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Muhammadidrees commited on Oct 23

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index.html +113 -19
pdfcode.py +875 -0
requirements.txt +5 -0
script.js +578 -0
styles.css +478 -0

index.html CHANGED Viewed

@@ -1,19 +1,113 @@
-<!doctype html>
-<html>
-	<head>
-		<meta charset="utf-8" />
-		<meta name="viewport" content="width=device-width" />
-		<title>My static Space</title>
-		<link rel="stylesheet" href="style.css" />
-	</head>
-	<body>
-		<div class="card">
-			<h1>Welcome to your static Space!</h1>
-			<p>You can modify this app directly by editing <i>index.html</i> in the Files and versions tab.</p>
-			<p>
-				Also don't forget to check the
-				<a href="https://huggingface.co/docs/hub/spaces" target="_blank">Spaces documentation</a>.
-			</p>
-		</div>
-	</body>
-</html>

+<!DOCTYPE html>
+<html lang="en">
+<head>
+    <meta charset="UTF-8">
+    <meta name="viewport" content="width=device-width, initial-scale=1.0">
+    <title>AI Doctor Consultation with Voice</title>
+    <link rel="stylesheet" href="styles.css">
+</head>
+<body>
+    <div class="notification" id="notification"></div>
+    <div class="container">
+        <div class="header">
+            <h1>🩺 AI Doctor Consultation</h1>
+            <p>Professional Medical Consultation with Voice & PDF Summary</p>
+            <div class="voice-controls">
+                <button class="voice-btn" id="continuousModeBtn" onclick="toggleContinuousMode()">
+                    <span class="voice-indicator"></span>
+                    <span>🔄 Continuous: OFF</span>
+                </button>
+                <button class="voice-btn" id="toggleAutoSpeak" onclick="toggleAutoSpeak()">
+                    <span class="voice-indicator" id="speakIndicator"></span>
+                    <span id="autoSpeakText">🔊 Auto-Speak: OFF</span>
+                </button>
+                <button class="voice-btn" id="voiceInputBtn" onclick="toggleVoiceInput()">
+                    🎤 Voice Input
+                </button>
+            </div>
+            <div class="voice-status" id="voiceStatus"></div>
+            <div class="session-info" id="sessionInfo">
+                Starting new session...
+            </div>
+            <div class="session-id-display" id="sessionIdDisplay" onclick="copySessionId()" title="Click to copy">
+                Session ID: Loading...
+            </div>
+        </div>
+        <div class="loading" id="loading">Dr. AI is typing...</div>
+        <div class="chat-container" id="chatContainer">
+            <!-- Messages will appear here -->
+        </div>
+        <div class="input-area">
+            <button class="btn btn-voice" id="voiceBtn" onclick="toggleVoiceInput()">
+                🎤
+            </button>
+            <input type="text" id="messageInput" placeholder="Type or speak your message..." />
+            <button class="btn btn-primary" onclick="sendMessage()">Send 📤</button>
+        </div>
+        <div class="controls">
+            <button class="btn btn-success" onclick="generateSummary()">📋 Generate Summary & PDF</button>
+            <button class="btn btn-info" onclick="showHistoryModal()">📜 Load History</button>
+            <button class="btn btn-secondary" onclick="restartSession()">🔄 Restart</button>
+        </div>
+    </div>
+    <!-- Summary Modal with PDF -->
+    <div class="modal" id="summaryModal">
+        <div class="modal-content">
+            <span class="close-btn" onclick="closeSummary()">&times;</span>
+            <h2>📋 Consultation Summary</h2>
+            <div id="pdfDownloadInfo" class="pdf-download-info" style="display: none;">
+                <div class="pdf-icon">📄</div>
+                <h3>PDF Generated Successfully!</h3>
+                <p>Your consultation summary has been saved as a PDF document.</p>
+            </div>
+            <div class="summary-actions">
+                <button class="btn btn-success" id="downloadPdfBtn" onclick="downloadPDF()" style="display: none;">
+                    📥 Download PDF
+                </button>
+                <button class="btn btn-info" id="viewPdfBtn" onclick="togglePDFViewer()" style="display: none;">
+                    👁️ View PDF
+                </button>
+            </div>
+            <div id="pdfViewerContainer" style="display: none;">
+                <h3 style="margin-top: 20px;">PDF Preview:</h3>
+                <iframe id="pdfViewer" class="pdf-viewer"></iframe>
+            </div>
+            <h3 style="margin-top: 20px;">Text Summary:</h3>
+            <pre id="summaryText"></pre>
+        </div>
+    </div>
+    <!-- History Modal -->
+    <div class="modal" id="historyModal">
+        <div class="modal-content">
+            <span class="close-btn" onclick="closeHistory()">&times;</span>
+            <h2>📜 Load Previous Consultation</h2>
+            <div class="load-session-form">
+                <input type="text" id="sessionIdInput" placeholder="Enter Session ID..." />
+                <button class="btn btn-primary" onclick="loadSessionById()">Load</button>
+            </div>
+            <h3>Recent Consultations:</h3>
+            <div class="history-list" id="historyList">
+                <p style="text-align: center; color: #999;">Loading history...</p>
+            </div>
+        </div>
+    </div>
+    <script src="script.js"></script>
+</body>
+</html>

