Update app.py

app.py

@@ -1,79 +1,26 @@
-import os
-import time
 import gradio as gr
-import google.generativeai as genai
-from typing import Optional, List
-
-# Cargar la clave API desde el entorno
-GOOGLE_API_KEY = os.getenv("GOOGLE_API_KEY")
+import random
+import time
 
-if not GOOGLE_API_KEY:
-    raise ValueError("GOOGLE_API_KEY is not set.")
+with gr.Blocks() as demo:
+    chatbot = gr.Chatbot(type="messages")
+    msg = gr.Textbox()
+    clear = gr.Button("Clear")
 
-# Configurar la API de Gemini
-genai.configure(api_key=GOOGLE_API_KEY)
+    def user(user_message, history: list):
+        return "", history + [{"role": "user", "content": user_message}]
 
-def transform_history(history):
-    """Transforma el historial en el formato esperado por Gemini."""
-    new_history = []
-    for user, assistant in history:
-        new_history.append({"role": "user", "content": user})
-        if assistant:
-            new_history.append({"role": "assistant", "content": assistant})
-    return new_history
+    def bot(history: list):
+        bot_message = random.choice(["How are you?", "I love you", "I'm very hungry"])
+        history.append({"role": "assistant", "content": ""})
+        for character in bot_message:
+            history[-1]['content'] += character
+            time.sleep(0.05)
+            yield history
 
-def bot(files: Optional[List[str]], model_choice: str, system_instruction: Optional[str], history):
-    """Procesa la interacción del chatbot."""
-    chat_history = transform_history(history)
-    
-    if system_instruction:
-        chat_history.insert(0, {"role": "system", "content": system_instruction})
-    
-    # Configuración del modelo Flash 1.5
-    generation_config = genai.types.GenerationConfig(
-        temperature=0.7,
-        max_output_tokens=8192,
-        top_k=10,
-        top_p=0.9
-    )
-    
-    # Si se incluyen archivos, procesa esa entrada multimodal
-    if files:
-        for file_path in files:
-            with open(file_path, "r") as file:
-                file_content = file.read()
-                chat_history.append({"role": "user", "content": f"Archivo cargado: {file_content}"})
-    
-    response = genai.ChatCompletion.create(
-        model=model_choice,
-        messages=chat_history,
-        generation_config=generation_config
+    msg.submit(user, [msg, chatbot], [msg, chatbot], queue=False).then(
+        bot, chatbot, chatbot
     )
+    clear.click(lambda: None, None, chatbot, queue=False)
 
-    reply = response['candidates'][0]['content']
-    for i in range(len(reply)):
-        time.sleep(0.05)
-        yield history + [[None, reply[:i + 1]]]  # Agrega la respuesta progresivamente al historial
-
-# Interfaz con Gradio
-with gr.Blocks() as demo:
-    chatbot = gr.Chatbot(elem_id="chatbot", bubble_full_width=False, type="messages")
-    
-    chat_input = gr.Textbox(
-        placeholder="Escribe un mensaje...",
-        show_label=False
-    )
-    
-    submit_btn = gr.Button("Enviar")
-    system_input = gr.Textbox(placeholder="Instrucción del sistema (opcional)", show_label=True, lines=2)
-    model_choice = gr.Dropdown(choices=["gemini-1.5-flash"], value="gemini-1.5-flash", label="Modelo")
-    file_input = gr.File(label="Subir archivo (opcional)", file_types=[".txt", ".md", ".json"])
-    
-    # Manejar el envío del mensaje
-    submit_btn.click(
-        bot,
-        inputs=[file_input, model_choice, system_input, chatbot],
-        outputs=chatbot
-    )
-    
 demo.launch()