Overview

Samples & Labs

Explore hands-on notebooks that demonstrate how to build and extend the Real-Time Voice Agent. The repository groups content into quickstart “Hello World” tutorials and deeper lab exercises.

Hello World Series

Beginner-friendly notebooks under samples/hello_world/ walk through the core features step by step.

Notebook	Summary
01-create-your-first-rt-agent.ipynb	Assemble a basic customer-support voice agent end to end.
02-run-test-rt-agent.ipynb	Execute call flows and validate the agent locally.
03-create-your-first-foundry-agents.ipynb	Provision Azure AI Foundry agents and wire them into the pipeline.
04-exploring-live-api.ipynb	Explore Azure Live Voice API capabilities.
05-create-your-first-livevoice.ipynb	Build out Live Voice scenarios using the accelerator scaffold.

Tips: - Run notebooks in sequence for a guided learning path. - Launch Jupyter from the repo root so relative imports work (jupyter lab). - Ensure .env contains valid Azure credentials before executing calls.

Advanced Labs

Deep-dive content lives in samples/labs/ and focuses on performance tuning, state management, and experimentation.

Notebook	Focus
01-build-your-audio-agent.ipynb	Full voice-to-voice pipeline with Azure AI components.
02-how-to-use-aoai-for-realtime-transcriptions.ipynb	Optimize Azure OpenAI for real-time STT.
03-latency-arena.ipynb	Measure and optimize end-to-end latency.
04-memory-agents.ipynb	Implement conversational memory and session persistence.
05-speech-to-text-multilingual.ipynb	Multi-language transcription workflows.
06-text-to-speech.ipynb	Tune neural voice synthesis and SSML.
07-vad.ipynb	Voice activity detection experiments.
08-speech-to-text-diarization.ipynb	Multi-speaker diarization strategies.
voice-live.ipynb	Real-time voice tests across environments.

Audio Experiment Bundles

• labs/podcast_voice_tests/ – Compare TTS model outputs against ground-truth recordings to evaluate voice quality.
• labs/recordings/ – Store captured audio samples for regression testing and debugging.

Environment Checklist

1. Python 3.11+ with project dependencies installed (pip install -r requirements.txt).
2. Jupyter or VS Code notebooks. Activate the project virtual environment first.
3. Azure resources (Speech, OpenAI, ACS, Redis) provisioned and referenced in .env.

Suggested Paths

• New to the stack? Start with the Hello World series (notebooks 01 → 05).
• Voice quality & tuning: Labs 06, 07, and the podcast voice tests.
• Performance & reliability: Labs 03 and voice-live.ipynb for latency and live validation.

For additional context, see samples/README.md in the repository root—this page is a condensed version suitable for the documentation site.