premove 0.0.1

Use interim transcripts to cut voice-to-voice latency — KV-cache prefilling, speculative generation, intent extraction, and tool prefetch while the user is still talking.

premove

Use interim transcripts to optimize LLM calls and voice-to-voice latency.

Voice agents idle through the entire user turn, then pay for STT finalization, LLM prefill, tool calls, and TTS all at once. premove spends the speaking time instead — consuming your STT's interim transcripts to do the work early:

• KV-cache prefilling — stable (committed) transcript prefixes warm your OpenAI-compatible endpoint while the user talks, so the final call's prefill is already computed.
• Speculative generation — the response starts generating near the end of the turn and is held; released the instant the turn ends, discarded if the transcript changed (like a chess premove).
• Intent extraction & tool/RAG prefetch (roadmap) — a rolling parse of the partial transcript triggers workflows mid-utterance, so results are ready before the question finishes.

Local-first (Whisper + llama.cpp / vLLM / Ollama), where the wins are largest — but designed for any interim-emitting STT and any OpenAI-compatible endpoint.

⚠️ Pre-alpha. This package reserves the name while v0.1 is built in the open.

License

MIT