feat: 更新语音助手名称为昆小创,修改欢迎语和提示词

This commit is contained in:
Pine
2026-08-18 08:31:53 +08:00
parent f75fe7b9b3
commit 94faf14f07
5 changed files with 396 additions and 52 deletions
+1 -1
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@@ -90,7 +90,7 @@ class Settings:
# 语音助手基础提示词(.env 设 DPM_S2S_INSTRUCTIONS 可覆盖;知识库内容由 rag 自动拼接)
S2S_INSTRUCTIONS = _env(
"DPM_S2S_INSTRUCTIONS",
"你是昆小,昆明市大学生创业园的专属智能语音助手。可用工具:get_park_overview(园区实时数据)、"
"你是昆小,昆明市大学生创业园的专属智能语音助手。可用工具:get_park_overview(园区实时数据)、"
"query_companies(企业名录)、control_display(大屏控制)、get_time(时间)。"
"涉及园区数据/企业/大屏控制时务必调用工具获取准确信息。请用简洁专业的中文回答,不超过三句话。",
)
+3 -3
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@@ -33,7 +33,7 @@ const pick = (arr) => arr[Math.floor(Math.random() * arr.length)];
const VOICE_SAMPLES = QUICK_QUESTIONS;
/* 默认欢迎语(新对话第一条消息,与初始一致) */
const WELCOME_TEXT = '您好,我是「问问小园」,昆明市大学生创业园的专属 AI 助手(通义千问)。\n\n可以为您解答入驻申请、创业政策、创业担保贷款、OPC 概念、AI 工具等问题,也可以介绍园区入驻企业。试试右侧的预设问题吧。';
const WELCOME_TEXT = '您好,我是昆小创,昆明市大学生创业园的专属 AI 助手。\n\n可以为您解答入驻申请、创业政策、创业担保贷款、OPC 概念、AI 工具等问题,也可以介绍园区入驻企业。试试右侧的预设问题吧。';
/* ---------- 消息 ---------- */
let msgId = 0;
@@ -320,9 +320,9 @@ export default function AiChatPanel() {
<span className="bd-chat-logo"><Icon name="robot" size={17} /></span>
<div className="bd-chat-titles">
<b>问问小园</b>
<span>昆明市大学生创业园 · 通义千问</span>
<span>昆明市大学生创业园 · 昆小创</span>
</div>
<span className="bd-chat-model"><i />通义千问</span>
<span className="bd-chat-model"><i />昆小创</span>
<button className="bd-chat-clear" title="清空对话" onClick={clear}>
<Icon name="eraser" size={15} />
</button>
+22 -48
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@@ -1,4 +1,10 @@
// @ts-check
// AudioWorklet processor 源码(构建期内联,运行时直接 Blob → addModule)。
// 打包环境(Tauri v2 + WebView2)无法可靠地从 tauri.localhost 自定义协议或
// 跨域后端 URL 用 addModule 加载 worklet 模块;源码内联后零网络、零 CORS、零后端依赖。
import micWorkletSrc from "./worklets/mic-capture.js?raw";
import playbackWorkletSrc from "./worklets/audio-playback.js?raw";
/**
* Minimal WebSocket client for the Hugging Face speech-to-speech load balancer.
*
@@ -479,57 +485,25 @@ export class S2sWsRealtimeClient extends EventTarget {
}
// AudioWorklet 加载(WebView2/打包兼容):
// 1) 先直接 addModule(http 地址) —— 浏览器/常规环境快路径
// 2) 失败则 fetch 源码 → Blob URL → addModule —— 打包 WebView2
// tauri.localhost 自定义协议与跨域均受限,Blob 同源最稳
// 3) 多个候选基址(后端 http / 页面源 / 相对路径)
const candidates = [
window.VOICE_WORKLETS_BASE,
`${window.location.origin}/voice-worklets/`,
"/voice-worklets/",
].filter(Boolean);
let workletErr = null;
let workletOk = false;
const addViaBlob = async (name) => {
for (const base of candidates) {
try {
const res = await fetch(base + name, { cache: "no-store" });
if (!res.ok) continue;
const src = await res.text();
const url = URL.createObjectURL(new Blob([src], { type: "application/javascript" }));
try {
await ctx.audioWorklet.addModule(url);
return true;
} finally {
URL.revokeObjectURL(url);
}
} catch (err) {
workletErr = err;
}
}
return false;
};
for (const base of candidates) {
// 源码已由 Vite `?raw` 内联进 bundle,运行时直接从内存字符串建 Blob → addModule。
// 彻底摆脱运行时 fetch/网络/CORS/后端可达性依赖,任何 WebView2 都能加载。
const addWorkletFromSrc = async (name, src) => {
const url = URL.createObjectURL(new Blob([src], { type: "text/javascript" }));
try {
await ctx.audioWorklet.addModule(base + "mic-capture.js?v=3");
