chore: sync API routes, dashboard hot-topics, MCP server, scraper package, scripts
This commit is contained in:
Rene Fichtmueller
parent
a8529d166b
commit
a1a525b332
@ -31,3 +31,28 @@ Default private Hugging Face datasets:
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- `renefichtmueller/blog-llm-sft`
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Local training is enabled by setting `TIP_LOCAL_TRAIN_COMMAND`; the API appends the lane name automatically.
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## TIPLLM Robot Experience Pool
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Crawler and verification robots must use TIPLLM only for planning/extraction feedback. Operational experience is written to the Gitea-backed TIP training pool:
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- Default local clone: `/tmp/tip-training-data`
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- Override: `TIP_TRAINING_REPO=/path/to/tip-training-data`
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- Gitea repo: `rene/tip-training-data`
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- SFT records: `qa-pairs/robot-control-high.jsonl`
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- Raw audit records: `robot-experiences/YYYY-MM-DD.jsonl`
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Useful commands:
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```bash
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npm run robots:verification -w packages/scraper -- --status
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npm run robots:verification -w packages/scraper -- --tipllm-plan --limit=5
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npm run robots:verification -w packages/scraper -- --enqueue=details-fast-lane --profile=erik-safe --dry-run
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```
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Safety defaults:
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- `erik-safe` is the default profile and caps to 3 lightweight queues.
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- Playwright/discovery work belongs on Proxmox or Pi workers, not Erik.
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- Every status snapshot, TIPLLM plan, dry-run plan, enqueue result and crawler result should become a TIPLLM training example.
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- `learning-pool:build` automatically imports Gitea pool SFT rows from `qa-pairs/` into the `tip_llm` lane.
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@ -25,6 +25,10 @@ interface HotTopic {
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data_context?: Record<string, unknown>;
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suggested_angle?: string;
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date?: string;
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blog_title_created?: boolean;
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last_blog_created_at?: string;
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rank_score?: number;
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llm_context?: string;
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}
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/**
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@ -32,10 +36,11 @@ interface HotTopic {
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*
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* Returns dynamically ranked blog topics based on real signals.
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*/
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hotTopicsRouter.get("/", async (_req, res) => {
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hotTopicsRouter.get("/", async (req, res) => {
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try {
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const topics: HotTopic[] = [];
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const year = new Date().getFullYear();
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const limit = Math.max(1, Math.min(50, parseInt(String(req.query.limit || "20"), 10) || 20));
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// ═══ SOURCE 1: Internal Data — Price Movements ═══
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const priceDrops = await pool.query(`
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@ -246,9 +251,33 @@ hotTopicsRouter.get("/", async (_req, res) => {
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// ═══ SOURCE 7: Evergreen High-Value Topics ═══
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topics.push(...getEvergreenTopics(year));
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// Sort by urgency: breaking > hot > trending > emerging
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const urgencyOrder: Record<string, number> = { breaking: 0, hot: 1, trending: 2, emerging: 3 };
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topics.sort((a, b) => (urgencyOrder[a.urgency] ?? 4) - (urgencyOrder[b.urgency] ?? 4));
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// Mark already-created topics and rank with daily rotation + source diversity.
