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2 Commits

Author SHA1 Message Date
9f2fdc1369 Remove Python cache artifacts 2026-04-30 03:21:40 +09:00
73546c15b9 Replace ElevenLabs with local STT and TTS 2026-04-30 03:21:30 +09:00
22 changed files with 945 additions and 326 deletions

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@@ -2,15 +2,23 @@ DISCORD_BOT_TOKEN=
DISCORD_APPLICATION_ID=
DISCORD_COMMAND_GUILD_ID=
ELEVENLABS_API_KEY=
ELEVENLABS_VOICE_ID=
ELEVENLABS_STT_MODEL=scribe_v2_realtime
ELEVENLABS_TTS_MODEL=eleven_flash_v2_5
OLLAMA_BASE_URL=http://localhost:11434
OLLAMA_MODEL=qwen3:0.6b
OLLAMA_KEEP_ALIVE=5m
OLLAMA_NUM_CTX=4096
LOCAL_AI_VENV_PATH=.local-ai/.venv
LOCAL_AI_CACHE_DIR=.local-ai/cache
LOCAL_AI_PYTHON=
LOCAL_STT_MODEL=tiny
LOCAL_STT_DEVICE=auto
LOCAL_STT_COMPUTE_TYPE=auto
LOCAL_STT_BEAM_SIZE=1
LOCAL_TTS_LANGUAGE=KR
LOCAL_TTS_SPEAKER=KR
LOCAL_TTS_DEVICE=auto
LOCAL_TTS_SPEED=1.12
BOT_DEFAULT_LANGUAGE=ko
MAX_CONVERSATION_TURNS=12
LOCAL_AUDIO_SOURCE=

3
.gitignore vendored
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@@ -1,3 +1,6 @@
node_modules
dist
.env
.local-ai
__pycache__
*.pyc

188
README.md
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@@ -1,127 +1,138 @@
# realtime_voice_bot
디스코드 음성 채널 또는 로컬 PC 마이크/스피커에서 한국어 음성을 인식하고, 로컬 LLM 응답을 생성한 뒤 ElevenLabs TTS로 다시 읽어주는 최소 프로토타입입니다.
디스코드 음성 채널 또는 로컬 PC 마이크에서 한국어 음성을 인식하고, 완전 로컬 스택으로 답변을 생성한 뒤 다시 음성으로 읽어주는 최소 프로토타입입니다.
## 현재 스택
- STT: `faster-whisper` + Whisper multilingual
- LLM: `Ollama` + `qwen3:0.6b`
- TTS: `MeloTTS` Korean
- VAD: `avr-vad`
외부 유료 API나 무료 한도형 API는 쓰지 않습니다.
## 현재 구현 범위
- Discord slash command 기반 제어: `/join`, `/leave`, `/status`, `/reset`, `/say`
- 로컬 테스트 모드: `pw-record` 입력, `pw-play` 출력
- 로컬 테스트 모드: PC 마이크로 직접 말하고 바로 응답 확인
- `@discordjs/voice` 기반 음성 채널 입장 및 유저별 오디오 수신
- 48k stereo PCM을 16k mono로 내려서 유저별 VAD 처리
- Silero 계열 VAD(`avr-vad`)로 발화 시작/종료 감지
- ElevenLabs Scribe Realtime WebSocket으로 발화 단위 STT
- Ollama 로컬 LLM으로 짧은 한국어 답변 생성
- ElevenLabs Flash v2.5 스트리밍 TTS
- 채널 단위 단일 재생 큐
- 사용자 발화 시작 시 현재 TTS와 대기열 중단(barge-in)
- 화자 발화 시작 시 현재 재생과 대기열 즉시 중단
- Python 로컬 워커를 한 번 띄워 STT/TTS 모델을 메모리에 유지
## 권장 환경
## 필수 준비물
- Bun `1.3+`
- Node.js `22.12+`
- Python `3.11+`
- `ffmpeg`
- Ollama
- Discord bot with Voice permissions
- ElevenLabs API key + 사용할 Voice ID
Discord 모드까지 쓸 거면 추가로:
- Discord bot token
- Discord application id
## 빠른 시작
```bash
bun install
ollama pull qwen3:0.6b
bun run setup:local-ai
```
그다음 로컬 장치 확인:
```bash
bun run devices
```
실행:
```bash
bun run start:local
```
Discord 모드:
```bash
bun run start:discord
```
## 환경 변수
`.env.example`참고해서 `.env`를 채우면 됩니다.
