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In this video, I’m exploring OpenAI’s new Responses API and how it makes building a RAG system easier than ever. We’ll walk through how to upload documents, retrieve relevant chunks, and generate responses—all without needing an external vector store. Plus, I’ll show you how to evaluate your pipeline to make sure it actually works. Let’s dive in!
LINKS:
https://cookbook.openai.com/examples/file_search_responses#evaluating-performance
https://arxiv.org/pdf/2404.12272
https://docs.ragas.io/en/latest/concepts/metrics/available_metrics/faithfulness/
https://openai.com/api/pricing/
https://openai.com/index/new-tools-for-building-agents/
https://colab.research.google.com/drive/16KCUPgYs6R7ULRFTyqf5zk2IpcEYmJQ5?usp=sharing
https://platform.openai.com/docs/guides/tools-file-search
RAG Beyond Basics Course:
https://prompt-s-site.thinkific.com/courses/rag
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Discord: https://discord.com/invite/t4eYQRUcXB
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00:00 Introduction to the New Developer Tools Series
00:13 Overview of the Responses API
02:20 Building a RAG System with Responses API
02:47 Setting Up the Environment
04:00 Creating and Uploading to Vector Stores
06:43 Retrieving Documents from Vector Stores
09:36 Generating Responses with the Responses API
12:12 Evaluation and Testing Strategies
13:34 Generating Evaluation Datasets Read More Prompt Engineering
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