feat: AI patient onboarding backend and documentation

2026-08-27 12:15:09 +05:30
parent b9440772d1
commit 59c1372fe3
49 changed files with 4012 additions and 0 deletions
@@ -0,0 +1,139 @@
+import json
+from app.ai.openai_client import OpenAIClient
+from app.config import OPENAI_API_KEY
+from app.schemas.onboarding import PatientOnboardingResult
+
+
+class ResultExtractionService:
+
+    def __init__(self):
+        self.openai = OpenAIClient()
+
+    async def extract_result(
+        self,
+        session,
+        state,
+        conversation_history,
+    ) -> dict:
+        current_state = json.loads(
+            state.state_json
+        )
+
+        prompt = f"""
+You are a hospital patient onboarding data extraction assistant.
+
+Your task is to convert the completed onboarding information
+into structured patient intake data.
+
+You are NOT a doctor.
+Do not diagnose the patient.
+Do not add information that was not provided.
+
+PATIENT:
+{json.dumps({
+    "id": session.patient_id,
+    "name": session.patient_name,
+    "age": session.age,
+    "gender": session.gender,
+}, indent=2)}
+
+CATEGORY:
+{json.dumps({
+    "type": session.category_type,
+    "code": session.category_code,
+    "name": session.category_name,
+}, indent=2)}
+
+CURRENT STATE:
+{json.dumps(current_state, indent=2)}
+
+CONVERSATION:
+{json.dumps(conversation_history, indent=2)}
+
+Return ONLY JSON conforming to this exact structure:
+{{
+    "patient_id": "{session.patient_id}",
+    "category": {{
+        "type": "{session.category_type}",
+        "code": "{session.category_code}",
+        "name": "{session.category_name}"
+    }},
+    "chief_complaint": "string or null",
+    "symptoms": [
+        {{
+            "name": "string",
+            "duration": "string or null",
+            "severity": "string or null",
+            "description": "string or null"
+        }}
+    ],
+    "medical_history": [],
+    "medications": [],
+    "allergies": [],
+    "additional_information": "string or null",
+    "language": "{session.language}",
+    "onboarding_completed": true
+}}
+"""
+
+        if OPENAI_API_KEY and OPENAI_API_KEY.strip() not in ["your_openai_api_key", "your_openai_key", ""]:
+            try:
+                raw_response = await self.openai.generate_response(
+                    system_prompt=prompt,
+                    user_message="Generate the final structured patient onboarding result.",
+                )
+                cleaned = raw_response.strip()
+                if cleaned.startswith("```json"):
+                    cleaned = cleaned[7:]
+                if cleaned.startswith("```"):
+                    cleaned = cleaned[3:]
+                if cleaned.endswith("```"):
+                    cleaned = cleaned[:-3]
+                cleaned = cleaned.strip()
+
+                parsed = json.loads(cleaned)
+                validated = PatientOnboardingResult.model_validate(parsed)
+                return validated.model_dump()
+            except Exception as e:
+                print(f"[Result Extraction Error]: {e}, falling back to structured state")
+
+
+        # Fallback simulator from state
+        chief_complaint = current_state.get("reason_for_visit")
+        if isinstance(chief_complaint, dict):
+            chief_complaint = chief_complaint.get("value")
+
+        symptoms_raw = current_state.get("symptoms")
+        symptoms_list = []
+        if isinstance(symptoms_raw, dict):
+            symptoms_list = symptoms_raw.get("items", [])
+        elif isinstance(symptoms_raw, list):
+            symptoms_list = symptoms_raw
+
+        meds_raw = current_state.get("medications")
+        meds_list = meds_raw.get("items", []) if isinstance(meds_raw, dict) else (meds_raw or [])
+
+        allergies_raw = current_state.get("allergies")
+        allergies_list = allergies_raw.get("items", []) if isinstance(allergies_raw, dict) else (allergies_raw or [])
+
+        history_raw = current_state.get("medical_history")
+        history_list = history_raw.get("items", []) if isinstance(history_raw, dict) else (history_raw or [])
+
+        fallback_result = {
+            "patient_id": session.patient_id,
+            "category": {
+                "type": session.category_type,
+                "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}],
+            "medical_history": history_list,
+            "medications": meds_list,
+            "allergies": allergies_list,
+            "additional_information": None,
+            "language": session.language,
+            "onboarding_completed": True,
+        }
+        validated = PatientOnboardingResult.model_validate(fallback_result)
+        return validated.model_dump()