Python AI Voice Agent Tutorial – TL;DR
Tech With Tim walks you through building a fast, accurate AI voice agent in Python using Deepgram for speech-to-text and Twilio for call handling. You’ll learn how to set up your environment (PyCharm, Deepgram creds, Twilio console, ngrok), follow a simple build, then level up with function-calling tools—all backed by a timestamped video guide and a GitHub repo.
Plus, grab $200 in Deepgram credit, explore docs and a handy playground, and if you’re looking for extra support, check out Tim’s DevLaunch mentorship for real-world projects and hands-on feedback.
Watch on YouTube
Top comments (1)
Great walkthrough - the timestamped video and repo make it easy to go from ngrok to a working call. In our experience, enabling Deepgram interim results and tuning VAD, sending periodic pings on Twilio media streams, and setting strict function-call timeouts with idempotency keys keeps the agent snappy and avoids duplicate side effects; DTMF fallback also helps when ASR confidence dips. We’re building similar agents at Fluents and saw better barge-in by biasing entity vocab and adding a 150-250 ms debounce before speaking - does Tim’s function-calling section touch on retries/backoff or a simple per-call state store?