Spaces:
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Sleeping
| """ | |
| Custom UI components for the homeopathic analyzer | |
| """ | |
| import streamlit as st | |
| from typing import Dict, List, Callable | |
| def render_header(): | |
| """Render application header""" | |
| st.set_page_config( | |
| page_title="Homeopathic Symptom Analyzer", | |
| page_icon="🌿", | |
| layout="wide" | |
| ) | |
| col1, col2 = st.columns([1, 4]) | |
| with col1: | |
| st.image("🌿", width=80) | |
| with col2: | |
| st.title("Homeopathic Symptom Analyzer AI") | |
| st.markdown("### Advanced Symptom Analysis & Remedy Matching") | |
| st.markdown("---") | |
| def render_sidebar() -> Dict: | |
| """Render sidebar with configuration options""" | |
| with st.sidebar: | |
| st.header("⚙️ Analysis Settings") | |
| # Search options | |
| st.subheader("Search Options") | |
| search_web = st.checkbox("Search Web Resources", value=False, | |
| help="Include web-based homeopathic resources") | |
| search_docs = st.checkbox("Search Internal Documents", value=True, | |
| help="Search in uploaded documents") | |
| # Analysis depth | |
| st.subheader("Analysis Depth") | |
| analysis_level = st.select_slider( | |
| "Analysis Detail", | |
| options=["Basic", "Standard", "Comprehensive", "Deep"], | |
| value="Comprehensive" | |
| ) | |
| # Upload documents | |
| st.subheader("📁 Document Upload") | |
| uploaded_files = st.file_uploader( | |
| "Upload medical documents (PDF, DOCX, TXT)", | |
| type=['pdf', 'docx', 'txt'], | |
| accept_multiple_files=True | |
| ) | |
| # Agent intelligence settings | |
| st.subheader("🤖 AI Agent Settings") | |
| agent_intelligence = st.select_slider( | |
| "Agent Intelligence Level", | |
| options=["Basic", "Intelligent", "Advanced", "Expert"], | |
| value="Intelligent", | |
| help="Higher levels provide more detailed reasoning" | |
| ) | |
| return { | |
| 'search_web': search_web, | |
| 'search_docs': search_docs, | |
| 'analysis_level': analysis_level, | |
| 'uploaded_files': uploaded_files, | |
| 'agent_intelligence': agent_intelligence | |
| } | |
| def render_case_sheet_form() -> Dict: | |
| """Render comprehensive case sheet form""" | |
| st.markdown("## 📋 Patient Case Sheet") | |
| with st.form("case_sheet_form"): | |
| # Patient information | |
| col1, col2 = st.columns(2) | |
| with col1: | |
| age = st.number_input("Age", min_value=0, max_value=120, value=30) | |
| gender = st.selectbox("Gender", ["Male", "Female", "Other"]) | |
| with col2: | |
| occupation = st.text_input("Occupation") | |
| constitution = st.selectbox("Constitution Type", | |
| ["Lean", "Stout", "Average", "Not Sure"]) | |
| # Main complaint | |
| st.subheader("Chief Complaint") | |
| main_complaint = st.text_area( | |
| "Describe your main health issue in detail", | |
| height=100, | |
| placeholder="Example: Severe headache on right side with throbbing pain..." | |
| ) | |
| # Symptom details | |
| st.subheader("Symptom Details") | |
| col1, col2, col3 = st.columns(3) | |
| with col1: | |
| st.markdown("**Location**") | |
| location = st.multiselect( | |
| "Where are symptoms located?", | |
| ["Head", "Stomach", "Chest", "Back", "Limbs", "Joints", "General"] | |
| ) | |
| with col2: | |
| st.markdown("**Sensation**") | |
| sensation = st.multiselect( | |
| "What does it feel like?", | |
| ["Burning", "Throbbing", "Stabbing", "Aching", "Pressing", "Numbness"] | |
| ) | |
| with col3: | |
| st.markdown("**Intensity**") | |
| intensity = st.slider("Pain/Symptom Intensity", 1, 10, 5) | |
| # Modalities | |
| st.subheader("Modalities") | |
| col1, col2 = st.columns(2) | |
| with col1: | |
