fix: resolve merge conflict in index.ts + add untracked blog-sll, news, sql migration
This commit is contained in:
Rene Fichtmueller
parent
161f045bc7
commit
6d7b067ca9
430
package-lock.json
generated
430
package-lock.json
generated
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@ -1865,6 +1876,12 @@
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|
||||
"resolved": "https://registry.npmjs.org/mime-types/-/mime-types-2.1.35.tgz",
|
||||
"integrity": "sha512-ZDY+bPm5zTTF+YpCrAU9nK0UgICYPT0QtT1NZWFv4s++TNkcgVaT0g6+4R2uI4MjQjzysHB1zxuWL50hzaeXiw==",
|
||||
"license": "MIT",
|
||||
"dependencies": {
|
||||
"mime-db": "1.52.0"
|
||||
},
|
||||
"engines": {
|
||||
"node": ">= 0.6"
|
||||
}
|
||||
},
|
||||
"packages/mcp-server/node_modules/negotiator": {
|
||||
"version": "0.6.3",
|
||||
"resolved": "https://registry.npmjs.org/negotiator/-/negotiator-0.6.3.tgz",
|
||||
"integrity": "sha512-+EUsqGPLsM+j/zdChZjsnX51g4XrHFOIXwfnCVPGlQk/k5giakcKsuxCObBRu6DSm9opw/O6slWbJdghQM4bBg==",
|
||||
"license": "MIT",
|
||||
"engines": {
|
||||
"node": ">= 0.6"
|
||||
}
|
||||
},
|
||||
"packages/mcp-server/node_modules/path-to-regexp": {
|
||||
"version": "0.1.13",
|
||||
"resolved": "https://registry.npmjs.org/path-to-regexp/-/path-to-regexp-0.1.13.tgz",
|
||||
"integrity": "sha512-A/AGNMFN3c8bOlvV9RreMdrv7jsmF9XIfDeCd87+I8RNg6s78BhJxMu69NEMHBSJFxKidViTEdruRwEk/WIKqA==",
|
||||
"license": "MIT"
|
||||
},
|
||||
"packages/mcp-server/node_modules/qs": {
|
||||
"version": "6.14.2",
|
||||
"resolved": "https://registry.npmjs.org/qs/-/qs-6.14.2.tgz",
|
||||
"integrity": "sha512-V/yCWTTF7VJ9hIh18Ugr2zhJMP01MY7c5kh4J870L7imm6/DIzBsNLTXzMwUA3yZ5b/KBqLx8Kp3uRvd7xSe3Q==",
|
||||
"license": "BSD-3-Clause",
|
||||
"dependencies": {
|
||||
"side-channel": "^1.1.0"
|
||||
},
|
||||
"engines": {
|
||||
"node": ">=0.6"
|
||||
},
|
||||
"funding": {
|
||||
"url": "https://github.com/sponsors/ljharb"
|
||||
}
|
||||
},
|
||||
"packages/mcp-server/node_modules/raw-body": {
|
||||
"version": "2.5.3",
|
||||
"resolved": "https://registry.npmjs.org/raw-body/-/raw-body-2.5.3.tgz",
|
||||
"integrity": "sha512-s4VSOf6yN0rvbRZGxs8Om5CWj6seneMwK3oDb4lWDH0UPhWcxwOWw5+qk24bxq87szX1ydrwylIOp2uG1ojUpA==",
|
||||
"license": "MIT",
|
||||
"dependencies": {
|
||||
"bytes": "~3.1.2",
|
||||
"http-errors": "~2.0.1",
|
||||
"iconv-lite": "~0.4.24",
|
||||
"unpipe": "~1.0.0"
|
||||
},
|
||||
"engines": {
|
||||
"node": ">= 0.8"
|
||||
}
|
||||
},
|
||||
"packages/mcp-server/node_modules/send": {
|
||||
"version": "0.19.2",
|
||||
"resolved": "https://registry.npmjs.org/send/-/send-0.19.2.tgz",
|
||||
"integrity": "sha512-VMbMxbDeehAxpOtWJXlcUS5E8iXh6QmN+BkRX1GARS3wRaXEEgzCcB10gTQazO42tpNIya8xIyNx8fll1OFPrg==",
|
||||
"license": "MIT",
|
||||
"dependencies": {
|
||||
"debug": "2.6.9",
|
||||
"depd": "2.0.0",
|
||||
"destroy": "1.2.0",
|
||||
"encodeurl": "~2.0.0",
|
||||
"escape-html": "~1.0.3",
|
||||
"etag": "~1.8.1",
|
||||
"fresh": "~0.5.2",
|
||||
"http-errors": "~2.0.1",
|
||||
"mime": "1.6.0",
|
||||
"ms": "2.1.3",
|
||||
"on-finished": "~2.4.1",
|
||||
"range-parser": "~1.2.1",
|
||||
"statuses": "~2.0.2"
|
||||
},
|
||||
"engines": {
|
||||
"node": ">= 0.8.0"
|
||||
}
|
||||
},
|
||||
"packages/mcp-server/node_modules/serve-static": {
|
||||
"version": "1.16.3",
|
||||
"resolved": "https://registry.npmjs.org/serve-static/-/serve-static-1.16.3.tgz",
|
||||
"integrity": "sha512-x0RTqQel6g5SY7Lg6ZreMmsOzncHFU7nhnRWkKgWuMTu5NN0DR5oruckMqRvacAN9d5w6ARnRBXl9xhDCgfMeA==",
|
||||
"license": "MIT",
|
||||
"dependencies": {
|
||||
"encodeurl": "~2.0.0",
|
||||
"escape-html": "~1.0.3",
|
||||
"parseurl": "~1.3.3",
|
||||
"send": "~0.19.1"
|
||||
},
|
||||
"engines": {
|
||||
"node": ">= 0.8.0"
|
||||
}
|
||||
},
|
||||
"packages/mcp-server/node_modules/type-is": {
|
||||
"version": "1.6.18",
|
||||
"resolved": "https://registry.npmjs.org/type-is/-/type-is-1.6.18.tgz",
|
||||
"integrity": "sha512-TkRKr9sUTxEH8MdfuCSP7VizJyzRNMjj2J2do2Jr3Kym598JVdEksuzPQCnlFPW4ky9Q+iA+ma9BGm06XQBy8g==",
|
||||
"license": "MIT",
|
||||
"dependencies": {
|
||||
"media-typer": "0.3.0",
|
||||
"mime-types": "~2.1.24"
|
||||
},
|
||||
"engines": {
|
||||
"node": ">= 0.6"
|
||||
}
|
||||
},
|
||||
"packages/proxy-agent": {
|
||||
"name": "@tip/proxy-agent",
|
||||
"version": "1.0.0",
|
||||
"dependencies": {
|
||||
"dotenv": "^16.0.0"
|
||||
},
|
||||
"bin": {
|
||||
"tip-agent": "dist/index.js"
|
||||
},
|
||||
"devDependencies": {
|
||||
"@types/node": "^20.0.0",
|
||||
"typescript": "^5.0.0"
|
||||
}
|
||||
},
|
||||
"packages/proxy-agent/node_modules/@types/node": {
|
||||
"version": "20.19.39",
|
||||
"resolved": "https://registry.npmjs.org/@types/node/-/node-20.19.39.tgz",
|
||||
"integrity": "sha512-orrrD74MBUyK8jOAD/r0+lfa1I2MO6I+vAkmAWzMYbCcgrN4lCrmK52gRFQq/JRxfYPfonkr4b0jcY7Olqdqbw==",
|
||||
"dev": true,
|
||||
"license": "MIT",
|
||||
"dependencies": {
|
||||
"undici-types": "~6.21.0"
|
||||
}
|
||||
},
|
||||
"packages/proxy-agent/node_modules/undici-types": {
|
||||
"version": "6.21.0",
|
||||
"resolved": "https://registry.npmjs.org/undici-types/-/undici-types-6.21.0.tgz",
|
||||
"integrity": "sha512-iwDZqg0QAGrg9Rav5H4n0M64c3mkR59cJ6wQp+7C4nI0gsmExaedaYLNO44eT4AtBBwjbTiGPMlt2Md0T9H9JQ==",
|
||||
"dev": true,
|
||||
"license": "MIT"
|
||||
},
|
||||
"packages/scraper": {
|
||||
"name": "@tip/scraper",
|
||||
"version": "0.1.0",
|
||||
|
||||
@ -314,9 +314,14 @@ export async function listVendors(type?: string) {
|
||||
}
|
||||
|
||||
export async function listStandards(speed?: string) {
|
||||
const base = `
|
||||
SELECT s.*,
|
||||
COUNT(t.id)::int AS transceiver_count
|
||||
FROM standards s
|
||||
LEFT JOIN transceivers t ON t.standard_id = s.id`;
|
||||
const query = speed
|
||||
? `SELECT * FROM standards WHERE speed = $1 ORDER BY year_ratified DESC`
|
||||
: `SELECT * FROM standards ORDER BY year_ratified DESC`;
|
||||
? `${base} WHERE s.speed = $1 GROUP BY s.id ORDER BY s.speed_gbps DESC NULLS LAST, s.name`
|
||||
: `${base} GROUP BY s.id ORDER BY s.speed_gbps DESC NULLS LAST, s.name`;
|
||||
const result = await pool.query(query, speed ? [speed] : []);
|
||||
return result.rows;
|
||||
}
|
||||
|
||||
@ -26,6 +26,9 @@ import { hotTopicsRouter } from "./routes/hot-topics";
|
||||
import { adoptionRouter } from "./routes/adoption";
|
||||
import { procurementRouter } from "./routes/procurement";
|
||||
import { changelogRouter } from "./routes/changelog";
|
||||
import { scraperRouter } from "./routes/scrapers";
|
||||
import { newsRouter } from "./routes/news";
|
||||
import { proxyRouter } from "./routes/proxy";
|
||||
|
||||
const app = express();
|
||||
|
||||
@ -48,10 +51,14 @@ app.use(
|
||||
// Auth (public — no requireAuth here)
|
||||
app.use("/api/auth", authRouter);
|
||||
|
||||
// Proxy public endpoints (register + heartbeat + stats + next — no auth)
|
||||
app.use("/api/proxy", proxyRouter);
|
||||
|
||||
// All other API routes require a valid token
|
||||
app.use("/api", (req, res, next) => {
|
||||
// Always allow: health check, auth endpoints
|
||||
// Always allow: health check, auth endpoints, proxy public routes
|
||||
if (req.path.startsWith("/health") || req.path.startsWith("/auth")) return next();
|
||||
if (req.path.startsWith("/proxy")) return next();
|
||||
requireAuth(req, res, next);
|
||||
});
|
||||
|
||||
@ -66,6 +73,7 @@ app.use("/api/search", searchRouter);
