enhance embedding model support and update database schema for multi-model compatibility

config.json

@@ -19,7 +19,8 @@
     "tickers": []
   },
   "openRouter": {
-    "apiKey": "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"
+    "apiKey": "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",
+    "embeddingModel": "qwen/qwen3-embedding-8b"
   },
   "gdelt": {
     "source": "api",

src/db.js

@@ -120,10 +120,12 @@ db.exec(`
 `);
 
 db.exec(`
-  CREATE TABLE IF NOT EXISTS query_embeddings (
+  CREATE TABLE IF NOT EXISTS article_embedding_store (
-    query TEXT PRIMARY KEY,
+    article_id INTEGER NOT NULL,
+    model TEXT NOT NULL,
     embedding BLOB NOT NULL,
-    created_at TEXT NOT NULL DEFAULT (datetime('now'))
+    embedded_at TEXT NOT NULL DEFAULT (datetime('now')),
+    PRIMARY KEY (article_id, model)
   );
 `);
 
@@ -135,6 +137,41 @@ db.exec(`
   );
 `);
 
+// migrate query_embeddings to include model in primary key
+{
+  const cols = db.prepare(`PRAGMA table_info(query_embeddings)`).all();
+  const hasModel = cols.some(c => c.name === 'model');
+
+  if (!hasModel) {
+    db.exec(`
+      BEGIN;
+
+      CREATE TABLE query_embeddings_new (
+        query TEXT NOT NULL,
+        model TEXT NOT NULL,
+        embedding BLOB NOT NULL,
+        created_at TEXT NOT NULL DEFAULT (datetime('now')),
+        PRIMARY KEY (query, model)
+      );
+
+      DROP TABLE IF EXISTS query_embeddings;
+      ALTER TABLE query_embeddings_new RENAME TO query_embeddings;
+
+      COMMIT;
+    `);
+  } else {
+    db.exec(`
+      CREATE TABLE IF NOT EXISTS query_embeddings (
+        query TEXT NOT NULL,
+        model TEXT NOT NULL,
+        embedding BLOB NOT NULL,
+        created_at TEXT NOT NULL DEFAULT (datetime('now')),
+        PRIMARY KEY (query, model)
+      );
+    `);
+  }
+}
+
 db.exec(`
   CREATE TABLE IF NOT EXISTS gdelt_backfill_windows (
     source_id TEXT NOT NULL,

src/embeddings.js

@@ -1,24 +1,32 @@
 const db = require('./db');
 const config = require('./config');
 
