const memory = require('../services/memory');
const inference = require('../services/inference');

const SYSTEM_PROMPT = `You are a helpful, context-aware AI assistant. 
You have access to memories of past conversations with the user. 
Use them to provide consistent, personalised responses.`;

const RECENT_EPISODE_LIMIT = 10; // Number of recent episodes to retrieve for context

function buildPrompt(recentEpisodes, userMessage) {
    const parts = [SYSTEM_PROMPT];

    if (recentEpisodes.length > 0) {
        parts.push(`Here are some relevant memories from your past conversations:`);
        for (const ep of recentEpisodes) {
            parts.push(`User: ${ep.user_message}\nAssistant: ${ep.ai_response}`);
        }
        parts.push('--- End of recent memories ---\n');
    }

    parts.push(`User: ${userMessage}`);
    parts.push('Assistant:');

    return parts.join('\n');
}

async function chat(externalId, userMessage, options = {}) {
    // 1. Resolve or create session
    let session = await memory.getSessionByExternalId(externalId);
    if (!session) {
        session = await memory.createSession(externalId);
    }

    // 2. Fetch recent episodes for context
    const recentEpisodes = await memory.getRecentEpisodes(
        session.id,
        RECENT_EPISODE_LIMIT
    );

    // 3. Assemble prompt
    const prompt = buildPrompt(recentEpisodes, userMessage);

    // 4. Run inference
    const result = await inference.complete(prompt, options);

    // 5. Write episode back to memory
    memory.createEpisode(
        session.id,
        userMessage,
        result.text,
        (result.evalCount || 0) + (result.promptEvalCount || 0 )
    ).catch(err => console.error(`[orchestration] Failed to save episode`, err.message));

    // 6. Return response
    return {
        sessionId: externalId,
        response: result.text,
        model: result.model,
        tokenCount: (result.evalCount || 0 ) + (result.promptEvalCount || 0 ),
    };
}

module.exports = { chat };