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const recentDrafts = await pool.query(`
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SELECT title, created_at
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FROM blog_drafts
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WHERE created_at > NOW() - INTERVAL '180 days'
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ORDER BY created_at DESC
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`).catch(() => ({ rows: [] }));
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const createdByTitle = new Map<string, string>();
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for (const draft of recentDrafts.rows) {
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const key = normalizeTopicTitle(String(draft.title || ""));
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if (key && !createdByTitle.has(key)) {
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createdByTitle.set(key, draft.created_at ? new Date(draft.created_at).toISOString() : new Date().toISOString());
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}
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}
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const daySeed = getDaySeed();
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const rotationSeed = daySeed + getQuerySeed(req.query.shuffle);
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for (const topic of topics) {
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const createdAt = createdByTitle.get(normalizeTopicTitle(topic.title));
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topic.blog_title_created = Boolean(createdAt);
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topic.last_blog_created_at = createdAt;
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topic.rank_score = scoreTopic(topic, rotationSeed);
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topic.llm_context = buildTopicBriefing(topic);
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}
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const rankedTopics = selectDiverseTopics(topics, limit);
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// Next daily rotation: tomorrow 00:00 UTC
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const tomorrow = new Date();
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@ -256,11 +285,12 @@ hotTopicsRouter.get("/", async (_req, res) => {
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tomorrow.setUTCHours(0, 0, 0, 0);
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res.json({
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topics: topics.slice(0, 20),
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topics: rankedTopics,
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total: topics.length,
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generated_at: new Date().toISOString(),
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refreshes_at: tomorrow.toISOString(),
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day_seed: getDaySeed(),
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day_seed: daySeed,
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rotation_seed: rotationSeed,
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sources: ["market_intelligence", "nog_talks", "internal_price_data", "competitor_alerts", "hype_cycle_model", "news_articles", "conference_calendar", "research_papers"],
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});
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} catch (err) {
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@ -269,6 +299,131 @@ hotTopicsRouter.get("/", async (_req, res) => {
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}
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});
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function normalizeTopicTitle(title: string): string {
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return title
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.toLowerCase()
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.replace(/\b20\d{2}\b/g, "{year}")
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.replace(/[^a-z0-9]+/g, " ")
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.replace(/\s+/g, " ")
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.trim();
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}
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function seededTopicJitter(title: string, seed: number): number {
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let s = seed;
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const normalized = normalizeTopicTitle(title);
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for (let i = 0; i < normalized.length; i++) {
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s = (s * 1664525 + normalized.charCodeAt(i) + 1013904223) & 0x7fffffff;
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}
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return s % 140;
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}
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function getQuerySeed(value: unknown): number {
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if (!value) return 0;
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const raw = Array.isArray(value) ? String(value[0] || "") : String(value);
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if (!raw) return 0;
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let hash = 0;
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for (let i = 0; i < raw.length; i++) {
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hash = ((hash << 5) - hash + raw.charCodeAt(i)) | 0;
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}
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return Math.abs(hash % 100000);
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}
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function compactDataContext(data: Record<string, unknown> | undefined): string {
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if (!data) return "";
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const replacer = (_key: string, value: unknown) => {
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if (Array.isArray(value)) return value.slice(0, 5);
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if (typeof value === "string" && value.length > 260) return `${value.slice(0, 257)}...`;
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return value;
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};
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return JSON.stringify(data, replacer, 2).slice(0, 1800);
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}
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function buildTopicBriefing(topic: HotTopic): string {
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const lines = [
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`Topic: ${topic.title}`,
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`Urgency: ${topic.urgency}`,
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`Source: ${topic.source_type} / ${topic.source}`,
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];
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if (topic.date) lines.push(`Signal date: ${topic.date}`);
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if (topic.description) lines.push(`Signal summary: ${topic.description}`);
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if (topic.suggested_angle) lines.push(`Recommended angle: ${topic.suggested_angle}`);
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if (topic.blog_title_created && topic.last_blog_created_at) {
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lines.push(`Editorial note: A blog with a very similar title already exists from ${topic.last_blog_created_at}. If used anyway, choose a materially different angle.`);
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}
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const dataContext = compactDataContext(topic.data_context);
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if (dataContext) lines.push(`Structured supporting data:\n${dataContext}`);
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lines.push("Editorial instruction: turn this into a practical optical networking article with procurement/engineering consequences, not a generic news summary.");
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return lines.join("\n");