pdfcode.py ADDED Viewed

	@@ -0,0 +1,875 @@

+from fastapi import FastAPI, HTTPException
+from fastapi.middleware.cors import CORSMiddleware
+from fastapi.responses import FileResponse
+from pydantic import BaseModel
+from typing import List, Optional, Dict
+import google.generativeai as genai
+import os
+from datetime import datetime
+import uuid
+import json
+from pathlib import Path
+from reportlab.lib.pagesizes import letter, A4
+from reportlab.lib.styles import getSampleStyleSheet, ParagraphStyle
+from reportlab.lib.units import inch
+from reportlab.platypus import SimpleDocTemplate, Paragraph, Spacer, PageBreak, Table, TableStyle
+from reportlab.lib import colors
+from reportlab.lib.enums import TA_CENTER, TA_LEFT, TA_JUSTIFY
+from reportlab.pdfgen import canvas
+# Configure Gemini API
+os.environ["GOOGLE_API_KEY"] = "AIzaSyDid3I53qFohhZTnLjnOjz4QqlvK4RZm7o"
+genai.configure(api_key=os.getenv("GOOGLE_API_KEY"))
+MODEL_ID = "gemini-2.0-flash-exp"
+# Create storage directories
+STORAGE_DIR = Path("consultation_storage")
+STORAGE_DIR.mkdir(exist_ok=True)
+PDF_DIR = Path("consultation_pdfs")
+PDF_DIR.mkdir(exist_ok=True)
+# System prompt (same as before)
+DOCTOR_SYSTEM_PROMPT = """
+You are Dr. HealBot, a calm, knowledgeable, and empathetic virtual doctor.
+GOAL:
+Hold a natural, focused conversation with the patient to understand their health issue and offer helpful preliminary medical guidance.
+CONVERSATION LOGIC:
+- Ask only relevant and concise medical questions necessary for diagnosing the illness.
+- Each question should help clarify symptoms or narrow possible causes.
+- Stop asking once enough information is collected for a basic assessment.
+- Then, provide a structured, friendly, and visually clear medical response using headings, emojis, and bullet points.
+FINAL RESPONSE FORMAT:
+When giving your full assessment, use this markdown-styled format:
+🩺 Based on what you've told me...
+Brief summary of what the patient described.
+💡 Possible Causes (Preliminary)
+- List 1–2 possible conditions using phrases like "It could be" or "This sounds like".
+- Include a disclaimer that this is not a confirmed diagnosis.
+💊 Suggested Over-the-Counter Medicines
+- Generic medicine names only (e.g., "Paracetamol 500mg every 6 hours if fever or pain")
+- Mention to check packaging or consult a pharmacist for dosage confirmation.
+🥗 Lifestyle & Home Care Tips
+- 2–3 practical suggestions (rest, hydration, warm compress, balanced diet, etc.)
+⚠ When to See a Real Doctor
+- 2–3 warning signs or conditions when urgent medical care is needed.
+📅 Follow-Up Advice
+- Brief recommendation for self-care or follow-up timing (e.g., "If not improving in 3 days, visit a clinic.")
+TONE & STYLE:
+- Speak like a real, caring doctor — short, clear, and empathetic (1–2 sentences per reply).
+- Use plain language, no jargon.
+- Only one question per turn unless clarification is essential.
+- Keep tone warm, calm, and professional.
+- Early messages: short questions only.
+- Final message: structured output with emojis and headings.
+IMPORTANT:
+- Always emphasize that this is preliminary guidance and not a substitute for professional care.
+- Never make definitive diagnoses; use phrases like "it sounds like" or "it could be".
+- If symptoms seem serious, always recommend urgent medical attention.
+CONVERSATION FLOW:
+1. Ask about the main symptom.
+2. Ask about its duration, severity, and any triggers.
+3. Ask about accompanying symptoms.
+4. Ask about medical history, allergies, or medications.
+5. Then, provide your structured assessment as described above.
+"""
+# =====================================================
+# PDF GENERATION FUNCTIONS
+# =====================================================
+def generate_pdf_summary(session_id: str, summary_text: str, patient_data: Dict, history: List[Dict]) -> str:
+    """Generate a professional PDF summary of the consultation"""
+    pdf_filename = f"{session_id}_summary.pdf"
+    pdf_path = PDF_DIR / pdf_filename
+    # Create PDF document
+    doc = SimpleDocTemplate(str(pdf_path), pagesize=letter,
+                           rightMargin=72, leftMargin=72,
+                           topMargin=72, bottomMargin=18)
+    # Container for the 'Flowable' objects
+    elements = []
+    # Define styles
+    styles = getSampleStyleSheet()
+    # Custom styles
+    title_style = ParagraphStyle(
+        'CustomTitle',
+        parent=styles['Heading1'],
+        fontSize=24,
+        textColor=colors.HexColor('#667eea'),
+        spaceAfter=30,
+        alignment=TA_CENTER,
+        fontName='Helvetica-Bold'
+    )
+    heading_style = ParagraphStyle(
+        'CustomHeading',
+        parent=styles['Heading2'],
+        fontSize=16,
+        textColor=colors.HexColor('#667eea'),
+        spaceAfter=12,
+        spaceBefore=12,
+        fontName='Helvetica-Bold'
+    )
+    normal_style = ParagraphStyle(
+        'CustomNormal',
+        parent=styles['Normal'],
+        fontSize=11,
+        spaceAfter=12,
+        alignment=TA_JUSTIFY,
+        leading=14
+    )
+    # Add Title
+    elements.append(Paragraph("🩺 AI DOCTOR CONSULTATION SUMMARY", title_style))
+    elements.append(Spacer(1, 0.3*inch))
+    # Add horizontal line
+    elements.append(Spacer(1, 0.1*inch))
+    # Patient Information Table
+    patient_info_data = [
+        ['Patient Name:', patient_data.get('name', 'N/A')],
+        ['Age:', patient_data.get('age', 'N/A')],
+        ['Session ID:', session_id[:20] + '...'],
+        ['Consultation Date:', datetime.now().strftime('%B %d, %Y at %I:%M %p')],
+        ['Total Messages:', str(len(history))]
+    ]
+    patient_table = Table(patient_info_data, colWidths=[2*inch, 4*inch])
+    patient_table.setStyle(TableStyle([
+        ('BACKGROUND', (0, 0), (0, -1), colors.HexColor('#f0f0f0')),
+        ('TEXTCOLOR', (0, 0), (-1, -1), colors.black),
+        ('ALIGN', (0, 0), (-1, -1), 'LEFT'),
+        ('FONTNAME', (0, 0), (0, -1), 'Helvetica-Bold'),
+        ('FONTNAME', (1, 0), (1, -1), 'Helvetica'),
+        ('FONTSIZE', (0, 0), (-1, -1), 10),
+        ('BOTTOMPADDING', (0, 0), (-1, -1), 8),
+        ('TOPPADDING', (0, 0), (-1, -1), 8),
+        ('GRID', (0, 0), (-1, -1), 1, colors.grey)
+    ]))
+    elements.append(patient_table)
+    elements.append(Spacer(1, 0.3*inch))
+    # Add Consultation Summary
+    elements.append(Paragraph("CONSULTATION SUMMARY", heading_style))
+    # Process summary text - split by lines and convert to paragraphs
+    summary_lines = summary_text.split('\n')
+    for line in summary_lines:
+        if line.strip():
+            # Replace emojis with text equivalents for PDF compatibility
+            line = line.replace('🩺', '[Medical] ')
+            line = line.replace('💡', '[Insight] ')
+            line = line.replace('💊', '[Medicine] ')
+            line = line.replace('🥗', '[Lifestyle] ')
+            line = line.replace('⚠️', '[Warning] ')
+            line = line.replace('⚠', '[Warning] ')
+            line = line.replace('📅', '[Follow-up] ')
+            line = line.replace('━', '-')
+            # Check if it's a heading (starts with **)
+            if line.strip().startswith('**') and line.strip().endswith('**'):
+                elements.append(Paragraph(line.strip('*'), heading_style))
+            else:
+                elements.append(Paragraph(line, normal_style))
+    elements.append(Spacer(1, 0.3*inch))
+    # Add Conversation History
+    elements.append(PageBreak())
+    elements.append(Paragraph("CONVERSATION HISTORY", heading_style))
+    elements.append(Spacer(1, 0.2*inch))
+    for i, msg in enumerate(history, 1):
+        role = "DOCTOR" if msg['role'] == 'assistant' else "PATIENT"
+        timestamp = msg.get('timestamp', 'N/A')
+        role_style = ParagraphStyle(
+            f'Role{i}',
+            parent=styles['Normal'],
+            fontSize=10,