필수:
- `ELEVENLABS_API_KEY`
- `ELEVENLABS_VOICE_ID`
`.env.example`복사해서 `.env`를 채우면 됩니다.
Discord 모드에서만 필수:
- `DISCORD_BOT_TOKEN`
- `DISCORD_APPLICATION_ID`
기본값이 이미 들어있는 로컬 AI 설정:
- `OLLAMA_BASE_URL`
- `OLLAMA_MODEL`
- `OLLAMA_KEEP_ALIVE`
- `OLLAMA_NUM_CTX`
- `LOCAL_AI_VENV_PATH`
- `LOCAL_AI_CACHE_DIR`
- `LOCAL_STT_MODEL`
- `LOCAL_STT_DEVICE`
- `LOCAL_STT_COMPUTE_TYPE`
- `LOCAL_STT_BEAM_SIZE`
- `LOCAL_TTS_LANGUAGE`
- `LOCAL_TTS_SPEAKER`
- `LOCAL_TTS_DEVICE`
- `LOCAL_TTS_SPEED`
선택:
- `DISCORD_COMMAND_GUILD_ID`
- 테스트 서버에만 slash command를 즉시 반영하려면 설정
- `OLLAMA_BASE_URL`
- 기본값: `http://localhost:11434`
- `OLLAMA_MODEL`
- 기본값: `qwen3:0.6b`
- 가장 빠른 무료 오픈웨이트 로컬 기본값
- `OLLAMA_KEEP_ALIVE`
- 기본값: `5m`
- `OLLAMA_NUM_CTX`
- 기본값: `4096`
- `LOCAL_AI_PYTHON`
- Python 경로 자동 탐지가 안 되면 설정
- 예시: `python`
- Windows 예시: `py -3`
- `LOCAL_AUDIO_SOURCE`
- `pw-record --target` 에 넣을 PipeWire source id 또는 node name
- 로컬 입력 장치
- Linux는 `pw-record --target`, Windows는 `ffmpeg dshow` 장치 이름
- `LOCAL_AUDIO_SINK`
- `pw-play --target` 에 넣을 PipeWire sink id 또는 node name
- Linux 로컬 출력 장치
- Windows는 현재 시스템 기본 출력 장치 사용
- `LOCAL_SPEAKER_NAME`
- 로컬 테스트에서 프롬프트에 넣을 화자 이름
- `ELEVENLABS_STT_MODEL`
- 기본값: `scribe_v2_realtime`
- `ELEVENLABS_TTS_MODEL`
- 기본값: `eleven_flash_v2_5`
- `BOT_DEFAULT_LANGUAGE`
- 기본값 `ko`
- `DEBUG_TEXT_EVENTS`
- `true` 명령을 실행한 텍스트 채널에 transcript/reply를 같이 올림
- `true`면 transcript/reply를 콘솔에 같이 출력
## 실행
## 속도 우선 기본값
```bash
bun install
- STT 기본 모델은 `tiny`
- LLM 기본 모델은 `qwen3:0.6b`
- TTS 기본 속도는 `1.12`
정확도가 아쉬우면:
```env
LOCAL_STT_MODEL=small
OLLAMA_MODEL=qwen3:1.7b
```
Ollama 준비:
## 로컬 테스트 순서
```bash
ollama pull qwen3:0.6b
```
속도보다 품질이 더 중요하면:
```bash
ollama pull qwen3:1.7b
# 또는
ollama pull qwen3:4b
```
디스코드 모드:
```bash
bun run start:discord
```
로컬 장치 목록:
```bash
bun run audio:devices
```
로컬 테스트 모드:
```bash
bun run start:local
```
타입 체크:
```bash
bun run check
```
## 사용 흐름
1. 봇을 서버에 초대하고 음성 권한을 부여합니다.
2. 음성 채널에 들어갑니다.
3. 텍스트 채널에서 `/join` 실행
4. 말을 하면 봇이 발화 단위로 인식하고 음성으로 짧게 답합니다.
5. 다시 말하면 현재 읽고 있던 TTS는 즉시 중단됩니다.
