What to build
A Python voice agent example that uses Deepgram Nova-3's automatic language detection to identify the caller's language and dynamically route the conversation — adjusting the LLM system prompt, TTS voice, and response language accordingly.
Why this matters
Multilingual voice agents are essential for global businesses and multilingual markets. Developers need a working example showing how to detect a caller's language from their first utterance, route to the appropriate language-specific configuration, and maintain a coherent multilingual conversation. Deepgram Nova-3 supports 36+ languages with automatic detection, making it the foundation for this pattern.
Suggested scope
- Python, using
deepgram-sdk
- Deepgram Nova-3 with
language=multi or detect_language=true
- Dynamic routing: detect language → set LLM system prompt in detected language → select appropriate TTS voice
- Support at least 3 languages (e.g., English, Spanish, Hindi)
- Deepgram Voice Agent API or direct STT + LLM + TTS pipeline
Acceptance criteria
Raised by the DX intelligence system.
What to build
A Python voice agent example that uses Deepgram Nova-3's automatic language detection to identify the caller's language and dynamically route the conversation — adjusting the LLM system prompt, TTS voice, and response language accordingly.
Why this matters
Multilingual voice agents are essential for global businesses and multilingual markets. Developers need a working example showing how to detect a caller's language from their first utterance, route to the appropriate language-specific configuration, and maintain a coherent multilingual conversation. Deepgram Nova-3 supports 36+ languages with automatic detection, making it the foundation for this pattern.
Suggested scope
deepgram-sdklanguage=multiordetect_language=trueAcceptance criteria
Raised by the DX intelligence system.