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app.py

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+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 = """
+<style>
+    .main { background-color: #f4f9f9; color: #000000; }
+    .sidebar .sidebar-content { background-color: #d1e7dd; }
+    .stTextInput textarea { color: #000000 !important; }
+    .stButton>button { 
+        background-color: #21eeef; 
+        color: white; 
+        font-size: 16px; 
+        border-radius: 5px; 
+    }
+    .report-container {
+        background-color: #ffffff;
+        border-radius: 15px;
+        padding: 20px;
+        margin-top: 20px;
+        box-shadow: 0 4px 6px rgba(0, 0, 0, 0.1);
+        border-left: 5px solid #21eeef;
+    }
+    .report-text {
+        font-family: 'Arial', sans-serif;
+        font-size: 14px;
+        line-height: 1.6;
+        color: #2c3e50;
+    }
+</style>
+"""
+
+# ======================
+# 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("<b>Rice Quality Report</b>", styles['Title'])
+    story.append(title)
+    story.append(Spacer(1, 12))
+    
+    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",
+            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'<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.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()

requirements.txt

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+streamlit
+groq
+Pillow
+python-dotenv
+reportlab
+requests