| aggravations = st.text_area( | |
| "What makes it worse?", | |
| placeholder="Example: Motion, heat, noise, after eating..." | |
| ) | |
| with col2: | |
| ameliorations = st.text_area( | |
| "What makes it better?", | |
| placeholder="Example: Rest, pressure, cold applications..." | |
| ) | |
| # Time factors | |
| st.subheader("Timing") | |
| timing = st.text_area( | |
| "When do symptoms occur or change?", | |
| placeholder="Example: Worse in morning, better in evening, periodic every week..." | |
| ) | |
| # Emotional state | |
| st.subheader("Emotional & Mental State") | |
| emotional_state = st.text_area( | |
| "Describe emotional state, fears, anxieties", | |
| placeholder="Example: Anxious about health, irritable, fear of crowds..." | |
| ) | |
| # Generalities | |
| st.subheader("General Symptoms") | |
| generalities = st.text_area( | |
| "Other symptoms, food desires/aversions, thermal preferences", | |
| placeholder="Example: Thirst for cold water, aversion to fat, chilly..." | |
| ) | |
| # Submit button | |
| submit_button = st.form_submit_button("🚀 Analyze Symptoms") | |
| if submit_button: | |
| return { | |
| 'age': age, | |
| 'gender': gender, | |
| 'occupation': occupation, | |
| 'constitution': constitution, | |
| 'main_complaint': main_complaint, | |
| 'location': location, | |
| 'sensation': sensation, | |
| 'intensity': intensity, | |
| 'aggravations': aggravations, | |
| 'ameliorations': ameliorations, | |
| 'timing': timing, | |
| 'emotional_state': emotional_state, | |
| 'generalities': generalities | |
| } | |
| return None | |
| def render_remedy_results(results: List[Dict], analysis: Dict): | |
| """Render remedy matching results with detailed analysis""" | |
| st.markdown("## 🔍 Analysis Results") | |
| # Summary card | |
| with st.expander("📊 Analysis Summary", expanded=True): | |
| col1, col2, col3 = st.columns(3) | |
| with col1: | |
| st.metric("Key Symptoms Identified", len(analysis.get('key_symptoms', []))) | |
| with col2: | |
| st.metric("SRP Symptoms", len(analysis.get('strange_rare_peculiar', []))) | |
| with col3: | |
| st.metric("Top Match Score", f"{results[0]['score']:.1f}%" if results else "N/A") | |
| # Display each remedy result | |
| for i, result in enumerate(results[:5], 1): | |
| with st.expander(f"🏆 #{i}: {result['remedy']} ({result['score']:.1f}% Match)", expanded=i==1): | |
| # Header with match score | |
| col1, col2 = st.columns([3, 1]) | |
| with col1: | |
| st.subheader(result['remedy']) | |
| st.caption(result['data']['description']) | |
| with col2: | |
| st.metric("Match Score", f"{result['score']:.1f}%") | |
| # Tabs for different analyses | |
| tab1, tab2, tab3, tab4 = st.tabs(["Physical", "Modalities", "Constitutional", "Analysis"]) | |
| with tab1: | |
| st.markdown("### Physical Symptoms") | |
| for keynote in result['data']['keynotes']: | |
| st.markdown(f"• {keynote}") | |
| with tab2: | |
| st.markdown("### Modalities") | |
| col1, col2 = st.columns(2) | |
| with col1: | |
| st.markdown("**Aggravations:**") | |
| for agg in result['data']['modalities']['aggravations']: | |
| st.markdown(f"• {agg}") | |
| with col2: | |
| st.markdown("**Ameliorations:**") | |
| for amel in result['data']['modalities']['ameliorations']: | |
| st.markdown(f"• {amel}") | |
| # Modality match analysis | |
| if result['modality_match']['reasoning']: | |
| st.markdown("**Modality Match Analysis:**") | |
| for reason in result['modality_match']['reasoning']: | |
| st.success(f"✓ {reason}") | |
| with tab3: | |
| st.markdown("### Constitutional Profile") | |
| st.info(result['data']['constitutional']) | |
| st.markdown("### Emotional Profile") | |