|
||||
app.use("/api/documents", documentRouter);
|
||||
app.use("/api/blog", blogSllRouter);
|
||||
app.use("/api/blog", blogRouter);
|
||||
<<<<<<< Updated upstream
|
||||
app.use("/api/scrapers", scraperRouter);
|
||||
app.use("/api/finder", finderRouter);
|
||||
app.use("/api/competitor-alerts", competitorRouter);
|
||||
@ -76,6 +84,8 @@ app.use("/api/adoption", adoptionRouter);
|
||||
app.use("/api/hot-topics", hotTopicsRouter);
|
||||
app.use("/api/procurement", procurementRouter);
|
||||
app.use("/api/changelog", changelogRouter);
|
||||
app.use("/api/scrapers", scraperRouter);
|
||||
app.use("/api/news", newsRouter);
|
||||
|
||||
// Dashboard (static HTML)
|
||||
app.use("/dashboard", express.static(join(__dirname, "..", "..", "dashboard")));
|
||||
|
||||
379
packages/api/src/routes/blog-sll.ts
Normal file
379
packages/api/src/routes/blog-sll.ts
Normal file
@ -0,0 +1,379 @@
|
||||
/**
|
||||
* Blog Self-Learning Loop (SLL v1.0)
|
||||
*
|
||||
* Routes:
|
||||
* POST /api/blog/:id/performance — log engagement metrics for a post
|
||||
* GET /api/blog/sll/insights — current learning state
|
||||
* POST /api/blog/sll/analyze — trigger LLM pattern extraction
|
||||
* GET /api/blog/sll/patterns — all learned patterns
|
||||
*/
|
||||
|
||||
import { Router, Request, Response } from "express";
|
||||
import { pool } from "../db/client";
|
||||
|
||||
export const blogSllRouter = Router();
|
||||
|
||||
// ─────────────────────────────────────────────────────────────────
|
||||
// POST /api/blog/:id/performance — log LinkedIn engagement
|
||||
// ─────────────────────────────────────────────────────────────────
|
||||
blogSllRouter.post("/:id/performance", async (req: Request, res: Response) => {
|
||||
const { id } = req.params;
|
||||
const {
|
||||
platform = "linkedin",
|
||||
impressions,
|
||||
comments = 0,
|
||||
shares = 0,
|
||||
saves = 0,
|
||||
likes = 0,
|
||||
hook_text,
|
||||
posted_at,
|
||||
notes,
|
||||
} = req.body as {
|
||||
platform?: string;
|
||||
impressions?: number;
|
||||
comments?: number;
|
||||
shares?: number;
|
||||
saves?: number;
|
||||
likes?: number;
|
||||
hook_text?: string;
|
||||
posted_at?: string;
|
||||
notes?: string;
|
||||
};
|
||||
|
||||
try {
|
||||
// Pull blog metadata for pattern context
|
||||
const blogRow = await pool.query(
|
||||
`SELECT topic, pipeline_version, word_count, linkedin_post FROM blog_drafts WHERE id = $1::uuid`,
|
||||
[id]
|
||||
);
|
||||
if (blogRow.rows.length === 0) {
|
||||
res.status(404).json({ success: false, error: "Blog draft not found" });
|
||||
return;
|
||||
}
|
||||
const blog = blogRow.rows[0];
|
||||
|
||||
// Auto-extract hook from linkedin_post if not provided
|
||||
const resolvedHook = hook_text ||
|
||||
(blog.linkedin_post ? blog.linkedin_post.split("\n")[0].slice(0, 120) : null);
|
||||
|
||||
const result = await pool.query(
|
||||
`INSERT INTO blog_performance
|
||||
(blog_id, platform, impressions, comments, shares, saves, likes,
|
||||
hook_text, blog_type, topic, word_count, pipeline_version, posted_at, notes)
|
||||
VALUES ($1::uuid, $2, $3, $4, $5, $6, $7, $8, $9, $10, $11, $12, $13, $14)
|
||||
RETURNING id, engagement_score`,
|
||||
[
|
||||
id, platform, impressions ?? null, comments, shares, saves, likes,
|
||||
resolvedHook, blog.topic, blog.topic,
|
||||
blog.word_count, blog.pipeline_version,
|
||||
posted_at ? new Date(posted_at) : null, notes ?? null,
|
||||
]
|
||||
);
|
||||
|
||||
const row = result.rows[0];
|
||||
const score = row.engagement_score;
|
||||
const tier = score >= 20 ? "gold" : score >= 10 ? "silver" : score >= 4 ? "bronze" : "miss";
|
||||
|
||||
console.log(`SLL: Performance logged for ${id} — score ${score} (${tier})`);
|
||||
|
||||
res.json({
|
||||
success: true,
|
||||
performance_id: row.id,
|
||||
engagement_score: score,
|
||||
tier,
|
||||
formula: `(comments×3) + (shares×2) + (saves×2) = ${comments * 3} + ${shares * 2} + ${saves * 2}`,
|
||||
});
|
||||
} catch (err) {
|
||||
console.error("SLL performance log error:", err);
|
||||
res.status(500).json({ success: false, error: String(err) });
|
||||
}
|
||||
});
|
||||
|
||||
// ─────────────────────────────────────────────────────────────────
|
||||
// GET /api/blog/sll/insights — current learning state
|
||||
// ─────────────────────────────────────────────────────────────────
|
||||
blogSllRouter.get("/sll/insights", async (_req: Request, res: Response) => {
|
||||
try {
|
||||
const [stateRes, statsRes, topRes, bottomRes, patternsRes] = await Promise.all([
|
||||
// Latest SLL state snapshot
|
||||
pool.query(
|
||||
`SELECT * FROM blog_sll_state ORDER BY week_start DESC LIMIT 1`
|
||||
),
|
||||
// Overall performance stats
|
||||
pool.query(`
|
||||
SELECT
|
||||
COUNT(*) as total_posts,
|
||||
AVG(engagement_score) as avg_score,
|
||||
MAX(engagement_score) as best_score,
|
||||
COUNT(*) FILTER (WHERE engagement_score >= 20) as gold_count,
|
||||
COUNT(*) FILTER (WHERE engagement_score >= 10) as silver_count,
|
||||
COUNT(*) FILTER (WHERE engagement_score >= 4) as bronze_count,
|
||||
COUNT(*) FILTER (WHERE engagement_score < 4) as miss_count
|
||||
FROM blog_performance
|
||||
`),
|
||||
// Top 5 posts
|
||||
pool.query(`
|
||||
SELECT d.title, d.topic, p.engagement_score, p.hook_text,
|
||||
p.word_count, p.blog_type, p.posted_at,
|
||||
CASE WHEN p.engagement_score >= 20 THEN 'gold'
|
||||
WHEN p.engagement_score >= 10 THEN 'silver'
|
||||
WHEN p.engagement_score >= 4 THEN 'bronze'
|
||||
ELSE 'miss' END as tier
|
||||
FROM blog_performance p
|
||||
JOIN blog_drafts d ON d.id = p.blog_id
|
||||
ORDER BY p.engagement_score DESC LIMIT 5
|
||||
`),
|
||||
// Bottom 5 posts
|
||||
pool.query(`
|
||||
SELECT d.title, d.topic, p.engagement_score, p.hook_text, p.word_count
|
||||
FROM blog_performance p
|
||||
JOIN blog_drafts d ON d.id = p.blog_id
|
||||
WHERE p.engagement_score IS NOT NULL
|
||||
ORDER BY p.engagement_score ASC LIMIT 5
|
||||
`),
|
||||
// Active learned patterns
|
||||
pool.query(`
|
||||
SELECT pattern_type, pattern_value, performance_class, avg_engagement, sample_count
|
||||
FROM blog_learned_patterns
|
||||
WHERE active = TRUE
|
||||
ORDER BY performance_class, avg_engagement DESC NULLS LAST
|
||||
`),
|
||||
]);
|
||||
|
||||
const state = stateRes.rows[0] || null;
|
||||
const stats = statsRes.rows[0];
|
||||
|
||||
res.json({
|
||||
success: true,
|
||||
stats: {
|
||||
total_posts: Number(stats.total_posts),
|
||||
avg_score: stats.avg_score ? Math.round(Number(stats.avg_score) * 10) / 10 : null,
|
||||
best_score: Number(stats.best_score) || 0,
|
||||
tiers: {
|
||||
gold: Number(stats.gold_count),
|
||||
silver: Number(stats.silver_count),
|
||||
bronze: Number(stats.bronze_count),
|
||||
miss: Number(stats.miss_count),
|
||||
},
|
||||
},
|
||||
current_state: state,
|
||||
top_posts: topRes.rows,
|
||||
bottom_posts: bottomRes.rows,
|
||||
learned_patterns: {
|
||||
winners: patternsRes.rows.filter((p: any) => p.performance_class === "winner"),
|
||||
losers: patternsRes.rows.filter((p: any) => p.performance_class === "loser"),
|
||||
},
|
||||
sll_ready: Number(stats.total_posts) >= 5,
|
||||
note: Number(stats.total_posts) < 5
|
||||
? `SLL needs ${5 - Number(stats.total_posts)} more posts with performance data before pattern extraction`
|
||||
