Upload QUICK_REFERENCE_FIXED.md

QUICK_REFERENCE_FIXED.md

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+# TabeebAI Quick Reference - FIXED for Latest Groq SDK
+
+## 🔧 The Issue
+The Groq SDK API changed. Use `client.chat.completions.create()` instead of `client.messages.create()`
+
+---
+
+## ✅ CELL 1: Install + Import (UNCHANGED)
+
+```python
+# Install packages
+import subprocess
+import sys
+
+for pkg in ["groq", "python-dotenv"]:
+    subprocess.check_call([sys.executable, "-m", "pip", "install", "-q", pkg])
+
+print("✓ Packages installed!")
+
+# Imports
+import os
+import json
+from groq import Groq
+from datetime import datetime
+
+# Set API key (from Colab secrets)
+from google.colab import userdata
+GROQ_API_KEY = userdata.get('GROQ_API_KEY')
+
+# Initialize client
+client = Groq(api_key=GROQ_API_KEY)
+print("✓ Groq client ready!")
+```
+
+---
+
+## ✅ CELL 2: Symptom Extraction - FIXED ⚡
+
+```python
+def extract_symptoms(text_input, language="auto"):
+    """Extract symptoms from patient speech"""
+    
+    prompt = f"""You are a medical assistant. Extract symptoms from this patient statement.
+
+Patient: "{text_input}"
+
+Respond ONLY with valid JSON (no markdown, no extra text):
+{{
+  "chief_complaint": "main problem",
+  "symptoms": [
+    {{"name": "symptom", "severity": "mild/moderate/severe", "duration": "time"}}
+  ],
+  "language_detected": "urdu/english",
+  "confidence": 0.0,
+  "needs_emergency": false
+}}"""
+
+    try:
+        # FIXED: Use chat.completions.create() instead of messages.create()
+        msg = client.chat.completions.create(
+            model="mixtral-8x7b-32768",
+            max_tokens=300,
+            messages=[{"role": "user", "content": prompt}]
+        )
+        
+        response = msg.choices[0].message.content.strip()
+        
+        # Extract JSON
+        start = response.find('{')
+        end = response.rfind('}') + 1
+        json_str = response[start:end]
+        data = json.loads(json_str)
+        
+        return {"success": True, "data": data}
+    
+    except Exception as e:
+        return {"success": False, "error": str(e)}
+
+# Test it!
+result = extract_symptoms("I have chest pain and I'm sweating")
+print(json.dumps(result, indent=2, ensure_ascii=False))
+```
+
+---
+
+## ✅ CELL 3: Test with Urdu (UNCHANGED)
+
+```python
+# Test cases - just copy and paste!
+
+test_cases = [
+    {
+        "text": "مجھے سینے میں بہت درد ہے اور مجھے سانس لینے میں دشواری ہو رہی ہے",
+        "language": "Urdu",
+        "expected": "EMERGENCY"
+    },
+    {
+        "text": "میرا درجہ حرارت 39 ڈگری ہے اور میرے سر میں درد ہے",
+        "language": "Urdu",
+        "expected": "High"
+    },
+    {
+        "text": "I have chest pain and difficulty breathing",
+        "language": "English",
+        "expected": "EMERGENCY"
+    },
+]
+
+# Run tests
+for i, test in enumerate(test_cases, 1):
+    print(f"\n{'='*50}")
+    print(f"Test {i}: {test['language']}")
+    print(f"Input: {test['text']}")
+    print(f"{'='*50}")
+    
+    result = extract_symptoms(test['text'])
+    if result['success']:
+        print("✓ Success!")