로컬 테스트:
1. `bun run audio:devices` 로 source/sink id 또는 이름 확인
1. `bun install`
2. `ollama pull qwen3:0.6b`
3. 필요하면 `.env``LOCAL_AUDIO_SOURCE`, `LOCAL_AUDIO_SINK`, `OLLAMA_MODEL` 설정
3. `bun run start:local`
4. 마이크로 바로 말해서 응답 확인
3. `bun run setup:local-ai`
4. `bun run devices`
5. 필요하면 `.env``LOCAL_AUDIO_SOURCE` 설정
6. `bun run start:local`
## Windows 메모
- `bun run devices` 와 Windows 로컬 녹음은 `ffmpeg`가 필요합니다.
- 출력 장치 직접 선택은 아직 미구현이라 시스템 기본 출력 장치로 재생됩니다.
- Python 탐지가 안 되면 `.env``LOCAL_AI_PYTHON=py -3` 또는 `LOCAL_AI_PYTHON=python` 을 넣으면 됩니다.
## 설계 메모
@@ -129,5 +140,4 @@ bun run check
- 출력은 길드 세션당 단일 큐
- 로컬 모드는 단일 화자 입력 기준
- 화자 구분은 `speaker_id`, `speaker_name`을 LLM 프롬프트에 항상 포함
- 현재 기본 LLM은 `qwen3:0.6b` 이며 속도 우선 설정이라 답변 품질이 약하면 `qwen3:1.7b` 또는 `qwen3:4b` 로 올리는 것을 권장합니다.
- STT/TTS는 아직 ElevenLabs API를 사용하므로 프로젝트 전체가 완전 무과금은 아닙니다.
- 모델 다운로드 캐시는 기본적으로 `.local-ai/cache` 아래에 저장

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@@ -12,7 +12,6 @@
"ffmpeg-static": "^5.3.0",
"opusscript": "^0.1.1",
"prism-media": "^1.3.5",
"ws": "^8.20.0",
"zod": "^4.3.6",
},
"devDependencies": {
@@ -22,6 +21,7 @@
},
},
"trustedDependencies": [
"ffmpeg-static",
"onnxruntime-node",
],
"packages": {

View File

@@ -8,6 +8,7 @@
"start": "bun src/index.ts discord",
"start:discord": "bun src/index.ts discord",
"start:local": "bun src/index.ts local",
"setup:local-ai": "bun src/setup-local-ai.ts",
"devices": "bun src/index.ts local-devices",
"audio:devices": "bun src/index.ts local-devices",
"check": "tsc --noEmit",
@@ -25,7 +26,6 @@
"ffmpeg-static": "^5.3.0",
"opusscript": "^0.1.1",
"prism-media": "^1.3.5",
"ws": "^8.20.0",
"zod": "^4.3.6"
},
"devDependencies": {

145
python/local_stt_worker.py Normal file
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@@ -0,0 +1,145 @@
import base64
import json
import os
import sys
import tempfile
import traceback
import wave
os.environ.setdefault("PYTHONIOENCODING", "utf-8")
def log(message: str) -> None:
print(message, file=sys.stderr, flush=True)
def write_response(request_id: int, ok: bool, result=None, error: str | None = None) -> None:
payload = {
"id": request_id,
"ok": ok,
}
if ok:
payload["result"] = result
else:
payload["error"] = error or "unknown error"
sys.stdout.write(json.dumps(payload, ensure_ascii=False) + "\n")
sys.stdout.flush()
def resolve_device() -> str:
raw = os.environ.get("LOCAL_STT_DEVICE", "auto").strip().lower()
if raw and raw != "auto":
return raw
try:
import ctranslate2
if ctranslate2.get_cuda_device_count() > 0:
return "cuda"
except Exception:
pass
return "cpu"
def resolve_compute_type(device: str) -> str:
raw = os.environ.get("LOCAL_STT_COMPUTE_TYPE", "auto").strip().lower()
if raw and raw != "auto":
return raw
if device == "cuda":
return "int8_float16"
return "int8"
class SttWorker:
def __init__(self) -> None:
from faster_whisper import WhisperModel
self.model_name = os.environ.get("LOCAL_STT_MODEL", "tiny").strip() or "tiny"
self.device = resolve_device()
self.compute_type = resolve_compute_type(self.device)
self.beam_size = int(os.environ.get("LOCAL_STT_BEAM_SIZE", "1"))
self.model = WhisperModel(
self.model_name,
device=self.device,
compute_type=self.compute_type,
)
log(
f"local-stt ready model={self.model_name} device={self.device} compute={self.compute_type} beam={self.beam_size}"
)
def transcribe(self, audio_base64: str, language: str | None) -> str:
pcm_bytes = base64.b64decode(audio_base64)
temp_path = ""
try:
with tempfile.NamedTemporaryFile(suffix=".wav", delete=False) as handle:
temp_path = handle.name
with wave.open(temp_path, "wb") as wav_file:
wav_file.setnchannels(1)
wav_file.setsampwidth(2)