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}
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function scoreTopic(topic: HotTopic, seed: number): number {
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const urgencyScore: Record<HotTopic["urgency"], number> = {
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breaking: 900,
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hot: 760,
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trending: 620,
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emerging: 500,
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};
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const sourceScore: Record<HotTopic["source_type"], number> = {
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internal_data: 90,
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competitor: 85,
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trade_press: 75,
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conference: 70,
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manufacturer: 65,
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research: 60,
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};
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let freshness = 0;
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if (topic.date) {
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const ageDays = Math.max(0, (Date.now() - new Date(topic.date).getTime()) / 86400000);
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freshness = Math.max(0, 90 - ageDays * 4);
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}
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const createdPenalty = topic.blog_title_created ? -950 : 0;
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return (
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(urgencyScore[topic.urgency] ?? 400) +
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(sourceScore[topic.source_type] ?? 40) +
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freshness +
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seededTopicJitter(topic.title, seed) +
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createdPenalty
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);
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}
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function selectDiverseTopics(topics: HotTopic[], limit: number): HotTopic[] {
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const sorted = [...topics].sort((a, b) => (b.rank_score ?? 0) - (a.rank_score ?? 0));
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const selected: HotTopic[] = [];
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const sourceTypeCount = new Map<string, number>();
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const sourceCount = new Map<string, number>();
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for (const topic of sorted) {
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if (selected.length >= limit) break;
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const sourceType = topic.source_type;
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const source = topic.source || "unknown";
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const typeCount = sourceTypeCount.get(sourceType) ?? 0;
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const srcCount = sourceCount.get(source) ?? 0;
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if (typeCount >= 5) continue;
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if (srcCount >= 3) continue;
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selected.push(topic);
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sourceTypeCount.set(sourceType, typeCount + 1);
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sourceCount.set(source, srcCount + 1);
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}
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if (selected.length < limit) {
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for (const topic of sorted) {
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if (selected.length >= limit) break;
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if (!selected.includes(topic)) selected.push(topic);
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}
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}
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return selected;
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}
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function detectNewsTheme(title: string): string {
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const tl = title.toLowerCase();
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if (tl.includes("800g") || tl.includes("osfp")) return "800G Deployment Wave";
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@ -37,7 +37,7 @@
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'<div style="background:linear-gradient(135deg,#1a1a1a,#2a2a2a);color:white;padding:2rem;border-radius:12px;text-align:center;margin-bottom:1rem">' +
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'<div style="font-size:1.4rem;font-weight:700;margin-bottom:1rem">Generating Blog with AI...</div>' +
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'<div id="bp-status" style="font-size:1rem;color:#FF8100;margin-bottom:0.5rem">Starting 10-step Flexoptix Style pipeline...</div>' +
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'<div id="bp-step" style="font-size:0.85rem;color:#aaa">Connecting to LLM (qwen2.5:14b)</div>' +
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'<div id="bp-step" style="font-size:0.85rem;color:#aaa">Connecting to FO_BlogLLM (fo-blog-v7)</div>' +
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'<div style="margin-top:1.5rem;background:#333;border-radius:8px;height:8px;overflow:hidden">' +
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'<div id="bp-bar" style="width:2%;height:100%;background:#FF8100;transition:width 0.5s ease"></div></div>' +
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'<div id="bp-pct" style="font-size:0.8rem;color:#666;margin-top:0.5rem">0%</div>' +
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@ -46,8 +46,8 @@
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var body = { topic: topic };
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if (speed) body.speed = speed;
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if (customTitle) body.customTitle = customTitle;
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if (customAngle) body.customAngle = customAngle;
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if (customTitle) body.custom_title = customTitle;
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if (customAngle) body.additional_context = customAngle;
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fetch(API + '/api/blog/generate', {
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method: 'POST',
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@ -137,7 +137,7 @@
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if (bar) bar.style.width = prog.pct + '%';
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if (pct) pct.textContent = prog.pct + '%';
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if (status) { status.style.color = '#FF8100'; status.textContent = prog.label || ('Step ' + prog.step + '/10'); }
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if (step) step.textContent = 'Step ' + prog.step + '/10 · qwen2.5:14b via Ollama';
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if (step) step.textContent = 'Step ' + prog.step + '/10 · fo-blog-v7 via adapter bridge';
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} else {
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_stallCount++;
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// After 5 consecutive non-running polls (~40s), show stall warning
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@ -185,7 +185,8 @@
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if (!grid) return;
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grid.innerHTML = '<div class="loading pulse">Discovering hot topics...</div>';
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fetch(API + '/api/hot-topics', { headers: authHeaders() })
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var shuffle = Date.now().toString(36);