+const EMBEDDING_MODEL = (config.openRouter && config.openRouter.embeddingModel)
+  ? config.openRouter.embeddingModel
+  : 'perplexity/pplx-embed-v1-0.6b';
+
 const selectArticleForEmbedding = db.prepare(`
   SELECT id, title, description, content
   FROM articles
   WHERE id = ?
 `);
+
 const insertEmbedding = db.prepare(`
   INSERT INTO article_embeddings (article_id, embedding)
   VALUES (?, ?)
 `);
+
 const deleteEmbedding = db.prepare(`
   DELETE FROM article_embeddings
   WHERE article_id = ?
 `);
+
 const selectEmbeddingBuffer = db.prepare(`
   SELECT embedding
   FROM article_embeddings
   WHERE article_id = ?
 `);
+
 const upsertEmbeddingMeta = db.prepare(`
   INSERT INTO article_embedding_meta (article_id, model, embedded_at)
   VALUES (?, ?, datetime('now'))
@@ -26,9 +34,20 @@ const upsertEmbeddingMeta = db.prepare(`
     model = excluded.model,
     embedded_at = excluded.embedded_at
 `);
-const selectEmbeddingModel = db.prepare(`
+
-  SELECT model FROM article_embedding_meta WHERE article_id = ?
+const upsertEmbeddingStore = db.prepare(`
+  INSERT INTO article_embedding_store (article_id, model, embedding, embedded_at)
+  VALUES (?, ?, ?, datetime('now'))
+  ON CONFLICT(article_id, model) DO UPDATE SET
+    embedding = excluded.embedding,
+    embedded_at = excluded.embedded_at
 `);
+
+const selectEmbeddingFromStore = db.prepare(`
+  SELECT embedding FROM article_embedding_store
+  WHERE article_id = ? AND model = ?
+`);
+
 const nearestNeighbors = db.prepare(`
   SELECT article_id, distance
   FROM article_embeddings
@@ -36,6 +55,7 @@ const nearestNeighbors = db.prepare(`
     AND k = ?
   ORDER BY distance
 `);
+
 const selectArticlesMissingEmbeddings = db.prepare(`
   SELECT a.id
   FROM articles a
@@ -45,40 +65,80 @@ const selectArticlesMissingEmbeddings = db.prepare(`
     AND TRIM(a.description) != ''
     AND a.content IS NOT NULL
     AND TRIM(a.content) != ''
-    AND (
+    AND NOT EXISTS (
-      NOT EXISTS (
+      SELECT 1 FROM article_embedding_store s
-        SELECT 1 FROM article_embeddings e WHERE e.article_id = a.id
+      WHERE s.article_id = a.id AND s.model = ?
-      )
-      OR NOT EXISTS (
-        SELECT 1 FROM article_embedding_meta m
-        WHERE m.article_id = a.id AND m.model = ?
-      )
     )
   ORDER BY a.ingested_at ASC, a.id ASC
   LIMIT ?
 `);
+
 const selectQueryEmbedding = db.prepare(`
-  SELECT embedding
+  SELECT embedding FROM query_embeddings WHERE query = ? AND model = ?
-  FROM query_embeddings
-  WHERE query = ?
 `);
+
 const upsertQueryEmbedding = db.prepare(`
-  INSERT INTO query_embeddings (query, embedding)
+  INSERT INTO query_embeddings (query, model, embedding)
-  VALUES (?, ?)
+  VALUES (?, ?, ?)
-  ON CONFLICT(query) DO UPDATE SET
+  ON CONFLICT(query, model) DO UPDATE SET
     embedding = excluded.embedding,
     created_at = datetime('now')
 `);
 
-const EMBEDDING_MODEL = 'perplexity/pplx-embed-v1-0.6b';
+// backfill store from any embeddings that predate multi-model support
+try {
+  db.prepare(`
+    INSERT OR IGNORE INTO article_embedding_store (article_id, model, embedding)
+    SELECT e.article_id, ?, e.embedding FROM article_embeddings e
+  `).run(EMBEDDING_MODEL);
+
+  db.prepare(`
+    INSERT OR IGNORE INTO article_embedding_meta (article_id, model)
+    SELECT article_id, ? FROM article_embedding_store WHERE model = ?
+  `).run(EMBEDDING_MODEL, EMBEDDING_MODEL);
+} catch (err) {
+  console.error('embedding store backfill failed:', err);
+}
+
+// if the config model changed, rebuild the vec0 search index from store
+function rebuildVec0IfModelChanged() {
+  const stale = db.prepare(`
+    SELECT 1 FROM article_embedding_meta WHERE model != ? LIMIT 1
+  `).get(EMBEDDING_MODEL);
+
+  if (!stale) return;
+
+  console.log(`embedding model changed to ${EMBEDDING_MODEL}, rebuilding search index...`);
+
+  db.exec('BEGIN');
+
+  try {
+    db.exec('DELETE FROM article_embeddings');
+    db.exec('DELETE FROM article_embedding_meta');
+
+    const rows = db.prepare(`
+      SELECT article_id, embedding FROM article_embedding_store WHERE model = ?
+    `).all(EMBEDDING_MODEL);
+
+    const insertVec = db.prepare(`INSERT INTO article_embeddings (article_id, embedding) VALUES (?, ?)`);
+    const insertMeta = db.prepare(`INSERT INTO article_embedding_meta (article_id, model) VALUES (?, ?)`);
+
+    for (const row of rows) {
+      insertVec.run(BigInt(row.article_id), row.embedding);
+      insertMeta.run(row.article_id, EMBEDDING_MODEL);
+    }
+
+    db.exec('COMMIT');
+    console.log(`rebuilt search index with ${rows.length} embeddings`);
+  } catch (err) {
+    db.exec('ROLLBACK');
+    throw err;
+  }
+}
+
+rebuildVec0IfModelChanged();
 
