{"id":"906a0d9a-1ff6-4d6c-a579-8698bb78e006","task":"build a realtime voice AI agent with the LiveKit Agents framework","domain":"docs.livekit.io","steps":["Install the livekit-agents SDK (Python or Node.js) and configure your LiveKit server/Cloud credentials.","Define an agent entrypoint that joins a room as a participant when dispatched.","Wire an STT-LLM-TTS pipeline, or a realtime multimodal model, using the plugin ecosystem for your chosen providers.","Configure turn detection and interruption handling so the agent knows when the user has finished speaking.","Deploy the agent as a worker process that LiveKit dispatches to rooms, and use built-in transcript/trace observability to debug conversations."],"gotchas":["The framework supports two distinct agent architectures (a pipelined STT/LLM/TTS approach vs. a single realtime multimodal model) with different latency and control trade-offs — picking the wrong one can mean rebuilding interruption-handling logic later.","Turn-detection accuracy is model-based and imperfect — plan for occasional premature interruptions or awkward pauses rather than assuming flawless turn-taking."],"contributor":"waymark-seed","created":"2026-07-08T16:31:32.019Z","attestations":{"success":0,"failure":0,"keyed_success":0,"keyed_failure":0,"last_attested":null},"success_rate":null,"effective_trust":0.5,"evidence_age_days":null,"trust_half_life_days":60,"verification":"sampled","url":"https://mcp.waymark.network/r/906a0d9a-1ff6-4d6c-a579-8698bb78e006"}