Update app.py

app.py

@@ -1,149 +1,44 @@
-import os
 import time
-import uuid
-from typing import List, Tuple, Optional
-import google.generativeai as genai
 import gradio as gr
-from PIL import Image
-from dotenv import load_dotenv
-
-# Cargar las variables de entorno desde el archivo .env
-load_dotenv()
-
-print("google-generativeai:", genai.__version__)
+import google.generativeai as genai
+import os
 
+# Cargar la clave de la API de Gemini desde el entorno
 GOOGLE_API_KEY = os.getenv("GOOGLE_API_KEY")
 
 if not GOOGLE_API_KEY:
     raise ValueError("GOOGLE_API_KEY is not set in environment variables.")
 
-IMAGE_CACHE_DIRECTORY = "/tmp"
-IMAGE_WIDTH = 512
-
-def preprocess_image(image: Image.Image) -> Optional[Image.Image]:
-    if image:
-        image_height = int(image.height * IMAGE_WIDTH / image.width)
-        return image.resize((IMAGE_WIDTH, image_height))
-
-def cache_pil_image(image: Image.Image) -> str:
-    image_filename = f"{uuid.uuid4()}.jpeg"
-    os.makedirs(IMAGE_CACHE_DIRECTORY, exist_ok=True)
-    image_path = os.path.join(IMAGE_CACHE_DIRECTORY, image_filename)
-    image.save(image_path, "JPEG")
-    return image_path
-
-def upload(files: Optional[List[str]], chatbot: List[tuple]) -> List[tuple]:
-    for file in files:
-        image = Image.open(file).convert('RGB')
-        image_preview = preprocess_image(image)
-        if image_preview:
-            gr.Image(image_preview).render()
-        image_path = cache_pil_image(image)
-        chatbot.append(((image_path,), None))
-    return chatbot
-
-def user(text_prompt: str, chatbot: List[tuple]) -> Tuple[str, List[tuple]]:
-    if text_prompt:
-        chatbot.append((text_prompt, None))
-    return "", chatbot
-
-def bot(
-    files: Optional[List[str]],
-    model_choice: str,
-    system_instruction: Optional[str],
-    chatbot: List[tuple]
-):
-    if not GOOGLE_API_KEY:
-        raise ValueError("GOOGLE_API_KEY is not set.")
-
-    genai.configure(api_key=GOOGLE_API_KEY)
-    generation_config = genai.types.GenerationConfig(
-        temperature=0.7,
-        max_output_tokens=8192,
-        top_k=10,
-        top_p=0.9
-    )
-
-    if not system_instruction:
-        system_instruction = "No system instruction provided."
-
-    text_prompt = [chatbot[-1][0]] if chatbot and chatbot[-1][0] and isinstance(chatbot[-1][0], str) else []
-    image_prompt = [preprocess_image(Image.open(file).convert('RGB')) for file in files] if files else []
-    
-    model = genai.GenerativeModel(
-        model_name=model_choice,
-        generation_config=generation_config,
-        system_instruction=system_instruction
-    )
-
-    response = model.generate_content(text_prompt + image_prompt, stream=True, generation_config=generation_config)
-
-    chatbot[-1][1] = ""
-    for chunk in response:
-        for i in range(0, len(chunk.text), 10):
-            section = chunk.text[i:i + 10]
-            chatbot[-1][1] += section
-            time.sleep(0.01)
-            yield chatbot
-
-system_instruction_component = gr.Textbox(
-    placeholder="Enter system instruction...",
-    show_label=True,
-    scale=8
-)
-
-chatbot_component = gr.Chatbot(label='Gemini', bubble_full_width=False, scale=2, height=300)
-text_prompt_component = gr.Textbox(placeholder="Message...", show_label=False, autofocus=True, scale=8)
-upload_button_component = gr.UploadButton(label="Upload Images", file_count="multiple", file_types=["image"], scale=1)
-run_button_component = gr.Button(value="Run", variant="primary", scale=1)
-model_choice_component = gr.Dropdown(
-    choices=["gemini-1.5-flash", "gemini-2.0-flash-exp", "gemini-1.5-pro"],
-    value="gemini-1.5-flash",
-    label="Select Model",
-    scale=2
-)
-
-user_inputs = [text_prompt_component, chatbot_component]
-bot_inputs = [upload_button_component, model_choice_component, system_instruction_component, chatbot_component]
-
-with gr.Blocks() as demo:
-    gr.HTML("<h1 align='center'>Gemini Playground ✨</h1>")
-    gr.HTML("<h2 align='center'>Play with Gemini Pro and Gemini Pro Vision</h2>")
-    
-    with gr.Column():
-        model_choice_component.render()
-        chatbot_component.render()
-        with gr.Row():
-            text_prompt_component.render()
-            upload_button_component.render()
-            run_button_component.render()
-
-        with gr.Accordion("System Instruction", open=False):
-            system_instruction_component.render()
-
-    run_button_component.click(
-        fn=user,
-        inputs=user_inputs,
-        outputs=[text_prompt_component, chatbot_component],
-        queue=False
-    ).then(
-        fn=bot, inputs=bot_inputs, outputs=[chatbot_component],
-    )
-
-    text_prompt_component.submit(
-        fn=user,
-        inputs=user_inputs,
-        outputs=[text_prompt_component, chatbot_component],
-        queue=False
-    ).then(
-        fn=bot, inputs=bot_inputs, outputs=[chatbot_component],
-    )
-
-    upload_button_component.upload(
-        fn=upload,
-        inputs=[upload_button_component, chatbot_component],
-        outputs=[chatbot_component],
-        queue=False
-    )
-
-demo.queue(max_size=99).launch(debug=False, show_error=True)
+# Configurar la API de Gemini
+genai.configure(api_key=GOOGLE_API_KEY)
+
+# Inicializar el chat de Gemini
+chat = genai.Chat()
+
+# Transformar el historial de Gradio a formato compatible con Gemini
+def transform_history(history):
+    new_history = []
+    for chat in history:
+        new_history.append({"parts": [{"text": chat[0]}], "role": "user"})
+        new_history.append({"parts": [{"text": chat[1]}], "role": "model"})
+    return new_history
+
+# Función para generar una respuesta con Gemini
+def response(message, history):
+    global chat
+    # Actualizar el historial con el formato correcto
+    chat.history = transform_history(history)
+    # Enviar el mensaje a la API de Gemini
+    response = chat.send_message(message)
+    response.resolve()
+
+    # Mostrar la respuesta mientras se escribe
+    for i in range(len(response.text)):
+        time.sleep(0.05)
+        yield response.text[: i + 1]
+
+# Interfaz de usuario con Gradio
+gr.ChatInterface(response,
+                 title='Gemini Chat',
+                 textbox=gr.Textbox(placeholder="Pregunta a Gemini"),
+                 retry_btn=None).launch(debug=True)