The

generate_reply

method can indeed result in a function_tool call, not just speech output. It operates through a pipeline that includes both LLM inference and tool execution. The LLM can decide to generate either text content or function calls based on the instructions, context, and available tools. For example: • When a user asks a question like "What is the weather in San Francisco?",

generate_reply

might trigger a

lookup_weather

function call with the appropriate arguments. • In multi-agent scenarios, it can even result in agent handoffs through function tools that return new Agent instances. You can control this behavior using the

tool_choice

parameter in `generate_reply`: • Setting

tool_choice=\"none\"

will prevent function calls. • Setting

tool_choice=\"auto\"

allows the LLM to decide whether to call functions. This flexibility ensures that

generate_reply

can handle both conversational and functional requirements effectively. Sources: livekit-agents/livekit/agents/voice/generation.py | main.py