initial commit: slides + practica_resueltos + README

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-05-29 11:50:55 +02:00
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+---
+layout: default
+---
+
+# Paso 2: Indexar en Qdrant
+
+```typescript
+import { QdrantVectorStore } from "@langchain/qdrant";
+import { OpenAIEmbeddings } from "@langchain/openai";
+
+const embeddings = new OpenAIEmbeddings();
+
+// Crear colección e insertar chunks con sus embeddings
+const vectorStore = await QdrantVectorStore.fromDocuments(
+  chunks,
+  embeddings,
+  {
+    url: "http://localhost:6333",
+    collectionName: "manuales",
+  }
+);
+
+console.log(`✅ ${chunks.length} chunks indexados en Qdrant`);
+```
+
+<v-click>
+
+<div class="mt-4 p-3 bg-green-500/10 rounded text-sm">
+
+`fromDocuments` hace todo: genera embeddings + crea la colección + inserta los vectores
+
+</div>
+
+</v-click>