better-sandwich-65834
02/20/2026, 7:57 AMtall-airline-16756
02/20/2026, 7:57 AMtall-airline-16756
02/20/2026, 7:57 AMparallel_tool_calls parameter available across multiple LLM plugins. When parallel_tool_calls is set to true, the model can invoke multiple tools simultaneously, which can improve performance for workflows that need several independent calls.
A few quick notes:
• The parameter is optional and may be disabled by default depending on the provider or plugin you’re using.
• If you want, tell me which plugin or provider you’re using (for example: Fireworks, DeepSeek, Perplexity, Azure OpenAI, Anthropic, etc.), and I’ll give plugin-specific guidance or an example of how to enable parallel_tool_calls. Sources: Fireworks AI LLM plugin guide | LiveKit Documentation | DeepSeek LLM plugin guide | LiveKit Documentation | Together AI LLM plugin guide | LiveKit Documentation | Perplexity LLM plugin guide | LiveKit Documentation | Telnyx LLM plugin guide | LiveKit Documentationbetter-sandwich-65834
02/20/2026, 8:00 AMtall-airline-16756
02/20/2026, 8:00 AMparallel_tool_calls is supported for STS models. The documentation and plugin notes describe parallel_tool_calls for LLM plugins (OpenAI, Anthropic, etc.), but they do not mention STS models or whether the parameter applies to them.
Could you tell me which STS model or provider you mean (name/version and where you’re configuring it)? With that, I can check more precisely and either show how to enable parallel calls if it’s supported or suggest alternative approaches.
Sources: OpenAI LLM plugin guide | LiveKit Documentationbetter-sandwich-65834
02/20/2026, 8:01 AMtall-airline-16756
02/20/2026, 8:01 AMgpt-realtime model supports parallel tool calls.
Yes. LiveKit Agents supports parallel tool calls for gpt-realtime via the OpenAI Realtime integration. You can enable this by setting parallel_tool_calls=True (or the equivalent) on the RealtimeModel / MultimodalAgent configuration. Enabling it lets the model invoke multiple tools simultaneously, which can speed up workflows that require several independent tool calls.
If you’d like, tell me:
• How you’re instantiating the model (code snippet or config), and
• Which tools you plan to call in parallel.
I can then give a concrete example of the configuration or point out anything to watch for (race conditions, ordering needs, or shared-resource considerations).
Sources: Azure OpenAI LLM plugin guide | LiveKit Documentation | OpenAI and LiveKit partner to turn Advanced Voice into an API