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
+---
+
+# Ejemplo: Agente con Tavily Search
+
+<div class="text-xs mt-2">
+
+```typescript
+import { createAgent } from "langchain";
+import { TavilySearchResults } from "@langchain/community/tools/tavily_search";
+
+const searchTool = new TavilySearchResults({ apiKey: process.env.TAVILY_API_KEY, maxResults: 5 });
+const agent = createAgent({
+  model: "openai:gpt-4.1-mini",
+  tools: [searchTool],
+});
+
+const result = await agent.invoke({
+  messages: [{ role: "user", content: "¿Cuales son las ultimas noticias sobre IA?" }],
+});
+```
+
+<div class="mt-2 grid grid-cols-2 gap-3">
+
+<div class="bg-blue-50 dark:bg-blue-900/20 p-2 rounded">
+
+**Tavily** - Optimizado para LLMs: extrae contenido relevante, filtra anuncios/ruido, API key gratuita limitada
+
+</div>
+
+<div class="bg-green-50 dark:bg-green-900/20 p-2 rounded">
+
+**Docs**: [langchain.com/integrations/tools](https://docs.langchain.com/oss/javascript/integrations/tools)
+
+</div>
+
+</div>
+
+</div>
+