nexusAI/packages/orchestration-service/src/services/summarization.js

const { getEnv, SERVICES, SUMMARIES } = require('@nexusai/shared');

const EXTRACTION_URL  = getEnv('EXTRACTION_URL', 'http://localhost:11434');
const EXTRACTION_MODEL = getEnv('EXTRACTION_MODEL', 'qwen2.5:3b');
const MEMORY_URL      = getEnv('MEMORY_SERVICE_URL', SERVICES.MEMORY_URL);

const THRESHOLD_TOKENS  = parseInt(getEnv('SUMMARY_THRESHOLD_TOKENS', SUMMARIES.THRESHOLD_TOKENS));
const MAX_SUMMARY_TOKENS = parseInt(getEnv('SUMMARY_MAX_TOKENS', SUMMARIES.MAX_SUMMARY_TOKENS));
const MIN_EPISODES_SINCE = parseInt(getEnv('SUMMARY_MIN_EPISODES', SUMMARIES.MIN_EPISODES_SINCE));

function buildSummaryPrompt(episodes, existingSummary = null) {
    const context = episodes
        .map(ep => `User: ${ep.user_message}\nAssistant: ${ep.ai_response}`)
        .join('\n\n');

    const instruction = existingSummary
    ? `Update this summary to include the new conversation exchanges below. Output only the updated summary — do not continue the conversation.

Previous summary:
${existingSummary}

New exchanges to incorporate:`
    : `Summarise this conversation. Output only the summary — do not continue the conversation or give recommendations.

Conversation:`;

    return [
        '<|im_start|>system',
        'You are a conversation summarisation assistant. You write concise, factual summaries for long-term memory storage. Output only the summary text — no preamble, no labels.<|im_end|>',
        '<|im_start|>user',
        instruction,
        '',
        context,
        '<|im_end|>',
        '<|im_start|>assistant',
    ].join('\n');
}

async function generateSummary(episodes, existingSummary = null) {
    const prompt = buildSummaryPrompt(episodes, existingSummary);

    const res = await fetch(`${EXTRACTION_URL}/api/generate`, {
        method: 'POST',
        headers: { 'Content-Type': 'application/json' },
        body: JSON.stringify({
            model: EXTRACTION_MODEL,
            prompt,
            stream: false,
            options: {
                temperature: 0.3,   // slightly higher than entities — summaries benefit from some fluency
                num_predict: 300,   // generous but bounded — keeps summaries from running long
            },
        }),
    });

    if (!res.ok) throw new Error(`Ollama responded ${res.status}`);
    const data = await res.json();
    return data.response?.trim() ?? '';
}

async function maybeSummarize(session, allEpisodes) {
    // 1. Sum total tokens for this session
    const totalTokens = allEpisodes.reduce((sum, ep) => sum + (ep.token_count || 0), 0);
    if (totalTokens < THRESHOLD_TOKENS) return; // under threshold — nothing to do
    console.log('[summarization] fetching existing summaries...');
    // 2. Fetch existing summaries for session
    const summariesRes = await fetch(`${MEMORY_URL}/sessions/${session.id}/summaries`);
    console.log('[summarization] summaries fetch status:', summariesRes.status);
    if (!summariesRes.ok) return;
    const summaries = await summariesRes.json();

    const latest = summaries.at(-1) ?? null;
    const lastCoveredId = latest 
        ? parseInt(latest.episode_range?.split('-').at(-1)) || 0 
        : 0;
    // 3. Guard — don't re-summarize until MIN_EPISODES_SINCE new episodes have accumulated
    if (latest) {
        const newEpisodes = allEpisodes.filter(ep => ep.id > lastCoveredId);
        if (newEpisodes.length < MIN_EPISODES_SINCE) return;
    }

    // 4. Determine episode range string  e.g. "1-42"
    const ids = allEpisodes.map(ep => ep.id).sort((a,b) => a - b);
    const episodeRange = `${ids.at(0)}-${ids.at(-1)}`;
    const totalEpisodeTokens = allEpisodes.reduce((sum, ep) => sum + (ep.token_count || 0), 0);

    // 5. Generate summary — pass existing content if updating
    const episodesToSummarize = latest 
    ? allEpisodes.filter(ep => ep.id > lastCoveredId)
    : allEpisodes;

    // add temporarily before the generateSummary call
    console.log('[summarization] episodes to summarize:', episodesToSummarize.length);
    console.log('[summarization] total chars:', episodesToSummarize.reduce((s, ep) => s + ep.user_message.length + ep.ai_response.length, 0));

    const content = await generateSummary(
        episodesToSummarize,
        latest && latest.content.length < MAX_SUMMARY_TOKENS ? latest.content : null
        // if existing summary is already large, treat as fresh rather than appending to a huge blob
    );

    if (!content) return;

    // 6. Create new row or update existing
    if (!latest || latest.content.length >= MAX_SUMMARY_TOKENS) {
        await fetch(`${MEMORY_URL}/summaries`, {
            method: 'POST',
            headers: { 'Content-Type': 'application/json' },
            body: JSON.stringify({
                sessionId: session.id,
                content,
                tokenCount: totalEpisodeTokens,
                episodeRange,
            }),
        });
        console.log(`[summarization] Created new summary for session ${session.id}`);
    } else {
        await fetch(`${MEMORY_URL}/summaries/${latest.id}`, {
            method: 'PATCH',
            headers: { 'Content-Type': 'application/json' },
            body: JSON.stringify({
                content,
                tokenCount: totalEpisodeTokens,
                episodeRange,
            }),
        });
        console.log(`[summarization] Updated summary ${latest.id} for session ${session.id}`);
    }
}

async function triggerSummary(session, allEpisodes) {
    // Intentionally fire-and-forget — caller doesn't await this
    maybeSummarize(session, allEpisodes).catch(err =>
        console.warn('[summarization] Summary failed (non-critical):', err.message)
    );
}

module.exports = { triggerSummary };