Update app.py

app.py

@@ -1,272 +1,272 @@
-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": "Radiology 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; }
-    .stSelectbox div[data-baseweb="select"],
-    .stSelectbox option,
-    .stSelectbox div[role="listbox"] div {
-        color: black !important;
-        background-color: #d1e7dd !important;
-    }
-    .stSelectbox svg { fill: black !important; }
-    .main-title { 
-        font-size: 88px; 
-        font-weight: bold; 
-        color: rgb(33, 238, 238); 
-    }
-    .sub-title { 
-        font-size: 100px; 
-        color: #6B6B6B; 
-        margin-top: -1px; 
-    }
-    .stButton>button { 
-        background-color: rgb(33, 225, 250); 
-        color: white; 
-        font-size: 69px; 
-    }
-    .stImage img { 
-        border-radius: 10px; 
-        box-shadow: 2px 2px 10px rgba(0,0,0,0.1); 
-    }
-    .logo { 
-        text-align: center; 
-        margin-bottom: 20px; 
-    }
-    .report-container {
-        background-color: #ffffff;
-        border-radius: 15px;
-        padding: 25px;
-        margin-top: 20px;
-        box-shadow: 0 4px 6px rgba(0, 0, 0, 0.1);
-        border-left: 5px solid #21eeef;
-    }
-    .report-text {
-        font-family: 'Courier New', monospace;
-        font-size: 16px;
-        line-height: 1.6;
-        color: #2c3e50;
-    }
-    .download-btn {
-        background-color: #21eeef !important;
-        color: white !important;
-        border: none !important;
-        border-radius: 8px !important;
-        padding: 12px 24px !important;
-    }
-</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 encode_logo(image_path):
-    """Encode logo image to base64"""
-    try:
-        with open(image_path, "rb") as img_file:
-            return base64.b64encode(img_file.read()).decode("utf-8")
-    except FileNotFoundError:
-        st.error("Logo image not found! Using placeholder.")
-        return ""
-
-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 = []
-    
-    # Add title
-    title = Paragraph("<b>Radiology Report</b>", styles['Title'])
-    story.append(title)
-    story.append(Spacer(1, 12))
-    
-    # Add report content
-    content = Paragraph(report_text.replace('\n', '<br/>'), styles['BodyText'])
-    story.append(content)
-    
-    doc.build(story)
-    buffer.seek(0)
-    return buffer
-
-def generate_radiology_report(uploaded_file, client):
-    """Generate AI-powered radiology 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": (
-                        "As an AI radiologist, provide a detailed structured report including: "
-                        "1. Imaging modality identification\n2. Anatomical structures visualized\n"
-                        "3. Abnormal findings description\n4. Differential diagnoses\n"
-                        "5. Clinical correlation recommendations"
-                    )},
-                    {"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"""
-    # Encode logo image
-    logo_b64 = encode_logo("src/radiology.png")
-    
-    # Center the logo and title using HTML and CSS
-    st.markdown(
-        f"""
-        <div style="text-align: center;">
-            <div class="logo">
-                <img src="data:image/png;base64,{logo_b64}" width="100">
-            </div>
-            <p class="main-title"> Radiology Analyzer</p>
-            <p class="sub-title">Advanced Medical Imaging Analysis</p>
-        </div>
-        """, 
-        unsafe_allow_html=True
-    )
-    
-    st.markdown("---")
-
-    # Action buttons
-    col1, col2 = st.columns([1, 1])
-    with col1:
-        if st.session_state.get('analysis_result'):
-            pdf_report = generate_pdf_report(st.session_state.analysis_result)
-            st.download_button(
-                label="📄 Download PDF Report",
-                data=pdf_report,
-                file_name="radiology_report.pdf",
-                mime="application/pdf",
-                use_container_width=True,
-                help="Download formal PDF version of the report",
-                key="download_pdf"
-            )
-
-    with col2:
-        if st.button("Clear Analysis 🗑️", use_container_width=True, help="Remove current results"):
-            st.session_state.pop('analysis_result')
-            st.rerun()
-
-    # Display analysis results
-    if st.session_state.get('analysis_result'):
-        st.markdown("### 🎯 Radiological Findings Report")
-        st.markdown(
-            f'<div class="report-container"><div class="report-text">{st.session_state.analysis_result}</div></div>', 
-            unsafe_allow_html=True
-        )
-
-def render_sidebar(client):
-    """Create sidebar interface elements"""
-    with st.sidebar:
-        st.divider()
-        st.markdown("### Diagnostic Capabilities")
-        st.markdown("""
-        - **Multi-Modality Analysis**: X-ray, MRI, CT, Ultrasound
-        - **Pathology Detection**: Fractures, tumors, infections
-        - **Comparative Analysis**: Track disease progression
-        - **Structured Reporting**: Standardized output format
-        - **Clinical Correlation**: Suggested next steps
-        - **Disclaimer: This service does not provide medical advice, consult a doctor for analysis and treatment
-        """)
-        st.divider()
-        
-        st.subheader("Image Upload Section")
-        uploaded_file = st.file_uploader(
-            "Select Medical Image", 
-            type=ALLOWED_FILE_TYPES,
-            help="Supported formats: PNG, JPG, JPEG"
-        )
-
-        if uploaded_file:
-            st.image(Image.open(uploaded_file), 
-                    caption="Uploaded Medical Image",
-                    use_container_width=True)
-
-            if st.button("Initiate Analysis 🔍", use_container_width=True):
-                with st.spinner("Analyzing image. This may take 20-30 seconds..."):
-                    report = generate_radiology_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__":
+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": "Radiology 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; }