 let embeddingBackfillRunning = false;
-
-// backfill meta for any embeddings that existed before model tracking
-db.prepare(`
-  INSERT OR IGNORE INTO article_embedding_meta (article_id, model)
-  SELECT article_id, ? FROM article_embeddings
-`).run(EMBEDDING_MODEL);
 const embeddingJobsRunning = new Set();
 
 function buildEmbeddingInput(article) {
@@ -157,7 +217,15 @@ async function generateAndStoreEmbedding(id) {
     return { stored: false, shouldPauseBatch: false };
   }
 
-  if (selectEmbeddingBuffer.get(id)) {
+  if (selectEmbeddingFromStore.get(id, EMBEDDING_MODEL)) {
+    // already in store — make sure vec0 is also up to date
+    if (!selectEmbeddingBuffer.get(id)) {
+      const row = selectEmbeddingFromStore.get(id, EMBEDDING_MODEL);
+      deleteEmbedding.run(BigInt(id));
+      insertEmbedding.run(BigInt(id), row.embedding);
+      upsertEmbeddingMeta.run(id, EMBEDDING_MODEL);
+    }
+
     return { stored: false, shouldPauseBatch: false };
   }
 
@@ -174,14 +242,18 @@ async function generateAndStoreEmbedding(id) {
   embeddingJobsRunning.add(id);
 
   try {
-    if (selectEmbeddingBuffer.get(id)) {
+    if (selectEmbeddingFromStore.get(id, EMBEDDING_MODEL)) {
       return { stored: false, shouldPauseBatch: false };
     }
 
     const embedding = await requestEmbedding(input);
+    const buffer = serializeEmbedding(embedding);
+
+    upsertEmbeddingStore.run(id, EMBEDDING_MODEL, buffer);
     deleteEmbedding.run(BigInt(id));
-    insertEmbedding.run(BigInt(id), serializeEmbedding(embedding));
+    insertEmbedding.run(BigInt(id), buffer);
     upsertEmbeddingMeta.run(id, EMBEDDING_MODEL);
+
     return { stored: true, shouldPauseBatch: false };
   } catch (error) {
     console.error(`embedding generation failed for article ${id}:`, error);
@@ -216,7 +288,7 @@ async function backfillMissingEmbeddings(limit = 100) {
 }
 
 function getEmbeddingBuffer(articleId) {
-  const row = selectEmbeddingBuffer.get(articleId);
+  const row = selectEmbeddingFromStore.get(articleId, EMBEDDING_MODEL);
   return row ? row.embedding : null;
 }
 
@@ -238,14 +310,14 @@ async function getOrCreateQueryEmbedding(query) {
     return null;
   }
 
-  const cached = selectQueryEmbedding.get(normalizedQuery);
+  const cached = selectQueryEmbedding.get(normalizedQuery, EMBEDDING_MODEL);
   if (cached) {
     return cached.embedding;
   }
 
   const embedding = await requestEmbedding(normalizedQuery);
   const buffer = serializeEmbedding(embedding);
-  upsertQueryEmbedding.run(normalizedQuery, buffer);
+  upsertQueryEmbedding.run(normalizedQuery, EMBEDDING_MODEL, buffer);
   return buffer;
 }
 

src/routes/status.js

@@ -28,6 +28,13 @@ async function statusRoutes(fastify) {
       { total: 0, usable: 0 }
     );
 
+    const embeddingModelRows = db.prepare(`
+      SELECT model, COUNT(*) AS article_count
+      FROM article_embedding_store
+      GROUP BY model
+      ORDER BY article_count DESC
+    `).all();
+
     return {
       total: totals.total,
       usable: totals.usable,
@@ -35,6 +42,10 @@ async function statusRoutes(fastify) {
       bySource: Object.fromEntries(
         bySourceRows.map((row) => [row.source, { total: row.total, usable: row.usable }])
       ),
+      embeddingModels: embeddingModelRows.map((row) => ({
+        model: row.model,
+        articles: row.article_count,
+      })),
     };
   });
 }