| st.info(result['data']['emotional']) | |
| with tab4: | |
| st.markdown("### Detailed Analysis") | |
| st.markdown(result['detailed_analysis']) | |
| # Reasoning section | |
| st.markdown("#### Reasoning for Selection") | |
| st.markdown(""" | |
| 1. **Symptom Correspondence**: Key symptoms match remedy picture | |
| 2. **Modality Alignment**: Aggravations/ameliorations correspond | |
| 3. **Constitutional Fit**: Patient profile matches remedy type | |
| 4. **Emotional Match**: Mental/emotional state aligns | |
| """) | |
| st.divider() | |
| def render_agent_intelligence(analysis: Dict, settings: Dict): | |
| """Render AI agent's intelligent analysis""" | |
| st.markdown("## 🤖 AI Agent Analysis") | |
| with st.chat_message("assistant", avatar="🤖"): | |
| st.markdown("### Intelligent Symptom Analysis") | |
| # Generate intelligent analysis based on settings | |
| intelligence_level = settings.get('agent_intelligence', 'Intelligent') | |
| analysis_text = f""" | |
| Based on my analysis ({intelligence_level} mode), here's my assessment: | |
| **Primary Analysis:** | |
| - **Chief Complaint**: {analysis.get('physical_symptoms', [{}])[0].get('description', 'Not specified') if analysis.get('physical_symptoms') else 'Not specified'} | |
| - **Key Modalities**: {', '.join(analysis.get('modalities', {}).get('aggravations', [])[:3]) if analysis.get('modalities', {}).get('aggravations') else 'Not specified'} | |
| - **Emotional State**: {', '.join(analysis.get('emotional_state', {}).get('primary_emotions', [])) if analysis.get('emotional_state', {}).get('primary_emotions') else 'Not specified'} | |
| **Pattern Recognition:** | |
| """ | |
| if intelligence_level in ["Advanced", "Expert"]: | |
| analysis_text += """ | |
| - Detected potential miasmatic influence based on symptom patterns | |
| - Noticed characteristic symptom combinations suggesting specific remedy families | |
| - Identified paradoxical symptoms that are highly characteristic | |
| """ | |
| else: | |
| analysis_text += """ | |
| - Symptoms suggest acute inflammatory process | |
| - Modalities indicate thermal preferences | |
| - Emotional state aligns with common remedy pictures | |
| """ | |
| analysis_text += f""" | |
| **Recommendation Approach:** | |
| Based on the {intelligence_level} analysis, I'm considering: | |
| 1. Matching physical symptoms with modalities | |
| 2. Aligning constitutional factors | |
| 3. Considering emotional/mental state | |
| 4. Evaluating time factors and periodicity | |
| **Next Steps:** | |
| Consider consultation with a qualified homeopath for: | |
| - Potency selection | |
| - Repetition schedule | |
| - Constitutional follow-up | |
| """ | |
| st.markdown(analysis_text) | |
| def render_document_search_results(search_results: List[Dict]): | |
| """Render document search results""" | |
| if search_results: | |
| st.markdown("## 📚 Document Search Results") | |
| for result in search_results: | |
| with st.expander(f"📄 {result['document']}"): | |
| st.markdown(f"**Match**: `{result['match']}`") | |
| st.markdown(f"**Context**: {result['context']}") | |
| st.caption(f"Relevance: {result['relevance']:.2f}") | |
| else: | |
| st.info("No matches found in uploaded documents.") | |
| def render_disclaimer(): | |
| """Render medical disclaimer""" | |
| st.markdown("---") | |
| st.warning(""" | |
| **IMPORTANT DISCLAIMER**: This application is for educational and informational purposes only. | |
| It is not a substitute for professional medical advice, diagnosis, or treatment. | |
| Always consult a qualified homeopath or medical professional for health concerns. | |
| """) |