Please extend Vapi’s Azure integration beyond LLM models so customers can use Azure AI Foundry / Azure-hosted models for the complete voice pipeline: Speech-to-text Text-to-speech LLMs Customers should be able to select an Azure AI Foundry deployment for STT or TTS even when that specific model is not yet available as a native Vapi provider. For example: An organization deploys or accesses GPT-Live-Transcribe through Azure AI Foundry, then connects that deployment to Vapi as the assistant’s realtime transcriber. Vapi would continue handling the phone call, turn-taking, tools, and orchestration, while Azure handles transcription. The integration should support: Azure AI Foundry deployment names and regional endpoints Azure authentication through managed credentials or API keys Streaming audio input for realtime STT Partial and final transcript events Streaming TTS audio output Configurable audio codecs, sample rates, and formats Language and pronunciation settings Custom model/deployment selection Regional routing and data-residency controls Clear timeout, retry, and provider-error reporting This would let customers use models that Vapi does not yet offer natively while keeping Vapi’s call handling and orchestration. It would also make Azure-hosted voice models practical for regulated deployments that require EU or Swiss-region processing. Please clarify whether this should be implemented through: A first-class Azure AI Foundry STT/TTS provider, A general custom streaming STT/TTS endpoint, Or both.