wav_file.setframerate(16000)
wav_file.writeframes(pcm_bytes)
segments, _info = self.model.transcribe(
temp_path,
language=language,
beam_size=self.beam_size,
best_of=1,
condition_on_previous_text=False,
vad_filter=False,
without_timestamps=True,
temperature=0.0,
)
return " ".join(segment.text.strip() for segment in segments if segment.text.strip()).strip()
finally:
if temp_path:
try:
os.unlink(temp_path)
except OSError:
pass
def main() -> int:
try:
worker = SttWorker()
except Exception as exc:
log("failed to initialize local STT worker")
log("run `bun run setup:local-ai` first if dependencies are missing")
log("".join(traceback.format_exception(exc)))
return 1
for line in sys.stdin:
line = line.strip()
if not line:
continue
try:
request = json.loads(line)
request_id = int(request["id"])
method = request["method"]
params = request.get("params", {})
if method == "ping":
write_response(request_id, True, {"ready": True})
continue
if method != "transcribe":
raise ValueError(f"unsupported method: {method}")
text = worker.transcribe(
audio_base64=str(params.get("audio_base64", "")),
language=str(params.get("language") or "").strip() or None,
)
write_response(request_id, True, {"text": text})
except Exception as exc:
error_text = "".join(traceback.format_exception_only(type(exc), exc)).strip()
write_response(request_id, False, error=error_text)
return 0
if __name__ == "__main__":
raise SystemExit(main())

125
python/local_tts_worker.py Normal file
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@@ -0,0 +1,125 @@
import base64
import json
import os
import sys
import tempfile
import traceback
os.environ.setdefault("PYTHONIOENCODING", "utf-8")
def log(message: str) -> None:
print(message, file=sys.stderr, flush=True)
def write_response(request_id: int, ok: bool, result=None, error: str | None = None) -> None:
payload = {
"id": request_id,
"ok": ok,
}
if ok:
payload["result"] = result
else:
payload["error"] = error or "unknown error"
sys.stdout.write(json.dumps(payload, ensure_ascii=False) + "\n")
sys.stdout.flush()
class TtsWorker:
def __init__(self) -> None:
from melo.api import TTS
self.language = os.environ.get("LOCAL_TTS_LANGUAGE", "KR").strip() or "KR"
self.speaker_key = os.environ.get("LOCAL_TTS_SPEAKER", "KR").strip() or "KR"
self.device = os.environ.get("LOCAL_TTS_DEVICE", "auto").strip() or "auto"
self.speed = float(os.environ.get("LOCAL_TTS_SPEED", "1.12"))
self.model = TTS(language=self.language, device=self.device)
speaker_ids = self.model.hps.data.spk2id
self.speaker_id = speaker_ids.get(self.speaker_key)
if self.speaker_id is None:
normalized = self.speaker_key.upper()
self.speaker_id = speaker_ids.get(normalized)
if self.speaker_id is None:
self.speaker_id = next(iter(speaker_ids.values()))
log(
f"local-tts ready language={self.language} speaker={self.speaker_key} device={self.device} speed={self.speed}"
)
def synthesize(self, text: str) -> bytes:
temp_path = ""
try:
with tempfile.NamedTemporaryFile(suffix=".wav", delete=False) as handle:
temp_path = handle.name
self.model.tts_to_file(
text,
self.speaker_id,
temp_path,
speed=self.speed,
quiet=True,
)
with open(temp_path, "rb") as handle:
return handle.read()
finally:
if temp_path:
try:
os.unlink(temp_path)
except OSError:
pass
def main() -> int:
try:
worker = TtsWorker()
except Exception as exc:
log("failed to initialize local TTS worker")
log("run `bun run setup:local-ai` first if dependencies are missing")
log("".join(traceback.format_exception(exc)))
return 1
for line in sys.stdin:
line = line.strip()
if not line:
continue
try:
request = json.loads(line)