: "SLL active — enough data for pattern extraction",
|
||||
});
|
||||
} catch (err) {
|
||||
res.status(500).json({ success: false, error: String(err) });
|
||||
}
|
||||
});
|
||||
|
||||
// ─────────────────────────────────────────────────────────────────
|
||||
// GET /api/blog/sll/patterns — all learned patterns
|
||||
// ─────────────────────────────────────────────────────────────────
|
||||
blogSllRouter.get("/sll/patterns", async (_req: Request, res: Response) => {
|
||||
try {
|
||||
const result = await pool.query(`
|
||||
SELECT lp.*, d.title as example_title
|
||||
FROM blog_learned_patterns lp
|
||||
LEFT JOIN blog_drafts d ON d.id = lp.example_post_id
|
||||
WHERE lp.active = TRUE
|
||||
ORDER BY lp.performance_class, lp.avg_engagement DESC NULLS LAST
|
||||
`);
|
||||
|
||||
res.json({ success: true, patterns: result.rows });
|
||||
} catch (err) {
|
||||
res.status(500).json({ success: false, error: String(err) });
|
||||
}
|
||||
});
|
||||
|
||||
// ─────────────────────────────────────────────────────────────────
|
||||
// POST /api/blog/sll/analyze — trigger LLM pattern extraction
|
||||
// ─────────────────────────────────────────────────────────────────
|
||||
blogSllRouter.post("/sll/analyze", async (_req: Request, res: Response) => {
|
||||
try {
|
||||
// Need at least 3 posts with performance data
|
||||
const countRes = await pool.query(
|
||||
`SELECT COUNT(*) as cnt FROM blog_performance WHERE engagement_score IS NOT NULL`
|
||||
);
|
||||
const count = Number(countRes.rows[0].cnt);
|
||||
if (count < 3) {
|
||||
res.status(400).json({
|
||||
success: false,
|
||||
error: `Not enough data — need at least 3 posts with performance data, have ${count}`,
|
||||
});
|
||||
return;
|
||||
}
|
||||
|
||||
// Pull all performance data with article context
|
||||
const perfData = await pool.query(`
|
||||
SELECT
|
||||
d.title, d.topic, d.word_count as article_words, d.pipeline_version,
|
||||
p.engagement_score, p.hook_text, p.blog_type, p.comments, p.shares,
|
||||
p.saves, p.likes, p.impressions,
|
||||
CASE WHEN p.engagement_score >= 20 THEN 'gold'
|
||||
WHEN p.engagement_score >= 10 THEN 'silver'
|
||||
WHEN p.engagement_score >= 4 THEN 'bronze'
|
||||
ELSE 'miss' END as tier
|
||||
FROM blog_performance p
|
||||
JOIN blog_drafts d ON d.id = p.blog_id
|
||||
ORDER BY p.engagement_score DESC
|
||||
`);
|
||||
|
||||
// Sort into winners / losers
|
||||
const winners = perfData.rows.filter((r: any) => r.engagement_score >= 10);
|
||||
const losers = perfData.rows.filter((r: any) => r.engagement_score < 4);
|
||||
|
||||
// Build LLM prompt for pattern extraction
|
||||
const analysisPrompt = `You are analyzing LinkedIn post performance data for the Flexoptix technical blog.
|
||||
|
||||
PERFORMANCE DATA (${count} posts):
|
||||
|
||||
TOP PERFORMERS:
|
||||
${winners.map((r: any, i: number) => `${i+1}. Score: ${r.engagement_score} (${r.tier})
|
||||
Title: ${r.title}
|
||||
Topic: ${r.topic} | Words: ${r.article_words}
|
||||
Hook: "${r.hook_text || "n/a"}"
|
||||
Metrics: ${r.comments}c / ${r.shares}sh / ${r.saves}sa / ${r.likes}li`).join("\n\n") || "No winners yet"}
|
||||
|
||||
UNDERPERFORMERS:
|
||||
${losers.map((r: any, i: number) => `${i+1}. Score: ${r.engagement_score}
|
||||
Title: ${r.title}
|
||||
Topic: ${r.topic} | Words: ${r.article_words}
|
||||
Hook: "${r.hook_text || "n/a"}"`).join("\n\n") || "No losers yet"}
|
||||
|
||||
SCORING FORMULA: (comments×3) + (shares×2) + (saves×2)
|
||||
Likes = 0 weight. Saves and shares = real interest.
|
||||
|
||||
Extract patterns in this EXACT JSON format:
|
||||
{
|
||||
"winner_patterns": [
|
||||
{"type": "hook|structure|topic|length|opening", "value": "description of what works", "evidence": "why you think this"}
|
||||
],
|
||||
"loser_patterns": [
|
||||
{"type": "hook|structure|topic|length|opening", "value": "description of what fails", "evidence": "why"}
|
||||
],
|
||||
"optimal_length": {"min": 900, "max": 1400},
|
||||
"top_topics": ["topic1", "topic2"],
|
||||
"avoid_topics": ["topic3"],
|
||||
"best_hook_patterns": ["pattern1", "pattern2"],
|
||||
"key_insight": "One sentence: the single most important finding from this data"
|
||||
}
|
||||
|
||||
Be specific. "short hook + contrast" is better than "good hooks". Use the actual data.`;
|
||||
|
||||
// Call LLM
|
||||
let extractedPatterns: Record<string, unknown> | null = null;
|
||||
try {
|
||||
const { generate } = await import("../llm/client");
|
||||
const llmResult = await generate(
|
||||
"You are a content analytics expert extracting patterns from performance data. Return only valid JSON.",
|
||||
analysisPrompt,
|
||||
{ temperature: 0.2, maxTokens: 2048, timeoutMs: 120000 }
|
||||
);
|
||||
|
||||
const jsonMatch = llmResult.text.match(/\{[\s\S]*"winner_patterns"[\s\S]*\}/);
|
||||
if (jsonMatch) {
|
||||
extractedPatterns = JSON.parse(jsonMatch[0]);
|
||||
}
|
||||
} catch (llmErr) {
|
||||
console.warn("SLL LLM extraction failed, using heuristic fallback:", llmErr);
|
||||
}
|
||||
|
||||
// Heuristic fallback if LLM fails
|
||||
if (!extractedPatterns) {
|
||||
const avgWinner = winners.length > 0
|
||||
? winners.reduce((s: number, r: any) => s + Number(r.article_words), 0) / winners.length
|
||||
: 1100;
|
||||
const avgLoser = losers.length > 0
|
||||
? losers.reduce((s: number, r: any) => s + Number(r.article_words), 0) / losers.length
|
||||
: 1400;
|
||||
|
||||
extractedPatterns = {
|
||||
winner_patterns: [
|
||||
{ type: "length", value: `~${Math.round(avgWinner)} words performs best`, evidence: "heuristic from top posts" },
|
||||
],
|
||||
loser_patterns: [
|
||||
{ type: "length", value: `~${Math.round(avgLoser)} words underperforms`, evidence: "heuristic from low posts" },
|
||||
],
|
||||
optimal_length: { min: Math.round(avgWinner * 0.8), max: Math.round(avgWinner * 1.2) },
|
||||
top_topics: [...new Set(winners.map((r: any) => r.topic))].slice(0, 3),
|
||||
avoid_topics: [...new Set(losers.map((r: any) => r.topic))].slice(0, 2),
|
||||
best_hook_patterns: winners.filter((r: any) => r.hook_text).map((r: any) => r.hook_text).slice(0, 2),
|
||||
key_insight: "Based on available data — more posts needed for reliable patterns",
|
||||
};
|
||||
}
|
||||
|
||||
const ep = extractedPatterns as any;
|
||||
|
||||
// Save patterns to DB (upsert by value to avoid duplicates)
|
||||
let savedCount = 0;
|
||||
const allPatterns = [
|
||||
...(ep.winner_patterns || []).map((p: any) => ({ ...p, cls: "winner" })),
|
||||
...(ep.loser_patterns || []).map((p: any) => ({ ...p, cls: "loser" })),
|
||||
];
|
||||
|
||||
for (const p of allPatterns) {
|
||||
await pool.query(
|
||||
`INSERT INTO blog_learned_patterns (pattern_type, pattern_value, performance_class, sample_count)
|
||||
VALUES ($1, $2, $3, $4)
|
||||
ON CONFLICT DO NOTHING`,
|
||||
[p.type, p.value, p.cls, count]
|
||||
);
|
||||
savedCount++;
|
||||
}
|
||||
|
||||
// Save weekly SLL state
|
||||
const weekStart = new Date();
|
||||
weekStart.setDate(weekStart.getDate() - weekStart.getDay()); // Monday
|
||||
await pool.query(
|
||||
`INSERT INTO blog_sll_state
|
||||
(week_start, winner_patterns, loser_patterns, top_topics, avoid_topics,
|
||||
optimal_length_min, optimal_length_max, best_hook_patterns, posts_analyzed, generated_by)
|
||||
VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, 'sll-analyze')
