initial commit: slides + practica_resueltos + README

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

slides/pages/rag/24e.md

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+---
+layout: default
+---
+
+# Consumir reranker self-hosted desde Node.js
+
+<v-clicks>
+
+No hay integración oficial con LangChain.js, pero la API REST es muy sencilla:
+
+```typescript
+async function rerank(query: string, docs: string[], topN = 3) {
+  const res = await fetch("http://localhost:7997/rerank", {
+    method: "POST",
+    headers: { "Content-Type": "application/json" },
+    body: JSON.stringify({ query, documents: docs }),
+  });
+  const results = await res.json();
+  // [{ index: 2, relevance_score: 0.95 }, { index: 0, relevance_score: 0.72 }, ...]
+
+  return results
+    .sort((a, b) => b.relevance_score - a.relevance_score)
+    .slice(0, topN);
+}
+
+// Uso con documentos de LangChain
+const searchResults = await vectorStore.similaritySearch(query, 10);
+const ranked = await rerank(query, searchResults.map(d => d.pageContent));
+const topDocs = ranked.map(r => searchResults[r.index]);
+```
+
+<div class="mt-4 p-4 bg-blue-500/10 rounded">
+💡 Misma API para Infinity y TEI — cambiar de runtime no requiere cambiar código
+</div>
+
+</v-clicks>