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| import streamlit as st | |
| import google.generativeai as genai | |
| from PIL import Image | |
| import io | |
| import os | |
| from typing import Optional | |
| # Configure page | |
| st.set_page_config( | |
| page_title="Image Q&A Assistant", | |
| page_icon="🖼️", | |
| layout="wide" | |
| ) | |
| # Language options for responses | |
| LANGUAGES = { | |
| "English": "en", | |
| "Spanish": "es", | |
| "French": "fr", | |
| "German": "de", | |
| "Italian": "it", | |
| "Portuguese": "pt", | |
| "Chinese": "zh", | |
| "Japanese": "ja", | |
| "Korean": "ko", | |
| "Arabic": "ar", | |
| "Hindi": "hi", | |
| "Russian": "ru" | |
| } | |
| def configure_gemini(): | |
| """Configure Gemini API using secrets""" | |
| try: | |
| api_key = st.secrets["GEMINI_API_KEY"] | |
| genai.configure(api_key=api_key) | |
| return True | |
| except KeyError: | |
| st.error("❌ GEMINI_API_KEY not found in secrets. Please add it to your Streamlit secrets.") | |
| return False | |
| except Exception as e: | |
| st.error(f"Failed to configure Gemini API: {str(e)}") | |
| return False | |
| def analyze_image_with_question(image: Image.Image, question: str, language: str) -> Optional[str]: | |
| """Analyze image and answer question using Gemini Vision""" | |
| try: | |
| # Configure the model | |
| model = genai.GenerativeModel('gemini-1.5-flash') | |
| # Prepare the prompt based on language | |
| language_instruction = "" | |
| if language != "en": | |
| lang_name = [k for k, v in LANGUAGES.items() if v == language][0] | |
| language_instruction = f"\n\nPlease respond in {lang_name}." | |
| prompt = f""" | |
| Analyze this image and answer the following question: {question} | |
| Please provide a detailed and accurate response based on what you can see in the image. | |
| If the question cannot be answered from the image content, please explain why. | |
| {language_instruction} | |
| """ | |
| # Generate response | |
| response = model.generate_content([prompt, image]) | |
| return response.text | |
| except Exception as e: | |
| return f"Error analyzing image: {str(e)}" | |
| def get_image_description(image: Image.Image, language: str) -> Optional[str]: | |
| """Get a general description of the image""" | |
| try: | |
| model = genai.GenerativeModel('gemini-1.5-flash') | |
| language_instruction = "" | |
| if language != "en": | |
| lang_name = [k for k, v in LANGUAGES.items() if v == language][0] | |
| language_instruction = f"\n\nPlease respond in {lang_name}." | |
| prompt = f""" | |
| Please provide a detailed description of this image. Include: | |
| - Main objects, people, or subjects visible | |
| - Colors, lighting, and composition | |
| - Setting or environment | |
| - Any text visible in the image | |
| - Overall mood or atmosphere | |
| Be thorough but concise in your description. | |
| {language_instruction} | |
| """ | |
| response = model.generate_content([prompt, image]) | |
| return response.text | |
| except Exception as e: | |
| return f"Error describing image: {str(e)}" | |
| def save_to_history(question: str, answer: str, language: str): | |
| """Save analysis to history""" | |
| if 'analysis_history' not in st.session_state: | |
| st.session_state.analysis_history = [] | |
| st.session_state.analysis_history.append({ | |
| 'question': question, | |
| 'answer': answer, | |
| 'language': language | |
| }) | |
| def main(): | |
| st.title("🖼️ Image Q&A Assistant") | |
| st.markdown("Upload an image and ask questions about it in multiple languages!") | |
| # Configure Gemini API from secrets | |
| api_configured = configure_gemini() | |
| # Sidebar for settings | |
| with st.sidebar: | |
| st.header("⚙️ Settings") | |
| # API Status | |
| if api_configured: | |
| st.success("✅ Gemini API configured successfully!") | |
| else: | |
| st.error("❌ Please configure GEMINI_API_KEY in secrets") | |
| st.markdown("---") | |
| # Language selection | |
| selected_language = st.selectbox( | |
| "Response Language", | |
| options=list(LANGUAGES.keys()), | |
| index=0, | |
| help="Choose the language for responses" | |
