feat: complete production hardening implementation, specialty canonicalization, google-genai migration, voice reliability, sqlite concurrency, and test suite consolidation

ai-patient-onboarding/diagnostics/diagnose_models.py

@@ -0,0 +1,95 @@
+import asyncio
+import os
+import sys
+from dotenv import load_dotenv
+
+if sys.stdout.encoding != 'utf-8':
+    try:
+        sys.stdout.reconfigure(encoding='utf-8')
+    except Exception:
+        pass
+
+load_dotenv()
+
+async def diagnose_anthropic():
+    api_key = os.getenv("ANTHROPIC_API_KEY")
+    print("\n--- Testing Anthropic Models ---")
+    candidate_models = [
+        "claude-3-5-sonnet-latest",
+        "claude-3-5-haiku-latest",
+        "claude-3-haiku-20240307",
+        "claude-3-sonnet-20240229",
+        "claude-3-opus-20240229",
+    ]
+    from anthropic import AsyncAnthropic
+    client = AsyncAnthropic(api_key=api_key)
+    for model in candidate_models:
+        try:
+            res = await client.messages.create(
+                model=model,
+                max_tokens=20,
+                messages=[{"role": "user", "content": "Hi"}],
+            )
+            print(f"[OK] Anthropic Model '{model}' WORKS! Response: {res.content[0].text.strip()}")
+            return model
+        except Exception as e:
+            print(f"[X] '{model}' failed: {e}")
+    return None
+
+async def diagnose_gemini():
+    api_key = os.getenv("GEMINI_API_KEY")
+    print("\n--- Testing Gemini Models ---")
+    from google import genai
+    genai.configure(api_key=api_key)
+    try:
+        models = [m.name for m in genai.list_models() if 'generateContent' in m.supported_generation_methods]
+        print(f"Available Gemini models: {models[:10]}")
+        for m_name in models[:5]:
+            try:
+                m = genai.GenerativeModel(m_name)
+                res = await m.generate_content_async("Hi")
+                print(f"[OK] Gemini Model '{m_name}' WORKS! Response: {res.text.strip()}")
+                return m_name
+            except Exception as e:
+                print(f"[X] Gemini Model '{m_name}' failed: {e}")
+    except Exception as e:
+        print(f"[FAIL] Listing Gemini models failed: {e}")
+    return None
+
+async def diagnose_sarvam():
+    api_key = os.getenv("SARVAM_API_KEY")
+    print("\n--- Testing Sarvam Speakers ---")
+    import httpx2
+    client = httpx2.AsyncClient(timeout=15.0)
+    headers = {
+        "api-subscription-key": api_key,
+        "Content-Type": "application/json",
+    }
+    payload = {
+        "inputs": ["வணக்கம்"],
+        "target_language_code": "ta-IN",
+        "speaker": "kavya",
+        "model": "bulbul:v1",
+    }
+    try:
+        res = await client.post(
+            "https://api.sarvam.ai/text-to-speech",
+            json=payload,
+            headers=headers,
+        )
+        if res.status_code == 200:
+            print("[OK] Sarvam TTS with speaker 'kavya' WORKS!")
+            return "kavya"
+        else:
+            print(f"[FAIL] Sarvam HTTP {res.status_code}: {res.text}")
+    except Exception as e:
+        print(f"[FAIL] Sarvam error: {e}")
+    return None
+
+async def main():
+    await diagnose_anthropic()
+    await diagnose_gemini()
+    await diagnose_sarvam()
+
+if __name__ == "__main__":
+    asyncio.run(main())

ai-patient-onboarding/diagnostics/test_5_stage_dialogue.py

@@ -0,0 +1,37 @@
+import httpx
+
+def main():
+    client = httpx.Client(timeout=60.0)
+
+    start_res = client.post('http://127.0.0.1:8000/v1/voice-onboarding/start', json={
+        'patient': {'id': 'PAT-INTAKE-5', 'first_name': 'Arun', 'last_name': 'Kumar'},
+        'category': {'type': 'general', 'code': 'general_medicine', 'name': 'General Medicine'},
+        'language': 'en-IN'
+    }).json()
+
+    sid = start_res['session_id']
+    print("=== DEBUGGING 5-STAGE DIALOGUE ===")
+    print("Session ID:", sid)
+
+    dialogue = [
+        "Chest pain and shortness of breath",
+        "2 days, pain severity is 8 out of 10",
+        "Yes, sweating and dizziness",
+        "High blood pressure and Diabetes",
+        "Taking Amlodipine, no drug allergies"
+    ]
+
+    for i, turn_input in enumerate(dialogue, 1):
+        res = client.post(f"http://127.0.0.1:8000/v1/voice-onboarding/{sid}/turn", data={"text_fallback": turn_input})
+        print(f"Turn {i} Status Code: {res.status_code}")
+        if res.status_code != 200:
+            print("FULL ERROR BODY:", res.text)
+            break
+        data = res.json()
+        print(f"Turn {i} Input: '{turn_input}'")
+        print(f"  --> Next Stage: {data['stage']} | Completed: {data['completed']}")
+        print("-" * 70)
+
+
+if __name__ == '__main__':
+    main()