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fetch(API + '/api/hot-topics?limit=20&shuffle=' + encodeURIComponent(shuffle), { headers: authHeaders({ 'Cache-Control': 'no-cache' }) })
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.then(function(r) { return r.json(); })
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.then(function(data) {
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if (!data.topics || data.topics.length === 0) {
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@ -196,7 +197,7 @@
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if (subtitle && data.refreshes_at) {
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var nextRefresh = new Date(data.refreshes_at);
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var hoursLeft = Math.round((nextRefresh - new Date()) / 3600000);
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subtitle.textContent = data.total + ' topics · rotates daily · next refresh in ' + hoursLeft + 'h · sources: ' + (data.sources || []).join(', ');
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subtitle.textContent = data.total + ' topics · refresh reshuffles · daily base rotation in ' + hoursLeft + 'h · sources: ' + (data.sources || []).join(', ');
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}
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var colors = { breaking: '#c1121f', hot: '#FF8100', trending: '#e6a800', emerging: '#2d6a4f' };
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@ -227,7 +228,7 @@
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window._generateFromHotTopic = function(cardId) {
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var t = window['_ht_' + cardId];
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if (!t) return;
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generateBlog(t.blog_type || 'hype_cycle', null, t.title, t.suggested_angle || t.description);
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generateBlog(t.blog_type || 'hype_cycle', null, t.title, t.llm_context || t.suggested_angle || t.description);
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};
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// Auto-load hot topics when blog tab activates
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@ -371,12 +371,15 @@ async function main() {
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);
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}
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// --- Ollama LLM tools: market analysis (qwen2.5:14b) + blog generation (fo-blog-v5) ---
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// --- Ollama-compatible LLM tools: market analysis (TIP_LLM) + blog generation (FO_BlogLLM) ---
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const OLLAMA_BASE = process.env["OLLAMA_BASE_URL"] ?? "https://ollama.fichtmueller.org";
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const TIP_LLM_MODEL = process.env["TIP_LLM_MODEL"] ?? "tip-llm-v1";
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const BLOG_LLM_MODEL = process.env["BLOG_LLM_MODEL"] ?? "fo-blog-v7";
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const BLOG_LLM_FALLBACK = process.env["BLOG_LLM_FALLBACK_MODEL"] ?? "qwen2.5:14b";
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server.tool(
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"analyze_market_with_llm",
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"Deep market analysis for a transceiver technology using local LLM (qwen2.5:14b). Provides expert narrative on adoption trends, pricing trajectory, competitive dynamics, and buy/wait/hold recommendation.",
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"Deep market analysis for a transceiver technology using TIP_LLM. Provides expert narrative on adoption trends, pricing trajectory, competitive dynamics, and buy/wait/hold recommendation.",
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{
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technology: z.string().describe("Technology to analyze, e.g. '400G QSFP-DD', '800G OSFP', '100G ZR'"),
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context: z.string().optional().describe("Additional context or specific questions to address"),
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@ -435,7 +438,7 @@ Keep the analysis actionable and data-driven. Under 400 words.`;
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const resp = await fetch(`${OLLAMA_BASE}/api/generate`, {
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method: "POST",
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headers: { "Content-Type": "application/json" },
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body: JSON.stringify({ model: "qwen2.5:14b", prompt, stream: false }),
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body: JSON.stringify({ model: TIP_LLM_MODEL, prompt, stream: false }),
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signal: AbortSignal.timeout(120_000),
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});
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if (!resp.ok) throw new Error(`Ollama HTTP ${resp.status}`);
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@ -449,7 +452,7 @@ Keep the analysis actionable and data-driven. Under 400 words.`;
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server.tool(
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"generate_blog_post",
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"Generate a professional Flexoptix blog post using the fine-tuned fo-blog-v5 model (Ollama). Automatically enriched with live pricing, hype cycle data, and competitor analysis.",
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"Generate a professional Flexoptix blog post using the latest FO_BlogLLM model. Automatically enriched with live pricing, hype cycle data, and competitor analysis.",
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{
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topic: z.string().describe("Blog topic, e.g. '400G QSFP-DD vs 400G ZR — which for your DC?'"),
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target_audience: z.enum(["network_engineer", "procurement", "executive", "general"]).default("network_engineer").describe("Target reader"),
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@ -492,7 +495,7 @@ Do not include a title (added separately). Start directly with the article body.
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method: "POST",
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headers: { "Content-Type": "application/json" },
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body: JSON.stringify({
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model: "fo-blog-v5",
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model: BLOG_LLM_MODEL,
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messages: [
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{ role: "system", content: systemPrompt },
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{ role: "user", content: userPrompt },
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@ -502,12 +505,12 @@ Do not include a title (added separately). Start directly with the article body.
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signal: AbortSignal.timeout(180_000),
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});
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if (!resp.ok) {
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// Fallback to qwen2.5:14b if fo-blog-v5 not available
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// Fallback to generic local model if FO_BlogLLM is unavailable
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const fallbackResp = await fetch(`${OLLAMA_BASE}/api/chat`, {
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method: "POST",
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headers: { "Content-Type": "application/json" },
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body: JSON.stringify({
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model: "qwen2.5:14b",
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model: BLOG_LLM_FALLBACK,
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messages: [
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{ role: "system", content: systemPrompt },
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{ role: "user", content: userPrompt },
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@ -516,9 +519,9 @@ Do not include a title (added separately). Start directly with the article body.
