Deepgram Voice Agent
Using jambonz to connect custom telephony to Deepgram’s conversational AI
The jambonz application referenced in this article can be found here.
This is an example jambonz application that connect to Deepgram’s Voice Agent and illustrates how to build a Voice-AI application using jambonz and OpenAI.
Authentication
To use this application, you’ll need a Deepgram API key. Set the api key as an environment variable before launching the application, like so:
Replace <api-key> with your actual Deepgram api key.
Configuring the assistant
With Deepgram, there is no “agent” that you need to create on their platform. You do, however, get to specify in your application the LLM model you want to use, as shown here and described here in the Deepgram docs.
You can also specify the STT model
in the think property and optionally a TTS voice in the
speak property.
Finally, you provide client-side tools as shown in the example here.
actionHook properties
Like many Jambonz verbs, the llm verb sends an actionHook with a final status when the verb completes.
The payload includes a completion_reason property indicating why the llm session ended.
Possible values for completion_reason are:
- Normal conversation end
- Connection failure
- Disconnect from remote end
- Server failure
- Server error
Ensure all environment variables are properly configured before starting the application. For detailed API references and documentation, visit the Deepgram Documentation.