", "content": "You are an expert art historian specializing in interactive exploration."},
-                {"role": "user", "content": CONTEXTUAL_ZOOM_PROMPT.format(
-                    user_query=query,
-                    current_zoom_states=json.dumps(current_zoom_states, indent=2)
-                )}
-            ]
-
-            print(messages)
-            response = self.client.chat.completions.create(
-                model="mixtral-8x7b-32768",
-                messages=messages,
-                temperature=0.1,
-                max_tokens=2048
-            )
-            print(response)
-            result = json.loads(response.choices[0].message.content)
-            return result
-        except Exception as e:
-            print(f"Error in LLM response: {str(e)}")
-            return self.get_default_response()
+      try:
+          current_zoom_states = {
+              "temporal": {"level": self.current_state["zoom_level"], "selection": ""},
+              "geographical": {"level": self.current_state["zoom_level"], "selection": ""},
+              "style": {"level": self.current_state["zoom_level"], "selection": ""},
+              "subject": {"level": self.current_state["zoom_level"], "selection": ""}
+          }
+    
+          if zoom_context:
+              for key, value in zoom_context.items():
+                  if key in current_zoom_states:
+                      current_zoom_states[key]["selection"] = value
+    
+          messages = [
+              {"role": "system", "content": "You are an expert art historian specializing in interactive exploration."},
+              {"role": "user", "content": CONTEXTUAL_ZOOM_PROMPT.format(
+                  user_query=query,
+                  current_zoom_states=json.dumps(current_zoom_states, indent=2)
+              )}
+          ]
+    
+          response = self.client.chat.completions.create(
+              model="mixtral-8x7b-32768",
+              messages=messages,
+              temperature=0.1,
+              max_tokens=2048
+          )
+    
+          result = json.loads(response.choices[0].message.content)
+          return result
+      except json.JSONDecodeError as json_err:
+          print(f"JSON decode error: {str(json_err)}")
+          print(f"Response content: {response.choices[0].message.content}")
+          return self.get_default_response()
+      except Exception as e:
+          print(f"Error in LLM response: {str(e)}")
+          return self.get_default_response()
+          
 
     def get_default_response(self):
         return CONTEXTUAL_ZOOM_default_response