+            textColor=colors.HexColor('#667eea') if role == "DOCTOR" else colors.HexColor('#28a745'),
+            fontName='Helvetica-Bold',
+            spaceAfter=4
+        )
+        elements.append(Paragraph(f"{role} ({timestamp}):", role_style))
+        content = msg['content'].replace('🩺', '').replace('💡', '').replace('💊', '')
+        content = content.replace('🥗', '').replace('⚠️', '').replace('⚠', '').replace('📅', '')
+        elements.append(Paragraph(content, normal_style))
+        elements.append(Spacer(1, 0.15*inch))
+    # Add disclaimer at the end
+    elements.append(Spacer(1, 0.3*inch))
+    disclaimer_style = ParagraphStyle(
+        'Disclaimer',
+        parent=styles['Normal'],
+        fontSize=9,
+        textColor=colors.red,
+        alignment=TA_CENTER,
+        fontName='Helvetica-Bold',
+        borderColor=colors.red,
+        borderWidth=1,
+        borderPadding=10,
+        spaceAfter=12
+    )
+    elements.append(Paragraph(
+        "⚠ IMPORTANT DISCLAIMER ⚠<br/>" +
+        "This is a preliminary AI-generated consultation for informational purposes only.<br/>" +
+        "It is NOT a substitute for professional medical advice, diagnosis, or treatment.<br/>" +
+        "Always seek the advice of a qualified healthcare provider with any questions regarding a medical condition.",
+        disclaimer_style
+    ))
+    # Build PDF
+    doc.build(elements)
+    return pdf_filename
+# =====================================================
+# STORAGE FUNCTIONS (same as before)
+# =====================================================
+def save_session_to_json(session_id: str, memory: 'ConversationMemory'):
+    """Save session data to JSON file"""
+    file_path = STORAGE_DIR / f"{session_id}.json"
+    session_data = {
+        "session_id": session_id,
+        "created_at": memory.created_at.isoformat(),
+        "last_updated": datetime.now().isoformat(),
+        "patient_data": memory.patient_data,
+        "questions_asked": memory.questions_asked,
+        "history": memory.history,
+        "message_count": len(memory.history),
+        "pdf_filename": getattr(memory, 'pdf_filename', None)
+    }
+    with open(file_path, 'w', encoding='utf-8') as f:
+        json.dump(session_data, f, indent=2, ensure_ascii=False)
+def load_session_from_json(session_id: str) -> Optional[Dict]:
+    """Load session data from JSON file"""
+    file_path = STORAGE_DIR / f"{session_id}.json"
+    if not file_path.exists():
+        return None
+    with open(file_path, 'r', encoding='utf-8') as f:
+        return json.load(f)
+def list_all_sessions() -> List[Dict]:
+    """List all stored sessions"""
+    sessions_list = []
+    for file_path in STORAGE_DIR.glob("*.json"):
+        try:
+            with open(file_path, 'r', encoding='utf-8') as f:
+                data = json.load(f)
+                sessions_list.append({
+                    "session_id": data["session_id"],
+                    "created_at": data["created_at"],
+                    "last_updated": data.get("last_updated", data["created_at"]),
+                    "patient_name": data["patient_data"].get("name", "Unknown"),
+                    "message_count": data["message_count"],
+                    "has_pdf": data.get("pdf_filename") is not None
+                })
+        except Exception as e:
+            print(f"Error reading {file_path}: {e}")
+    return sorted(sessions_list, key=lambda x: x["last_updated"], reverse=True)
+# =====================================================
+# MEMORY MANAGEMENT (same as before)
+# =====================================================
+class ConversationMemory:
+    """Manages short-term memory for each session"""
+    def __init__(self, max_messages: int = 20, session_id: str = None):
+        self.max_messages = max_messages
+        self.history = []
+        self.patient_data = {}
+        self.created_at = datetime.now()
+        self.questions_asked = 0
+        self.session_id = session_id
+        self.pdf_filename = None
+    def add_message(self, role: str, content: str):
+        """Add message to history with memory management"""
+        self.history.append({
+            "role": role,
+            "content": content,
+            "timestamp": datetime.now().isoformat()
+        })
+        if role == "assistant" and "?" in content:
+            self.questions_asked += 1
+        if len(self.history) > self.max_messages:
+            self.history = [self.history[0]] + self.history[-(self.max_messages-1):]
+        if self.session_id:
+            save_session_to_json(self.session_id, self)
+    def extract_patient_info(self, message: str):
+        """Extract and store patient information from conversation"""
+        message_lower = message.lower()
+        if any(word in message_lower for word in ["name is", "i'm", "i am", "im"]):
+            words = message.split()
+            for i, word in enumerate(words):
+                if word.lower() in ["is", "i'm", "am", "im"] and i + 1 < len(words):
+                    self.patient_data["name"] = words[i + 1].strip(".,!?")
+        if "year" in message_lower or "age" in message_lower:
+            import re
+            age_match = re.search(r'\b(\d{1,3})\b', message)
+            if age_match:
+                self.patient_data["age"] = age_match.group(1)
+        if "fever" in message_lower or "pain" in message_lower or "sick" in message_lower:
+            self.patient_data["has_symptoms"] = True
+    def should_give_recommendations(self) -> bool:
+        """Check if we should provide recommendations now"""
+        return (
+            self.questions_asked >= 7 or
+            self.patient_data.get("has_symptoms", False)
+        )
+    def get_context_summary(self) -> str:
+        """Generate a brief context summary for the AI"""
+        summary = "\n[Session Context: "
+        if "name" in self.patient_data:
+            summary += f"Name: {self.patient_data['name']}, "
+        if "age" in self.patient_data:
+            summary += f"Age: {self.patient_data['age']}, "
+        summary += f"Questions asked: {self.questions_asked}/7, "
+        if self.questions_asked >= 5:
+            summary += "⚠️ IMPORTANT: You've asked enough questions. After the next 1-2 answers, IMMEDIATELY provide comprehensive medical recommendations.]"
+        elif self.questions_asked >= 7:
+            summary += "⚠️ CRITICAL: You MUST provide comprehensive medical recommendations NOW. Do not ask more questions!]"
+        else:
+            summary += f"Ask {7 - self.questions_asked} more essential questions then give recommendations.]"
+        return summary
+    def get_gemini_history(self) -> List[Dict]:
+        """Convert history to Gemini format"""
+        gemini_history = []
+        for msg in self.history:
+            gemini_history.append({
+                "role": "user" if msg["role"] == "user" else "model",
+                "parts": [msg["content"]]
+            })
+        return gemini_history
+    @classmethod
+    def from_json(cls, session_data: Dict) -> 'ConversationMemory':
+        """Create ConversationMemory from JSON data"""
+        memory = cls(session_id=session_data["session_id"])
+        memory.history = session_data["history"]
+        memory.patient_data = session_data["patient_data"]
+        memory.questions_asked = session_data["questions_asked"]
+        memory.created_at = datetime.fromisoformat(session_data["created_at"])
+        memory.pdf_filename = session_data.get("pdf_filename")
+        return memory
+sessions: Dict[str, ConversationMemory] = {}
+def cleanup_old_sessions():
+    """Remove sessions older than 1 hour from memory"""
+    current_time = datetime.now()
+    expired_sessions = []
+    for session_id, memory in sessions.items():
+        age = (current_time - memory.created_at).total_seconds()
+        if age > 3600:
+            expired_sessions.append(session_id)
