initial commit: slides ready + upgraded

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# Qdrant - Crear e insertar
```typescript
import { QdrantVectorStore } from "@langchain/qdrant";
import { OpenAIEmbeddings } from "@langchain/openai";
const vectorStore = await QdrantVectorStore.fromTexts(
[
"LangChain es un framework para aplicaciones con LLMs",
"Los embeddings capturan el significado del texto",
"RAG combina búsqueda con generación de texto",
],
[{ source: "doc1" }, { source: "doc2" }, { source: "doc3" }],
new OpenAIEmbeddings(),
{
url: "http://localhost:6333",
collectionName: "langchain_docs",
}
);
console.log("Documentos indexados correctamente");
```