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Update app.py
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app.py
CHANGED
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@@ -5,11 +5,11 @@ import os
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import time
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import uuid
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from typing import List, Tuple, Optional, Dict, Union
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import google.generativeai as genai
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import gradio as gr
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from PIL import Image
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from dotenv import load_dotenv
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# Cargar las variables de entorno desde el archivo .env
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load_dotenv()
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@@ -27,6 +27,7 @@ IMAGE_CACHE_DIRECTORY = "/tmp"
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IMAGE_WIDTH = 512
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CHAT_HISTORY = List[Tuple[Optional[Union[Tuple[str], str]], Optional[str]]]
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def preprocess_stop_sequences(stop_sequences: str) -> Optional[List[str]]:
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return [sequence.strip() for sequence in stop_sequences.split(",")] if stop_sequences else None
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@@ -47,7 +48,6 @@ def upload(files: Optional[List[str]], chatbot: CHAT_HISTORY) -> CHAT_HISTORY:
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image = Image.open(file).convert('RGB')
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image_preview = preprocess_image(image)
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if image_preview:
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# Display a preview of the uploaded image
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gr.Image(image_preview).render()
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image_path = cache_pil_image(image)
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chatbot.append(((image_path,), None))
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@@ -65,13 +65,18 @@ def bot(
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stop_sequences: str,
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top_k: int,
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top_p: float,
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chatbot: CHAT_HISTORY
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):
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if not GOOGLE_API_KEY:
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raise ValueError("GOOGLE_API_KEY is not set.")
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# Configurar la API con la clave
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genai.configure(api_key=GOOGLE_API_KEY)
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generation_config = genai.types.GenerationConfig(
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temperature=temperature,
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max_output_tokens=max_output_tokens,
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@@ -80,11 +85,9 @@ def bot(
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top_p=top_p
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)
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model = genai.GenerativeModel(model_name)
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response = model.generate_content(text_prompt + image_prompt, stream=True, generation_config=generation_config)
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chatbot[-1][1] = ""
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for chunk in response:
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@@ -94,67 +97,29 @@ def bot(
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time.sleep(0.01)
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yield chatbot
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text_prompt_component = gr.Textbox(
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placeholder="Message...", show_label=False, autofocus=True, scale=8
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)
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upload_button_component = gr.UploadButton(
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label="Upload Images", file_count="multiple", file_types=["image"], scale=1
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)
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run_button_component = gr.Button(value="Run", variant="primary", scale=1)
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temperature_component = gr.Slider(
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minimum=0,
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maximum=1.0,
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value=0.4,
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step=0.05,
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label="Temperature",
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)
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max_output_tokens_component = gr.Slider(
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minimum=1,
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maximum=2048,
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value=1024,
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step=1,
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label="Token limit",
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)
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stop_sequences_component = gr.Textbox(
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label="Add stop sequence",
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value="",
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type="text",
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placeholder="STOP, END",
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)
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top_k_component = gr.Slider(
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minimum=1,
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maximum=40,
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value=32,
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step=1,
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label="Top-K",
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)
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top_p_component = gr.Slider(
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minimum=0,
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maximum=1,
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value=1,
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step=0.01,
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label="Top-P",
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)
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]
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bot_inputs = [
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upload_button_component,
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max_output_tokens_component,
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stop_sequences_component,
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top_k_component,
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top_p_component,
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chatbot_component
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]
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with gr.Blocks() as demo:
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import time
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import uuid
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from typing import List, Tuple, Optional, Dict, Union
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import google.generativeai as genai
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import gradio as gr
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from PIL import Image
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from dotenv import load_dotenv
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from langdetect import detect
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# Cargar las variables de entorno desde el archivo .env
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load_dotenv()
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IMAGE_WIDTH = 512
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CHAT_HISTORY = List[Tuple[Optional[Union[Tuple[str], str]], Optional[str]]]
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# Preprocesamiento y configuraci贸n de secuencias y im谩genes
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def preprocess_stop_sequences(stop_sequences: str) -> Optional[List[str]]:
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return [sequence.strip() for sequence in stop_sequences.split(",")] if stop_sequences else None
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image = Image.open(file).convert('RGB')
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image_preview = preprocess_image(image)
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if image_preview:
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gr.Image(image_preview).render()
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image_path = cache_pil_image(image)
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chatbot.append(((image_path,), None))
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stop_sequences: str,
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top_k: int,
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top_p: float,
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model_name: str, # Recibimos el modelo seleccionado
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chatbot: CHAT_HISTORY
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):
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if not GOOGLE_API_KEY:
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raise ValueError("GOOGLE_API_KEY is not set.")
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genai.configure(api_key=GOOGLE_API_KEY)
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# Detectar el idioma del texto ingresado
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text_prompt = [chatbot[-1][0]] if chatbot and chatbot[-1][0] and isinstance(chatbot[-1][0], str) else []
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detected_language = detect(text_prompt[-1]) if text_prompt else 'en'
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generation_config = genai.types.GenerationConfig(
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temperature=temperature,
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max_output_tokens=max_output_tokens,
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top_p=top_p
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)
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# Configurar el modelo seleccionado
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model = genai.GenerativeModel(model_name) # Usamos el modelo seleccionado por el usuario
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response = model.generate_content(text_prompt + [], stream=True, generation_config=generation_config)
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chatbot[-1][1] = ""
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for chunk in response:
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time.sleep(0.01)
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yield chatbot
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# Dropdown para seleccionar el modelo
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model_dropdown = gr.Dropdown(
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label="Selecciona un modelo",
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choices=["gemini-1.5-flash", "gemini-2.0-flash-exp", "gemini-1.5-pro"], # Opciones de modelo
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value="gemini-1.5-flash", # Valor predeterminado
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type="value", # Valor que se selecciona
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)
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# Componente Gradio
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chatbot_component = gr.Chatbot(label='Gemini', bubble_full_width=False, scale=2, height=300)
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text_prompt_component = gr.Textbox(placeholder="Message...", show_label=False, autofocus=True, scale=8)
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upload_button_component = gr.UploadButton(label="Upload Images", file_count="multiple", file_types=["image"], scale=1)
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run_button_component = gr.Button(value="Run", variant="primary", scale=1)
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temperature_component = gr.Slider(minimum=0, maximum=1.0, value=0.4, step=0.05, label="Temperature")
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max_output_tokens_component = gr.Slider(minimum=1, maximum=2048, value=1024, step=1, label="Token limit")
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stop_sequences_component = gr.Textbox(label="Add stop sequence", value="", type="text", placeholder="STOP, END")
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top_k_component = gr.Slider(minimum=1, maximum=40, value=32, step=1, label="Top-K")
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top_p_component = gr.Slider(minimum=0, maximum=1, value=1, step=0.01, label="Top-P")
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user_inputs = [text_prompt_component, chatbot_component]
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bot_inputs = [
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upload_button_component, temperature_component, max_output_tokens_component,
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stop_sequences_component, top_k_component, top_p_component, model_dropdown, chatbot_component
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]
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with gr.Blocks() as demo:
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