+    for session_id in expired_sessions:
+        del sessions[session_id]
+# =====================================================
+# FASTAPI APPLICATION
+# =====================================================
+app = FastAPI(
+    title="AI Doctor Consultation API with PDF Generation",
+    description="Professional medical consultation API with PDF summary generation",
+    version="3.0.0"
+)
+app.add_middleware(
+    CORSMiddleware,
+    allow_origins=["*"],
+    allow_credentials=True,
+    allow_methods=["*"],
+    allow_headers=["*"],
+)
+# Pydantic models
+class ChatRequest(BaseModel):
+    session_id: Optional[str] = None
+    message: str
+class ChatResponse(BaseModel):
+    session_id: str
+    response: str
+    timestamp: str
+    patient_data: Dict
+class SessionRequest(BaseModel):
+    session_id: str
+class SummaryResponse(BaseModel):
+    summary: str
+    session_id: str
+    pdf_filename: str
+    pdf_url: str
+class HealthCheck(BaseModel):
+    status: str
+    timestamp: str
+    active_sessions: int
+    stored_sessions: int
+    stored_pdfs: int
+# =====================================================
+# API ENDPOINTS
+# =====================================================
+@app.get("/", response_model=HealthCheck)
+async def root():
+    """Health check endpoint"""
+    cleanup_old_sessions()
+    stored_count = len(list(STORAGE_DIR.glob("*.json")))
+    pdf_count = len(list(PDF_DIR.glob("*.pdf")))
+    return {
+        "status": "healthy",
+        "timestamp": datetime.now().isoformat(),
+        "active_sessions": len(sessions),
+        "stored_sessions": stored_count,
+        "stored_pdfs": pdf_count
+    }
+@app.post("/start-session")
+async def start_session():
+    """Start a new consultation session"""
+    session_id = str(uuid.uuid4())
+    sessions[session_id] = ConversationMemory(max_messages=20, session_id=session_id)
+    initial_message = "Hello! I'm Dr. AI Assistant. I'm here to help you today.\n\n👤 May I have your name, please?"
+    sessions[session_id].add_message("assistant", initial_message)
+    return {
+        "session_id": session_id,
+        "message": initial_message,
+        "timestamp": datetime.now().isoformat()
+    }
+@app.post("/chat", response_model=ChatResponse)
+async def chat(request: ChatRequest):
+    """Send a message and get doctor's response"""
+    try:
+        if not request.session_id or request.session_id not in sessions:
+            session_id = str(uuid.uuid4())
+            sessions[session_id] = ConversationMemory(max_messages=20, session_id=session_id)
+        else:
+            session_id = request.session_id
+        memory = sessions[session_id]
+        memory.extract_patient_info(request.message)
+        memory.add_message("user", request.message)
+        context = memory.get_context_summary()
+        system_prompt = DOCTOR_SYSTEM_PROMPT + context
+        model = genai.GenerativeModel(
+            model_name=MODEL_ID,
+            system_instruction=system_prompt
+        )
+        chat = model.start_chat(history=memory.get_gemini_history()[:-1])
+        response = chat.send_message(request.message)
+        doctor_response = response.text
+        memory.add_message("assistant", doctor_response)
+        return {
+            "session_id": session_id,
+            "response": doctor_response,
+            "timestamp": datetime.now().isoformat(),
+            "patient_data": memory.patient_data
+        }
+    except Exception as e:
+        raise HTTPException(status_code=500, detail=f"Error: {str(e)}")
+@app.post("/summary", response_model=SummaryResponse)
+async def generate_summary(request: SessionRequest):
+    """Generate consultation summary and PDF"""
+    if request.session_id not in sessions:
+        session_data = load_session_from_json(request.session_id)
+        if not session_data:
+            raise HTTPException(status_code=404, detail="Session not found")
+        memory = ConversationMemory.from_json(session_data)
+        sessions[request.session_id] = memory
+    else:
+        memory = sessions[request.session_id]
+    summary_request = """Please generate a COMPREHENSIVE and DETAILED medical consultation summary based on our entire conversation. Make it thorough and professional:
+📋 **COMPREHENSIVE MEDICAL CONSULTATION SUMMARY**
+━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
+**PATIENT INFORMATION:**
+- Full Name: [Patient's name]
+- Age: [Patient's age if mentioned]
+- Gender: [If mentioned]
+- Consultation Date: [Current date and time]
+- Session Duration: [Approximate]
+- Current Medications: [List all mentioned]
+- Known Allergies: [If mentioned]
+**CHIEF COMPLAINTS & SYMPTOMS:**
+[Provide a detailed description of ALL symptoms mentioned, including:]
+- Primary symptom and severity
+- Duration of each symptom
+- Onset and progression
+- Associated symptoms
+- Aggravating and relieving factors
+- Impact on daily activities
+**DETAILED MEDICAL HISTORY:**
+[Include everything discussed:]
+- Current medications and dosages
+- Past medical conditions
+- Recent illnesses or infections
+- Family medical history (if mentioned)
+- Lifestyle factors (sleep, stress, diet)
+- Recent travel or exposures
+**CLINICAL ASSESSMENT:**
+[Provide detailed analysis:]
+- Most likely diagnosis with explanation
+- Differential diagnoses (2-3 possibilities)
+- Reasoning behind each possibility
+- Risk factors present
+- Severity assessment
+**COMPREHENSIVE TREATMENT PLAN:**
+1. **IMMEDIATE CARE RECOMMENDATIONS:**
+   - What to do in the next 24-48 hours
+   - Symptom management strategies
+   - Warning signs to watch for
+2. **MEDICATION RECOMMENDATIONS:**
+   - Primary medications (generic names, dosages, frequency, duration)
+   - Alternative options if first choice unavailable
+   - Potential side effects to monitor
+   - Drug interactions to avoid
+   - When to take each medication (with/without food)
+   - Important: Check with pharmacist for exact dosing
+3. **DETAILED DIETARY RECOMMENDATIONS:**
+   - Foods to eat (specific examples and portions)
+   - Foods to avoid completely
+   - Meal timing and frequency
+   - Hydration guidelines (specific amounts)
+   - Nutritional supplements if needed
+   - Sample meal plan for recovery
+4. **LIFESTYLE MODIFICATIONS:**
+   - Sleep recommendations (hours, timing, environment)
+   - Rest and activity balance
+   - Stress management techniques
+   - Environmental modifications
+   - Work/school attendance guidance
+   - Specific activities to avoid
+5. **HOME CARE REMEDIES:**
+   - Natural remedies that may help
+   - Temperature management techniques
+   - Pain relief methods
+   - Steam inhalation or other therapies
+   - Specific home treatments for symptoms
+6. **EXERCISE & PHYSICAL ACTIVITY:**
+   - Current activity restrictions
+   - Safe exercises during recovery
+   - When to resume normal activities
+   - Gradual activity progression plan
+   - Post-recovery exercise recommendations
+7. **PREVENTIVE MEASURES:**
+   - How to prevent recurrence
+   - Hygiene practices
+   - Vaccination recommendations
+   - Family/household precautions
+   - Long-term health maintenance
+8. **MONITORING PLAN:**
+   - Symptoms to track daily
+   - How to measure improvement
+   - When improvement should be expected
+   - What to document for doctor visit
+**CRITICAL WARNING SIGNS - SEEK IMMEDIATE MEDICAL ATTENTION IF:**
+[List 5-7 specific warning signs that require emergency care:]
+- [Specific symptom with threshold]
+- [Specific symptom with threshold]
+- [Continue with detailed warnings]
+**FOLLOW-UP CARE PLAN:**
+- Timeline for self-care (e.g., "Monitor for 48 hours")
+- When to schedule doctor appointment (specific timeframe)
+- What information to bring to doctor
+- Specialist referral recommendations if needed
+- Follow-up testing that may be needed
+**PROGNOSIS & EXPECTED RECOVERY:**
+- Expected recovery timeline
+- What to expect during recovery process