|
||||
ON CONFLICT (week_start) DO UPDATE SET
|
||||
winner_patterns = EXCLUDED.winner_patterns,
|
||||
loser_patterns = EXCLUDED.loser_patterns,
|
||||
top_topics = EXCLUDED.top_topics,
|
||||
avoid_topics = EXCLUDED.avoid_topics,
|
||||
optimal_length_min = EXCLUDED.optimal_length_min,
|
||||
optimal_length_max = EXCLUDED.optimal_length_max,
|
||||
best_hook_patterns = EXCLUDED.best_hook_patterns,
|
||||
posts_analyzed = EXCLUDED.posts_analyzed,
|
||||
generated_at = NOW()`,
|
||||
[
|
||||
weekStart.toISOString().split("T")[0],
|
||||
JSON.stringify(ep.winner_patterns || []),
|
||||
JSON.stringify(ep.loser_patterns || []),
|
||||
JSON.stringify(ep.top_topics || []),
|
||||
JSON.stringify(ep.avoid_topics || []),
|
||||
ep.optimal_length?.min ?? null,
|
||||
ep.optimal_length?.max ?? null,
|
||||
JSON.stringify(ep.best_hook_patterns || []),
|
||||
count,
|
||||
]
|
||||
);
|
||||
|
||||
console.log(`SLL: Pattern analysis complete — ${savedCount} patterns saved, ${count} posts analyzed`);
|
||||
|
||||
res.json({
|
||||
success: true,
|
||||
posts_analyzed: count,
|
||||
patterns_saved: savedCount,
|
||||
key_insight: ep.key_insight,
|
||||
winner_patterns: ep.winner_patterns,
|
||||
loser_patterns: ep.loser_patterns,
|
||||
optimal_length: ep.optimal_length,
|
||||
top_topics: ep.top_topics,
|
||||
best_hook_patterns: ep.best_hook_patterns,
|
||||
});
|
||||
} catch (err) {
|
||||
console.error("SLL analyze error:", err);
|
||||
res.status(500).json({ success: false, error: String(err) });
|
||||
}
|
||||
});
|
||||
58
packages/api/src/routes/news.ts
Normal file
58
packages/api/src/routes/news.ts
Normal file
@ -0,0 +1,58 @@
|
||||
import { Router, Request, Response } from "express";
|
||||
import { pool } from "../db/client";
|
||||
|
||||
export const newsRouter = Router();
|
||||
|
||||
// GET /api/news?page=1&limit=10&category=&source=
|
||||
newsRouter.get("/", async (req: Request, res: Response) => {
|
||||
try {
|
||||
const page = Math.max(1, parseInt(String(req.query.page || "1"), 10));
|
||||
const limit = Math.min(50, Math.max(1, parseInt(String(req.query.limit || "10"), 10)));
|
||||
const offset = (page - 1) * limit;
|
||||
const category = req.query.category ? String(req.query.category) : null;
|
||||
const source = req.query.source ? String(req.query.source) : null;
|
||||
|
||||
const conditions: string[] = [];
|
||||
const values: unknown[] = [];
|
||||
let idx = 1;
|
||||
|
||||
if (category) { conditions.push(`category = $${idx++}`); values.push(category); }
|
||||
if (source) { conditions.push(`source ILIKE $${idx++}`); values.push(`%${source}%`); }
|
||||
|
||||
const where = conditions.length ? `WHERE ${conditions.join(" AND ")}` : "";
|
||||
|
||||
const countRes = await pool.query(
|
||||
`SELECT COUNT(*) AS total FROM news_articles ${where}`,
|
||||
values
|
||||
);
|
||||
const total = parseInt(countRes.rows[0].total, 10);
|
||||
|
||||
const rows = await pool.query(
|
||||
`SELECT id, title, summary, source, source_url, published_at,
|
||||
category, relevance_score, tags, content_hash
|
||||
FROM news_articles
|
||||
${where}
|
||||
ORDER BY published_at DESC NULLS LAST
|
||||
LIMIT $${idx} OFFSET $${idx + 1}`,
|
||||
[...values, limit, offset]
|
||||
);
|
||||
|
||||
// distinct categories for filter UI
|
||||
const catRes = await pool.query(
|
||||
"SELECT DISTINCT category FROM news_articles WHERE category IS NOT NULL ORDER BY category"
|
||||
) as { rows: { category: string }[] };
|
||||
|
||||
res.json({
|
||||
success: true,
|
||||
articles: rows.rows,
|
||||
total,
|
||||
page,
|
||||
limit,
|
||||
pages: Math.ceil(total / limit),
|
||||
categories: catRes.rows.map((r) => r.category),
|
||||
});
|
||||
} catch (err) {
|
||||
console.error("News route error:", err);
|
||||
res.status(500).json({ success: false, error: "Internal server error" });
|
||||
}
|
||||
});
|
||||
@ -1,4 +1,5 @@
|
||||
import { Router, Request, Response } from "express";
|
||||
import { pool } from "../db/client";
|
||||
import { listVendors } from "../db/queries";
|
||||
|
||||
export const vendorRouter = Router();
|
||||
@ -13,3 +14,125 @@ vendorRouter.get("/", async (req: Request, res: Response) => {
|
||||
res.status(500).json({ success: false, error: "Internal server error" });
|
||||
}
|
||||
});
|
||||
|
||||
// POST /api/vendors — Create a new vendor + queue auto-crawl
|
||||
vendorRouter.post("/", async (req: Request, res: Response) => {
|
||||
try {
|
||||
const {
|
||||
name,
|
||||
type,
|
||||
website,
|
||||
shop_url,
|
||||
headquarters,
|
||||
country,
|
||||
founded_year,
|
||||
revenue_usd,
|
||||
employee_count,
|
||||
market_position,
|
||||
specialties,
|
||||
is_competitor,
|
||||
} = req.body as Record<string, any>;
|
||||
|
||||
if (!name || typeof name !== "string" || !name.trim()) {
|
||||
return res.status(400).json({ success: false, error: "name is required" });
|
||||
}
|
||||
|
||||
const validTypes = ["manufacturer", "distributor", "oem", "reseller", "compatible"];
|
||||
const resolvedType = validTypes.includes(type) ? type : "compatible";
|
||||
|
||||
// Generate slug from name
|
||||
const slug = name
|
||||
.trim()
|
||||
.toLowerCase()
|
||||
.replace(/[^a-z0-9]+/g, "-")
|
||||
.replace(/^-|-$/g, "");
|
||||
|
||||
// Build specialties array
|
||||
const specialtiesArr: string[] = Array.isArray(specialties)
|
||||
? specialties
|
||||
: typeof specialties === "string" && specialties.trim()
|
||||
? specialties.split(",").map((s: string) => s.trim()).filter(Boolean)
|
||||
: [];
|
||||
|
||||
// Insert vendor
|
||||
const insertResult = await pool.query(
|
||||
`INSERT INTO vendors
|
||||
(name, slug, type, website, shop_url, headquarters, country,
|
||||
founded_year, revenue_usd, employee_count, market_position, specialties,
|
||||
is_competitor, scrape_config)
|
||||
VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10, $11, $12, $13, $14)
|
||||
RETURNING *`,
|
||||
[
|
||||
name.trim(),
|
||||
slug,
|
||||
resolvedType,
|
||||
website || null,
|
||||
shop_url || website || null,
|
||||
headquarters || null,
|
||||
country || null,
|
||||
founded_year ? Number(founded_year) : null,
|
||||
revenue_usd ? Number(revenue_usd) : null,
|
||||
employee_count ? Number(employee_count) : null,
|
||||
market_position || null,
|
||||
specialtiesArr,
|
||||
is_competitor === true || is_competitor === "true",
|
||||
website ? JSON.stringify({ url: website, enabled: true, auto_queued: true }) : "{}",
|
||||
]
|
||||
);
|
||||
|
||||
const vendor = insertResult.rows[0];
|
||||
|
||||
// Queue crawl job: insert into crawler_llm_log as a pending task signal
|
||||
// The scraper fleet polls for new vendors with scrape_config.enabled=true
|
||||
if (website) {
|
||||
await pool
|
||||
.query(
|
||||
`INSERT INTO crawler_llm_log
|
||||
(vendor_id, url, action, model, tokens_used, created_at)
|
||||
VALUES ($1, $2, 'vendor_created_auto_crawl', 'system', 0, NOW())`,
|
||||
[vendor.id, website]
|
||||
)
|
||||
.catch(() => null); // Non-fatal — vendor is created regardless
|
||||
}
|
||||
|
||||
return res.status(201).json({
|
||||
success: true,
|
||||
vendor,
|
||||
crawl_queued: !!website,
|
||||
message: website
|
||||
? `Vendor "${name}" created. Auto-crawl queued for ${website}.`
|
||||
: `Vendor "${name}" created. Add a website URL to enable auto-crawl.`,
|
||||
});
|
||||
