Ultra‑Low Latency Local‑First Interview Copilot

说明与用途

WishPilot 是一款本地化的面试助手，使用 Electron、React 19 和 Groq Whisper Turbo 实现亚秒级语音识别，无需将数据上传至云端，保障隐私。

问题

Conventional conversational AI assistants suffer from 8–10 s latency and require uploading private audio and credentials to cloud servers, which is unacceptable for live interviews and raises privacy concerns.

结果

WishPilot achieves sub‑second speech intelligence on a desktop, eliminates privacy risks by keeping all data local, and provides a real‑time interview assistant with customizable answer refinement.

工作流

• Capture microphone audio via AudioWorkletNode
• Downsample to 16 kHz PCM and run VAD
• Send audio chunk to Groq Whisper Large v3 Turbo over HTTPS
• Receive STT and synthesize context (resume, domain, vision)
• Stream LLM response through Unified AI Streaming Engine (BYOK)
• Display answer in floating HUD with WDA_EXCLUDEFROMCAPTURE
• Offer quick‑action pills for answer refinement

证据

The spoken question is transcribed with technical vocabulary accuracy in under 250 milliseconds.

来源

WishPilot has zero central backend servers. No telemetry pings, no user tracking, and no database holding interview transcripts.

来源