await ctx.audioWorklet.addModule(base + "audio-playback.js?v=3");
workletOk = true;
break;
} catch (err) {
workletErr = err;
console.warn("[ws] worklet 直接加载失败,改走 Blob 方案:", base, err);
await ctx.audioWorklet.addModule(url);
return true;
} finally {
URL.revokeObjectURL(url);
}
};
const workletOk =
(await addWorkletFromSrc("mic-capture", micWorkletSrc)) &&
(await addWorkletFromSrc("audio-playback", playbackWorkletSrc));
if (workletOk) {
console.info("[ws] AudioWorklet 已通过内联源码 Blob URL 加载(WebView2 兼容模式)");
} else {
throw new Error("AudioWorklet 模块加载失败(内联源码 Blob addModule 失败)");
}
if (!workletOk) {
// 回退:fetch → Blob → addModuleWebView2 打包环境最稳)
const micOk = await addViaBlob("mic-capture.js?v=3");
const playOk = await addViaBlob("audio-playback.js?v=3");
workletOk = micOk && playOk;
if (workletOk) console.info("[ws] AudioWorklet 已通过 Blob URL 加载(WebView2 兼容模式)");
}
if (!workletOk) throw workletErr || new Error("AudioWorklet 模块加载失败");
const captureNode = new AudioWorkletNode(ctx, "mic-capture", {
numberOfInputs: 1,
+211
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@@ -0,0 +1,211 @@
// @ts-check
/**
* AudioWorkletProcessor that plays back Float32 mono samples received from
* the main thread, upsampling whatever incoming rate the server uses
* (typically 16 kHz PCM16) to the AudioContext rate (typically 48 kHz).
*
* Lifecycle / messaging:
*
* main -> worklet:
* { kind: "config", inputRate: 16000, muted: false } one-shot at startup
* { kind: "audio", samples: Float32Array } per chunk
* { kind: "clear" } wipe queue (barge-in)
*
* worklet -> main:
* { kind: "stats", queuedMs, played } every ~250 ms
* { kind: "underrun" } every time the queue
* runs dry mid-playback
*
* `muted` (default false): the Live Avatar (LiveTalking WebRTC) carries the
* same audio, so the page mutes its own playback to avoid double audio. When
* the avatar is NOT running (e.g. dev on macOS), keep muted=false so the page
* plays the backend audio itself.
*
* IMPORTANT: the read position only advances while audio is actually being
* played (`_playing`). Advancing during idle would drift `_readIdx` far past
* the next chunk's length and turn every read into NaN (silence) once audio
* arrives.
*/
const STATS_INTERVAL_FRAMES = 12000;
const FADE_FRAMES = 32;
class AudioPlaybackProcessor extends AudioWorkletProcessor {
constructor() {
super();
this._inputRate = 16000;
this._stepRatio = this._inputRate / sampleRate;
this._muted = false;
this._queue = [];
this._readIdx = 0;
this._fracPos = 0;
this._playing = false;
this._lastSample = 0;
this._framesSinceStats = 0;
this._totalPlayed = 0;
this._dbgReceived = 0;
this._dbgOutPeak = 0;
this._fadeIn = 0;
this._fadeOut = 0;
this.port.onmessage = (e) => {
const data = e.data;
if (!data || typeof data !== "object") return;
switch (data.kind) {
case "config":
if (typeof data.inputRate === "number" && data.inputRate > 0) {
this._inputRate = data.inputRate;
this._stepRatio = this._inputRate / sampleRate;
}
if (typeof data.muted === "boolean") this._muted = data.muted;
break;
case "audio": {
// Accept Float32Array, a transferred ArrayBuffer, or a plain
// {buffer, byteOffset, length} descriptor: cross-realm structured
// cloning can deliver the samples in any of these shapes.