| ) | |
| st.markdown("---") | |
| # Quick question templates | |
| st.subheader("🚀 Quick Questions") | |
| quick_questions = [ | |
| "What's in this image?", | |
| "Describe the main objects", | |
| "What colors do you see?", | |
| "What is the setting/location?", | |
| "Are there any people in the image?", | |
| "What text is visible?", | |
| "What is the mood or atmosphere?", | |
| "Identify any brands or logos" | |
| ] | |
| for question in quick_questions: | |
| if st.button(question, key=f"quick_{question}"): | |
| st.session_state.quick_question = question | |
| # Main content area | |
| col1, col2 = st.columns([1, 1]) | |
| with col1: | |
| st.subheader("📤 Upload Image") | |
| uploaded_file = st.file_uploader( | |
| "Choose an image file", | |
| type=['png', 'jpg', 'jpeg', 'gif', 'bmp', 'webp'], | |
| help="Upload an image to analyze" | |
| ) | |
| if uploaded_file is not None: | |
| # Display the image | |
| image = Image.open(uploaded_file) | |
| st.image(image, caption="Uploaded Image", use_container_width=True) | |
| # Store image in session state | |
| st.session_state.current_image = image | |
| # Image info | |
| st.info(f"📊 Image size: {image.size[0]}x{image.size[1]} pixels") | |
| with col2: | |
| st.subheader("💬 Ask Questions") | |
| if 'current_image' in st.session_state and api_configured: | |
| # Question input | |
| question = st.text_area( | |
| "Your question about the image:", | |
| value=st.session_state.get('quick_question', ''), | |
| height=100, | |
| help="Ask anything about the uploaded image" | |
| ) | |
| # Clear quick question after use | |
| if 'quick_question' in st.session_state: | |
| del st.session_state.quick_question | |
| col_btn1, col_btn2 = st.columns([1, 1]) | |
| with col_btn1: | |
| analyze_btn = st.button("🔍 Analyze Image", type="primary") | |
| with col_btn2: | |
| describe_btn = st.button("📝 Describe Image") | |
| # Process requests | |
| if analyze_btn and question.strip(): | |
| with st.spinner("Analyzing image..."): | |
| result = analyze_image_with_question( | |
| st.session_state.current_image, | |
| question, | |
| LANGUAGES[selected_language] | |
| ) | |
| # Save to history | |
| save_to_history(question, result, selected_language) | |
| st.subheader("🎯 Analysis Result") | |
| st.write(result) | |
| elif describe_btn: | |
| with st.spinner("Describing image..."): | |
| description = get_image_description( | |
| st.session_state.current_image, | |
| LANGUAGES[selected_language] | |
| ) | |
| # Save to history | |
| save_to_history("General Description", description, selected_language) | |
| st.subheader("📋 Image Description") | |
| st.write(description) | |
| elif analyze_btn and not question.strip(): | |
| st.warning("⚠️ Please enter a question about the image.") | |
| elif 'current_image' not in st.session_state: | |
| st.info("📷 Please upload an image first.") | |
| elif not api_configured: | |
| st.warning("🔑 Please configure GEMINI_API_KEY in your Streamlit secrets.") | |
| # Results history (optional feature) | |
| if st.checkbox("📚 Show Analysis History"): | |
| if 'analysis_history' not in st.session_state: | |
| st.session_state.analysis_history = [] | |
| if st.session_state.analysis_history: | |
| st.subheader("📜 Previous Analyses") | |
| for i, item in enumerate(reversed(st.session_state.analysis_history[-5:])): | |
| with st.expander(f"Analysis {len(st.session_state.analysis_history) - i}"): | |
| st.write(f"**Question:** {item['question']}") | |
| st.write(f"**Answer:** {item['answer']}") | |
| st.write(f"**Language:** {item['language']}") | |
| else: | |
| st.info("No analysis history yet.") | |
| # Footer | |
| st.markdown("---") | |
| st.markdown( | |
| """ | |
| <div style='text-align: center; color: gray;'> | |
| Built with Streamlit and Google Gemini AI | | |
| Supports multiple languages and various image formats | |
| </div> | |
| """, | |
| unsafe_allow_html=True | |
| ) | |
| if __name__ == "__main__": | |
| # Initialize session state | |
| if 'analysis_history' not in st.session_state: | |
| st.session_state.analysis_history = [] | |
| main() | |