Voice RAG OpenAI SDK

🎙️ Voice RAG with OpenAI SDK

🎓 FREE Step-by-Step Tutorial

👉 Click here to follow our complete step-by-step tutorial and learn how to build this from scratch with detailed code walkthroughs, explanations, and best practices.

This script demonstrates how to build a voice-enabled Retrieval-Augmented Generation (RAG) system using OpenAI's SDK and Streamlit. The application allows users to upload PDF documents, ask questions, and receive both text and voice responses using OpenAI's text-to-speech capabilities.

Features

• Creates a voice-enabled RAG system using OpenAI's SDK
• Supports PDF document processing and chunking
• Uses Qdrant as the vector database for efficient similarity search
• Implements real-time text-to-speech with multiple voice options
• Provides a user-friendly Streamlit interface
• Allows downloading of generated audio responses
• Supports multiple document uploads and tracking

How to get Started?

1. Clone the GitHub repository

git clone https://github.com/Shubhamsaboo/awesome-llm-apps.git
cd awesome-llm-apps/voice_ai_agents/voice_rag_openaisdk

2. Install the required dependencies:

pip install -r requirements.txt

3. Set up your API keys:

• Get your OpenAI API key
• Set up a Qdrant Cloud account and get your API key and URL
• Create a .env file with your credentials:

OPENAI_API_KEY='your-openai-api-key'
QDRANT_URL='your-qdrant-url'
QDRANT_API_KEY='your-qdrant-api-key'

4. Run the Voice RAG application:

streamlit run rag_voice.py

5. Open your web browser and navigate to the URL provided in the console output to interact with the Voice RAG system.

How it works?

1. Document Processing:

• Upload PDF documents through the Streamlit interface
• Documents are split into chunks using LangChain's RecursiveCharacterTextSplitter
• Each chunk is embedded using FastEmbed and stored in Qdrant

2. Query Processing:

• User questions are converted to embeddings
• Similar documents are retrieved from Qdrant
• A processing agent generates a clear, spoken-word friendly response
• A TTS agent optimizes the response for speech synthesis

3. Voice Generation:

• Text responses are converted to speech using OpenAI's TTS
• Users can choose from multiple voice options
• Audio can be played directly or downloaded as MP3

4. Features:

• Real-time audio streaming
• Multiple voice personality options
• Document source tracking
• Download capability for audio responses
• Progress tracking for document processing