+        print(json.dumps(result['data'], indent=2, ensure_ascii=False))
+    else:
+        print(f"✗ Failed: {result['error']}")
+```
+
+---
+
+## ✅ CELL 4: Risk Scoring (UNCHANGED)
+
+```python
+def calculate_risk_score(symptoms_data):
+    """Convert symptoms to risk score (0-100)"""
+    
+    if not symptoms_data.get('data'):
+        return 0
+    
+    data = symptoms_data['data']
+    score = 0
+    
+    # Severity scoring
+    severity_map = {"mild": 5, "moderate": 25, "severe": 40}
+    
+    for symptom in data.get('symptoms', []):
+        sev = symptom.get('severity', 'mild')
+        score += severity_map.get(sev, 5)
+    
+    # Emergency bonus
+    if data.get('needs_emergency'):
+        score += 50
+    
+    # Normalize
+    score = min(score, 100)
+    
+    return score
+
+def get_risk_level(score):
+    """Convert score to severity level"""
+    if score >= 71:
+        return "🔴 RED - EMERGENCY"
+    elif score >= 31:
+        return "🟡 YELLOW - MODERATE"
+    else:
+        return "🟢 GREEN - LOW RISK"
+
+# Test
+result = extract_symptoms("I have chest pain and difficulty breathing")
+score = calculate_risk_score(result)
+level = get_risk_level(score)
+
+print(f"Risk Score: {score}/100")
+print(f"Severity: {level}")
+```
+
+---
+
+## ✅ CELL 5: SOAP Report (UNCHANGED)
+
+```python
+def generate_soap_report(symptoms_data, risk_score):
+    """Generate SOAP format medical report"""
+    
+    if not symptoms_data.get('success'):
+        return "Unable to generate report"
+    
+    data = symptoms_data['data']
+    symptoms_list = data.get('symptoms', [])
+    chief_complaint = data.get('chief_complaint', 'Not specified')
+    
+    # Build SOAP
+    subjective = f"Patient reports: {chief_complaint}"
+    for s in symptoms_list:
+        subjective += f"\n  • {s.get('name', 'Unknown')}: {s.get('duration', 'Unknown duration')}"
+    
+    objective = "Speech indicates " + ("distress" if risk_score > 50 else "no acute distress")
+    
+    assessment = f"Clinical risk assessment score: {risk_score}/100"
+    
+    plan = get_risk_level(risk_score)
+    if risk_score >= 71:
+        plan += "\n  • Immediate emergency evaluation required\n  • Call ambulance\n  • Do not delay treatment"
+    elif risk_score >= 31:
+        plan += "\n  • Medical evaluation within 24 hours\n  • Schedule urgent appointment"
+    else:
+        plan += "\n  • Home care with monitoring\n  • Follow up if symptoms worsen"
+    
+    report = f"""
+╔═══════════════════════════════════════╗
+║        MEDICAL ASSESSMENT REPORT       ║
+╚═══════════════════════════════════════╝
+
+SUBJECTIVE:
+{subjective}
+
+OBJECTIVE:
+{objective}
+
+ASSESSMENT:
+{assessment}
+{get_risk_level(risk_score)}
+
+PLAN:
+{plan}
+
+═══════════════════════════════════════
+Generated: {datetime.now().strftime('%Y-%m-%d %H:%M:%S')}
+    """
+    
+    return report
+
+# Test
+result = extract_symptoms("مجھے سینے میں درد ہے اور مجھے پسینہ آ رہا ہے")
+score = calculate_risk_score(result)
+report = generate_soap_report(result, score)
+print(report)
+```
+
+---
+
+## ✅ CELL 6: Complete Pipeline (UNCHANGED)
+
+```python
+def complete_pipeline(patient_input):
+    """One function to rule them all!"""
+    
+    print(f"\n🔄 Processing: {patient_input[:50]}...")
+    
+    # Step 1: Extract symptoms
+    symptoms_result = extract_symptoms(patient_input)
+    
+    if not symptoms_result['success']:
+        return f"❌ Error: {symptoms_result['error']}"
+    
+    # Step 2: Calculate risk
+    risk_score = calculate_risk_score(symptoms_result)
+    risk_level = get_risk_level(risk_score)
+    
+    # Step 3: Generate report
+    report = generate_soap_report(symptoms_result, risk_score)
+    
+    # Return formatted output
+    output = {
+        "status": "✓ Complete",
+        "risk_score": risk_score,
+        "severity": risk_level,
+        "symptoms": symptoms_result['data'].get('symptoms', []),
+        "report": report
+    }
+    
+    return output
+
+# Test it!