ai-patient-onboarding/diagnostics/test_ai_providers.py

@@ -0,0 +1,135 @@
+import asyncio
+import os
+import sys
+from dotenv import load_dotenv
+
+if sys.stdout.encoding != 'utf-8':
+    try:
+        sys.stdout.reconfigure(encoding='utf-8')
+    except Exception:
+        pass
+
+load_dotenv()
+
+async def test_openai():
+    api_key = os.getenv("OPENAI_API_KEY")
+    model = os.getenv("OPENAI_MODEL", "gpt-4o-mini")
+    print(f"\n--- [1/4] Testing OpenAI ({model}) ---")
+    if not api_key:
+        print("[FAIL] OPENAI_API_KEY is not set.")
+        return False, "Key missing"
+    try:
+        from openai import AsyncOpenAI
+        client = AsyncOpenAI(api_key=api_key)
+        response = await client.chat.completions.create(
+            model=model,
+            messages=[{"role": "user", "content": "Respond with JSON: {\"status\": \"ok\"}"}],
+            response_format={"type": "json_object"},
+            max_completion_tokens=50,
+        )
+        content = response.choices[0].message.content
+        print(f"[OK] OpenAI Success: {content.strip()}")
+        return True, "Connected & Working"
+    except Exception as e:
+        err_msg = str(e)
+        print(f"[FAIL] OpenAI Error: {err_msg}")
+        return False, err_msg
+
+async def test_anthropic():
+    api_key = os.getenv("ANTHROPIC_API_KEY")
+    model = os.getenv("ANTHROPIC_MODEL", "claude-sonnet-4-5-20250929")
+    print(f"\n--- [2/4] Testing Anthropic Claude ({model}) ---")
+    if not api_key:
+        print("[FAIL] ANTHROPIC_API_KEY is not set.")
+        return False, "Key missing"
+    try:
+        from anthropic import AsyncAnthropic
+        client = AsyncAnthropic(api_key=api_key)
+        response = await client.messages.create(
+            model=model,
+            max_tokens=50,
+            messages=[{"role": "user", "content": "Reply with 'ok'"}],
+        )
+        content = response.content[0].text
+        print(f"[OK] Claude Success: {content.strip()}")
+        return True, "Connected & Working"
+    except Exception as e:
+        err_msg = str(e)
+        print(f"[FAIL] Claude Error: {err_msg}")
+        return False, err_msg
+
+async def test_gemini():
+    api_key = os.getenv("GEMINI_API_KEY")
+    model_name = os.getenv("GEMINI_MODEL", "gemini-3.6-flash")
+    print(f"\n--- [3/4] Testing Google Gemini ({model_name}) ---")
+    if not api_key:
+        print("[FAIL] GEMINI_API_KEY is not set.")
+        return False, "Key missing"
+    try:
+        from google import genai
+        genai.configure(api_key=api_key)
+        model = genai.GenerativeModel(model_name)
+        response = await model.generate_content_async("Say 'ok'")
+        print(f"[OK] Gemini Success: {response.text.strip()}")
+        return True, "Connected & Working"
+    except Exception as e:
+        err_msg = str(e)
+        print(f"[FAIL] Gemini Error: {err_msg}")
+        return False, err_msg
+
+async def test_sarvam():
+    api_key = os.getenv("SARVAM_API_KEY")
+    print(f"\n--- [4/4] Testing Sarvam AI (TTS bulbul:v2) ---")
+    if not api_key:
+        print("[FAIL] SARVAM_API_KEY is not set.")
+        return False, "Key missing"
+    try:
+        import httpx2
+        client = httpx2.AsyncClient(timeout=15.0)
+        headers = {
+            "api-subscription-key": api_key,
+            "Content-Type": "application/json",
+        }
+        payload = {
+            "inputs": ["வணக்கம்"],
+            "target_language_code": "ta-IN",
+            "speaker": "anushka",
+            "model": "bulbul:v2",
+        }
+        res = await client.post(
+            "https://api.sarvam.ai/text-to-speech",
+            json=payload,
+            headers=headers,
+        )
+        if res.status_code == 200:
+            audios = res.json().get("audios", [])
+            print(f"[OK] Sarvam AI Success: Generated {len(audios)} audio stream(s)")
+            return True, "Connected & Working"
+        else:
+            err_msg = f"HTTP {res.status_code}: {res.text}"
+            print(f"[FAIL] Sarvam AI Error: {err_msg}")
+            return False, err_msg
+    except Exception as e:
+        err_msg = str(e)
+        print(f"[FAIL] Sarvam AI Error: {err_msg}")
+        return False, err_msg
+
+async def main():
+    print("========================================")
+    print("AI Patient Onboarding - Key Verification")
+    print("========================================")
+    results = {}
+    results["OpenAI"] = await test_openai()
+    results["Anthropic Claude"] = await test_anthropic()
+    results["Google Gemini"] = await test_gemini()
+    results["Sarvam AI"] = await test_sarvam()
+
+    print("\n========================================")
+    print("SUMMARY")
+    print("========================================")
+    for provider, (passed, msg) in results.items():
+        tag = "[PASS]" if passed else "[FAIL]"
+        print(f"{tag} {provider}: {msg}")
+
+if __name__ == "__main__":
+    asyncio.run(main())

