Master LLMs with our FREE course in collaboration with Activeloop & Intel Disruptor Initiative. Join now!

Publication

Crafting QA Tool with Reading Abilities Using RAG and Text-to-Speech
Data Science   Latest   Machine Learning

Crafting QA Tool with Reading Abilities Using RAG and Text-to-Speech

Last Updated on May 15, 2024 by Editorial Team

Author(s): Cornellius Yudha Wijaya

Originally published on Towards AI.

Develop your QA Chat Tool with the latest advancements in AI research.
Image generated with ideogram.ai

We have been in a year where LLM has been used massively by many companies. From simple search engines to extensive chatbots, LLM has facilitated all business needs.

One of the tools that are often required by the business is the Question-Answering (QA) tool. It's an AI-powered tool that can quickly answer user input questions.

In this article, we will develop the QA-LLM-powered tools with RAG and text-to-speech(TTS) capability. How can we do that? Let's get into it.

All the source code can be accessed via this repository.

For this project, we will follow the structure below.

Image by Author

The project would follow these steps:

Deploy the Open-Source Weaviate Vector Database with Docker.Read the Insurance Handbook PDF file and use the public-hosted embedding model from HuggingFace to embed the data.Store the embedding into the Weaviate Vector Store (Knowledge Base).Develop an RAG system with HuggingFace's public-hosted embedding and generative model.Use the ElevenLabs Text-to-Speech Model to transform the RAG output into audio.Create the front end with Streamlit.

In general, there are 6 steps we would follow to create the QA tool with RAG and TTS. Let's start now.

Before we start, we will prepare a few Python files that contain all the requirements so our application can… Read the full blog for free on Medium.

Join thousands of data leaders on the AI newsletter. Join over 80,000 subscribers and keep up to date with the latest developments in AI. From research to projects and ideas. If you are building an AI startup, an AI-related product, or a service, we invite you to consider becoming a sponsor.

Published via Towards AI

Feedback ↓