+- Signs of improvement to look for
+- Long-term outlook
+**ADDITIONAL RESOURCES:**
+- Reputable health information sources
+- Support resources if applicable
+- Emergency contact information reminder
+**PATIENT EDUCATION:**
+- Understanding your condition
+- How the body fights this illness
+- Why specific recommendations are important
+- Common misconceptions about this condition
+━━━━━━━��━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
+⚠️ **CRITICAL DISCLAIMER** ⚠️
+This is a preliminary AI-generated consultation for informational and educational purposes ONLY.
+This is NOT a substitute for professional medical advice, diagnosis, or treatment.
+This AI cannot examine you physically, run laboratory tests, or make definitive diagnoses.
+ALWAYS seek the advice of a qualified, licensed healthcare provider with any questions regarding a medical condition.
+Never disregard professional medical advice or delay seeking it because of this AI consultation.
+In case of emergency, call your local emergency services immediately.
+━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
+Please make this summary as detailed, professional, and helpful as possible. Include specific, actionable advice."""
+    try:
+        model = genai.GenerativeModel(
+            model_name=MODEL_ID,
+            system_instruction=DOCTOR_SYSTEM_PROMPT
+        )
+        chat = model.start_chat(history=memory.get_gemini_history())
+        response = chat.send_message(summary_request)
+        summary_text = response.text
+        # Generate PDF
+        pdf_filename = generate_pdf_summary(
+            request.session_id,
+            summary_text,
+            memory.patient_data,
+            memory.history
+        )
+        # Save PDF filename to memory
+        memory.pdf_filename = pdf_filename
+        save_session_to_json(request.session_id, memory)
+        return {
+            "summary": summary_text,
+            "session_id": request.session_id,
+            "pdf_filename": pdf_filename,
+            "pdf_url": f"/download-pdf/{request.session_id}"
+        }
+    except Exception as e:
+        raise HTTPException(status_code=500, detail=f"Error generating summary: {str(e)}")
+@app.get("/download-pdf/{session_id}")
+async def download_pdf(session_id: str):
+    """Download PDF summary for a session"""
+    # Check if session exists
+    if session_id in sessions:
+        memory = sessions[session_id]
+    else:
+        session_data = load_session_from_json(session_id)
+        if not session_data:
+            raise HTTPException(status_code=404, detail="Session not found")
+        memory = ConversationMemory.from_json(session_data)
+    if not memory.pdf_filename:
+        raise HTTPException(status_code=404, detail="PDF not generated yet. Please generate summary first.")
+    pdf_path = PDF_DIR / memory.pdf_filename
+    if not pdf_path.exists():
+        raise HTTPException(status_code=404, detail="PDF file not found")
+    patient_name = memory.patient_data.get('name', 'Patient')
+    download_filename = f"Consultation_Summary_{patient_name}_{datetime.now().strftime('%Y%m%d')}.pdf"
+    return FileResponse(
+        path=str(pdf_path),
+        media_type='application/pdf',
+        filename=download_filename
+    )
+@app.get("/load-session/{session_id}")
+async def load_session(session_id: str):
+    """Load a previous consultation session by ID"""
+    if session_id in sessions:
+        memory = sessions[session_id]
+        return {
+            "session_id": session_id,
+            "loaded": True,
+            "from_cache": True,
+            "history": memory.history,
+            "patient_data": memory.patient_data,
+            "created_at": memory.created_at.isoformat(),
+            "questions_asked": memory.questions_asked,
+            "has_pdf": memory.pdf_filename is not None,
+            "pdf_url": f"/download-pdf/{session_id}" if memory.pdf_filename else None
+        }
+    session_data = load_session_from_json(session_id)
+    if not session_data:
+        raise HTTPException(status_code=404, detail=f"Session {session_id} not found")
+    memory = ConversationMemory.from_json(session_data)
+    sessions[session_id] = memory
+    return {
+        "session_id": session_id,
+        "loaded": True,
+        "from_cache": False,
+        "history": memory.history,
+        "patient_data": memory.patient_data,
+        "created_at": memory.created_at.isoformat(),
+        "questions_asked": memory.questions_asked,
+        "has_pdf": memory.pdf_filename is not None,
+        "pdf_url": f"/download-pdf/{session_id}" if memory.pdf_filename else None,
+        "message": "Session loaded successfully. You can continue the conversation."
+    }
+@app.get("/all-sessions")
+async def get_all_sessions():
+    """Get list of all stored consultation sessions"""
+    return {
+        "total_sessions": len(list(STORAGE_DIR.glob("*.json"))),
+        "sessions": list_all_sessions()
+    }
+@app.post("/restart-session")
+async def restart_session(request: SessionRequest):
+    """Restart a consultation session"""
+    if request.session_id in sessions:
+        del sessions[request.session_id]
+    sessions[request.session_id] = ConversationMemory(max_messages=20, session_id=request.session_id)
+    initial_message = "Consultation restarted. Hello! I'm Dr. AI Assistant. May I have your name please?"
+    sessions[request.session_id].add_message("assistant", initial_message)
+    return {
+        "session_id": request.session_id,
+        "message": initial_message,
+        "timestamp": datetime.now().isoformat()
+    }
+@app.delete("/session/{session_id}")
+async def delete_session(session_id: str):
+    """Delete a consultation session (from memory, JSON, and PDF)"""
+    if session_id in sessions:
+        memory = sessions[session_id]
+        pdf_filename = memory.pdf_filename
+        del sessions[session_id]
+    else:
+        session_data = load_session_from_json(session_id)
+        pdf_filename = session_data.get('pdf_filename') if session_data else None
+    # Remove JSON file
+    file_path = STORAGE_DIR / f"{session_id}.json"
+    if file_path.exists():
+        file_path.unlink()
+    # Remove PDF file if exists
+    if pdf_filename:
+        pdf_path = PDF_DIR / pdf_filename
+        if pdf_path.exists():
+            pdf_path.unlink()
+    return {"message": "Session and associated files deleted successfully"}
+@app.get("/session/{session_id}/history")
+async def get_session_history(session_id: str):
+    """Get conversation history for a session"""
+    if session_id in sessions:
+        memory = sessions[session_id]
+    else:
+        session_data = load_session_from_json(session_id)
+        if not session_data:
+            raise HTTPException(status_code=404, detail="Session not found")
+        memory = ConversationMemory.from_json(session_data)
+    return {
+        "session_id": session_id,
+        "history": memory.history,
+        "patient_data": memory.patient_data,
+        "created_at": memory.created_at.isoformat(),
+        "questions_asked": memory.questions_asked,
+        "has_pdf": memory.pdf_filename is not None
+    }
+@app.get("/active-sessions")
+async def get_active_sessions():
+    """Get list of all active sessions in memory"""
+    cleanup_old_sessions()
+    return {
+        "active_sessions": len(sessions),
+        "sessions": [
+            {
+                "session_id": sid,
+                "created_at": mem.created_at.isoformat(),
+                "message_count": len(mem.history),
+                "questions_asked": mem.questions_asked,
+                "patient_data": mem.patient_data,
+                "has_pdf": mem.pdf_filename is not None
+            }
+            for sid, mem in sessions.items()
+        ]
+    }
+if __name__ == "__main__":
+    import uvicorn
+    uvicorn.run(app, host="0.0.0.0", port=8000)