ai-patient-onboarding/diagnostics/test_auto_specialty.py

@@ -0,0 +1,35 @@
+import httpx
+
+def main():
+    client = httpx.Client(timeout=30.0)
+
+    test_cases = [
+        ("Cardiology Test", "எனக்கு நெஞ்சு வலி மற்றும் மூச்சு திணறல் இருக்கு"),
+        ("Dermatology Test", "தோல் அரிப்பு மற்றும் படை உள்ளது"),
+        ("Orthopedics Test", "மூட்டு வலி நடக்க முடியல"),
+        ("Neurology Test", "headache and dizziness for 3 days"),
+        ("Gastroenterology Test", "வயிற்று வலி மற்றும் வாந்தி"),
+        ("Pulmonology Test", "இருமல் மற்றும் சளி அதிகமாக உள்ளது"),
+        ("ENT Test", "காது வலி மற்றும் தொண்டை வலி")
+    ]
+
+    print("=== AUTOMATIC SPECIALTY TRIAGE ENGINE TEST ===")
+    for label, symptom in test_cases:
+        start_res = client.post("http://127.0.0.1:8000/v1/voice-onboarding/start", json={
+            "patient": {"id": "PAT-AUTO", "first_name": "Arun", "last_name": "Kumar"},
+            "category": {"type": "general", "code": "general_medicine", "name": "General Medicine"},
+            "language": "ta-IN"
+        })
+        sid = start_res.json()["session_id"]
+        
+        turn_res = client.post(f"http://127.0.0.1:8000/v1/voice-onboarding/{sid}/turn", data={"text_fallback": symptom})
+        spec = turn_res.json().get("suggested_specialty", {})
+        
+        print(f"Label: {label}")
+        print(f"  Patient Symptom: '{symptom}'")
+        print(f"  --> Auto-Assigned Specialty: {spec.get('name')} (Code: {spec.get('code')})")
+        print(f"  --> Reasoning: {spec.get('reason')}\n")
+
+
+if __name__ == '__main__':
+    main()

ai-patient-onboarding/diagnostics/test_direct_classifier.py

@@ -0,0 +1,16 @@
+from app.ai.orchestrator import classify_specialty_from_symptoms
+
+test_cases = [
+    ("Cardiology", "நெஞ்சு வலி மற்றும் மூச்சு திணறல்"),
+    ("Dermatology", "தோல் அரிப்பு மற்றும் படை"),
+    ("Orthopedics", "மூட்டு வலி"),
+    ("Neurology", "headache and dizziness"),
+    ("Gastroenterology", "வயிற்று வலி மற்றும் வாந்தி"),
+    ("Pulmonology", "இருமல் மற்றும் சளி"),
+    ("ENT", "காது வலி மற்றும் தொண்டை வலி")
+]
+
+print("=== DIRECT SYMPTOM SPECIALTY CLASSIFIER TEST ===")
+for label, text in test_cases:
+    res = classify_specialty_from_symptoms(text)
+    print("Test:", label, "| Code:", res["code"], "| Specialty:", res["name"])

