Métricas de evaluación: Resumen

• •Punto final de HTTP Webhook (n8n generará automáticamente)
• •Credenciales de API de Google Drive
• •Clave de API de OpenAI
• •Clave de API de Google Gemini

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        "content": "## 1. Setup Your AI Workflow to Use Evaluations\n[Learn more about the Evaluations Trigger](https://docs.n8n.io/integrations/builtin/?utm_source=n8n_app&utm_medium=node_settings_modal-credential_link&utm_campaign=n8n-nodes-base.evaluationTrigger)\n\nIn this scenario, we're evaluating the LLM's ability to summarise Youtube Video Transcripts. The transcripts are stored remotely in Google Drive and the expected input is the file's URL."
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        "content": "## Try It Out!\n### This n8n template demonstrates how to calculate the evaluation metric \"Summarization\" which in this scenario, measures the LLM's accuracy and faithfulness in producing summaries which are based on an incoming transcript.\n\nThe scoring approach is adapted from [https://cloud.google.com/vertex-ai/generative-ai/docs/models/metrics-templates#pointwise_summarization_quality](https://cloud.google.com/vertex-ai/generative-ai/docs/models/metrics-templates#pointwise_summarization_quality)\n\n### How it works\n* This evaluation works best for an AI summarization workflows.\n* For our scoring, we simple compare the generated response to the original transcript.\n* A key factor is to look out information in the response which is not mentioned in the documents.\n* A high score indicates LLM adherence and alignment whereas a low score could signal inadequate prompt or model hallucination.\n\n### Requirements\n* n8n version 1.94+\n* Check out this Google Sheet for a sample data [https://docs.google.com/spreadsheets/d/1YOnu2JJjlxd787AuYcg-wKbkjyjyZFgASYVV0jsij5Y/edit?usp=sharing](https://docs.google.com/spreadsheets/d/1YOnu2JJjlxd787AuYcg-wKbkjyjyZFgASYVV0jsij5Y/edit?usp=sharing)\n\n\n### Need Help?\nJoin the [Discord](https://discord.com/invite/XPKeKXeB7d) or ask in the [Forum](https://community.n8n.io/)!\n\nHappy Hacking!"
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