+    .stSelectbox div[data-baseweb="select"],
+    .stSelectbox option,
+    .stSelectbox div[role="listbox"] div {
+        color: black !important;
+        background-color: #d1e7dd !important;
+    }
+    .stSelectbox svg { fill: black !important; }
+    .main-title { 
+        font-size: 88px; 
+        font-weight: bold; 
+        color: rgb(33, 238, 238); 
+    }
+    .sub-title { 
+        font-size: 100px; 
+        color: #6B6B6B; 
+        margin-top: -1px; 
+    }
+    .stButton>button { 
+        background-color: rgb(33, 225, 250); 
+        color: white; 
+        font-size: 69px; 
+    }
+    .stImage img { 
+        border-radius: 10px; 
+        box-shadow: 2px 2px 10px rgba(0,0,0,0.1); 
+    }
+    .logo { 
+        text-align: center; 
+        margin-bottom: 20px; 
+    }
+    .report-container {
+        background-color: #ffffff;
+        border-radius: 15px;
+        padding: 25px;
+        margin-top: 20px;
+        box-shadow: 0 4px 6px rgba(0, 0, 0, 0.1);
+        border-left: 5px solid #21eeef;
+    }
+    .report-text {
+        font-family: 'Courier New', monospace;
+        font-size: 16px;
+        line-height: 1.6;
+        color: #2c3e50;
+    }
+    .download-btn {
+        background-color: #21eeef !important;
+        color: white !important;
+        border: none !important;
+        border-radius: 8px !important;
+        padding: 12px 24px !important;
+    }
+</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 encode_logo(image_path):
+    """Encode logo image to base64"""
+    try:
+        with open(image_path, "rb") as img_file:
+            return base64.b64encode(img_file.read()).decode("utf-8")
+    except FileNotFoundError:
+        st.error("Logo image not found! Using placeholder.")
+        return ""
+
+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 = []
+    
+    # Add title
+    title = Paragraph("<b>Radiology Report</b>", styles['Title'])
+    story.append(title)
+    story.append(Spacer(1, 12))
+    
+    # Add report content
+    content = Paragraph(report_text.replace('\n', '<br/>'), styles['BodyText'])
+    story.append(content)
+    
+    doc.build(story)
+    buffer.seek(0)
+    return buffer
+
+def generate_radiology_report(uploaded_file, client):
+    """Generate AI-powered radiology 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-3.2-90b-vision-preview",
+            messages=[{
+                "role": "user",
+                "content": [
+                    {"type": "text", "text": (
+                        "As an AI radiologist, provide a detailed structured report including: "
+                        "1. Imaging modality identification\n2. Anatomical structures visualized\n"
+                        "3. Abnormal findings description\n4. Differential diagnoses\n"
+                        "5. Clinical correlation recommendations"
+                    )},
+                    {"type": "image_url", "image_url": {"url": image_url}},
+                ]
+            }],
+            temperature=0.2,
+            max_tokens=500,
+            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"""
+    # Encode logo image
+    logo_b64 = encode_logo("src/radiology.png")
+    
+    # Center the logo and title using HTML and CSS
+    st.markdown(
+        f"""
+        <div style="text-align: center;">
+            <div class="logo">
+                <img src="data:image/png;base64,{logo_b64}" width="100">
+            </div>
+            <p class="main-title"> Radiology Analyzer</p>
+            <p class="sub-title">Advanced Medical Imaging Analysis</p>
+        </div>
+        """, 
+        unsafe_allow_html=True
+    )
+    
+    st.markdown("---")
+
+    # Action buttons
+    col1, col2 = st.columns([1, 1])
+    with col1:
+        if st.session_state.get('analysis_result'):
+            pdf_report = generate_pdf_report(st.session_state.analysis_result)
+            st.download_button(
+                label="📄 Download PDF Report",
+                data=pdf_report,
+                file_name="radiology_report.pdf",
+                mime="application/pdf",
+                use_container_width=True,
+                help="Download formal PDF version of the report",
+                key="download_pdf"
+            )
+
+    with col2:
+        if st.button("Clear Analysis 🗑️", use_container_width=True, help="Remove current results"):
+            st.session_state.pop('analysis_result')
+            st.rerun()
+
+    # Display analysis results
+    if st.session_state.get('analysis_result'):
+        st.markdown("### 🎯 Radiological Findings Report")
+        st.markdown(
+            f'<div class="report-container"><div class="report-text">{st.session_state.analysis_result}</div></div>', 
+            unsafe_allow_html=True
+        )
+
+def render_sidebar(client):
+    """Create sidebar interface elements"""
+    with st.sidebar:
+        st.divider()
+        st.markdown("### Diagnostic Capabilities")
+        st.markdown("""
+        - **Multi-Modality Analysis**: X-ray, MRI, CT, Ultrasound
+        - **Pathology Detection**: Fractures, tumors, infections
+        - **Comparative Analysis**: Track disease progression
+        - **Structured Reporting**: Standardized output format
+        - **Clinical Correlation**: Suggested next steps
+        - **Disclaimer: This service does not provide medical advice, consult a doctor for analysis and treatment
+        """)
+        st.divider()
+        
+        st.subheader("Image Upload Section")
+        uploaded_file = st.file_uploader(
+            "Select Medical Image", 
+            type=ALLOWED_FILE_TYPES,
+            help="Supported formats: PNG, JPG, JPEG"
+        )
+
+        if uploaded_file:
+            st.image(Image.open(uploaded_file), 
+                    caption="Uploaded Medical Image",
+                    use_container_width=True)
+
+            if st.button("Initiate Analysis 🔍", use_container_width=True):
+                with st.spinner("Analyzing image. This may take 20-30 seconds..."):
+                    report = generate_radiology_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()