import streamlit as st from PIL import Image import os import base64 import io from dotenv import load_dotenv from groq import Groq from reportlab.lib.pagesizes import letter from reportlab.platypus import SimpleDocTemplate, Paragraph, Spacer from reportlab.lib.styles import getSampleStyleSheet # ====================== # CONFIGURATION SETTINGS # ====================== PAGE_CONFIG = { "page_title": "Rice Quality Analyzer", "page_icon": "🌾", "layout": "wide", "initial_sidebar_state": "expanded" } ALLOWED_FILE_TYPES = ['png', 'jpg', 'jpeg'] CSS_STYLES = """ """ # ====================== # CORE FUNCTIONS # ====================== def configure_application(): """Initialize application settings and styling""" st.set_page_config(**PAGE_CONFIG) st.markdown(CSS_STYLES, unsafe_allow_html=True) def initialize_api_client(): """Create and validate Groq API client""" load_dotenv() api_key = os.getenv("GROQ_API_KEY") if not api_key: st.error("API key not found. Please verify .env configuration.") st.stop() return Groq(api_key=api_key) def process_image_data(uploaded_file): """Convert image to base64 encoded string""" try: image = Image.open(uploaded_file) buffer = io.BytesIO() image.save(buffer, format=image.format) return base64.b64encode(buffer.getvalue()).decode('utf-8'), image.format except Exception as e: st.error(f"Image processing error: {str(e)}") return None, None def generate_pdf_report(report_text): """Generate PDF document from report text""" buffer = io.BytesIO() doc = SimpleDocTemplate(buffer, pagesize=letter) styles = getSampleStyleSheet() story = [] title = Paragraph("Rice Quality Report", styles['Title']) story.append(title) story.append(Spacer(1, 12)) content = Paragraph(report_text.replace('\n', '
'), styles['BodyText']) story.append(content) doc.build(story) buffer.seek(0) return buffer def generate_rice_report(uploaded_file, client): """Generate AI-powered rice quality analysis""" base64_image, img_format = process_image_data(uploaded_file) if not base64_image: return None image_url = f"data:image/{img_format.lower()};base64,{base64_image}" try: response = client.chat.completions.create( model="llama-3.2-11b-vision-preview", messages=[{ "role": "user", "content": [ {"type": "text", "text": ( "Analyze the rice grain image and provide a detailed report including:\n" "1. Rice type classification\n2. Quality assessment (broken grains %, discoloration %, impurities %)\n" "3. Foreign object detection\n4. Size and shape consistency\n5. Recommendations for processing or improvement" )}, {"type": "image_url", "image_url": {"url": image_url}}, ] }], temperature=0.2, max_tokens=400, top_p=0.5 ) return response.choices[0].message.content except Exception as e: st.error(f"API communication error: {str(e)}") return None # ====================== # UI COMPONENTS # ====================== def display_main_interface(): """Render primary application interface""" st.title("🌾 Rice Quality Analyzer") st.subheader("AI-Powered Rice Grain Inspection") st.markdown("---") # Display analysis results if st.session_state.get('analysis_result'): st.markdown("### 📋 Analysis Report") st.markdown( f'
{st.session_state.analysis_result}
', unsafe_allow_html=True ) pdf_report = generate_pdf_report(st.session_state.analysis_result) st.download_button( label="📄 Download PDF Report", data=pdf_report, file_name="rice_quality_report.pdf", mime="application/pdf" ) if st.button("Clear Analysis 🗑️"): st.session_state.pop('analysis_result', None) st.rerun() def render_sidebar(client): """Create sidebar interface elements""" with st.sidebar: st.markdown("### Features") st.markdown(""" - **Rice Type Classification** (e.g., Basmati, Jasmine, Indica) - **Quality Check** (Broken grains %, impurities %, discoloration %) - **Foreign Object Detection** (Husks, stones, debris) - **Grain Size & Shape Analysis** - **Processing Recommendations** """) st.markdown("---") st.subheader("Upload Rice Image") uploaded_file = st.file_uploader( "Select an image of rice grains", type=ALLOWED_FILE_TYPES ) if uploaded_file: st.image(Image.open(uploaded_file), caption="Uploaded Image", use_column_width=True) if st.button("Analyze Rice Quality 🔍"): with st.spinner("Processing image... This may take a few seconds."): report = generate_rice_report(uploaded_file, client) st.session_state.analysis_result = report st.rerun() # ====================== # APPLICATION ENTRYPOINT # ====================== def main(): """Primary application controller""" configure_application() groq_client = initialize_api_client() display_main_interface() render_sidebar(groq_client) if __name__ == "__main__": main()