LocalLLaMA seeks dual-agent setup

The right answer is usually modular, not monolithic: keep the task agent, speech-to-text, and text-to-speech layers separate, then wire them together with a small controller. That gives you clearer failure modes, easier model swaps, and a setup that can scale from hobby scripts to a real local assistant.

• –A routine automation agent wants a planner/executor loop, tool access, and scheduling, not heavy audio plumbing.
• –Voice workloads are a different pipeline: STT for capture, an LLM for reasoning, then TTS for response generation.
• –Splitting the stacks lets you mix and match models, for example one model for chat reasoning and another optimized for low-latency speech.
• –A self-hosted architecture also makes privacy and offline use much easier, which is usually the point of going local.
• –The main design choice is the glue layer: queue, API server, or event bus, depending on how interactive the voice path needs to be.