let arr = data.samples;
let f32 = null;
if (arr instanceof Float32Array) {
f32 = arr;
} else if (arr instanceof ArrayBuffer) {
f32 = new Float32Array(arr);
} else if (arr && typeof arr === "object" && arr.buffer instanceof ArrayBuffer) {
f32 = new Float32Array(arr.buffer, arr.byteOffset || 0, (arr.byteLength || arr.buffer.byteLength) >> 2);
}
if (f32 && f32.length > 0) {
this._queue.push(f32);
this._dbgReceived += 1;
if (!this._playing) {
this._playing = true;
this._fadeIn = FADE_FRAMES;
this._fadeOut = 0;
}
}
break;
}
case "clear":
this._queue.length = 0;
this._readIdx = 0;
this._fracPos = 0;
this._playing = false;
this._lastSample = 0;
this._fadeOut = FADE_FRAMES;
break;
}
};
}
_queuedSamples() {
let total = -this._readIdx;
for (const buf of this._queue) total += buf.length;
return Math.max(0, total);
}
/** Linear-interp read at the current fractional position. */
_readInterpolated() {
if (this._queue.length === 0) return null;
const head = this._queue[0];
const idx = this._readIdx;
const frac = this._fracPos;
let a = head[idx];
let b;
if (idx + 1 < head.length) {
b = head[idx + 1];
} else if (this._queue.length > 1) {
b = this._queue[1][0];
} else {
b = a;
}
return a + (b - a) * frac;
}
/** Advance the read position by `stepRatio`; pop consumed buffers. */
_advance() {
this._fracPos += this._stepRatio;
while (this._fracPos >= 1) {
this._fracPos -= 1;
this._readIdx += 1;
}
while (this._queue.length > 0 && this._readIdx >= this._queue[0].length) {
this._readIdx -= this._queue[0].length;
this._queue.shift();
}
}
process(_, outputs) {
const channels = outputs[0];
if (!channels || channels.length === 0) return true;
const out = channels[0];
const stereo = channels.length > 1 ? channels[1] : null;
// Muted mode (Live Avatar WebRTC carries the audio): output silence.
if (this._muted) {
for (let i = 0; i < out.length; i++) {
out[i] = 0;
if (stereo) stereo[i] = 0;
}
this._framesSinceStats += out.length;
return true;
}
for (let i = 0; i < out.length; i++) {
let sample = 0;
if (this._playing) {
const v = this._readInterpolated();
if (v === null) {
// Underrun: ramp out cleanly to avoid clicks.
sample = this._lastSample * Math.max(0, 1 - 1 / FADE_FRAMES);
this._lastSample = sample;
if (Math.abs(sample) < 1e-4) {
this._playing = false;
this._lastSample = 0;
this.port.postMessage({ kind: "underrun" });
}
} else {
sample = v;
this._lastSample = v;
this._advance();
}
if (this._fadeIn > 0) {
const gain = 1 - this._fadeIn / FADE_FRAMES;
sample *= gain;
this._fadeIn -= 1;
}
if (this._fadeOut > 0) {
const gain = this._fadeOut / FADE_FRAMES;
sample *= gain;
this._fadeOut -= 1;
if (this._fadeOut === 0) {
this._playing = false;
this._lastSample = 0;
}
}
this._totalPlayed += 1;
const abs = sample < 0 ? -sample : sample;
if (abs > this._dbgOutPeak) this._dbgOutPeak = abs;
}
out[i] = sample;
if (stereo) stereo[i] = sample;
}
this._framesSinceStats += out.length;
if (this._framesSinceStats >= STATS_INTERVAL_FRAMES) {
this.port.postMessage({
kind: "stats",
queuedMs: Math.round((this._queuedSamples() / this._inputRate) * 1000),
played: this._totalPlayed,
received: this._dbgReceived,
outPeak: this._dbgOutPeak,
});
this._framesSinceStats = 0;
}
return true;
}
}
registerProcessor("audio-playback", AudioPlaybackProcessor);
+159
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@@ -0,0 +1,159 @@
// @ts-check
/**
* AudioWorkletProcessor that resamples the AudioContext rate (typically 48 kHz)
* down to 16 kHz, packs the result as little-endian Int16 PCM, and posts it
* back to the main thread in fixed-size chunks.
*
* The Hugging Face speech-to-speech WebSocket route expects the
* `input_audio_buffer.append` payload at 16 kHz PCM16 mono.
*
* Design notes:
* - 48 -> 16 is an exact 3:1 ratio so we use a 3-tap boxcar average as a
* cheap low-pass before decimating. Good enough for voice STT; we lose
* a tiny bit of >8 kHz content which the pipeline discards anyway.
* - Output frames are emitted at the cadence dictated by `chunkMs`
* (default 40 ms = 640 samples = 1280 bytes). The OpenAI Realtime
* server batches incoming audio so the cadence is flexible; 20-100 ms
* is the sweet spot.
* - Float -> Int16 saturates to [-1, 1] before scaling.
* - Optional noise gate: per-chunk RMS decides open/closed against a
* threshold; the gain ramps (fast attack, hold, slow release) so word
* onsets aren't clipped and quiet tails don't click. The gate only
* affects the audio we SEND; the main-thread visualiser taps the raw
* mic separately. We post the chunk RMS up every frame so the Settings
* mic meter can show the live level against the threshold.
