mcp: implement warm_cache using libKI embeddings + DAL upserts (chunks + embeddings); returns queued count

src/mcp/HandlersMemory.hpp

@@ -716,17 +716,68 @@ inline std::string embed_text(const std::string& reqJson) {
 }
 
 /**
- * warm_cache (stub)
+ * warm_cache
- * Request: { "namespace": string }
+ * Request: { "namespace": string, "model?": string, "limit?": int }
  * Response: { "queued": int }
+ *
+ * Implementation: fetches recent items for the namespace, embeds their text via libKI,
+ * creates a single chunk (ord=0) per item and upserts the (chunk, embedding) rows.
  */
 inline std::string warm_cache(const std::string& reqJson) {
     const std::string nsName = detail::extract_string_field(reqJson, "namespace");
     if (nsName.empty()) {
         return detail::error_response("bad_request", "namespace is required");
     }
-    // For now, just return a dummy successful response
+    std::string model = detail::extract_string_field(reqJson, "model");
-    return "{\"queued\":0}";
+    int limit = 10;
+    if (auto lim = detail::extract_int_field(reqJson, "limit")) { if (*lim > 0) limit = *lim; }
+
+    auto nsRow = detail::database().findNamespace(nsName);
+    if (!nsRow) {
+        return std::string("{\"queued\":0}");
+    }
+
+    // Fetch recent items
+    std::vector<std::string> tags; // empty
+    auto rows = detail::database().fetchContext(nsRow->id, std::nullopt, tags, std::nullopt, limit);
+    if (rows.empty()) {
+        return std::string("{\"queued\":0}");
+    }
+
+    // Collect texts
+    std::vector<std::pair<std::string, std::string>> toEmbed; toEmbed.reserve(rows.size());
+    for (const auto &row : rows) {
+        if (row.text && !row.text->empty()) {
+            toEmbed.emplace_back(row.id, *row.text);
+        }
+        if ((int)toEmbed.size() >= limit) break;
+    }
+    if (toEmbed.empty()) {
+        return std::string("{\"queued\":0}");
+    }
+
+    // libKI
+    KI::KIClient client; KI::OllamaProvider provider; client.setProvider(&provider);
+    KI::KIEmbedOptions opts; if (!model.empty()) opts.model = QString::fromStdString(model);
+    QStringList texts; for (auto &p : toEmbed) texts.push_back(QString::fromStdString(p.second));
+    QEventLoop loop; QFuture<KI::KIEmbeddingResult> fut = client.embed(texts, opts);
+    QFutureWatcher<KI::KIEmbeddingResult> watcher; QObject::connect(&watcher, &QFutureWatcher<KI::KIEmbeddingResult>::finished, &loop, &QEventLoop::quit);
+    watcher.setFuture(fut); loop.exec(); const KI::KIEmbeddingResult result = watcher.result();
+
+    // Persist
+    int persisted = 0; const int n = std::min(result.vectors.size(), (int)toEmbed.size());
+    for (int i = 0; i < n; ++i) {
+        const auto &pair = toEmbed[(size_t)i];
+        ki::ChunkRow chunk; chunk.item_id = pair.first; chunk.ord = 0; chunk.text = pair.second;
+        auto chunkIds = detail::database().upsertChunks(std::vector<ki::ChunkRow>{chunk});
+        if (chunkIds.empty()) continue;
+        const auto &vec = result.vectors[i];
+        ki::EmbeddingRow emb; emb.chunk_id = chunkIds.front(); emb.model = result.model.toStdString(); emb.dim = vec.size();
+        emb.vector.reserve(vec.size()); for (float f : vec) emb.vector.push_back(f);
+        detail::database().upsertEmbeddings(std::vector<ki::EmbeddingRow>{emb});
+        persisted++;
+    }
+    std::ostringstream os; os << "{\"queued\":" << persisted << "}"; return os.str();
 }
 
 } // namespace Handlers