import json

from app.ai.openai_client import OpenAIClient
from app.ai.prompts import build_system_prompt
from app.ai.validator import validate_ai_response
from app.config import OPENAI_API_KEY
from app.specialties.registry import get_specialty_config


class AIOrchestrator:

    def __init__(self):
        self.openai = OpenAIClient()

    async def process(
        self,
        session,
        state,
        conversation_history,
        user_message,
    ):
        specialty = get_specialty_config(
            session.category_code
        )

        current_state = json.loads(
            state.state_json
        )

        context = {
            "patient": {
                "id": session.patient_id,
                "name": session.patient_name,
                "age": session.age,
                "gender": session.gender,
            },
            "category": {
                "type": session.category_type,
                "code": session.category_code,
                "name": session.category_name,
            },
            "specialty_config": specialty,
            "language": session.language,
            "current_stage": session.stage,
            "current_state": current_state,
            "conversation_history": conversation_history,
            "new_patient_message": user_message,
        }

        prompt = build_system_prompt(context)

        # Real OpenAI Call if valid API key is set
        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=user_message,
                )
                parsed = json.loads(raw_response)
                validated = validate_ai_response(parsed)
                return validated.model_dump()
            except Exception as e:
                print(f"[OpenAI Orchestrator Error]: {e}")

        # Fallback simulator for offline development with concise clinical flow
        parsed = self._simulate_specialty_response(session, specialty, user_message, len(conversation_history))
        validated = validate_ai_response(parsed)
        return validated.model_dump()

    def _simulate_specialty_response(self, session, specialty, user_message, turn_count=0):
        stage = session.stage
        code = specialty.get("code", "general")
        msg_lower = user_message.lower().strip()
        is_negative = msg_lower in ["no", "no more", "nothing", "nothing else", "know nothing", "none", "illness none"]

        # Fast conclusion if patient says "No" or already had 4 turns
        if is_negative or turn_count >= 6:
            return {
                "reply": "Thank you. I have recorded your intake details for the doctor to review.",
                "next_stage": "confirmation",
                "state_updates": {
                    "reason_for_visit": None,
                    "symptoms": [],
                    "medical_history": ["None reported"] if is_negative else [],
                    "medications": [],
                    "allergies": ["None"] if is_negative else []
                },
                "completed": True
            }

        if stage == "greeting":
            if code == "cardiology":
                reply = "Could you please share what cardiac or chest symptoms you are experiencing?"
            else:
                reply = "Could you please describe what primary symptoms you are experiencing today?"
            return {
                "reply": reply,
                "next_stage": "reason_for_visit",
                "state_updates": {
                    "reason_for_visit": user_message,
                    "symptoms": [{"name": user_message, "duration": "recent"}],
                    "medical_history": [],
                    "medications": [],
                    "allergies": []
                },
                "completed": False
            }
        elif stage == "reason_for_visit":
            reply = "How long have you had these symptoms, and have you taken any medicines?"
            return {
                "reply": reply,
                "next_stage": "medications",
                "state_updates": {
                    "reason_for_visit": user_message,
                    "symptoms": [{"name": user_message, "duration": "reported"}],
                    "medical_history": [],
                    "medications": [],
                    "allergies": []
                },
                "completed": False
            }
        elif stage == "medications":
            reply = "Thank you. Do you have any known drug allergies or existing health conditions?"
            return {
                "reply": reply,
                "next_stage": "allergies",
                "state_updates": {
                    "reason_for_visit": None,
                    "symptoms": [],
                    "medical_history": [],
                    "medications": [user_message] if not is_negative else [],
                    "allergies": []
                },
                "completed": False
            }
        else:
            return {
                "reply": "Thank you. I have recorded your intake details for the doctor to review.",
                "next_stage": "confirmation",
                "state_updates": {
                    "reason_for_visit": None,
                    "symptoms": [],
                    "medical_history": [],
                    "medications": [],
                    "allergies": ["None"] if is_negative else [user_message]
                },
                "completed": True
            }