Update app.py

app.py

@@ -1,70 +1,69 @@
+import os
 import time
 import gradio as gr
 import google.generativeai as genai
-import os
-from dotenv import load_dotenv
-
-# Cargar variables de entorno
-load_dotenv()
+from typing import Optional, List
 
-# Configurar clave de API
+# Cargar la clave API desde el entorno
 GOOGLE_API_KEY = os.getenv("GOOGLE_API_KEY")
 
 if not GOOGLE_API_KEY:
-    raise ValueError("GOOGLE_API_KEY is not configurada en las variables de entorno.")
+    raise ValueError("GOOGLE_API_KEY is not set.")
 
+# Configurar la API de Gemini
 genai.configure(api_key=GOOGLE_API_KEY)
 
-# Transformar el historial a formato Gemini
 def transform_history(history):
+    """Transforma el historial en el formato esperado por Gemini."""
     new_history = []
     for chat in history:
         new_history.append({"role": "user", "content": chat[0]})
         new_history.append({"role": "assistant", "content": chat[1]})
     return new_history
 
-# Agregar mensaje al historial
-def add_message(history, message):
-    for file in message["files"]:
-        history.append({"role": "user", "content": {"path": file}})
-    if message["text"] is not None:
-        history.append({"role": "user", "content": message["text"]})
-    return history, gr.MultimodalTextbox(value=None, interactive=False)
-
-# Generar respuesta del chatbot
-def bot(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)
-    try:
-        response = genai.chat(
-            model="gemini-1.5-flash",  # Asegúrate de usar el modelo correcto
-            messages=chat_history + [{"role": "user", "content": history[-1][0]}],
-            max_output_tokens=150
-        )
-        reply = response["candidates"][0]["content"]
+    
+    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
+    )
+    
+    response = genai.ChatCompletion.create(
+        model=model_choice,
+        messages=chat_history + [{"role": "user", "content": history[-1][0]}],
+        generation_config=generation_config
+    )
 
-        # Mostrar respuesta de manera progresiva
-        for i in range(len(reply)):
-            time.sleep(0.05)
-            yield history + [{"role": "assistant", "content": reply[:i + 1]}]
-    except Exception as e:
-        yield history + [{"role": "assistant", "content": f"Error: {e}"}]
+    reply = response['candidates'][0]['content']
+    for i in range(len(reply)):
+        time.sleep(0.05)
+        yield history + [{"role": "assistant", "content": reply[:i + 1]}]
 
-# Crear interfaz Gradio
+# Interfaz con Gradio
 with gr.Blocks() as demo:
     chatbot = gr.Chatbot(elem_id="chatbot", bubble_full_width=False, type="messages")
-
-    chat_input = gr.MultimodalTextbox(
-        interactive=True,
-        file_count="multiple",
-        placeholder="Escribe un mensaje o sube un archivo...",
-        show_label=False,
-        sources=["microphone", "upload"],
+    
+    chat_input = gr.Textbox(
+        placeholder="Escribe un mensaje...",
+        show_label=False
     )
-
-    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.MultimodalTextbox(interactive=True), None, [chat_input])
-
-    chatbot.like(lambda x: print(x.index, x.value, x.liked), None, None, like_user_message=True)
-
+    
+    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")
+    
+    submit_btn.click(
+        bot,
+        inputs=[None, model_choice, system_input, chatbot],
+        outputs=chatbot
+    )
+    
 demo.launch()