import streamlit as st
from PIL import Image
import google.generativeai as genai
import io
import os
import base64

# Configure Google Gemini API (replace with your actual API key)
GOOGLE_API_KEY = os.environ.get("GOOGLE_API_KEY")
if not GOOGLE_API_KEY:
    st.error("Please set the GOOGLE_API_KEY environment variable.")
    st.stop()
genai.configure(api_key=GOOGLE_API_KEY)

# Function to generate the modified image
def generate_modified_image(uploaded_image, background_description):
    try:
        model = genai.GenerativeModel('gemini-1.5-flash')

        img = Image.open(uploaded_image)

        prompt_parts = [
            "You are an AI that can modify the background of an image based on a text description.",
            "Here is the image:",
            img,  # Pass the PIL Image object directly
            f"Modify the background of this image to: '{background_description}'. Be creative and make the new background look realistic and integrated with the foreground.",
            "Output only the modified image. Ensure the output is a valid image format (like PNG or JPEG) encoded as bytes."
        ]

        response = model.generate_content(prompt_parts, stream=False)
        response.resolve()

        if response and hasattr(response, 'parts') and len(response.parts) > 0:
            for part in response.parts:
                try:
                    # Try to get the image data directly if it's a blob
                    if hasattr(part, 'blob'):
                        image_bytes = part.blob.data
                        return Image.open(io.BytesIO(image_bytes))
                    elif hasattr(part, 'text'):
                        st.warning(f"Received text response instead of image: {part.text}")
                    else:
                        st.warning(f"Unexpected part type in response: {part}")
                except Exception as part_err:
                    st.error(f"Error processing response part: {part_err}")
            st.error("No valid image data found in the response.")
            return None
        else:
            st.error("Failed to get a valid response from the model.")
            return None

    except Exception as e:
        st.error(f"An error occurred during generation: {e}")
        return None

# Streamlit web app
st.title("Image Background Modifier")

uploaded_file = st.file_uploader("Upload an image...", type=["png", "jpg", "jpeg"])
background_text = st.text_area("Describe the desired background:", "")

if uploaded_file is not None and background_text:
    if st.button("Modify Background"):
        with st.spinner("Generating modified image..."):
            modified_image = generate_modified_image(uploaded_file, background_text)

        if modified_image:
            st.image(modified_image, caption="Modified Image", use_column_width=True)
else:
    st.info("Please upload an image and describe the desired background.")