Upload 2 files
Browse files- app.py +271 -0
- requirements.txt +5 -0
app.py
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import streamlit as st
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from PIL import Image
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import os
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import base64
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import io
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from dotenv import load_dotenv
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from groq import Groq
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from reportlab.lib.pagesizes import letter
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from reportlab.platypus import SimpleDocTemplate, Paragraph, Spacer
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from reportlab.lib.styles import getSampleStyleSheet
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# ======================
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# CONFIGURATION SETTINGS
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# ======================
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PAGE_CONFIG = {
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"page_title": "Radiology Analyzer",
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"page_icon": "π©Ί",
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"layout": "wide",
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"initial_sidebar_state": "expanded"
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}
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ALLOWED_FILE_TYPES = ['png', 'jpg', 'jpeg']
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CSS_STYLES = """
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<style>
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.main { background-color: #f4f9f9; color: #000000; }
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.sidebar .sidebar-content { background-color: #d1e7dd; }
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.stTextInput textarea { color: #000000 !important; }
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.stSelectbox div[data-baseweb="select"],
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.stSelectbox option,
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.stSelectbox div[role="listbox"] div {
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color: black !important;
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background-color: #d1e7dd !important;
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}
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.stSelectbox svg { fill: black !important; }
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.main-title {
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font-size: 88px;
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font-weight: bold;
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color: rgb(33, 238, 238);
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}
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.sub-title {
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font-size: 100px;
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color: #6B6B6B;
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margin-top: -1px;
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}
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.stButton>button {
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background-color: rgb(33, 225, 250);
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color: white;
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font-size: 69px;
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}
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.stImage img {
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border-radius: 10px;
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box-shadow: 2px 2px 10px rgba(0,0,0,0.1);
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}
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.logo {
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text-align: center;
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margin-bottom: 20px;
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}
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.report-container {
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background-color: #ffffff;
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border-radius: 15px;
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padding: 25px;
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margin-top: 20px;
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box-shadow: 0 4px 6px rgba(0, 0, 0, 0.1);
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border-left: 5px solid #21eeef;
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}
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.report-text {
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font-family: 'Courier New', monospace;
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font-size: 16px;
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line-height: 1.6;
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color: #2c3e50;
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}
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.download-btn {
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background-color: #21eeef !important;
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color: white !important;
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border: none !important;
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border-radius: 8px !important;
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padding: 12px 24px !important;
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}
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</style>
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"""
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# ======================
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# CORE FUNCTIONS
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# ======================
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def configure_application():
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"""Initialize application settings and styling"""
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st.set_page_config(**PAGE_CONFIG)
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st.markdown(CSS_STYLES, unsafe_allow_html=True)
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def initialize_api_client():
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"""Create and validate Groq API client"""
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load_dotenv()
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api_key = os.getenv("GROQ_API_KEY")
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if not api_key:
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st.error("API key not found. Please verify .env configuration.")
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st.stop()
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return Groq(api_key=api_key)
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def encode_logo(image_path):
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"""Encode logo image to base64"""
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try:
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with open(image_path, "rb") as img_file:
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return base64.b64encode(img_file.read()).decode("utf-8")
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except FileNotFoundError:
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st.error("Logo image not found! Using placeholder.")