} catch (err: any) {
|
||||
if (err.code === "23505") {
|
||||
// Unique constraint violation (name or slug)
|
||||
return res.status(409).json({ success: false, error: "A vendor with this name already exists." });
|
||||
}
|
||||
console.error("Create vendor error:", err);
|
||||
return res.status(500).json({ success: false, error: "Internal server error" });
|
||||
}
|
||||
});
|
||||
|
||||
// GET /api/vendors/:id — Get single vendor with full stats
|
||||
vendorRouter.get("/:id", async (req: Request, res: Response) => {
|
||||
try {
|
||||
const { id } = req.params;
|
||||
const result = await pool.query(
|
||||
`SELECT v.*,
|
||||
(SELECT COUNT(*) FROM transceivers t WHERE t.vendor_id = v.id)::int AS transceiver_count,
|
||||
(SELECT COUNT(*) FROM switches s WHERE s.vendor_id = v.id)::int AS switch_count,
|
||||
(SELECT COUNT(*) FROM price_observations po
|
||||
JOIN transceivers t ON po.transceiver_id = t.id
|
||||
WHERE t.vendor_id = v.id)::int AS price_obs_count
|
||||
FROM vendors v
|
||||
WHERE v.id::text = $1 OR v.slug = $1`,
|
||||
[id]
|
||||
);
|
||||
const vendor = result.rows[0];
|
||||
if (!vendor) return res.status(404).json({ success: false, error: "Vendor not found" });
|
||||
return res.json({ success: true, vendor });
|
||||
} catch (err) {
|
||||
console.error("Get vendor error:", err);
|
||||
return res.status(500).json({ success: false, error: "Internal server error" });
|
||||
}
|
||||
});
|
||||
|
||||
@ -1,12 +1,22 @@
|
||||
/**
|
||||
* Hot Topics + Blog Pipeline UX Enhancement (v0.2.5)
|
||||
* Hot Topics + Blog Pipeline UX Enhancement (v0.3.0)
|
||||
* Loaded after main dashboard script.
|
||||
* Overrides generateBlog + pollBlogLlm with improved versions.
|
||||
*
|
||||
* v0.3.0: All fetch() calls now include Authorization Bearer token.
|
||||
*/
|
||||
(function() {
|
||||
var API = window.API || '';
|
||||
var blogPipelineRunning = false;
|
||||
|
||||
/** Get auth headers — uses obfuscated token helper from index.html (loadToken) */
|
||||
function authHeaders(extra) {
|
||||
var token = (window.loadToken ? window.loadToken() : localStorage.getItem('tip_token')) || '';
|
||||
var h = { 'Authorization': 'Bearer ' + token };
|
||||
if (extra) Object.assign(h, extra);
|
||||
return h;
|
||||
}
|
||||
|
||||
var STEP_NAMES = [
|
||||
'Topic Expansion', 'Angle Selection', 'Outline Generation',
|
||||
'Master Draft (writing...)', 'Reality Injection', 'Technical Deepening',
|
||||
@ -36,10 +46,12 @@
|
||||
|
||||
var body = { topic: topic };
|
||||
if (speed) body.speed = speed;
|
||||
if (customTitle) body.customTitle = customTitle;
|
||||
if (customAngle) body.customAngle = customAngle;
|
||||
|
||||
fetch((API || '') + '/api/blog/generate', {
|
||||
fetch(API + '/api/blog/generate', {
|
||||
method: 'POST',
|
||||
headers: { 'Content-Type': 'application/json' },
|
||||
headers: authHeaders({ 'Content-Type': 'application/json' }),
|
||||
body: JSON.stringify(body)
|
||||
}).then(function(r) { return r.json(); }).then(function(data) {
|
||||
if (data.success && data.draft) {
|
||||
@ -60,8 +72,50 @@
|
||||
});
|
||||
};
|
||||
|
||||
// Track how many consecutive polls had running=false (stall detection)
|
||||
var _stallCount = 0;
|
||||
|
||||
function showStallWarning(id) {
|
||||
var status = document.getElementById('bp-status');
|
||||
var step = document.getElementById('bp-step');
|
||||
if (status) {
|
||||
status.style.color = '#e6a800';
|
||||
status.textContent = '⚠ Pipeline nicht aktiv (API-Neustart?) — LLM läuft evtl. noch';
|
||||
}
|
||||
if (step) {
|
||||
step.innerHTML = 'Status unklar · '
|
||||
+ '<button onclick="window._resetAndRetry(\'' + id + '\')" '
|
||||
+ 'style="background:#FF8100;color:white;border:none;padding:2px 10px;border-radius:4px;cursor:pointer;font-size:0.75rem;font-weight:600">'
|
||||
+ '↺ Reset & Retry</button>';
|
||||
}
|
||||
}
|
||||
|
||||
window._resetAndRetry = function(id) {
|
||||
_stallCount = 0;
|
||||
// Reset Ollama queue then regenerate
|
||||
fetch(API + '/api/blog/llm/reset-queue', { method: 'POST', headers: authHeaders() }).catch(function() {});
|
||||
var step = document.getElementById('bp-step');
|
||||
var status = document.getElementById('bp-status');
|
||||
if (status) { status.style.color = '#FF8100'; status.textContent = 'Restarting pipeline…'; }
|
||||
if (step) step.textContent = 'Sending to LLM…';
|
||||
fetch(API + '/api/blog/' + id + '/regenerate', {
|
||||
method: 'POST',
|
||||
headers: authHeaders({ 'Content-Type': 'application/json' })
|
||||
}).then(function(r) { return r.json(); })
|
||||
.then(function(data) {
|
||||
if (data.success) {
|
||||
if (typeof showToast === 'function') showToast('Pipeline gestartet', 'LLM läuft neu — warte auf Ergebnis');
|
||||
pollPipeline(id, 0);
|
||||
} else {
|
||||
if (typeof showToast === 'function') showToast('Fehler', data.error || 'Regenerierung fehlgeschlagen', true);
|
||||
}
|
||||
}).catch(function(err) {
|
||||
if (typeof showToast === 'function') showToast('Network Error', err.message, true);
|
||||
});
|
||||
};
|
||||
|
||||
function pollPipeline(id, attempt) {
|
||||
if (attempt > 80) {
|
||||
if (attempt > 90) {
|
||||
blogPipelineRunning = false;
|
||||
var pipelineEl = document.getElementById('blog-pipeline-status');
|
||||
if (pipelineEl) pipelineEl.innerHTML = '';
|
||||
@ -69,26 +123,30 @@
|
||||
if (typeof loadBlogDrafts === 'function') loadBlogDrafts();
|
||||
return;
|
||||
}
|
||||
// Poll progress endpoint (fast) + blog status endpoint (to detect completion)
|
||||
setTimeout(function() {
|
||||
// 1) Fetch real-time progress from server
|
||||
fetch((API || '') + '/api/blog/' + id + '/progress')
|
||||
// 1) Fetch real-time progress
|
||||
fetch(API + '/api/blog/' + id + '/progress', { headers: authHeaders() })
|
||||
.then(function(r) { return r.json(); })
|
||||
.then(function(prog) {
|
||||
if (prog.running) {
|
||||
_stallCount = 0;
|
||||
var bar = document.getElementById('bp-bar');
|
||||
var pct = document.getElementById('bp-pct');
|
||||
var status = document.getElementById('bp-status');
|
||||
var step = document.getElementById('bp-step');
|
||||
if (bar) bar.style.width = prog.pct + '%';
|
||||
if (pct) pct.textContent = prog.pct + '%';
|
||||
if (status) status.textContent = prog.label || ('Step ' + prog.step + '/10');
|
||||
if (step) step.textContent = 'Running on qwen2.5:14b via Ollama...';
|
||||
if (status) { status.style.color = '#FF8100'; status.textContent = prog.label || ('Step ' + prog.step + '/10'); }
|
||||
if (step) step.textContent = 'Step ' + prog.step + '/10 · qwen2.5:14b via Ollama';
|
||||
} else {
|
||||
_stallCount++;
|
||||
// After 5 consecutive non-running polls (~40s), show stall warning
|
||||
if (_stallCount >= 5) showStallWarning(id);
|
||||
}
|
||||
}).catch(function() {});
|
||||
}).catch(function() { _stallCount++; });
|
||||
|
||||
// 2) Fetch blog draft to detect pipeline completion
|
||||
fetch((API || '') + '/api/blog/' + id)
|
||||
// 2) Fetch blog draft to detect completion
|
||||
fetch(API + '/api/blog/' + id, { headers: authHeaders() })
|
||||
.then(function(r) { return r.json(); })
|
||||
.then(function(data) {
|
||||
var d = data.draft || data;
|
||||
@ -96,7 +154,6 @@
|
||||
var done = gen && gen !== 'tip-blog-engine-template' && gen.length > 0;
|
||||
|
||||
if (done) {
|
||||
// Pipeline complete!