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}),
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signal: AbortSignal.timeout(180_000),
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});
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if (!fallbackResp.ok) throw new Error(`Both fo-blog-v5 and qwen2.5:14b unavailable`);
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if (!fallbackResp.ok) throw new Error(`Both ${BLOG_LLM_MODEL} and ${BLOG_LLM_FALLBACK} unavailable`);
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const fallbackData = await fallbackResp.json() as { message?: { content?: string } };
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return { content: [{ type: "text" as const, text: `[Generated with qwen2.5:14b — fo-blog-v5 unavailable]\n\n${fallbackData.message?.content ?? "No content"}` }] };
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return { content: [{ type: "text" as const, text: `[Generated with ${BLOG_LLM_FALLBACK} — ${BLOG_LLM_MODEL} unavailable]\n\n${fallbackData.message?.content ?? "No content"}` }] };
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}
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const data = await resp.json() as { message?: { content?: string } };
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return { content: [{ type: "text" as const, text: data.message?.content ?? "No content generated." }] };
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@ -11,7 +11,8 @@
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"scrape:cisco": "tsx src/scrapers/cisco-tmg.ts",
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"scrape:optcore": "tsx src/scrapers/optcore.ts",
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"scrape:news": "tsx src/scrapers/news.ts",
|
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"scrape:all": "tsx src/index.ts --all"
|
||||
"scrape:all": "tsx src/index.ts --all",
|
||||
"robots:verification": "tsx src/robots/verification-robots.ts"
|
||||
},
|
||||
"dependencies": {
|
||||
"crawlee": "^3.12.0",
|
||||
|
||||
@ -15,7 +15,7 @@ import { VENDOR_PROFILES } from "./stock-schema";
|
||||
import { validateStockExtraction } from "./validator";
|
||||
|
||||
const OLLAMA_HOST = process.env.OLLAMA_HOST || "http://192.168.178.169:11434";
|
||||
const OLLAMA_MODEL = process.env.CRAWLER_LLM_MODEL || "qwen2.5:14b";
|
||||
const OLLAMA_MODEL = process.env.CRAWLER_LLM_MODEL || "tip-llm-v1";
|
||||
const MAX_HTML_CHARS = 12_000; // truncate to keep prompt manageable
|
||||
|
||||
// ─────────────────────────────────────────────────────────────────────────────
|
||||
|
||||
@ -9,6 +9,7 @@ type Row = { id: string; lane: Lane; source: string; kind: string; messages: Mes
|
||||
|
||||
const repoRoot = process.cwd();
|
||||
const externalRoot = process.env.TIP_LEARNING_SOURCE_DIR || join(homedir(), "transceiver-training-data");
|
||||
const giteaTrainingRoot = process.env.TIP_TRAINING_REPO || "/tmp/tip-training-data";
|
||||
const blogMegaRoot = process.env.BLOG_LLM_SOURCE_DIR || join(homedir(), "Desktop", "BlogLLM-v5-Mega-Training");
|
||||
const outRoot = join(repoRoot, "training-data", "runpod");
|
||||
|
||||
@ -128,11 +129,25 @@ function markdownBlog(path: string): Row[] {
|
||||
}];
|
||||
}
|
||||
|
||||
function collectJsonlDir(dir: string, lane: Lane): Row[] {
|
||||
if (!existsSync(dir)) return [];
|
||||
const rows: Row[] = [];
|
||||
for (const entry of readdirSync(dir, { withFileTypes: true })) {
|
||||
const path = join(dir, entry.name);
|
||||
if (entry.isDirectory()) rows.push(...collectJsonlDir(path, lane));
|
||||
else if (entry.isFile() && entry.name.endsWith(".jsonl")) rows.push(...jsonl(path, lane));
|
||||
}
|
||||
return rows;
|
||||
}
|
||||
|
||||
function collect(lane: Lane): Row[] {
|
||||
const rows: Row[] = [];
|
||||
for (const file of files[lane]) {
|
||||
for (const root of [externalRoot, blogMegaRoot, repoRoot]) rows.push(...jsonl(join(root, file), lane));
|
||||
}
|
||||
if (lane === "tip_llm") {
|
||||
rows.push(...collectJsonlDir(join(giteaTrainingRoot, "qa-pairs"), lane));
|
||||
}
|
||||
if (lane === "blog_llm") {
|
||||
for (const dir of [join(repoRoot, "blog-training-data"), join(externalRoot, "v6-tip-blogs")]) {
|
||||
if (!existsSync(dir)) continue;
|
||||
|
||||
Loading…
x
Reference in New Issue
Block a user