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| import streamlit as st | |
| from PIL import Image | |
| import torch | |
| from transformers import AutoModelForCausalLM, AutoTokenizer | |
| import os | |
| def load_model(): | |
| # Placeholder for model loading | |
| # In real implementation, you would load the Maya model here | |
| pass | |
| def process_image_text(image, text, language): | |
| # Placeholder for processing | |
| # In real implementation, this would use the Maya model | |
| pass | |
| def main(): | |
| st.set_page_config(page_title="Maya - Multilingual Vision Language Assistant", layout="wide") | |
| st.title("🌟 Maya: Multimodal Multilingual Assistant") | |
| st.markdown("Interact with images and text in multiple languages") | |
| # Sidebar for language selection | |
| languages = ["English", "Hindi", "Spanish", "French", "Chinese", "Arabic"] | |
| selected_language = st.sidebar.selectbox("Select Language", languages) | |
| # Main content area | |
| col1, col2 = st.columns(2) | |
| with col1: | |
| st.subheader("Upload Image") | |
| uploaded_file = st.file_uploader("Choose an image...", type=["jpg", "png", "jpeg"]) | |
| if uploaded_file is not None: | |
| image = Image.open(uploaded_file) | |
| st.image(image, caption="Uploaded Image", use_container_width=True) | |
| with col2: | |
| st.subheader("Enter Your Query") | |
| user_query = st.text_area("Type your question about the image...") | |
| if st.button("Process"): | |
| if uploaded_file is None: | |
| st.error("Please upload an image first!") | |
| elif not user_query: | |
| st.error("Please enter a query!") | |
| else: | |
| with st.spinner("Processing..."): | |
| try: | |
| response = process_image_text(image, user_query, selected_language) | |
| st.success("Processing Complete!") | |
| st.markdown("### Response:") | |
| st.write(response) | |
| except Exception as e: | |
| st.error(f"An error occurred: {str(e)}") | |
| # Footer | |
| st.markdown("---") | |
| st.markdown("Powered by Maya: Multimodal Multilingual LLM") | |
| if __name__ == "__main__": | |
| main() |