neural-maze/realtime-phone-agents-course resource

Health v2 · maintenance only

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1085 stars · 248 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

A hands-on course repository teaching how to build realtime AI voice agents that handle live phone calls. It covers FastRTC for low-latency audio streaming, Superlinked for vector search, Twilio telephony, speech-to-text and text-to-speech models, and GPU deployment on Runpod.

Use cases

• build an AI agent that answers inbound phone calls
• make outbound calls with a voice agent
• stream realtime audio conversations with low latency
• transcribe speech instantly for a voice bot
• generate lifelike speech with open-source TTS models
• search property data with vector search for a voice agent
• deploy open-source voice models on a GPU cloud

When to choose

• you want a structured, project-based course on realtime voice agents
• you need to integrate Twilio phone calls with AI agents
• you want to learn the full STT/TTS/LLM voice pipeline end to end

When to avoid

• you need a production-ready call center product rather than learning material
• you want a plug-and-play voice agent library instead of a course
• you are not working in Python

Facets

learning-resource · maturity active

speech-recognition tts rag agent-framework llm-inference gpu-computing artificial-intelligence speech-processing tutorials python cloud voice-agents phone-calls twilio fastrtc course realtime-audio vector-search runpod ai-agents retrieval-augmented-generation gpu

Member repositories

For agents

markdown · JSON · MCP: product_card(name="neural-maze/realtime-phone-agents-course")