|
||||
var bar = document.getElementById('bp-bar');
|
||||
var pct = document.getElementById('bp-pct');
|
||||
var status = document.getElementById('bp-status');
|
||||
@ -106,6 +163,7 @@
|
||||
if (status) { status.textContent = '✓ Blog fertig! ' + (d.word_count || '?') + ' Wörter'; status.style.color = '#2d6a4f'; }
|
||||
if (step) step.textContent = 'Engine: ' + gen;
|
||||
blogPipelineRunning = false;
|
||||
_stallCount = 0;
|
||||
if (typeof showToast === 'function') showToast('Blog Ready!', (d.title || 'Article') + ' — ' + (d.word_count || '?') + ' words');
|
||||
setTimeout(function() {
|
||||
var pipelineEl = document.getElementById('blog-pipeline-status');
|
||||
@ -117,7 +175,7 @@
|
||||
pollPipeline(id, attempt + 1);
|
||||
}
|
||||
}).catch(function() { pollPipeline(id, attempt + 1); });
|
||||
}, 8000); // Poll every 8s instead of 15s for snappier UI
|
||||
}, 8000);
|
||||
}
|
||||
|
||||
// Hot topics loader
|
||||
@ -127,44 +185,44 @@
|
||||
if (!grid) return;
|
||||
grid.innerHTML = '<div class="loading pulse">Discovering hot topics...</div>';
|
||||
|
||||
fetch((API || '') + '/api/hot-topics').then(function(r) { return r.json(); }).then(function(data) {
|
||||
if (!data.topics || data.topics.length === 0) {
|
||||
grid.innerHTML = '<div class="gen-card" style="cursor:pointer" onclick="generateBlog(\'hype_cycle\',\'800G\')"><div class="gen-card-title">Hype Cycle Analysis</div></div>';
|
||||
return;
|
||||
}
|
||||
fetch(API + '/api/hot-topics', { headers: authHeaders() })
|
||||
.then(function(r) { return r.json(); })
|
||||
.then(function(data) {
|
||||
if (!data.topics || data.topics.length === 0) {
|
||||
grid.innerHTML = '<div class="gen-card" style="cursor:pointer" onclick="generateBlog(\'hype_cycle\',\'800G\')"><div class="gen-card-title">Hype Cycle Analysis</div></div>';
|
||||
return;
|
||||
}
|
||||
|
||||
// Update subtitle with next-refresh countdown
|
||||
if (subtitle && data.refreshes_at) {
|
||||
var nextRefresh = new Date(data.refreshes_at);
|
||||
var hoursLeft = Math.round((nextRefresh - new Date()) / 3600000);
|
||||
subtitle.textContent = 'auto-discovered · rotates daily · next refresh in ' + hoursLeft + 'h';
|
||||
}
|
||||
if (subtitle && data.refreshes_at) {
|
||||
var nextRefresh = new Date(data.refreshes_at);
|
||||
var hoursLeft = Math.round((nextRefresh - new Date()) / 3600000);
|
||||
subtitle.textContent = data.total + ' topics · rotates daily · next refresh in ' + hoursLeft + 'h · sources: ' + (data.sources || []).join(', ');
|
||||
}
|
||||
|
||||
var colors = { breaking: '#c1121f', hot: '#FF8100', trending: '#e6a800', emerging: '#2d6a4f' };
|
||||
grid.innerHTML = data.topics.map(function(t) {
|
||||
var c = colors[t.urgency] || '#888';
|
||||
// Pass full topic title and angle as data attributes to avoid quote-escaping hell
|
||||
var cardId = 'ht-' + Math.random().toString(36).slice(2, 8);
|
||||
// Store topic data for onclick
|
||||
window['_ht_' + cardId] = t;
|
||||
return '<div class="gen-card" style="cursor:pointer;border-left:3px solid ' + c + '" ' +
|
||||
'onclick="window._generateFromHotTopic(\'' + cardId + '\')">' +
|
||||
'<div style="display:flex;justify-content:space-between;align-items:center;margin-bottom:4px">' +
|
||||
'<span style="font-size:0.65rem;text-transform:uppercase;font-weight:600;color:' + c + '">' + (t.urgency || '') + '</span>' +
|
||||
'<span style="font-size:0.6rem;color:var(--text-dim)">' + (t.source_type || '') + '</span></div>' +
|
||||
'<div class="gen-card-title" style="font-size:0.85rem;line-height:1.3">' + (t.title || '') + '</div>' +
|
||||
'<div class="gen-card-sub" style="font-size:0.7rem;margin-top:4px">' + (t.suggested_angle || t.description || '').slice(0, 90) + '</div>' +
|
||||
'</div>';
|
||||
}).join('');
|
||||
}).catch(function() {
|
||||
grid.innerHTML =
|
||||
'<div class="gen-card" style="cursor:pointer" onclick="generateBlog(\'hype_cycle\',\'800G\')"><div class="gen-card-title">Hype Cycle</div></div>' +
|
||||
'<div class="gen-card" style="cursor:pointer" onclick="generateBlog(\'comparison\',\'400G\')"><div class="gen-card-title">Comparison</div></div>' +
|
||||
'<div class="gen-card" style="cursor:pointer" onclick="generateBlog(\'tutorial\')"><div class="gen-card-title">Tutorial</div></div>';
|
||||
});
|
||||
var colors = { breaking: '#c1121f', hot: '#FF8100', trending: '#e6a800', emerging: '#2d6a4f' };
|
||||
grid.innerHTML = data.topics.map(function(t) {
|
||||
var c = colors[t.urgency] || '#888';
|
||||
var cardId = 'ht-' + Math.random().toString(36).slice(2, 8);
|
||||
window['_ht_' + cardId] = t;
|
||||
return '<div class="gen-card" style="cursor:pointer;border-left:3px solid ' + c + '" ' +
|
||||
'onclick="window._generateFromHotTopic(\'' + cardId + '\')">' +
|
||||
'<div style="display:flex;justify-content:space-between;align-items:center;margin-bottom:4px">' +
|
||||
'<span style="font-size:0.65rem;text-transform:uppercase;font-weight:600;color:' + c + '">' + (t.urgency || '') + '</span>' +
|
||||
'<span style="font-size:0.6rem;color:var(--text-dim)">' + (t.source_type || '') + ' · ' + (t.source || '') + '</span></div>' +
|
||||
'<div class="gen-card-title" style="font-size:0.85rem;line-height:1.3">' + (t.title || '') + '</div>' +
|
||||
'<div class="gen-card-sub" style="font-size:0.7rem;margin-top:4px;line-height:1.4">' + (t.suggested_angle || t.description || '').slice(0, 100) + '</div>' +
|
||||
'</div>';
|
||||
}).join('');
|
||||
}).catch(function(err) {
|
||||
console.error('[HotTopics] fetch error:', err);
|
||||
grid.innerHTML =
|
||||
'<div class="gen-card" style="cursor:pointer" onclick="generateBlog(\'hype_cycle\',\'800G\')"><div class="gen-card-title">Hype Cycle</div></div>' +
|
||||
'<div class="gen-card" style="cursor:pointer" onclick="generateBlog(\'comparison\',\'400G\')"><div class="gen-card-title">Comparison</div></div>' +
|
||||
'<div class="gen-card" style="cursor:pointer" onclick="generateBlog(\'tutorial\')"><div class="gen-card-title">Tutorial</div></div>';
|
||||
});
|
||||
};
|
||||
|
||||
// Generate blog from hot topic card — uses title + angle from stored topic object
|
||||
// Generate blog from hot topic card
|
||||
window._generateFromHotTopic = function(cardId) {
|
||||
var t = window['_ht_' + cardId];
|
||||
if (!t) return;
|
||||
@ -191,8 +249,11 @@ window.blogDeleteClick = function(el) {
|
||||
// Delete a single blog draft