request_id = int(request["id"])
method = request["method"]
params = request.get("params", {})
if method == "ping":
write_response(request_id, True, {"ready": True})
continue
if method != "synthesize":
raise ValueError(f"unsupported method: {method}")
text = str(params.get("text", "")).strip()
if not text:
raise ValueError("text is empty")
audio = worker.synthesize(text)
write_response(
request_id,
True,
{
"wav_base64": base64.b64encode(audio).decode("ascii"),
},
)
except Exception as exc:
error_text = "".join(traceback.format_exception_only(type(exc), exc)).strip()
write_response(request_id, False, error=error_text)
return 0
if __name__ == "__main__":
raise SystemExit(main())

2
python/requirements.txt Normal file
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@@ -0,0 +1,2 @@
faster-whisper==1.2.1
git+https://github.com/myshell-ai/MeloTTS.git@v0.1.2

View File

@@ -22,9 +22,9 @@ import type { AppConfig } from "../config.js";
import { Logger } from "../logger.js";
import { float32ToPcm16Buffer, int16ArrayToFloat32, Stereo48kToMono16kDownsampler, takeFrame } from "./pcm.js";
import { ConversationMemory, type UserUtterance } from "../services/conversation.js";
import { ElevenLabsSttService } from "../services/elevenlabs-stt.js";
import { ElevenLabsTtsService, type PreparedSpeechAudio } from "../services/elevenlabs-tts.js";
import type { LlmService } from "../services/llm.js";
import type { SttService } from "../services/stt.js";
import type { PreparedSpeechAudio, TtsService } from "../services/tts.js";
interface GuildVoiceSessionOptions {
client: Client;
@@ -33,8 +33,8 @@ interface GuildVoiceSessionOptions {
guild: Guild;
voiceChannel: VoiceBasedChannel;
textChannelId?: string;
stt: ElevenLabsSttService;
tts: ElevenLabsTtsService;
stt: SttService;
tts: TtsService;
llm: LlmService;
}

View File

@@ -12,15 +12,15 @@ import { Logger } from "../logger.js";
import { requireFfmpegPath } from "./ffmpeg-path.js";
import { takeFrame, int16ArrayToFloat32, float32ToPcm16Buffer } from "./pcm.js";
import { ConversationMemory, type UserUtterance } from "../services/conversation.js";
import { ElevenLabsSttService } from "../services/elevenlabs-stt.js";
import { ElevenLabsTtsService, type PreparedSpeechAudio } from "../services/elevenlabs-tts.js";
import type { LlmService } from "../services/llm.js";
import type { SttService } from "../services/stt.js";
import type { PreparedSpeechAudio, TtsService } from "../services/tts.js";
interface LocalVoiceSessionOptions {
config: AssistantRuntimeConfig;
logger: Logger;
stt: ElevenLabsSttService;
tts: ElevenLabsTtsService;
stt: SttService;
tts: TtsService;
llm: LlmService;
}

View File

@@ -15,14 +15,21 @@ const envSchema = z.object({
DISCORD_BOT_TOKEN: emptyToUndefined,
DISCORD_APPLICATION_ID: emptyToUndefined,
DISCORD_COMMAND_GUILD_ID: emptyToUndefined,
ELEVENLABS_API_KEY: emptyToUndefined,
ELEVENLABS_VOICE_ID: emptyToUndefined,
ELEVENLABS_STT_MODEL: z.string().min(1).default("scribe_v2_realtime"),
ELEVENLABS_TTS_MODEL: z.string().min(1).default("eleven_flash_v2_5"),
OLLAMA_BASE_URL: z.string().min(1).default("http://localhost:11434"),
OLLAMA_MODEL: z.string().min(1).default("qwen3:0.6b"),
OLLAMA_KEEP_ALIVE: z.string().min(1).default("5m"),
OLLAMA_NUM_CTX: z.coerce.number().int().min(512).max(32768).default(4096),
LOCAL_AI_VENV_PATH: z.string().min(1).default(".local-ai/.venv"),
LOCAL_AI_CACHE_DIR: z.string().min(1).default(".local-ai/cache"),
LOCAL_AI_PYTHON: emptyToUndefined,
LOCAL_STT_MODEL: z.string().min(1).default("tiny"),
LOCAL_STT_DEVICE: z.string().min(1).default("auto"),
