AudioQnA Application¶

AudioQnA is an example that demonstrates the integration of Generative AI (GenAI) models for performing question-answering (QnA) on audio files, with the added functionality of Text-to-Speech (TTS) for generating spoken responses. The example showcases how to convert audio input to text using Automatic Speech Recognition (ASR), generate answers to user queries using a language model, and then convert those answers back to speech using Text-to-Speech (TTS).

Architecture¶

The AudioQnA example is implemented using the component-level microservices defined in GenAIComps. The flow chart below shows the information flow between different microservices for this example.

flowchart LR %% Colors %% classDef blue fill:#ADD8E6,stroke:#ADD8E6,stroke-width:2px,fill-opacity:0.5 classDef orange fill:#FBAA60,stroke:#ADD8E6,stroke-width:2px,fill-opacity:0.5 classDef orchid fill:#C26DBC,stroke:#ADD8E6,stroke-width:2px,fill-opacity:0.5 classDef invisible fill:transparent,stroke:transparent; style AudioQnA-MegaService stroke:#000000 %% Subgraphs %% subgraph AudioQnA-MegaService["AudioQnA MegaService "] direction LR ASR([ASR MicroService]):::blue LLM([LLM MicroService]):::blue TTS([TTS MicroService]):::blue end subgraph UserInterface[" User Interface "] direction LR a([User Input Query]):::orchid UI([UI server ]):::orchid end WSP_SRV{{whisper service }} SPC_SRV{{speecht5 service }} LLM_gen{{LLM Service }} GW([AudioQnA GateWay ]):::orange %% Questions interaction direction LR a[User Audio Query] --> UI UI --> GW GW <==> AudioQnA-MegaService ASR ==> LLM LLM ==> TTS %% Embedding service flow direction LR ASR <-.-> WSP_SRV LLM <-.-> LLM_gen TTS <-.-> SPC_SRV

Deployment Options¶

The table below lists currently available deployment options. They outline in detail the implementation of this example on selected hardware.

Category	Deployment Option	Description
On-premise Deployments	Docker compose	AudioQnA deployment on Xeon
		AudioQnA deployment on Gaudi
		AudioQnA deployment on AMD ROCm
	Kubernetes	Helm Charts