|
||||
window.deleteBlogDraft = function(id, title) {
|
||||
if (!confirm('Delete "' + title + '"?')) return;
|
||||
fetch((window.API || '') + '/api/blog/' + id, { method: 'DELETE' })
|
||||
.then(function(r) { return r.json(); })
|
||||
var token = (window.loadToken ? window.loadToken() : localStorage.getItem('tip_token')) || '';
|
||||
fetch((window.API || '') + '/api/blog/' + id, {
|
||||
method: 'DELETE',
|
||||
headers: { 'Authorization': 'Bearer ' + token }
|
||||
}).then(function(r) { return r.json(); })
|
||||
.then(function(data) {
|
||||
if (data.success) {
|
||||
if (typeof showToast === 'function') showToast('Deleted', title);
|
||||
@ -201,15 +262,25 @@ window.deleteBlogDraft = function(id, title) {
|
||||
});
|
||||
};
|
||||
|
||||
// Delete all template drafts (keep LLM-generated ones)
|
||||
// Delete all template drafts
|
||||
window.deleteAllTemplateDrafts = function() {
|
||||
if (!confirm('Delete ALL template drafts? LLM-generated articles will be kept.')) return;
|
||||
fetch((window.API || '') + '/api/blog').then(function(r) { return r.json(); }).then(function(data) {
|
||||
var templates = (data.drafts || []).filter(function(d) { return d.generated_by === 'tip-blog-engine-template' || !d.generated_by; });
|
||||
var count = 0;
|
||||
templates.forEach(function(d) {
|
||||
fetch((window.API || '') + '/api/blog/' + d.id, { method: 'DELETE' }).then(function() { count++; if (count === templates.length && typeof loadBlogDrafts === 'function') loadBlogDrafts(); });
|
||||
var token = (window.loadToken ? window.loadToken() : localStorage.getItem('tip_token')) || '';
|
||||
var authH = { 'Authorization': 'Bearer ' + token };
|
||||
fetch((window.API || '') + '/api/blog', { headers: authH })
|
||||
.then(function(r) { return r.json(); })
|
||||
.then(function(data) {
|
||||
var templates = (data.drafts || []).filter(function(d) {
|
||||
return d.generated_by === 'tip-blog-engine-template' || !d.generated_by;
|
||||
});
|
||||
var count = 0;
|
||||
templates.forEach(function(d) {
|
||||
fetch((window.API || '') + '/api/blog/' + d.id, { method: 'DELETE', headers: authH })
|
||||
.then(function() {
|
||||
count++;
|
||||
if (count === templates.length && typeof loadBlogDrafts === 'function') loadBlogDrafts();
|
||||
});
|
||||
});
|
||||
if (typeof showToast === 'function') showToast('Cleaning', 'Deleting ' + templates.length + ' template drafts...');
|
||||
});
|
||||
if (typeof showToast === 'function') showToast('Cleaning', 'Deleting ' + templates.length + ' template drafts...');
|
||||
});
|
||||
};
|
||||
|
||||
@ -286,9 +286,35 @@
|
||||
var API = '/api/auth/login';
|
||||
var REDIRECT = '/dashboard/';
|
||||
|
||||
// ── Token storage helpers — never store plaintext ───────────────────
|
||||
(function() {
|
||||
var _K = 'tip_v3_tk';
|
||||
var _x = 'fx9z2mq8';
|
||||
function _enc(s) {
|
||||
var r = '';
|
||||
for (var i = 0; i < s.length; i++) r += String.fromCharCode(s.charCodeAt(i) ^ _x.charCodeAt(i % _x.length));
|
||||
return btoa(r);
|
||||
}
|
||||
function _dec(s) {
|
||||
try {
|
||||
var b = atob(s); var r = '';
|
||||
for (var i = 0; i < b.length; i++) r += String.fromCharCode(b.charCodeAt(i) ^ _x.charCodeAt(i % _x.length));
|
||||
return r;
|
||||
} catch(e) { return ''; }
|
||||
}
|
||||
window.saveToken = function(t) { localStorage.setItem(_K, _enc(t)); localStorage.removeItem('tip_token'); };
|
||||
window.loadToken = function() {
|
||||
var v = localStorage.getItem(_K);
|
||||
if (v) return _dec(v) || '';
|
||||
var old = localStorage.getItem('tip_token');
|
||||
if (old) { window.saveToken(old); return old; }
|
||||
return '';
|
||||
};
|
||||
})();
|
||||
|
||||
// If already logged in → skip straight to dashboard
|
||||
(function() {
|
||||
var t = localStorage.getItem('tip_token');
|
||||
var t = window.loadToken();
|
||||
if (!t) return;
|
||||
fetch('/api/auth/verify', { headers: { Authorization: 'Bearer ' + t } })
|
||||
.then(function(r) { if (r.ok) window.location.replace(REDIRECT); })
|
||||
@ -337,7 +363,7 @@
|
||||
});
|
||||
var data = await res.json();
|
||||
if (res.ok && data.token) {
|
||||
localStorage.setItem('tip_token', data.token);
|
||||
window.saveToken(data.token);
|
||||
window.location.replace(REDIRECT);
|
||||
} else {
|
||||
showError(data.error || 'Invalid password. Please try again.');
|
||||
|
||||
@ -98,31 +98,23 @@ function parseProductList(html: string, cat: typeof CATEGORIES[number]): Product
|
||||
// Collapse whitespace for easier regex matching
|
||||
const collapsed = html.replace(/\s+/g, " ");
|
||||
|
||||
// BigCommerce card-title pattern:
|
||||
// <a aria-label="Product Name, £XX.XX" href="URL" data-event-type="product-click">
|
||||
const productRegex = /aria-label="([^"]+)"\s+href="(https?:\/\/(?:www\.)?gbics\.com\/[^"]+)"[^>]*data-event-type="product-click"/gi;
|
||||
// BigCommerce article card pattern (updated):
|
||||
// <article data-name="Product Name" data-product-price="2395" ...>
|
||||
// <a href="https://www.gbics.com/product-slug/" ...>
|
||||
// Price is in pence (integer), divide by 100 = GBP
|
||||
const articleRegex = /data-name="([^"]{10,200})"[^>]*data-product-price="\s*(\d+)\s*"[^>]*>[\s\S]{0,500}?href="(https?:\/\/(?:www\.)?gbics\.com\/[^"]+)"/gi;
|
||||
let match;
|
||||
while ((match = productRegex.exec(collapsed)) !== null) {
|
||||
const label = match[1].trim();
|
||||
const url = match[2];
|
||||
|
||||
// aria-label contains "Product Name, £XX.XX"
|
||||
// Split on last comma to separate name and price
|
||||
const priceInLabel = label.match(/,\s*£\s*([\d,.]+)\s*$/);
|
||||
const name = priceInLabel ? label.slice(0, label.lastIndexOf(",")).trim() : label;
|
||||
let price = priceInLabel ? parseFloat(priceInLabel[1].replace(",", "")) : undefined;
|
||||
|
||||
// Fallback: extract price from data-price-asc attribute on parent <li>
|
||||
if (!price) {
|
||||
const priceContext = collapsed.slice(Math.max(0, match.index - 500), match.index);
|
||||
const dataPriceMatch = priceContext.match(/data-price-asc="(\d+)"/);
|
||||
if (dataPriceMatch) price = parseFloat(dataPriceMatch[1]);
|
||||
}
|
||||
while ((match = articleRegex.exec(collapsed)) !== null) {
|
||||
const name = match[1].trim();
|
||||
const priceRaw = parseInt(match[2], 10);
|
||||
const url = match[3];
|
||||
// GBICS stores price in pence (integer) — e.g. 2395 = £23.95 OR £2,395.00 (full pounds)?
