import streamlit as st
import base64
import requests
import os
import random
import time

# Function to convert image to base64
def convert_image_to_base64(image):
    image_bytes = image.read()
    encoded_image = base64.b64encode(image_bytes).decode("utf-8")
    return encoded_image

# Function to generate a caption using Nebius API
def generate_caption(encoded_image):
    API_URL = "https://api.studio.nebius.ai/v1/chat/completions"
    API_KEY = os.environ.get("NEBIUS_API_KEY")

    headers = {
        "Authorization": f"Bearer {API_KEY}",
        "Content-Type": "application/json"
    }

    # Add a random string to the URL to prevent caching issues
    random_string = str(random.randint(100000, 999999))

    payload = {
        "model": "Qwen/Qwen2-VL-72B-Instruct",
        "messages": [
            {
                "role": "system",
                "content": """describe this image in great detail"""
            },
            {
                "role": "user",
                "content": "write a detailed caption for this image"
            }
        ],
        "image": {
            "type": "image_url",
            "image_url": {
                "url": f"data:image/png;base64,{encoded_image}?{random_string}"  # Added random query to avoid cache
            }
        },
        "temperature": 1
    }

    # Send request to API
    response = requests.post(API_URL, headers=headers, json=payload)

    if response.status_code == 200:
        result = response.json()
        caption = result.get("choices", [{}])[0].get("message", {}).get("content", "No caption generated.")
        return caption
    else:
        st.error(f"API Error {response.status_code}: {response.text}")
        return None

# Streamlit app
def main():
    st.set_page_config(page_title="Image to Caption Converter", layout="centered", initial_sidebar_state="collapsed")

    st.title("🖼️ Image to Caption Converter")
    st.markdown("Upload an image and let the AI generate a detailed caption for it.")

    uploaded_file = st.file_uploader("Upload an image", type=["jpg", "jpeg", "png"])

    if uploaded_file:
        # Display the uploaded image
        st.image(uploaded_file, caption="Uploaded Image", use_container_width=True)

        # Convert image to base64 and get caption
        if st.button("Generate Caption"):
            with st.spinner("Generating caption..."):
                encoded_image = convert_image_to_base64(uploaded_file)

                # Debugging: print out the base64 string length to verify if it's changing
                st.write(f"Encoded image length: {len(encoded_image)} characters")

                caption = generate_caption(encoded_image)

                if caption:
                    st.subheader("Generated Caption:")
                    st.text_area("", caption, height=100, key="caption_area")

                    # Copy button (if you want to implement this, use st.session_state)
                    st.button("Copy to Clipboard", on_click=lambda: st.session_state.update({"caption": caption}))

if __name__ == "__main__":
    main()