requirements.txt ADDED Viewed

	@@ -0,0 +1,5 @@

+fastapi==0.115.0
+uvicorn[standard]==0.32.0
+google-generativeai==0.8.3
+pydantic==2.9.2
+python-multipart==0.0.12

script.js ADDED Viewed

	@@ -0,0 +1,578 @@

+const API_URL = 'http://localhost:8000';
+let sessionId = null;
+let patientData = {};
+let currentPdfUrl = null;
+// Voice recognition variables
+let recognition = null;
+let isRecording = false;
+let autoSpeak = false;
+let currentUtterance = null;
+let isSpeaking = false;
+let continuousMode = false;
+// Initialize Speech Recognition
+function initSpeechRecognition() {
+    if ('webkitSpeechRecognition' in window || 'SpeechRecognition' in window) {
+        const SpeechRecognition = window.SpeechRecognition || window.webkitSpeechRecognition;
+        recognition = new SpeechRecognition();
+        recognition.continuous = false;
+        recognition.interimResults = false;
+        recognition.lang = 'en-US';
+        recognition.onstart = function() {
+            isRecording = true;
+            document.getElementById('voiceBtn').classList.add('recording');
+            document.getElementById('voiceInputBtn').classList.add('active');
+            updateVoiceStatus('🎤 Listening... Speak now');
+        };
+        recognition.onresult = function(event) {
+            const transcript = event.results[0][0].transcript;
+            document.getElementById('messageInput').value = transcript;
+            updateVoiceStatus('✓ Voice input received: "' + transcript + '"');
+            // In continuous mode, automatically send the message
+            if (continuousMode) {
+                setTimeout(() => {
+                    sendMessage();
+                }, 500);
+            } else {
+                setTimeout(() => hideVoiceStatus(), 2000);
+            }
+        };
+        recognition.onerror = function(event) {
+            console.error('Speech recognition error:', event.error);
+            updateVoiceStatus('❌ Error: ' + event.error, 'error');
+            stopRecording();
+            // Restart listening in continuous mode if it wasn't a user abort
+            if (continuousMode && event.error !== 'aborted' && event.error !== 'no-speech') {
+                setTimeout(() => {
+                    if (continuousMode && !isSpeaking) {
+                        startListening();
+                    }
+                }, 1000);
+            }
+        };
+        recognition.onend = function() {
+            stopRecording();
+            // Restart listening in continuous mode after a brief pause
+            if (continuousMode && !isSpeaking) {
+                setTimeout(() => {
+                    if (continuousMode) {
+                        startListening();
+                    }
+                }, 500);
+            }
+        };
+    } else {
+        showNotification('Voice recognition not supported in this browser', 'error');
+    }
+}
+function startListening() {
+    if (!recognition) {
+        initSpeechRecognition();
+    }
+    if (!isRecording) {
+        try {
+            recognition.start();
+        } catch (e) {
+            console.error('Error starting recognition:', e);
+        }
+    }
+}
+function toggleVoiceInput() {
+    if (!recognition) {
+        initSpeechRecognition();
+    }
+    if (isRecording) {
+        recognition.stop();
+    } else {
+        startListening();
+    }
+}
+function stopRecording() {
+    isRecording = false;
+    document.getElementById('voiceBtn').classList.remove('recording');
+    document.getElementById('voiceInputBtn').classList.remove('active');
+}
+function updateVoiceStatus(message, type = 'info') {
+    const status = document.getElementById('voiceStatus');
+    status.textContent = message;
+    status.className = 'voice-status active';
+    if (type === 'error') {
+        status.style.background = '#ffebee';
+        status.style.color = '#c62828';
+    } else {
+        status.style.background = '#e3f2fd';
+        status.style.color = '#1565c0';
+    }
+}
+function hideVoiceStatus() {
+    document.getElementById('voiceStatus').classList.remove('active');
+}
+// Text-to-Speech functions
+function speakText(text) {
+    if (!('speechSynthesis' in window)) {
+        console.error('Speech synthesis not supported');
+        showNotification('Text-to-speech not supported in this browser', 'error');
+        return;
+    }
+    if (isSpeaking) {
+        window.speechSynthesis.cancel();
+    }
+    let cleanText = text
+        .replace(/🩺|💡|💊|🥗|⚠️|⚠|📅|🎯|📊|🛡️|🏃|👤/g, '')
+        .replace(/━+/g, '')
+        .replace(/\*\*/g, '')
+        .replace(/\n{3,}/g, '\n\n');
+    currentUtterance = new SpeechSynthesisUtterance(cleanText);
+    currentUtterance.rate = 0.85;
+    currentUtterance.pitch = 1.1;
+    currentUtterance.volume = 1;
+    currentUtterance.lang = 'en-US';
+    const voices = window.speechSynthesis.getVoices();
+    if (voices.length > 0) {
+        const preferredVoice = voices.find(voice =>
+            (voice.lang.includes('en-US') || voice.lang.includes('en-GB')) &&
+            (voice.name.includes('Female') ||
+             voice.name.includes('Samantha') ||
+             voice.name.includes('Victoria') ||
+             voice.name.includes('Google') ||
+             voice.name.includes('Microsoft'))
+        ) || voices.find(voice => voice.lang.includes('en')) || voices[0];
+        currentUtterance.voice = preferredVoice;
+    }
+    currentUtterance.onstart = function() {
+        isSpeaking = true;
+    };
+    currentUtterance.onend = function() {
+        isSpeaking = false;
+        // In continuous mode, start listening again after doctor finishes speaking
+        if (continuousMode) {
+            setTimeout(() => {
+                if (continuousMode && !isRecording) {
+                    startListening();
+                }
+            }, 500);
+        }
+    };
+    currentUtterance.onerror = function(event) {
+        console.error('Speech synthesis error:', event);
+        isSpeaking = false;
+        if (event.error !== 'interrupted') {
+            showNotification('Speech error: ' + event.error, 'error');
+        }
+    };
+    setTimeout(() => {
+        window.speechSynthesis.speak(currentUtterance);
+    }, 100);
+}
+function stopSpeaking() {
+    window.speechSynthesis.cancel();
+    isSpeaking = false;
+}
+function toggleAutoSpeak() {
+    autoSpeak = !autoSpeak;
+    const indicator = document.getElementById('speakIndicator');
+    const text = document.getElementById('autoSpeakText');
+    if (autoSpeak) {
+        indicator.style.background = '#4CAF50';
+        text.textContent = '🔊 Auto-Speak: ON';
+        showNotification('Auto-speak enabled - Doctor responses will be spoken', 'success');
+    } else {
+        indicator.style.background = '#999';
+        text.textContent = '🔊 Auto-Speak: OFF';
+        stopSpeaking();
+        showNotification('Auto-speak disabled', 'info');
+    }
+}
+function toggleContinuousMode() {
+    continuousMode = !continuousMode;
+    const btn = document.getElementById('continuousModeBtn');
+    if (continuousMode) {
+        btn.classList.add('active');
+        btn.innerHTML = '<span class="voice-indicator recording"></span><span>🔄 Continuous: ON</span>';
+        autoSpeak = true;
+        toggleAutoSpeak(); // Enable auto-speak
+        showNotification('Continuous conversation mode enabled! Speak naturally.', 'success');
+        startListening();
+    } else {
+        btn.classList.remove('active');
+        btn.innerHTML = '<span class="voice-indicator"></span><span>🔄 Continuous: OFF</span>';
+        showNotification('Continuous mode disabled', 'info');
+        if (isRecording) {
+            recognition.stop();
+        }
+    }
+}
+window.onload = async () => {
+    await startNewSession();
+    initSpeechRecognition();
+    if ('speechSynthesis' in window) {
+        window.speechSynthesis.onvoiceschanged = function() {
+            window.speechSynthesis.getVoices();
+        };
+    }
+};
+async function startNewSession() {
+    try {
+        const response = await fetch(`${API_URL}/start-session`, {
+            method: 'POST'
+        });
+        const data = await response.json();
+        sessionId = data.session_id;
+        updateSessionInfo();
+        addMessage('doctor', data.message);
+        if (autoSpeak) {
+            speakText(data.message);
+        }
+        showNotification('New consultation started!', 'success');
+    } catch (error) {
+        console.error('Error starting session:', error);
+        showNotification('Failed to connect to server', 'error');
+    }
+}
+function updateSessionInfo() {
+    const info = document.getElementById('sessionInfo');
+    const patientInfo = patientData.name ? `Patient: ${patientData.name}` : 'New Patient';
+    info.innerHTML = `${patientInfo}`;
+    const sessionDisplay = document.getElementById('sessionIdDisplay');
+    sessionDisplay.textContent = `Session ID: ${sessionId} (Click to copy)`;
+}
+function copySessionId() {
+    navigator.clipboard.writeText(sessionId).then(() => {
+        showNotification('Session ID copied to clipboard!', 'success');
+    }).catch(() => {
+        showNotification('Failed to copy Session ID', 'error');
+    });
+}
+async function sendMessage() {
