Build Real-Time AI Voice Assistant With RAG Pipeline And Memory | Mistral LLM | Ollama | LlamaIndex

Start your journey from ground zero and master the creation of a real-time AI voice assistant using Python’s RAG pipeline. This comprehensive tutorial guides you through the process of building an advanced assistant capable of handling voice interactions, transcribing speech, and generating intelligent responses from scratch. Ideal for those eager to dive into AI development, this guide offers a solid foundation for creating powerful voice-enabled applications. Perfect for call centers, customer support, and virtual receptionist applications. In this comprehensive tutorial, you’ll learn how to integrate top AI technologies: ✅ Faster Whisper: A reimplementation of Whisper from OpenAI Speech-to-Text API, ensuring faster and precise real-time transcription. ✅ TTS (Google Text-to-Speech): Harness Google Translate’s text-to-speech API with ease using Python. ✅ Qdrant Vector DB: Leverage vector data storage for efficient processing. ✅ LlamaIndex: Master thi