ai-patient-onboarding/diagnostics/test_sarvam_and_claude.py

@@ -0,0 +1,60 @@
+import asyncio
+import os
+import sys
+from dotenv import load_dotenv
+
+if sys.stdout.encoding != 'utf-8':
+    try:
+        sys.stdout.reconfigure(encoding='utf-8')
+    except Exception:
+        pass
+
+load_dotenv()
+
+async def test_sarvam_anushka():
+    api_key = os.getenv("SARVAM_API_KEY")
+    import httpx2
+    client = httpx2.AsyncClient(timeout=15.0)
+    headers = {
+        "api-subscription-key": api_key,
+        "Content-Type": "application/json",
+    }
+    payload = {
+        "inputs": ["வணக்கம், உங்கள் உடல்நலம் எப்படி உள்ளது?"],
+        "target_language_code": "ta-IN",
+        "speaker": "anushka",
+        "model": "bulbul:v2",
+    }
+    res = await client.post(
+        "https://api.sarvam.ai/text-to-speech",
+        json=payload,
+        headers=headers,
+    )
+    if res.status_code == 200:
+        audios = res.json().get("audios", [])
+        print(f"[OK] Sarvam TTS bulbul:v2 (anushka) SUCCESS! Audio segments: {len(audios)}")
+        return True
+    else:
+        print(f"[FAIL] Sarvam error {res.status_code}: {res.text}")
+        return False
+
+async def list_anthropic_models():
+    api_key = os.getenv("ANTHROPIC_API_KEY")
+    from anthropic import AsyncAnthropic
+    client = AsyncAnthropic(api_key=api_key)
+    try:
+        models = await client.models.list()
+        print("Available Anthropic models on this account:")
+        for m in models.data:
+            print(f" - {m.id} ({m.display_name})")
+    except Exception as e:
+        print(f"Anthropic list models error: {e}")
+
+async def main():
+    print("--- 1. Testing Sarvam ---")
+    await test_sarvam_anushka()
+    print("\n--- 2. Listing Anthropic Models ---")
+    await list_anthropic_models()
+
+if __name__ == "__main__":
+    asyncio.run(main())

ai-patient-onboarding/diagnostics/test_updated_models.py

@@ -0,0 +1,87 @@
+import asyncio
+import os
+import sys
+from dotenv import load_dotenv
+
+if sys.stdout.encoding != 'utf-8':
+    try:
+        sys.stdout.reconfigure(encoding='utf-8')
+    except Exception:
+        pass
+
+load_dotenv()
+
+async def test_sarvam_v2():
+    api_key = os.getenv("SARVAM_API_KEY")
+    import httpx2
+    client = httpx2.AsyncClient(timeout=15.0)
+    headers = {
+        "api-subscription-key": api_key,
+        "Content-Type": "application/json",
+    }
+    payload = {
+        "inputs": ["வணக்கம், உங்கள் உடல்நலம் எப்படி உள்ளது?"],
+        "target_language_code": "ta-IN",
+        "speaker": "kavya",
+        "model": "bulbul:v2",
+    }
+    res = await client.post(
+        "https://api.sarvam.ai/text-to-speech",
+        json=payload,
+        headers=headers,
+    )
+    if res.status_code == 200:
+        audios = res.json().get("audios", [])
+        print(f"[OK] Sarvam TTS bulbul:v2 WORKS! Generated {len(audios)} audio clips.")
+        return True
+    else:
+        print(f"[FAIL] Sarvam error {res.status_code}: {res.text}")
+        return False
+
+async def test_gemini_models():
+    api_key = os.getenv("GEMINI_API_KEY")
+    from google import genai
+    genai.configure(api_key=api_key)
+    for model_name in ["gemini-3.6-flash", "gemini-flash-latest", "gemini-2.5-flash-lite", "gemma-4-26b-a4b-it"]:
+        try:
+            m = genai.GenerativeModel(model_name)
+            res = await m.generate_content_async("Hello")
+            print(f"[OK] Gemini '{model_name}' WORKS! Response: {res.text.strip()}")
+            return model_name
+        except Exception as e:
+            print(f"[X] Gemini '{model_name}' failed: {e}")
+    return None
+
+async def test_anthropic_models():
+    api_key = os.getenv("ANTHROPIC_API_KEY")
+    from anthropic import AsyncAnthropic
+    client = AsyncAnthropic(api_key=api_key)
+    for model_name in [
+        "claude-3-7-sonnet-20250219",
+        "claude-3-5-sonnet-20240620",
+        "claude-3-sonnet-20240229",
+        "claude-2.1",
+        "claude-instant-1.2"
+    ]:
+        try:
+            res = await client.messages.create(
+                model=model_name,
+                max_tokens=20,
+                messages=[{"role": "user", "content": "Hi"}],
+            )
+            print(f"[OK] Anthropic '{model_name}' WORKS! Response: {res.content[0].text.strip()}")
+            return model_name
+        except Exception as e:
+            print(f"[X] Anthropic '{model_name}' failed: {e}")
+    return None
+
+async def main():
+    print("--- Testing Sarvam v2 ---")
+    await test_sarvam_v2()
+    print("\n--- Testing Gemini Models ---")
+    await test_gemini_models()
+    print("\n--- Testing Anthropic Models ---")
+    await test_anthropic_models()
+
+if __name__ == "__main__":
+    asyncio.run(main())