+    const input = document.getElementById('messageInput');
+    const message = input.value.trim();
+    if (!message) return;
+    addMessage('user', message);
+    input.value = '';
+    showLoading(true);
+    try {
+        const response = await fetch(`${API_URL}/chat`, {
+            method: 'POST',
+            headers: {
+                'Content-Type': 'application/json'
+            },
+            body: JSON.stringify({
+                session_id: sessionId,
+                message: message
+            })
+        });
+        const data = await response.json();
+        sessionId = data.session_id;
+        patientData = data.patient_data;
+        updateSessionInfo();
+        addMessage('doctor', data.response);
+        if (autoSpeak || continuousMode) {
+            speakText(data.response);
+        }
+    } catch (error) {
+        console.error('Error sending message:', error);
+        addMessage('doctor', '❌ Sorry, there was an error. Please try again.');
+    } finally {
+        showLoading(false);
+    }
+}
+function addMessage(type, text) {
+    const container = document.getElementById('chatContainer');
+    const messageDiv = document.createElement('div');
+    messageDiv.className = `message ${type}`;
+    const contentDiv = document.createElement('div');
+    contentDiv.className = 'message-content';
+    contentDiv.textContent = text;
+    if (type === 'doctor' && 'speechSynthesis' in window) {
+        const speakerIcon = document.createElement('span');
+        speakerIcon.className = 'speaker-icon';
+        speakerIcon.innerHTML = '🔊';
+        speakerIcon.title = 'Click to hear this message';
+        speakerIcon.onclick = function() {
+            if (isSpeaking) {
+                stopSpeaking();
+                speakerIcon.classList.remove('speaking');
+            } else {
+                speakText(text);
+                speakerIcon.classList.add('speaking');
+                setTimeout(() => speakerIcon.classList.remove('speaking'), 3000);
+            }
+        };
+        contentDiv.appendChild(speakerIcon);
+    }
+    messageDiv.appendChild(contentDiv);
+    container.appendChild(messageDiv);
+    container.scrollTop = container.scrollHeight;
+}
+function showLoading(show) {
+    const loading = document.getElementById('loading');
+    loading.className = show ? 'loading active' : 'loading';
+}
+async function generateSummary() {
+    if (!sessionId) {
+        showNotification('No active session', 'error');
+        return;
+    }
+    showLoading(true);
+    showNotification('Generating comprehensive detailed summary and PDF... This may take 30-60 seconds', 'success');
+    try {
+        const response = await fetch(`${API_URL}/summary`, {
+            method: 'POST',
+            headers: {
+                'Content-Type': 'application/json'
+            },
+            body: JSON.stringify({
+                session_id: sessionId
+            })
+        });
+        const data = await response.json();
+        currentPdfUrl = `${API_URL}${data.pdf_url}`;
+        document.getElementById('summaryText').textContent = data.summary;
+        document.getElementById('pdfDownloadInfo').style.display = 'block';
+        document.getElementById('downloadPdfBtn').style.display = 'inline-block';
+        document.getElementById('viewPdfBtn').style.display = 'inline-block';
+        document.getElementById('summaryModal').classList.add('active');
+        showNotification('Comprehensive summary and professional PDF generated successfully!', 'success');
+    } catch (error) {
+        console.error('Error generating summary:', error);
+        showNotification('Failed to generate summary. Please try again.', 'error');
+    } finally {
+        showLoading(false);
+    }
+}
+function downloadPDF() {
+    if (!currentPdfUrl) {
+        showNotification('No PDF available', 'error');
+        return;
+    }
+    const link = document.createElement('a');
+    link.href = currentPdfUrl;
+    link.download = `Consultation_Summary_${sessionId.substring(0, 8)}.pdf`;
+    document.body.appendChild(link);
+    link.click();
+    document.body.removeChild(link);
+    showNotification('PDF download started!', 'success');
+}
+function togglePDFViewer() {
+    const viewerContainer = document.getElementById('pdfViewerContainer');
+    const viewer = document.getElementById('pdfViewer');
+    const btn = document.getElementById('viewPdfBtn');
+    if (viewerContainer.style.display === 'none') {
+        viewer.src = currentPdfUrl;
+        viewerContainer.style.display = 'block';
+        btn.textContent = '🙈 Hide PDF';
+    } else {
+        viewerContainer.style.display = 'none';
+        btn.textContent = '👁️ View PDF';
+    }
+}
+function closeSummary() {
+    document.getElementById('summaryModal').classList.remove('active');
+    document.getElementById('pdfViewerContainer').style.display = 'none';
+    document.getElementById('viewPdfBtn').textContent = '👁️ View PDF';
+}
+async function showHistoryModal() {
+    document.getElementById('historyModal').classList.add('active');
+    await loadHistoryList();
+}
+function closeHistory() {
+    document.getElementById('historyModal').classList.remove('active');
+}
+async function loadHistoryList() {
+    const historyList = document.getElementById('historyList');
+    historyList.innerHTML = '<p style="text-align: center; color: #999;">Loading...</p>';
+    try {
+        const response = await fetch(`${API_URL}/all-sessions`);
+        const data = await response.json();
+        if (data.sessions.length === 0) {
+            historyList.innerHTML = '<p style="text-align: center; color: #999;">No previous consultations found</p>';
+            return;
+        }
+        historyList.innerHTML = '';
+        data.sessions.forEach(session => {
+            const item = document.createElement('div');
+            item.className = 'history-item';
+            item.onclick = () => loadSession(session.session_id);
+            const date = new Date(session.last_updated).toLocaleString();
+            const pdfBadge = session.has_pdf ? '<span class="pdf-badge">📄 PDF Available</span>' : '';
+            item.innerHTML = `
+                <h4>👤 ${session.patient_name} ${pdfBadge}</h4>
+                <p>📅 ${date}</p>
+                <p>💬 Messages: ${session.message_count}</p>
+                <p style="font-family: monospace; font-size: 0.8em;">🔑 ${session.session_id.substring(0, 20)}...</p>
+            `;
+            historyList.appendChild(item);
+        });
+    } catch (error) {
+        console.error('Error loading history:', error);
+        historyList.innerHTML = '<p style="text-align: center; color: #dc3545;">Failed to load history</p>';
+    }
+}
+async function loadSessionById() {
+    const input = document.getElementById('sessionIdInput');
+    const id = input.value.trim();
+    if (!id) {
+        showNotification('Please enter a Session ID', 'error');
+        return;
+    }
+    await loadSession(id);
+}
+async function loadSession(id) {
+    showLoading(true);
+    closeHistory();
+    try {
+        const response = await fetch(`${API_URL}/load-session/${id}`);
+        if (!response.ok) {
+            throw new Error('Session not found');
+        }
+        const data = await response.json();
+        stopSpeaking();
+        document.getElementById('chatContainer').innerHTML = '';
+        sessionId = data.session_id;
+        patientData = data.patient_data;
+        updateSessionInfo();
+        data.history.forEach(msg => {
+            addMessage(msg.role === 'user' ? 'user' : 'doctor', msg.content);
+        });
+        if (data.has_pdf && data.pdf_url) {
+            currentPdfUrl = `${API_URL}${data.pdf_url}`;
+        }
+        showNotification('Consultation loaded successfully!', 'success');
+    } catch (error) {
+        console.error('Error loading session:', error);
+        showNotification('Failed to load session. Check the ID and try again.', 'error');
+    } finally {
+        showLoading(false);
+    }
+}
+async function restartSession() {
+    if (!confirm('Are you sure you want to start a new consultation? Current session will be saved.')) {
+        return;
+    }
+    // Disable continuous mode when restarting
+    if (continuousMode) {
+        toggleContinuousMode();
+    }
+    stopSpeaking();
+    document.getElementById('chatContainer').innerHTML = '';
+    patientData = {};
+    currentPdfUrl = null;
+    await startNewSession();
+}
+function showNotification(message, type) {
+    const notification = document.getElementById('notification');
+    notification.textContent = message;
+    notification.className = `notification ${type} active`;
+    setTimeout(() => {
+        notification.classList.remove('active');
+    }, 3000);
+}
+document.getElementById('messageInput').addEventListener('keypress', (e) => {
+    if (e.key === 'Enter') {
+        sendMessage();
+    }
+});
+document.getElementById('sessionIdInput').addEventListener('keypress', (e) => {
+    if (e.key === 'Enter') {
+        loadSessionById();
+    }
+});
+window.addEventListener('beforeunload', () => {
+    stopSpeaking();
+    if (continuousMode && recognition) {
+        recognition.stop();
+    }
+});

