import PIL.Image
import gradio as gr
import base64
import time
import os
import google.generativeai as genai

# Set Google API key
# os.environ['GOOGLE_API_KEY'] = 'YOUR_API_KEY'
genai.configure(api_key=os.environ['GOOGLE_API_KEY'])

# Create the Model
txt_model = genai.GenerativeModel('gemini-pro')
vis_model = genai.GenerativeModel('gemini-pro-vision')

# Image to Base 64 Converter
def image_to_base64(image_path):
    with open(image_path, 'rb') as img:
        encoded_string = base64.b64encode(img.read())
    return encoded_string.decode('utf-8')

# Function that takes user Inputs and displays it on ChatUI
def query_message(history, txt, img):
    if not img:
        history += [(txt, None)]
        return history
    base64 = image_to_base64(img)
    data_url = f"data:image/jpeg;base64,{base64}"
    history += [(f"{txt} ![]({data_url})", None)]
    return history

# Function that takes user Inputs, generates Response and displays it on ChatUI
def llm_response(history, text, img):
    if not img:
        response = txt_model.generate_content(text)
        history += [(None, response.text)]
    else:
        img = PIL.Image.open(img)
        response = vis_model.generate_content([text, img])
        history += [(None, response.text)]

    text = ''
    img = None
    return history, text, img

# Interface Code
with gr.Blocks(theme=gr.themes.Default()) as app:
    with gr.Row():
        image_box = gr.Image(type="filepath")

        chatbot = gr.Chatbot(
            scale = 2,
            height = 550
        )
    
    text_box = gr.Textbox(
        placeholder = "Enter text and press enter, or upload an image",
        container = False,
    )

    btn = gr.Button("Submit")
    clicked = btn.click(query_message,
                        [chatbot, text_box, image_box],
                        chatbot).then(llm_response,
                        [chatbot, text_box, image_box],
                        [chatbot, text_box, image_box])
    
app.queue()
app.launch()