Implementing a Virtual Veterinarian Using Deepgram API

The article presents a client-side virtual veterinary telehealth application that uses Deepgram’s automatic speech recognition and audio intelligence features to make consultations easier for pet owners to understand and revisit. It describes how real-time transcription, topic detection, sentiment analysis, and summarization can identify diagnoses, symptoms, treatments, and key advice while reducing confusion caused by medical jargon. The walkthrough explains obtaining a Deepgram API key, setting up a Python 3.10 environment, installing the Deepgram SDK and dotenv, configuring prerecorded-audio analysis with the Nova-2 model, extracting transcript topics and summaries from the API response, and generating a spoken summary as a WAV file. It also suggests future enhancements such as using large language models to answer follow-up questions about consultations and applying predictive analytics to pet health data for proactive care recommendations.

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