LOCAL_STT_COMPUTE_TYPE: z.string().min(1).default("auto"),
LOCAL_STT_BEAM_SIZE: z.coerce.number().int().min(1).max(8).default(1),
LOCAL_TTS_LANGUAGE: z.string().min(1).default("KR"),
LOCAL_TTS_SPEAKER: z.string().min(1).default("KR"),
LOCAL_TTS_DEVICE: z.string().min(1).default("auto"),
LOCAL_TTS_SPEED: z.coerce.number().min(0.8).max(1.6).default(1.12),
BOT_DEFAULT_LANGUAGE: z.string().min(2).default("ko"),
MAX_CONVERSATION_TURNS: z.coerce.number().int().min(4).max(30).default(12),
LOCAL_AUDIO_SOURCE: emptyToUndefined,
@@ -36,10 +43,7 @@ const envSchema = z.object({
});
export type AppConfig = z.infer<typeof envSchema>;
export type AssistantRuntimeConfig = AppConfig & {
ELEVENLABS_API_KEY: string;
ELEVENLABS_VOICE_ID: string;
};
export type AssistantRuntimeConfig = AppConfig;
export type DiscordRuntimeConfig = AssistantRuntimeConfig & {
DISCORD_BOT_TOKEN: string;
DISCORD_APPLICATION_ID: string;
@@ -57,11 +61,7 @@ function requirePresent(value: string | undefined, name: string): string {
}
export function requireAssistantRuntimeConfig(config: AppConfig): AssistantRuntimeConfig {
return {
...config,
ELEVENLABS_API_KEY: requirePresent(config.ELEVENLABS_API_KEY, "ELEVENLABS_API_KEY"),
ELEVENLABS_VOICE_ID: requirePresent(config.ELEVENLABS_VOICE_ID, "ELEVENLABS_VOICE_ID"),
};
return config;
}
export function requireDiscordRuntimeConfig(config: AppConfig): DiscordRuntimeConfig {

View File

@@ -15,8 +15,8 @@ import { Client as DiscordClient } from "discord.js";
import { GuildVoiceSession } from "./audio/guild-voice-session.js";
import { type DiscordRuntimeConfig } from "./config.js";
import { Logger } from "./logger.js";
import { ElevenLabsSttService } from "./services/elevenlabs-stt.js";
import { ElevenLabsTtsService } from "./services/elevenlabs-tts.js";
import { LocalFasterWhisperSttService } from "./services/local-stt.js";
import { LocalMeloTtsService } from "./services/local-tts.js";
import { OllamaLlmService } from "./services/ollama-llm.js";
export async function runDiscordBot(config: DiscordRuntimeConfig, logger: Logger): Promise<void> {
@@ -37,11 +37,14 @@ export async function runDiscordBot(config: DiscordRuntimeConfig, logger: Logger
intents: [GatewayIntentBits.Guilds, GatewayIntentBits.GuildVoiceStates],
});
const stt = new ElevenLabsSttService(config);
const tts = new ElevenLabsTtsService(config);
const stt = new LocalFasterWhisperSttService(config, logger);
const tts = new LocalMeloTtsService(config, logger);
const llm = new OllamaLlmService(config);
const sessions = new Map<string, GuildVoiceSession>();
await stt.warmup();
await tts.warmup();
function getVoiceChannel(interaction: ChatInputCommandInteraction): VoiceBasedChannel | null {
const member = interaction.member as GuildMember | null;
return member?.voice.channel ?? null;
@@ -174,6 +177,7 @@ export async function runDiscordBot(config: DiscordRuntimeConfig, logger: Logger
});
}
sessions.clear();
await Promise.allSettled([stt.destroy?.(), tts.destroy?.()]);
await client.destroy();
process.exit(exitCode);
}

View File

@@ -5,8 +5,8 @@ import type { AssistantRuntimeConfig } from "./config.js";
import { Logger } from "./logger.js";
import { LocalVoiceSession } from "./audio/local-voice-session.js";
import { requireFfmpegPath } from "./audio/ffmpeg-path.js";
import { ElevenLabsSttService } from "./services/elevenlabs-stt.js";
import { ElevenLabsTtsService } from "./services/elevenlabs-tts.js";
import { LocalFasterWhisperSttService } from "./services/local-stt.js";
import { LocalMeloTtsService } from "./services/local-tts.js";
import { OllamaLlmService } from "./services/ollama-llm.js";
