{"id":1440,"date":"2025-03-13T09:16:12","date_gmt":"2025-03-13T09:16:12","guid":{"rendered":"https:\/\/ignos.blog\/agents-extending-llm-functionality-with-openai"},"modified":"2025-03-13T09:24:52","modified_gmt":"2025-03-13T09:24:52","slug":"agents-extending-llm-functionality-with-openai","status":"publish","type":"post","link":"https:\/\/ignos.blog\/en\/agents-extending-llm-functionality-with-openai","title":{"rendered":"Agents: Extending LLM functionality with OpenAI"},"content":{"rendered":"\n<p>Today, the use of intelligent agents is revolutionizing the interaction between humans and technology. These agents, powered by <a href=\"https:\/\/ignos.blog\/en\/llm-ignos\">LLMs<\/a> such as GPT-4, are capable of performing complex tasks autonomously and efficiently. OpenAI offers tools to develop and deploy these agents, commonly known as OpenAI Agents.  <\/p>\n\n<h3 class=\"wp-block-heading\" id=\"h-que-son-los-agentes-openai\">What are OpenAI Agents?<\/h3>\n\n<p>OpenAI Agents are intelligent systems designed to perform specific tasks without human intervention. These agents can perform anything from simple automated tasks to achieving complex goals through a combination of reasoning, planning and continuous learning. <\/p>\n\n<h3 class=\"wp-block-heading\" id=\"h-componentes-esenciales-para-crear-agentes-openai\">Essential components for creating OpenAI Agents<\/h3>\n\n<p>OpenAI provides a set of tools to <a href=\"https:\/\/platform.openai.com\/docs\/guides\/agents\">build robust and efficient agents<\/a>:<\/p>\n\n<ul class=\"wp-block-list\">\n<li><strong>Models:<\/strong> These provide the core intelligence of the agent. Models such as GPT-4o, GPT-4.5 and GPT-4o-mini have different levels of capacity and latency. GPT-4o is ideal for tasks that require a balance between performance and speed, while GPT-4.5 stands out for its ability to execute complex tasks and GPT-4o-mini offers low latency for fast responses.  <\/li>\n\n\n\n<li><strong>Tools:<\/strong> They facilitate the agent&#8217;s interaction with the environment. The main ones include: \n<ul class=\"wp-block-list\">\n<li><strong>Function calls:<\/strong> They allow integrating the agent with developer-defined functions to execute specific tasks.<\/li>\n\n\n\n<li><strong>Web search:<\/strong> Provides access to real-time, up-to-date information from the Internet.<\/li>\n\n\n\n<li><strong>Search in archives:<\/strong> Allows semantic searches in internal documents of the organization to extract relevant information.<\/li>\n<\/ul>\n<\/li>\n\n\n\n<li><strong>Memory and knowledge:<\/strong> Using vector stores and embeddings, agents can store information and retrieve it efficiently to continuously improve their performance and accuracy. This long-term memory enables more complex and contextual tasks. <\/li>\n\n\n\n<li><strong>Guardrails (Safeguards):<\/strong> These are essential to ensure that the agent behaves in a safe and predictable manner. OpenAI provides: \n<ul class=\"wp-block-list\">\n<li><strong>Moderation API:<\/strong> Helps filter unsafe or inappropriate content automatically.<\/li>\n\n\n\n<li><strong>Hierarchies of instructions:<\/strong> They allow clearly defining priorities and specific rules on how the agent should act when faced with different situations.<\/li>\n<\/ul>\n<\/li>\n\n\n\n<li><strong>Orchestration:<\/strong> OpenAI offers the Agent SDK, real-time monitoring tools and continuous evaluation systems, which facilitate the deployment, monitoring and optimization of agents in production.