Guide to Building a Python AI Call Agent with Speech-to-Text, Groq LLM and TTS

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A developer explains how to build an AI calling agent in Python by chaining speech-to-text, a language model, and text-to-speech in a continuous loop. The approach is illustrated through the author's Google Voice Dispatch Agent, a tool built for trucking dispatch outreach. The system waits for confirmed call connection before speaking, using a conservative gate on ringing states and a minimum ring window. Caller audio is transcribed with Groq-hosted Whisper, replies are generated by a Groq chat model with short responses, and speech is produced with Edge TTS, with pre-generated opening and voicemail lines to reduce delay. Voicemail detection runs after connection and switches the agent to a prerecorded message when triggered.

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