Build a Simple RAG App with Telnyx AI Inference
This repository provides a Python code example demonstrating how to build a simple Retrieval-Augmented Generation (RAG) application using Telnyx AI Inference, showcasing the integration of retrieval and generation capabilities.
Background
- Telnyx is a telecommunications and API company that provides voice, messaging, and networking services, and has recently expanded into AI inference APIs.
- RAG (Retrieval-Augmented Generation) is a technique that lets an LLM pull in relevant information from your own documents or databases before generating a response, making answers more accurate and grounded in your data.
- This GitHub repository contains example Python code showing how to build a simple RAG app using Telnyx's AI Inference API — essentially a how-to guide for developers who want to combine document retrieval with Telnyx-hosted language models.
- AI Inference refers to the API endpoint that runs large language models (LLMs) in the cloud, so you don't need to host or manage the model yourself.