+test_input = "مجھے سر میں درد ہے اور میرا درجہ حرارت بہت زیادہ ہے"
+result = complete_pipeline(test_input)
+print(json.dumps(result, indent=2, ensure_ascii=False))
+```
+
+---
+
+## 🎯 Key Changes Made
+
+| Old | New |
+|-----|-----|
+| `client.messages.create()` | `client.chat.completions.create()` |
+| `msg.content[0].text` | `msg.choices[0].message.content` |
+
+---
+
+## 📋 Copy-Paste All at Once
+
+If you want to paste everything in one cell:
+
+```python
+import subprocess, sys
+for pkg in ["groq"]:
+    subprocess.check_call([sys.executable, "-m", "pip", "install", "-q", pkg])
+
+import os, json
+from groq import Groq
+from datetime import datetime
+from google.colab import userdata
+
+GROQ_API_KEY = userdata.get('GROQ_API_KEY')
+client = Groq(api_key=GROQ_API_KEY)
+print("✓ Ready!")
+
+# ===== SYMPTOM EXTRACTION =====
+def extract_symptoms(text_input, language="auto"):
+    prompt = f"""You are a medical assistant. Extract symptoms from: "{text_input}"
+    
+Respond ONLY with JSON:
+{{"chief_complaint": "problem", "symptoms": [{{"name": "symptom", "severity": "mild/moderate/severe", "duration": "time"}}], "language_detected": "urdu/english", "confidence": 0.0, "needs_emergency": false}}"""
+    
+    try:
+        msg = client.chat.completions.create(
+            model="mixtral-8x7b-32768",
+            max_tokens=300,
+            messages=[{"role": "user", "content": prompt}]
+        )
+        response = msg.choices[0].message.content.strip()
+        start = response.find('{')
+        end = response.rfind('}') + 1
+        data = json.loads(response[start:end])
+        return {"success": True, "data": data}
+    except Exception as e:
+        return {"success": False, "error": str(e)}
+
+# ===== RISK SCORING =====
+def calculate_risk_score(symptoms_data):
+    if not symptoms_data.get('data'): return 0
+    data = symptoms_data['data']
+    score = sum({"mild": 5, "moderate": 25, "severe": 40}.get(s.get('severity', 'mild'), 5) 
+                for s in data.get('symptoms', []))
+    if data.get('needs_emergency'): score += 50
+    return min(score, 100)
+
+def get_risk_level(score):
+    if score >= 71: return "🔴 RED - EMERGENCY"
+    elif score >= 31: return "🟡 YELLOW - MODERATE"
+    else: return "🟢 GREEN - LOW RISK"
+
+# ===== SOAP REPORT =====
+def generate_soap_report(symptoms_data, risk_score):
+    if not symptoms_data.get('success'): return "Error"
+    data = symptoms_data['data']
+    report = f"""
+SUBJECTIVE: {data.get('chief_complaint', 'N/A')}
+"""
+    for s in data.get('symptoms', []):
+        report += f"\n  • {s.get('name', 'Unknown')} ({s.get('severity', 'Unknown')})"
+    report += f"""
+OBJECTIVE: Speech indicates {'distress' if risk_score > 50 else 'no distress'}
+ASSESSMENT: Risk Score {risk_score}/100
+PLAN: {get_risk_level(risk_score)}
+    """
+    return report
+
+# ===== COMPLETE PIPELINE =====
+def complete_pipeline(text):
+    result = extract_symptoms(text)
+    if not result['success']: return result
+    score = calculate_risk_score(result)
+    return {"status": "✓", "risk_score": score, "severity": get_risk_level(score), "report": generate_soap_report(result, score)}
+
+# TEST
+print(complete_pipeline("I have chest pain and difficulty breathing"))
+print("\n" + "="*50 + "\n")
+print(complete_pipeline("مجھے سینے میں درد ہے"))
+```
+
+---
+
+## ✅ Now Run This
+
+1. **Cell 1**: Install + Init (copy-paste above)
+2. **Cell 2**: Test with English
+3. **Cell 3**: Test with Urdu
+
+You should see ✓ Success now!
+
+Let me know if you still get errors!