*/
const TARGET_RATE = 16000;
const DEFAULT_CHUNK_MS = 40;
// Gate envelope timing (fixed; only the threshold is user-tunable).
const GATE_ATTACK_MS = 5; // open almost instantly so word onsets survive
const GATE_HOLD_MS = 250; // stay open this long after the level drops back under
const GATE_RELEASE_MS = 80; // then fade closed over this long (no click)
class MicCaptureProcessor extends AudioWorkletProcessor {
constructor(options) {
super();
const chunkMs = options?.processorOptions?.chunkMs ?? DEFAULT_CHUNK_MS;
this._inputRate = sampleRate;
this._ratio = this._inputRate / TARGET_RATE;
this._chunkSamples16k = Math.round((TARGET_RATE * chunkMs) / 1000);
this._scratch = new Float32Array(0);
this._decimated = new Float32Array(this._chunkSamples16k);
this._enabled = true;
// Noise gate state. Disabled by default (pure passthrough).
this._gateEnabled = false;
this._thresholdLin = 0; // linear amplitude; signal RMS must exceed this to open
this._gateGain = 1; // smoothed gain currently applied
this._holdRemaining = 0; // samples left before the gate may start closing
this._attackCoef = Math.exp(-1 / ((GATE_ATTACK_MS / 1000) * TARGET_RATE));
this._releaseCoef = Math.exp(-1 / ((GATE_RELEASE_MS / 1000) * TARGET_RATE));
this._holdSamples = Math.round((GATE_HOLD_MS / 1000) * TARGET_RATE);
this.port.onmessage = (e) => {
const data = e.data;
if (data?.kind === "enable") this._enabled = !!data.value;
else if (data?.kind === "gate") {
this._gateEnabled = !!data.enabled;
// dB -> linear amplitude. When off, threshold 0 keeps the gate open.
this._thresholdLin = data.enabled ? Math.pow(10, data.thresholdDb / 20) : 0;
}
};
}
/**
* Append `incoming` to the internal scratch buffer, then emit as many
* full output chunks as we have material for.
* @param {Float32Array} incoming
*/
_ingest(incoming) {
if (incoming.length === 0) return;
const next = new Float32Array(this._scratch.length + incoming.length);
next.set(this._scratch, 0);
next.set(incoming, this._scratch.length);
this._scratch = next;
this._maybeEmit();
}
_maybeEmit() {
const r = this._ratio;
const n = this._chunkSamples16k;
const needIn = Math.ceil(n * r);
const dec = this._decimated;
while (this._scratch.length >= needIn) {
// 1. Decimate to 16 kHz floats and accumulate energy for the gate/meter.
let sumSq = 0;
if (Math.abs(r - 3) < 1e-6) {
// 48 kHz -> 16 kHz fast path with boxcar lowpass.
for (let i = 0; i < n; i++) {
const idx = i * 3;
const s = (this._scratch[idx] + this._scratch[idx + 1] + this._scratch[idx + 2]) / 3;
dec[i] = s;
sumSq += s * s;
}
} else {
// Generic path: linear interpolation. Slower but works at any rate
// (e.g. some Windows boxes report sampleRate=44100).
for (let i = 0; i < n; i++) {
const srcPos = i * r;
const idx = Math.floor(srcPos);
const frac = srcPos - idx;
const a = this._scratch[idx];
const b = this._scratch[idx + 1] ?? a;
const s = a + (b - a) * frac;
dec[i] = s;
sumSq += s * s;
}
}
const rms = Math.sqrt(sumSq / n);
// 2. Decide the gate target for this chunk, then ramp sample-by-sample.
let target = 1;
if (this._gateEnabled) {
if (rms >= this._thresholdLin) {
this._holdRemaining = this._holdSamples; // re-arm the hold
} else if (this._holdRemaining > 0) {
this._holdRemaining -= n; // coasting through the hold window
} else {
target = 0;
}
}
// 3. Apply the (smoothed) gain and pack to Int16.
const out = new Int16Array(n);
let gain = this._gateGain;
for (let i = 0; i < n; i++) {
const coef = target > gain ? this._attackCoef : this._releaseCoef;
gain = target + (gain - target) * coef;
const s = dec[i] * gain;
const clamped = s < -1 ? -1 : s > 1 ? 1 : s;
out[i] = clamped < 0 ? clamped * 0x8000 : clamped * 0x7fff;
}
this._gateGain = gain;
// Shift the scratch buffer to keep only the trailing unused samples.
const consumed = Math.floor(n * r);
this._scratch = this._scratch.slice(consumed);
// Live input level for the Settings meter (raw RMS, pre-gate).
this.port.postMessage({ kind: "level", rms });
if (this._enabled) {
this.port.postMessage(out.buffer, [out.buffer]);
}
// When disabled (mic muted) we silently consume input so the worklet
// stays alive and the buffer never grows unbounded.
}
}
process(inputs) {
const input = inputs[0];
if (!input || input.length === 0 || !input[0]) return true;
const mono = input[0];
if (mono.length > 0) this._ingest(mono);
return true;
}
}
registerProcessor("mic-capture", MicCaptureProcessor);