Build a Simple RAG App with Telnyx AI Inference

Short summary

A practical introduction to retrieval-augmented generation using Telnyx AI Inference. The tutorial walks through building a RAG system: embedding questions, retrieving relevant documents, and passing them as context to a model for grounded answers with source citations. Includes complete working Python/Flask code; scales to production by swapping in-memory storage for a vector database.

• •Step-by-step RAG tutorial with working Python/Flask example on GitHub
• •Demonstrates core RAG components: embeddings, retrieval, source grounding, and chat completion
• •Foundation for production use cases like support bots, product Q&A, and internal knowledge search

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