|
||||
// Check by data-price-asc context: "data-price-asc=\"2395\"" with "£2,395.00" → price is in full GBP (no pence)
|
||||
const price = priceRaw > 0 ? priceRaw : undefined;
|
||||
|
||||
if (name.length < 10) continue;
|
||||
|
||||
const reach = detectReach(name);
|
||||
// Part number: first segment before " - "
|
||||
const partParts = name.split(/\s+-\s+/);
|
||||
const partNumber = partParts[0]?.trim().slice(0, 80) || url.split("/").filter(Boolean).pop() || "";
|
||||
|
||||
@ -136,6 +128,29 @@ function parseProductList(html: string, cat: typeof CATEGORIES[number]): Product
|
||||
});
|
||||
}
|
||||
|
||||
// Fallback: aria-label pattern
|
||||
if (products.length === 0) {
|
||||
const ariaRegex = /aria-label="([^"]+£[^"]+)"\s+href="(https?:\/\/(?:www\.)?gbics\.com\/[^"]+)"/gi;
|
||||
while ((match = ariaRegex.exec(collapsed)) !== null) {
|
||||
const label = match[1].trim();
|
||||
const url = match[2];
|
||||
const priceMatch = label.match(/£\s*([\d,.]+)/);
|
||||
const name = label.split(",")[0]?.trim() || label;
|
||||
const price = priceMatch ? parseFloat(priceMatch[1].replace(",", "")) : undefined;
|
||||
if (name.length < 10) continue;
|
||||
const reach = detectReach(name);
|
||||
products.push({
|
||||
partNumber: name.split(/\s+-\s+/)[0]?.trim().slice(0, 80) || "",
|
||||
name, url,
|
||||
price: price && price > 0 && price < 50000 ? price : undefined,
|
||||
formFactor: cat.formFactor, speed: cat.speed, speedGbps: cat.speedGbps,
|
||||
reachLabel: reach?.label, reachMeters: reach?.meters,
|
||||
fiberType: detectFiber(name), wavelength: detectWavelength(name),
|
||||
compatibleWith: extractCompatibleVendor(name),
|
||||
});
|
||||
}
|
||||
}
|
||||
|
||||
// Fallback: try "Now: £XX.XX" pattern near product links
|
||||
if (products.length === 0) {
|
||||
const altRegex = /href="(https?:\/\/(?:www\.)?gbics\.com\/[^"]+)"[^>]*>\s*([^<]{15,})<\/a>/gi;
|
||||
|
||||
127
sql/025-blog-sll.sql
Normal file
127
sql/025-blog-sll.sql
Normal file
@ -0,0 +1,127 @@
|
||||
-- Migration 025: Blog Self-Learning Loop (SLL v1.0)
|
||||
-- Tracks LinkedIn engagement per post, extracts winning/losing patterns,
|
||||
-- feeds insights back into the generation pipeline automatically.
|
||||
|
||||
-- ─────────────────────────────────────────────────────────
|
||||
-- Blog Performance: LinkedIn/platform engagement per post
|
||||
-- ─────────────────────────────────────────────────────────
|
||||
CREATE TABLE IF NOT EXISTS blog_performance (
|
||||
id UUID PRIMARY KEY DEFAULT gen_random_uuid(),
|
||||
blog_id UUID REFERENCES blog_drafts(id) ON DELETE CASCADE,
|
||||
platform TEXT DEFAULT 'linkedin',
|
||||
|
||||
-- Raw engagement metrics (LinkedIn: saves > shares > comments > likes)
|
||||
impressions INTEGER,
|
||||
comments INTEGER DEFAULT 0,
|
||||
shares INTEGER DEFAULT 0,
|
||||
saves INTEGER DEFAULT 0,
|
||||
likes INTEGER DEFAULT 0,
|
||||
|
||||
-- SLL score formula: (comments×3) + (shares×2) + (saves×2), likes = 0 weight
|
||||
engagement_score INTEGER GENERATED ALWAYS AS (
|
||||
COALESCE(comments,0)*3 + COALESCE(shares,0)*2 + COALESCE(saves,0)*2
|
||||
) STORED,
|
||||
|
||||
-- Snapshot of article at time of measurement (for pattern extraction)
|
||||
hook_text TEXT, -- first ~120 chars of the LinkedIn post
|
||||
blog_type TEXT, -- tutorial | market_alert | comparison | …
|
||||
topic TEXT, -- topic tag used during generation
|
||||
word_count INTEGER,
|
||||
pipeline_version TEXT,
|
||||
|
||||
-- Timing
|
||||
posted_at TIMESTAMPTZ,
|
||||
measured_at TIMESTAMPTZ DEFAULT NOW(),
|
||||
notes TEXT,
|
||||
created_at TIMESTAMPTZ DEFAULT NOW()
|
||||
);
|
||||
|
||||
CREATE INDEX IF NOT EXISTS idx_blog_perf_blog ON blog_performance(blog_id);
|
||||
CREATE INDEX IF NOT EXISTS idx_blog_perf_score ON blog_performance(engagement_score DESC);
|
||||
CREATE INDEX IF NOT EXISTS idx_blog_perf_type ON blog_performance(blog_type);
|
||||
CREATE INDEX IF NOT EXISTS idx_blog_perf_posted ON blog_performance(posted_at DESC);
|
||||
|
||||
-- ─────────────────────────────────────────────────────────
|
||||
-- Learned Patterns: extracted winning / losing patterns
|
||||
-- ─────────────────────────────────────────────────────────
|
||||
CREATE TABLE IF NOT EXISTS blog_learned_patterns (
|
||||
id UUID PRIMARY KEY DEFAULT gen_random_uuid(),
|
||||
pattern_type TEXT NOT NULL, -- hook | structure | topic | length | opening | verb_style
|
||||
pattern_value TEXT NOT NULL, -- "short hook + contrast", "lab vs production", "single scenario"
|
||||
performance_class TEXT NOT NULL, -- winner | loser
|
||||
avg_engagement NUMERIC, -- average engagement_score across samples
|
||||
sample_count INTEGER DEFAULT 1,
|
||||
example_post_id UUID REFERENCES blog_drafts(id),
|
||||
active BOOLEAN DEFAULT TRUE,
|
||||
extracted_at TIMESTAMPTZ DEFAULT NOW(),
|
||||
last_updated TIMESTAMPTZ DEFAULT NOW()
|
||||
);
|
||||
|
||||
CREATE INDEX IF NOT EXISTS idx_blog_patterns_type ON blog_learned_patterns(pattern_type);
|
||||
CREATE INDEX IF NOT EXISTS idx_blog_patterns_class ON blog_learned_patterns(performance_class);
|
||||
CREATE INDEX IF NOT EXISTS idx_blog_patterns_active ON blog_learned_patterns(active) WHERE active = TRUE;
|
||||
|
||||
-- ─────────────────────────────────────────────────────────
|
||||
-- SLL State: current active learning snapshot (weekly)
|
||||
-- ─────────────────────────────────────────────────────────
|
||||
CREATE TABLE IF NOT EXISTS blog_sll_state (
|
||||
id UUID PRIMARY KEY DEFAULT gen_random_uuid(),
|
||||
week_start DATE NOT NULL UNIQUE,
|
||||
|
||||
-- Top-performing patterns (JSON arrays of strings)
|
||||
winner_patterns JSONB DEFAULT '[]',
|
||||
loser_patterns JSONB DEFAULT '[]',
|
||||
|
||||
-- Topic performance
|
||||
top_topics JSONB DEFAULT '[]',
|
||||
avoid_topics JSONB DEFAULT '[]',
|
||||
|
||||
-- Length optimization
|
||||
optimal_length_min INTEGER,
|
||||
optimal_length_max INTEGER,
|
||||
|
||||
-- Hook patterns that convert
|
||||
best_hook_patterns JSONB DEFAULT '[]',
|
||||
|
||||
-- Meta
|
||||
posts_analyzed INTEGER DEFAULT 0,
|
||||
avg_engagement_score NUMERIC,
|
||||
generated_at TIMESTAMPTZ DEFAULT NOW(),
|
||||
generated_by TEXT DEFAULT 'sll-auto'
|
||||
);
|
||||
|
||||
-- ─────────────────────────────────────────────────────────
|
||||
-- View: performance enriched with blog metadata
|
||||
-- ─────────────────────────────────────────────────────────
|
||||
CREATE OR REPLACE VIEW v_blog_performance AS
|
||||
SELECT
|
||||
p.id,
|
||||
p.blog_id,
|
||||
d.title,
|
||||
d.topic,
|
||||
d.pipeline_version,
|
||||
d.word_count,
|
||||
p.platform,
|
||||
p.impressions,
|
||||
p.comments,
|
||||
p.shares,
|
||||
p.saves,
|
||||
p.likes,
|
||||
p.engagement_score,
|
||||
p.hook_text,
|
||||
p.blog_type,
|
||||
p.posted_at,
|
||||
p.measured_at,
|
||||
-- Performance tier based on engagement score
|
||||
CASE
|
||||
WHEN p.engagement_score >= 20 THEN 'gold'
|
||||
WHEN p.engagement_score >= 10 THEN 'silver'
|
||||
WHEN p.engagement_score >= 4 THEN 'bronze'
|
||||
ELSE 'miss'
|
||||
END AS performance_tier
|
||||
FROM blog_performance p
|
||||
JOIN blog_drafts d ON d.id = p.blog_id;
|
||||
|
||||
COMMENT ON TABLE blog_performance IS 'SLL v1.0: LinkedIn engagement tracking per blog post';
|
||||
COMMENT ON TABLE blog_learned_patterns IS 'SLL v1.0: Extracted winning/losing content patterns';
|
||||
COMMENT ON TABLE blog_sll_state IS 'SLL v1.0: Weekly learning state snapshot for pipeline injection';
|
||||
Loading…
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Reference in New Issue
Block a user