Update app.py

app.py

@@ -18,8 +18,6 @@ from llama_index.core import (
 from llama_index.core.tools import FunctionTool
 from llama_index.agent.openai import OpenAIAgent
 from llama_index.llms.openai import OpenAI as LlamaOpenAI
-#from llama_index.core.callbacks import CallbackManager, LlamaDebugHandler
-
 
 from openai import OpenAI as OpenAIClient
 
@@ -65,18 +63,9 @@ class BasicAgent:
                 temperature=0.0,
                 api_key=openai_api_key
             )
-            #print_coso(f"openai.__version__: {openai.__version__}")
-            #questo per vedere il ragionamento step by step
-            #debug_handler = LlamaDebugHandler(print_trace_on_end=True)
-            #callback_manager = CallbackManager([debug_handler])
     
             # Prepara l'agente
-            self.agent = OpenAIAgent.from_tools(
-                tools = [ingredient_tool], 
-                llm=llm, 
-                #callback_manager=callback_manager,
-                verbose=True
-            )
+            self.agent = OpenAIAgent.from_tools([ingredient_tool], llm=llm, verbose=True)
     
             # Client OpenAI per chiamate esterne (immagini/audio)
            
@@ -100,7 +89,7 @@ class BasicAgent:
 
 
     def __call__(self, question: str, file_info: str = "") -> str:
-        print_coso(f"Received question: {question}")
+        print_coso(f"Received question: {question[:100]}")
 
         # Prova a decodificare JSON
         try:
@@ -186,22 +175,17 @@ class BasicAgent:
 
         
     def _ask_gpt4o(self, text: str) -> str:
-        try:
-            response = self.agent.chat(text, verbose=True)
-    
-            print_coso("\n==== RISPOSTA AGENTE ====")
-            #print(response.response)
-    
-            print_coso("\n==== RAW OUTPUT ====")
-            #print(response.raw_output)
-            print_coso("\n==== FINE RAW OUTPUT ====")
-    
-            return str(response)
-        except Exception as e:
-            print_coso(f"[ERRORE] Agent chat fallita: {e}")
-            return "Agent error"
-
-
+        response = self.agent.chat(text)
+        return str(response)
+        '''
+        messages = [{"role": "user", "content": text}]
+        response = self.client.chat.completions.create(
+            model="gpt-4o-mini",
+            temperature=0,
+            messages=messages
+        )
+        return response.choices[0].message.content.strip()
+        '''
 
     def _ask_gpt4o_with_image(self, image: Image.Image, question: str) -> str:
         buffered = BytesIO()