feat: implement AI-orchestrated result extraction and service connectivity tests

ai-patient-onboarding/app/services/result_extraction_service.py

@@ -95,10 +95,42 @@ Return ONLY JSON conforming to this exact structure:
                 validated = PatientOnboardingResult.model_validate(parsed)
                 return validated.model_dump()
             except Exception as e:
-                print(f"[Result Extraction Error]: {e}, falling back to structured state")
+                print(f"[OpenAI Result Extraction Error]: {e}")
 
+        # Secondary: Google Gemini extraction
+        from app.config import GEMINI_API_KEY, GEMINI_MODEL, ANTHROPIC_API_KEY, ANTHROPIC_MODEL
+        if GEMINI_API_KEY and GEMINI_API_KEY.strip() not in ["your_gemini_key", ""]:
+            try:
+                import google.generativeai as genai
+                genai.configure(api_key=GEMINI_API_KEY)
+                model = genai.GenerativeModel(GEMINI_MODEL or "gemini-3.6-flash")
+                res = await model.generate_content_async(prompt)
+                cleaned = res.text.replace("```json", "").replace("```", "").strip()
+                parsed = json.loads(cleaned)
+                validated = PatientOnboardingResult.model_validate(parsed)
+                return validated.model_dump()
+            except Exception as e:
+                print(f"[Gemini Result Extraction Error]: {e}")
 
-        # Fallback simulator from state
+        # Tertiary: Anthropic Claude extraction
+        if ANTHROPIC_API_KEY and ANTHROPIC_API_KEY.strip() not in ["your_anthropic_key", ""]:
+            try:
+                from anthropic import AsyncAnthropic
+                client = AsyncAnthropic(api_key=ANTHROPIC_API_KEY)
+                res = await client.messages.create(
+                    model=ANTHROPIC_MODEL or "claude-sonnet-4-5-20250929",
+                    max_tokens=800,
+                    system=prompt,
+                    messages=[{"role": "user", "content": "Generate structured onboarding result"}],
+                )
+                cleaned = res.content[0].text.replace("```json", "").replace("```", "").strip()
+                parsed = json.loads(cleaned)
+                validated = PatientOnboardingResult.model_validate(parsed)
+                return validated.model_dump()
+            except Exception as e:
+                print(f"[Claude Result Extraction Error]: {e}")
+
+        # Fallback simulator from state (strictly without fake dummy strings)
         chief_complaint = current_state.get("reason_for_visit")
         if isinstance(chief_complaint, dict):
             chief_complaint = chief_complaint.get("value")
@@ -126,8 +158,8 @@ Return ONLY JSON conforming to this exact structure:
                 "code": session.category_code,
                 "name": session.category_name,
             },
-            "chief_complaint": chief_complaint or "Consultation Intake",
-            "symptoms": symptoms_list or [{"name": chief_complaint or "Reported discomfort", "duration": "recent", "severity": "mild", "description": None}],
+            "chief_complaint": chief_complaint or None,
+            "symptoms": symptoms_list,
             "medical_history": history_list,
             "medications": meds_list,
             "allergies": allergies_list,