Update app.py

app.py

@@ -1,10 +1,8 @@
 import streamlit as st
 from PIL import Image
-import cv2
 import os
 import base64
 import io
-import pandas as pd
 from dotenv import load_dotenv
 from groq import Groq
 from reportlab.lib.pagesizes import letter
@@ -22,7 +20,6 @@ PAGE_CONFIG = {
 }
 
 ALLOWED_FILE_TYPES = ['png', 'jpg', 'jpeg']
-ALLOWED_VIDEO_TYPES = ['mp4', 'avi', 'mov']
 
 CSS_STYLES = """
 <style>
@@ -82,13 +79,33 @@ def process_image_data(uploaded_file):
         st.error(f"Image processing error: {str(e)}")
         return None, None
 
-def generate_rice_report(image_data, img_format, client):
-    """Generate AI-powered rice quality analysis"""
-    if not image_data:
-        return 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("<b>Rice Quality Report</b>", styles['Title'])
+    story.append(title)
+    story.append(Spacer(1, 12))
     
-    image_url = f"data:image/{img_format.lower()};base64,{image_data}"
+    content = Paragraph(report_text.replace('\n', '<br/>'), 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",
@@ -96,12 +113,9 @@ def generate_rice_report(image_data, img_format, client):
                 "role": "user",
                 "content": [
                     {"type": "text", "text": (
-                        "Analyze the rice grain image and provide a detailed report including:",
-                        "Rice type classification",
-                        "Quality assessment (broken grains %, discoloration %, impurities %)",
-                        "Foreign object detection",
-                        "Size and shape consistency",
-                        "Recommendations for processing or improvement"
+                        "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}},
                 ]
@@ -115,42 +129,71 @@ def generate_rice_report(image_data, img_format, client):
         st.error(f"API communication error: {str(e)}")
         return None
 
-def format_report_as_table(report_text):
-    """Convert report text into structured table format"""
-    rows = [row.split(': ') for row in report_text.split('\n') if ': ' in row]
-    df = pd.DataFrame(rows, columns=["Category", "Details"])
-    return df
-
+# ======================
+# 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'<div class="report-container"><div class="report-text">{st.session_state.analysis_result}</div></div>', 
+            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.subheader("Upload Image")
-        uploaded_file = st.file_uploader("Select an image", type=ALLOWED_FILE_TYPES)
+        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:
-            base64_image, img_format = process_image_data(uploaded_file)
-            report = generate_rice_report(base64_image, img_format, client)
-            
-            if report:
-                st.session_state.analysis_result = report
-                st.rerun()
-    
-    if "analysis_result" in st.session_state:
-        st.markdown("### 📋 Analysis Report")
-        report_df = format_report_as_table(st.session_state.analysis_result)
-        st.table(report_df)
+            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()
+    main()