import google.generativeai as genai
import gradio as gr
import numpy as np
import PIL.Image
import pandas as pd
import io

genai.configure(api_key="AIzaSyA7tPavobVN5_3-BJ0qhFT5HVjO4V19QWk")

def ImageChat(image):
    # Configuración de la personalidad del sistema
    system_prompt = "Sólo puedes responder en idioma español: Sí o No."
    
    # Lista de preguntas preconfiguradas
    questions = [
        "¿La persona está utilizando auriculares?",
        "¿La persona está utilizando capucha o algo que le cubra la cabeza?",
        "¿Existe dinero como monedas o billetes que estén el piso?",
        "¿La persona se encuentra interactuando con su teléfono móvil?"
    ]

    # load model
    model = genai.GenerativeModel("gemini-1.5-flash")

    # check image file and convert to a Numpy array
    try:
        if isinstance(image, np.ndarray):
            img = PIL.Image.fromarray(image)
        else:
            img = image  # image is already a PIL.Image object
    except Exception as e:
        return str(e)

    # Initialize results list
    results = []

    # Process each question
    for question in questions:
        full_prompt = f"{system_prompt}\n\n{question}"
        response = model.generate_content([full_prompt, img])
        results.append(response.text)

    # Create a DataFrame to display results as a table
    df = pd.DataFrame({"Pregunta": questions, "Respuesta": results})

    return df

def load_image(image_path):
    with open(image_path, "rb") as image_file:
        return PIL.Image.open(io.BytesIO(image_file.read()))

# Preloaded images
preloaded_images = {
    "Imagen Ejemplo 1": "chat_with_image.png",
    "Imagen Ejemplo 2": "chatwithimg_2.jpg",
    "Imagen Ejemplo 3": "chatwithimg3.png"
}

def get_selected_image(image_name):
    return load_image(preloaded_images[image_name])

with gr.Blocks() as app:
    image_selector = gr.Radio(
        choices=list(preloaded_images.keys()),
        label="Selecciona una imagen"
    )

    image_display = gr.Image(label="Imagen", type="pil")

    def update_image(selected_image_name):
        image_data = get_selected_image(selected_image_name)
        return image_data

    image_selector.change(fn=update_image, inputs=image_selector, outputs=image_display)

    analyze_button = gr.Button("Analizar Imagen")

    results_display = gr.Dataframe(headers=["Pregunta", "Respuesta"], label="Resultados")

    def analyze_image(image):
        return ImageChat(image)

    analyze_button.click(fn=analyze_image, inputs=image_display, outputs=results_display)

app.launch()