/**
 * ClinicAgent: An agentic orchestrator for Curio.
 * It uses natural language understanding to map user requests to hospital tools.
 */

const patientManager = require('./patientManager');
const queueManager = require('./queueManager');
const pharmacyAgent = require('./pharmacyAgent');
const configManager = require('./configManager');

class ClinicAgent {
    constructor() {
        this.systemPrompt = `
        You are 'Curio AI', the assistant for Curio Health.
        Your goal is to help patients book appointments, manage family members, and check clinic status.
        
        TOOLS:
        - list_family: Shows all members linked to the phone.
        - add_member: Registers a new family member name.
        - book_today: Books an appointment for today.
        - check_status: Checks current queue position.
        
        RULES:
        1. Always be polite and professional.
        2. If a patient asks for someone not in their family list, offer to add them.
        3. If multiple people have same name, ask for clarification.
        `;
    }

    async processMessage(phone, message, context = {}) {
        const text = message.toLowerCase();
        console.log(`[Agent] Processing for ${phone}: "${message}"`);

        // Mock LLM Intent Extraction & Tool Execution
        // In a real app, this would be: const response = await llm.call({ prompt: ..., tools: [...] });
        
        const family = patientManager.getProfiles(phone);
        
        // Scenario 1: Greeting + Profile Check
        if (text.includes("hi") || text.includes("hello")) {
            if (family.length === 0) {
                return {
                    reply: "Hello! I'm Curio AI. I don't see a profile for this number yet. What is your full name so I can get you started?",
                    nextStep: "AWAIT_REGISTRATION"
                };
            }
            return {
                reply: `Hello again! I see profiles for ${family.map(p => p.name).join(', ')}. Who can I help you with today?`,
                buttons: [...family.map(p => p.name), "+ Add New Member"]
            };
        }

        // Scenario 2: Adding a Member
        if (context.lastStep === "AWAIT_REGISTRATION" || text.includes("add new member")) {
            if (text.includes("add new member")) {
                return { reply: "Sure! What is the name of the family member you'd like to add?" };
            }
            const newId = patientManager.addProfile(phone, { name: message, relation: "Family" });
            return {
                reply: `Perfect! I've added ${message} to your family account. Would you like to book an appointment for them today?`,
                buttons: ["Book for Today", "Check Queue"]
            };
        }

        // Scenario 3: Booking Intent
        if (text.includes("book") || text.includes("today")) {
            return {
                reply: "I can help with that. Which time works best for you?",
                buttons: ["10:00 AM", "11:00 AM", "06:00 PM"]
            };
        }

        // Scenario 3.5: Medicine Query
        if (text.includes("have") || text.includes("medicine") || text.includes("syrup") || text.includes("tablet")) {
            const pharmacyReply = pharmacyAgent.handlePatientQuery(message);
            return {
                reply: "💊 *Pharmacy Update*: " + pharmacyReply,
                buttons: ["Book for Today", "Check Other Meds"]
            };
        }

        // Scenario 4: Natural Language Match for Family Members
        const matchedMember = family.find(p => text.includes(p.name.toLowerCase()));
        if (matchedMember) {
            return {
                reply: `I've switched context to ${matchedMember.name}. What would you like to do for them?`,
                buttons: ["Book for Today", "View History"]
            };
        }

        // Fallback to "Smart" LLM reply
        return {
            reply: "I'm not sure how to help with that yet, but I'm learning! You can ask me to book an appointment or add a family member."
        };
    }
}

module.exports = new ClinicAgent();