Update app.py

app.py

@@ -1,9 +1,9 @@
 import gradio as gr
-import plotly.express as px
 from openai import OpenAI
 import time
 import os
 from dotenv import load_dotenv
+import json
 
 load_dotenv()
 api_key = os.getenv("OPENAI_API_KEY")
@@ -15,15 +15,6 @@ print("Cliente OpenAI inicializado")
 
 assistant_id = "asst_0hq3iRy6LX0YLZP0QVzg17fT"
 
-def random_plot():
-    df = px.data.iris()
-    fig = px.scatter(df, x="sepal_width", y="sepal_length", color="species",
-                    size='petal_length', hover_data=['petal_width'])
-    return fig
-
-def print_like_dislike(x: gr.LikeData):
-    print(x.index, x.value, x.liked)
-
 def add_message(history, message):
     if message.strip() != "":
         history.append((message, None))
@@ -65,8 +56,30 @@ def bot(history):
             
             if run.status == "requires_action":
                 print("La ejecución requiere una acción")
-                client.beta.threads.runs.cancel(thread_id=thread.id, run_id=run.id)
-                return history + [("Lo siento, el asistente requiere acciones adicionales que no puedo manejar en este momento. Por favor, intenta reformular tu pregunta.", None)]
+                required_actions = run.required_action.submit_tool_outputs.tool_calls
+                tool_outputs = []
+                
+                for action in required_actions:
+                    function_name = action.function.name
+                    function_args = json.loads(action.function.arguments)
+                    
+                    # Aquí simplemente pasamos la llamada a la función al asistente
+                    result = json.dumps({
+                        "function_called": function_name,
+                        "arguments": function_args
+                    })
+                    
+                    tool_outputs.append({
+                        "tool_call_id": action.id,
+                        "output": result
+                    })
+                
+                client.beta.threads.runs.submit_tool_outputs(
+                    thread_id=thread.id,
+                    run_id=run.id,
+                    tool_outputs=tool_outputs
+                )
+                continue
 
         if run.status != "completed":
             print(f"La ejecución terminó con estado: {run.status}")
@@ -93,8 +106,6 @@ def bot(history):
         print(f"Error en la función bot: {e}")
         return history + [("Lo siento, ocurrió un error inesperado. Por favor, intenta de nuevo.", None)]
 
-fig = random_plot()
-
 with gr.Blocks(fill_height=True) as demo:
     chatbot = gr.Chatbot(
         elem_id="chatbot",
@@ -109,7 +120,6 @@ with gr.Blocks(fill_height=True) as demo:
     chat_msg = chat_input.submit(add_message, [chatbot, chat_input], [chatbot, chat_input])
     bot_msg = chat_msg.then(bot, chatbot, chatbot, api_name="bot_response")
     bot_msg.then(lambda: gr.Textbox(interactive=True), None, [chat_input])
-    chatbot.like(print_like_dislike, None, None)
 
 print("Iniciando la aplicación Gradio")
 demo.queue()