styles.css ADDED Viewed

	@@ -0,0 +1,478 @@

+* {
+    margin: 0;
+    padding: 0;
+    box-sizing: border-box;
+}
+body {
+    font-family: 'Segoe UI', Tahoma, Geneva, Verdana, sans-serif;
+    background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
+    min-height: 100vh;
+    display: flex;
+    justify-content: center;
+    align-items: center;
+    padding: 20px;
+}
+.container {
+    max-width: 900px;
+    width: 100%;
+    background: white;
+    border-radius: 20px;
+    box-shadow: 0 20px 60px rgba(0,0,0,0.3);
+    overflow: hidden;
+}
+.header {
+    background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
+    color: white;
+    padding: 30px;
+    text-align: center;
+}
+.header h1 {
+    font-size: 2em;
+    margin-bottom: 10px;
+}
+.session-info {
+    background: rgba(255,255,255,0.2);
+    padding: 10px;
+    border-radius: 10px;
+    margin-top: 15px;
+    font-size: 0.9em;
+}
+.session-id-display {
+    background: rgba(0,0,0,0.2);
+    padding: 8px;
+    border-radius: 5px;
+    margin-top: 10px;
+    font-family: monospace;
+    font-size: 0.85em;
+    cursor: pointer;
+    transition: background 0.3s;
+}
+.session-id-display:hover {
+    background: rgba(0,0,0,0.3);
+}
+.voice-controls {
+    display: flex;
+    gap: 10px;
+    justify-content: center;
+    padding: 15px;
+    background: rgba(255,255,255,0.1);
+    margin-top: 15px;
+    border-radius: 10px;
+}
+.voice-btn {
+    padding: 10px 20px;
+    border: 2px solid white;
+    border-radius: 20px;
+    background: transparent;
+    color: white;
+    cursor: pointer;
+    transition: all 0.3s;
+    font-weight: bold;
+    display: flex;
+    align-items: center;
+    gap: 8px;
+}
+.voice-btn:hover {
+    background: white;
+    color: #667eea;
+}
+.voice-btn.active {
+    background: #ff4444;
+    border-color: #ff4444;
+    animation: pulse 1.5s infinite;
+}
+@keyframes pulse {
+    0%, 100% { transform: scale(1); }
+    50% { transform: scale(1.05); }
+}
+.voice-indicator {
+    width: 12px;
+    height: 12px;
+    border-radius: 50%;
+    background: #4CAF50;
+    display: inline-block;
+}
+.voice-indicator.recording {
+    background: #ff4444;
+    animation: blink 1s infinite;
+}
+@keyframes blink {
+    0%, 100% { opacity: 1; }
+    50% { opacity: 0.3; }
+}
+.chat-container {
+    height: 500px;
+    overflow-y: auto;
+    padding: 20px;
+    background: #f8f9fa;
+}
+.message {
+    margin-bottom: 20px;
+    display: flex;
+    animation: slideIn 0.3s ease;
+}
+@keyframes slideIn {
+    from {
+        opacity: 0;
+        transform: translateY(10px);
+    }
+    to {
+        opacity: 1;
+        transform: translateY(0);
+    }
+}
+.message.user {
+    justify-content: flex-end;
+}
+.message-content {
+    max-width: 70%;
+    padding: 15px 20px;
+    border-radius: 20px;
+    word-wrap: break-word;
+    white-space: pre-wrap;
+    position: relative;
+}
+.message.doctor .message-content {
+    background: white;
+    color: #333;
+    border: 2px solid #667eea;
+    border-radius: 20px 20px 20px 5px;
+}
+.message.user .message-content {
+    background: #667eea;
+    color: white;
+    border-radius: 20px 20px 5px 20px;
+}
+.speaker-icon {
+    position: absolute;
+    bottom: 8px;
+    right: 8px;
+    cursor: pointer;
+    font-size: 18px;
+    opacity: 0.6;
+    transition: opacity 0.3s;
+}
+.speaker-icon:hover {
+    opacity: 1;
+}
+.speaker-icon.speaking {
+    animation: speakPulse 0.5s infinite;
+}
+@keyframes speakPulse {
+    0%, 100% { transform: scale(1); }
+    50% { transform: scale(1.2); }
+}
+.input-area {
+    padding: 20px;
+    background: white;
+    border-top: 2px solid #e0e0e0;
+    display: flex;
+    gap: 10px;
+}
+.input-area input {
+    flex: 1;
+    padding: 15px;
+    border: 2px solid #e0e0e0;
+    border-radius: 25px;
+    font-size: 16px;
+    transition: border 0.3s;
+}
+.input-area input:focus {
+    outline: none;
+    border-color: #667eea;
+}
+.btn {
+    padding: 15px 30px;
+    border: none;
+    border-radius: 25px;
+    font-size: 16px;
+    cursor: pointer;
+    transition: all 0.3s;
+    font-weight: bold;
+}
+.btn-primary {
+    background: #667eea;
+    color: white;
+}
+.btn-primary:hover {
+    background: #5568d3;
+    transform: translateY(-2px);
+    box-shadow: 0 5px 15px rgba(102, 126, 234, 0.4);
+}
+.btn-secondary {
+    background: #6c757d;
+    color: white;
+}
+.btn-secondary:hover {
+    background: #5a6268;
+}
+.btn-success {
+    background: #28a745;
+    color: white;
+}
+.btn-success:hover {
+    background: #218838;
+}
+.btn-info {
+    background: #17a2b8;
+    color: white;
+}
+.btn-info:hover {
+    background: #138496;
+}
+.btn-voice {
+    background: #ff6b6b;
+    color: white;
+    min-width: 60px;
+}
+.btn-voice:hover {
+    background: #ff5252;
+}
+.btn-voice.recording {
+    background: #f44336;
+    animation: pulse 1.5s infinite;
+}
+.controls {
+    padding: 15px 20px;
+    background: #f8f9fa;
+    display: flex;
+    gap: 10px;
+    justify-content: center;
+    flex-wrap: wrap;
+}
+.loading {
+    display: none;
+    text-align: center;
+    padding: 10px;
+    color: #667eea;
+    font-style: italic;
+}
+.loading.active {
+    display: block;
+}
+.modal {
+    display: none;
+    position: fixed;
+    top: 0;
+    left: 0;
+    width: 100%;
+    height: 100%;
+    background: rgba(0,0,0,0.7);
+    justify-content: center;
+    align-items: center;
+    z-index: 1000;
+}
+.modal.active {
+    display: flex;
+}
+.modal-content {
+    background: white;
+    padding: 30px;
+    border-radius: 15px;
+    max-width: 800px;
+    max-height: 80vh;
+    overflow-y: auto;
+    width: 90%;
+}
+.modal-content pre {
+    white-space: pre-wrap;
+    font-family: 'Segoe UI', sans-serif;
+    line-height: 1.6;
+}
+.close-btn {
+    float: right;
+    font-size: 28px;
+    cursor: pointer;
+    color: #999;
+}
+.close-btn:hover {
+    color: #333;
+}
+.history-list {
+    max-height: 400px;
+    overflow-y: auto;
+    margin-top: 20px;
+}
+.history-item {
+    padding: 15px;
+    border: 2px solid #e0e0e0;
+    border-radius: 10px;
+    margin-bottom: 10px;
+    cursor: pointer;
+    transition: all 0.3s;
+}
+.history-item:hover {
+    border-color: #667eea;
+    background: #f8f9fa;
+    transform: translateX(5px);
+}
+.history-item h4 {
+    color: #667eea;
+    margin-bottom: 5px;
+}
+.history-item p {
+    font-size: 0.9em;
+    color: #666;
+    margin: 5px 0;
+}
+.pdf-badge {
+    display: inline-block;
+    background: #28a745;
+    color: white;
+    padding: 3px 8px;
+    border-radius: 5px;
+    font-size: 0.8em;
+    margin-left: 10px;
+}
+.load-session-form {
+    margin: 20px 0;
+    display: flex;
+    gap: 10px;
+}
+.load-session-form input {
+    flex: 1;
+    padding: 10px;
+    border: 2px solid #e0e0e0;
+    border-radius: 10px;
+    font-family: monospace;
+}
+.notification {
+    position: fixed;
+    top: 20px;
+    right: 20px;
+    padding: 15px 25px;
+    border-radius: 10px;
+    color: white;
+    font-weight: bold;
+    z-index: 2000;
+    animation: slideInRight 0.3s ease;
+    display: none;
+}
+.notification.success {
+    background: #28a745;
+}
+.notification.error {
+    background: #dc3545;
+}
+.notification.info {
+    background: #17a2b8;
+}
+.notification.active {
+    display: block;
+}
+@keyframes slideInRight {
+    from {
+        transform: translateX(100%);
+    }
+    to {
+        transform: translateX(0);
+    }
+}
+.pdf-viewer {
+    width: 100%;
+    height: 600px;
+    border: none;
+    border-radius: 10px;
+    margin-top: 20px;
+}
+.summary-actions {
+    display: flex;
+    gap: 10px;
+    margin-top: 20px;
+    justify-content: center;
+}
+.pdf-download-info {
+    text-align: center;
+    padding: 15px;
+    background: #e8f5e9;
+    border-radius: 10px;
+    margin-top: 15px;
+    color: #2e7d32;
+}
+.pdf-icon {
+    font-size: 48px;
+    margin-bottom: 10px;
+}
+.voice-status {
+    text-align: center;
+    padding: 10px;
+    background: #e3f2fd;
+    border-radius: 10px;
+    margin: 10px 0;
+    font-size: 0.9em;
+    color: #1565c0;
+    display: none;
+}
+.voice-status.active {
+    display: block;
+}