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return ""
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def process_image_data(uploaded_file):
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"""Convert image to base64 encoded string"""
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try:
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image = Image.open(uploaded_file)
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buffer = io.BytesIO()
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image.save(buffer, format=image.format)
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return base64.b64encode(buffer.getvalue()).decode('utf-8'), image.format
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except Exception as e:
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st.error(f"Image processing error: {str(e)}")
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return None, None
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def generate_pdf_report(report_text):
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"""Generate PDF document from report text"""
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buffer = io.BytesIO()
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doc = SimpleDocTemplate(buffer, pagesize=letter)
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styles = getSampleStyleSheet()
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story = []
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# Add title
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title = Paragraph("<b>Radiology Report</b>", styles['Title'])
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story.append(title)
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story.append(Spacer(1, 12))
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# Add report content
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content = Paragraph(report_text.replace('\n', '<br/>'), styles['BodyText'])
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story.append(content)
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doc.build(story)
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buffer.seek(0)
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return buffer
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def generate_radiology_report(uploaded_file, client):
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"""Generate AI-powered radiology analysis"""
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base64_image, img_format = process_image_data(uploaded_file)
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if not base64_image:
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return None
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image_url = f"data:image/{img_format.lower()};base64,{base64_image}"
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try:
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response = client.chat.completions.create(
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model="llama-3.2-11b-vision-preview",
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messages=[{
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"role": "user",
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"content": [
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{"type": "text", "text": (
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"As an AI radiologist, provide a detailed structured report including: "
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"1. Imaging modality identification\n2. Anatomical structures visualized\n"
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"3. Abnormal findings description\n4. Differential diagnoses\n"
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"5. Clinical correlation recommendations"
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)},
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{"type": "image_url", "image_url": {"url": image_url}},
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]
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}],
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temperature=0.2,
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max_tokens=400,
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+
top_p=0.5
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)
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return response.choices[0].message.content
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except Exception as e:
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st.error(f"API communication error: {str(e)}")
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return None
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+
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# ======================
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+
# UI COMPONENTS
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# ======================
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def display_main_interface():
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"""Render primary application interface"""
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# Encode logo image
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logo_b64 = encode_logo("src/radiology.png")
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# Center the logo and title using HTML and CSS
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st.markdown(
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f"""
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<div style="text-align: center;">
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<div class="logo">
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<img src="data:image/png;base64,{logo_b64}" width="100">
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</div>
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<p class="main-title"> Radiology Analyzer</p>
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<p class="sub-title">Advanced Medical Imaging Analysis</p>
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</div>
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""",
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unsafe_allow_html=True
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)
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+
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st.markdown("---")
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+
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# Action buttons
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col1, col2 = st.columns([1, 1])
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with col1:
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if st.session_state.get('analysis_result'):
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+
pdf_report = generate_pdf_report(st.session_state.analysis_result)
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st.download_button(
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label="π Download PDF Report",
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206 |
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data=pdf_report,
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207 |
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file_name="radiology_report.pdf",
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mime="application/pdf",
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use_container_width=True,
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help="Download formal PDF version of the report",
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key="download_pdf"
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)
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+
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with col2:
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if st.button("Clear Analysis ποΈ", use_container_width=True, help="Remove current results"):
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+
st.session_state.pop('analysis_result')
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st.rerun()
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# Display analysis results
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220 |
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if st.session_state.get('analysis_result'):
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st.markdown("### π― Radiological Findings Report")
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st.markdown(
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f'<div class="report-container"><div class="report-text">{st.session_state.analysis_result}</div></div>',
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224 |
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unsafe_allow_html=True
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)
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227 |
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def render_sidebar(client):
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"""Create sidebar interface elements"""
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with st.sidebar:
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st.divider()
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st.markdown("### Diagnostic Capabilities")
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st.markdown("""
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- **Multi-Modality Analysis**: X-ray, MRI, CT, Ultrasound
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- **Pathology Detection**: Fractures, tumors, infections
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- **Comparative Analysis**: Track disease progression
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- **Structured Reporting**: Standardized output format
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- **Clinical Correlation**: Suggested next steps
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""")
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st.divider()
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st.subheader("Image Upload Section")
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242 |
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uploaded_file = st.file_uploader(
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243 |
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"Select Medical Image",
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type=ALLOWED_FILE_TYPES,
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help="Supported formats: PNG, JPG, JPEG"
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)
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247 |
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if uploaded_file:
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st.image(Image.open(uploaded_file),
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caption="Uploaded Medical Image",
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use_container_width=True)
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252 |
+
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253 |
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if st.button("Initiate Analysis π", use_container_width=True):
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with st.spinner("Analyzing image. This may take 20-30 seconds..."):
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report = generate_radiology_report(uploaded_file, client)
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st.session_state.analysis_result = report
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st.rerun()
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258 |
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259 |
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# ======================
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260 |
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# APPLICATION ENTRYPOINT
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261 |
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# ======================
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262 |
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def main():
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263 |
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"""Primary application controller"""
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264 |
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configure_application()
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265 |
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groq_client = initialize_api_client()
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display_main_interface()
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render_sidebar(groq_client)
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270 |
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if __name__ == "__main__":
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main()
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requirements.txt
ADDED
@@ -0,0 +1,5 @@
|
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|
|
|
|
1 |
+
streamlit
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2 |
+
groq
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3 |
+
Pillow
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4 |
+
python-dotenv
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5 |
+
reportlab
|