<\/li>\n<\/ul>\n\n<h3 class=\"wp-block-heading\" id=\"h-como-empezar-a-construir-tu-agente-con-openai\">How to Start Building Your Agent with OpenAI<\/h3>\n\n<p>Here is a practical and simple example to start developing an OpenAI Agent.<\/p>\n\n<h4 class=\"wp-block-heading\" id=\"h-paso-1-instalacion-del-sdk\">Step 1: Installing the SDK<\/h4>\n\n<pre class=\"wp-block-code\"><code>pip install openai-agents<\/code><\/pre>\n\n<h4 class=\"wp-block-heading\" id=\"h-paso-2-crear-un-agente-simple\">Step 2: Create a Simple Agent<\/h4>\n\n<p>Here is a basic example for defining an agent that makes calls to custom functions:<\/p>\n\n<pre class=\"wp-block-code\"><code>from openai import OpenAI\n\nclient = OpenAI(api_key=\"tu_clave_api\")\n\n# Definir una funci\u00f3n personalizada\ndef obtener_clima(ciudad):\n    # Simulaci\u00f3n de respuesta\n    return f\"El clima actual en {ciudad} es soleado.\"\n\n# Registrar la funci\u00f3n en el agente\nagente = client.agents.create(\n    model=\"gpt-4o\",\n    tools=&#091;{\"type\": \"function\", \"function\": obtener_clima}]\n)\n\n# Ejecutar el agente\nrespuesta = agente.execute(\"\u00bfCu\u00e1l es el clima en Madrid hoy?\")\nprint(respuesta)<\/code><\/pre>\n\n<h4 class=\"wp-block-heading\" id=\"h-paso-3-anadir-memoria-usando-vector-stores\">Step 3: Add memory using Vector Stores<\/h4>\n\n<p>To provide your agent with memory, you can use vector stores:<\/p>\n\n<pre class=\"wp-block-code\"><code>from openai.embeddings_utils import get_embedding, cosine_similarity\n\n# Crear embeddings\ntexto1 = \"Madrid es una ciudad de Espa\u00f1a\"\ntexto2 = \"Sevilla es una ciudad espa\u00f1ola\"\n\nembedding1 = get_embedding(texto1, engine=\"text-embedding-3-large\")\nembedding2 = get_embedding(texto2, engine=\"text-embedding-3-large\")\n\nsimilitud = cosine_similarity(embedding1, embedding2)\nprint(f\"Similitud entre textos: {similitud}\")<\/code><\/pre>\n\n<p>This approach allows the agent to remember relevant information and improve its responses through semantic comparisons.<\/p>\n\n<h4 class=\"wp-block-heading\" id=\"h-paso-4-desplegar-y-monitorizar-tu-agente\">Step 4: Deploy and Monitor your Agent<\/h4>\n\n<p>Use the SDK to easily deploy and monitor your agents:<\/p>\n\n<pre class=\"wp-block-code\"><code>from openai.agents import Agent\n\nagente = Agent.deploy(\n    model=\"gpt-4o\",\n    tools=&#091;\"web_search\"],\n    guardrails=&#091;\"moderation\"]\n)\n\nresultado = agente.execute(\"Encuentra las \u00faltimas noticias sobre inteligencia artificial.\")\nprint(resultado)\n\n# Monitorizar rendimiento\nagente.monitor()<\/code><\/pre>\n\n<h3 class=\"wp-block-heading\" id=\"h-conclusion\">Conclusion<\/h3>\n\n<p>OpenAI Agents offer enormous potential to extend the capabilities of LLMs in a variety of scenarios, enabling more intelligent and autonomous interactions. With the tools provided by OpenAI, creating these agents is easier than ever. Ignos has the knowledge to assist you in the implementation of these types of solutions, simplifying the process of adopting these technologies and ensuring the return on investment.  <\/p>\n<div class=\"shariff shariff-align-left shariff-widget-align-left\"><ul class=\"shariff-buttons theme-default orientation-horizontal buttonsize-medium\"><li class=\"shariff-button mastodon shariff-nocustomcolor\" style=\"background-color:#563ACC\"><a href=\"https:\/\/s2f.kytta.dev\/?text=Agents%3A%20Extending%20LLM%20functionality%20with%20OpenAI https%3A%2F%2Fignos.blog%2Fen%2Fagents-extending-llm-functionality-with-openai\" title=\"Compartir en Mastodon\" aria-label=\"Compartir en Mastodon\" role=\"button\" rel=\"noopener nofollow\" class=\"shariff-link\" style=\"; background-color:#6364FF; color:#fff\" target=\"_blank\"><span class=\"shariff-icon\" style=\"\"><svg width=\"75\" height=\"79\" viewBox=\"0 0 75 79\" fill=\"none\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\"><path d=\"M37.813-.025C32.462-.058 27.114.13 21.79.598c-8.544.621-17.214 5.58-20.203 13.931C-1.12 23.318.408 32.622.465 41.65c.375 7.316.943 14.78 3.392 21.73 4.365 9.465 14.781 14.537 24.782 15.385 7.64.698 15.761-.213 22.517-4.026a54.1 54.1 0 0 0 .01-6.232c-6.855 1.316-14.101 2.609-21.049 1.074-3.883-.88-6.876-4.237-7.25-8.215-1.53-3.988 3.78-.43 5.584-.883 9.048 1.224 18.282.776 27.303-.462 7.044-.837 14.26-4.788 16.65-11.833 2.263-6.135 1.215-12.79 1.698-19.177.06-3.84.09-7.692-.262-11.52C72.596 7.844 63.223.981 53.834.684a219.453 219.453 0 0 0-16.022-.71zm11.294 12.882c5.5-.067 10.801 4.143 11.67 9.653.338 1.48.471 3 .471 4.515v21.088h-8.357c-.07-7.588.153-15.182-.131-22.765-.587-4.368-7.04-5.747-9.672-2.397-2.422 3.04-1.47 7.155-1.67 10.735v6.392h-8.307c-.146-4.996.359-10.045-.404-15.002-1.108-4.218-7.809-5.565-10.094-1.666-1.685 3.046-.712 6.634-.976 9.936v14.767h-8.354c.109-8.165-.238-16.344.215-24.5.674-5.346 5.095-10.389 10.676-10.627 4.902-.739 10.103 2.038 12.053 6.631.375 1.435 1.76 1.932 1.994.084 1.844-3.704 5.501-6.739 9.785-6.771.367-.044.735-.068 1.101-.073z\"\/><defs><linearGradient id=\"paint0_linear_549_34\" x1=\"37.0692\" y1=\"0\" x2=\"37.0692\" y2=\"79\" gradientUnits=\"userSpaceOnUse\"><stop stop-color=\"#6364FF\"\/><stop offset=\"1\" stop-color=\"#563ACC\"\/><\/linearGradient><\/defs><\/svg><\/span><span class=\"shariff-text\">compartir<\/span>&nbsp;<\/a><\/li><li class=\"shariff-button facebook shariff-nocustomcolor\" style=\"background-color:#4273c8\"><a href=\"https:\/\/www.facebook.com\/sharer\/sharer.php?u=https%3A%2F%2Fignos.blog%2Fen%2Fagents-extending-llm-functionality-with-openai\" title=\"Compartir en Facebook\" aria-label=\"Compartir en Facebook\" role=\"button\" rel=\"nofollow\" class=\"shariff-link\" style=\"; 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These agents, powered by LLMs such as GPT-4, are capable of<\/p>\n","protected":false},"author":2,"featured_media":1436,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_themeisle_gutenberg_block_has_review":false,"footnotes":""},"categories":[46],"tags":[],"class_list":["post-1440","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-artificial-intelligence-en"],"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v27.3 (Yoast SEO v27.4) - https:\/\/yoast.com\/product\/yoast-seo-premium-wordpress\/ -->\n<title>Agents: Extending LLM functionality with OpenAI - Ignos Blog<\/title>\n<meta name=\"description\" content=\"Learn about OpenAI tools to create OpenAI Agents and improve automation and continuous learning in your projects.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/ignos.blog\/en\/agents-extending-llm-functionality-with-openai\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Agents: Extending LLM functionality with OpenAI\" \/>\n<meta property=\"og:description\" content=\"Today, the use of intelligent agents is revolutionizing the interaction between humans and technology. 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