export async function printLocalAudioDevices(): Promise<void> {
@@ -67,9 +67,13 @@ export async function printLocalAudioDevices(): Promise<void> {
}
export async function runLocalAssistant(config: AssistantRuntimeConfig, logger: Logger): Promise<void> {
const stt = new ElevenLabsSttService(config);
const tts = new ElevenLabsTtsService(config);
const stt = new LocalFasterWhisperSttService(config, logger);
const tts = new LocalMeloTtsService(config, logger);
const llm = new OllamaLlmService(config);
await stt.warmup();
await tts.warmup();
const session = new LocalVoiceSession({
config,
logger,
@@ -91,6 +95,7 @@ export async function runLocalAssistant(config: AssistantRuntimeConfig, logger:
await session.destroy().catch((error) => {
logger.warn("Local session shutdown failed", error);
});
await Promise.allSettled([stt.destroy?.(), tts.destroy?.()]);
process.exit(exitCode);
};

90
src/python-runtime.ts Normal file
View File

@@ -0,0 +1,90 @@
import { existsSync } from "node:fs";
import { spawnSync } from "node:child_process";
import path from "node:path";
import type { AppConfig } from "./config.js";
export interface PythonLaunch {
command: string;
args: string[];
source: "venv" | "configured" | "system";
}
function splitCommandSpec(spec: string): string[] {
return spec.match(/(?:[^\s"]+|"[^"]*")+/g)?.map((part) => part.replace(/^"|"$/g, "")) ?? [];
}
function canRun(command: string, args: string[]): boolean {
const result = spawnSync(command, [...args, "--version"], {
encoding: "utf8",
});
return result.status === 0;
}
export function resolveLocalAiVenvPath(config: AppConfig): string {
return path.resolve(process.cwd(), config.LOCAL_AI_VENV_PATH);
}
export function resolveLocalAiCachePath(config: AppConfig): string {
return path.resolve(process.cwd(), config.LOCAL_AI_CACHE_DIR);
}
export function resolveVenvPythonPath(config: AppConfig): string {
const venvPath = resolveLocalAiVenvPath(config);
return process.platform === "win32"
? path.join(venvPath, "Scripts", "python.exe")
: path.join(venvPath, "bin", "python");
}
export function resolvePythonLaunch(config: AppConfig, options?: { preferVenv?: boolean }): PythonLaunch {
const preferVenv = options?.preferVenv ?? true;
const venvPython = resolveVenvPythonPath(config);
if (preferVenv && existsSync(venvPython)) {
return {
command: venvPython,
args: [],
source: "venv",
};
}
const configured = config.LOCAL_AI_PYTHON ? splitCommandSpec(config.LOCAL_AI_PYTHON) : [];
if (configured.length > 0 && canRun(configured[0]!, configured.slice(1))) {
return {
command: configured[0]!,
args: configured.slice(1),
source: "configured",
};
}
const candidates =
process.platform === "win32"
? [
["py", "-3"],
["python"],
["python3"],
]
: [
["python3"],
["python"],
];
for (const [command, ...args] of candidates) {
if (canRun(command, args)) {
return {
command,
args,
source: "system",
};
}
}
throw new Error(
[
"Python 실행 파일을 찾지 못했습니다.",
"1. Python 3.11 이상을 설치",
"2. 필요하면 `.env` 에 `LOCAL_AI_PYTHON=python` 또는 `LOCAL_AI_PYTHON=py -3` 설정",
"3. 그 다음 `bun run setup:local-ai` 실행",
].join("\n"),
);
}

View File

@@ -1,124 +0,0 @@
import WebSocket from "ws";
import type { AssistantRuntimeConfig } from "../config.js";
interface ElevenLabsMessage {
message_type?: string;
text?: string;
error?: string;
}
const NON_FATAL_ERROR_TYPES = new Set([
"insufficient_audio_activity",
]);
export class ElevenLabsSttService {
constructor(private readonly config: AssistantRuntimeConfig) {}
async transcribePcm16(pcm16MonoAudio: Buffer): Promise<string | null> {
if (pcm16MonoAudio.byteLength === 0) {
return null;
}
const url = new URL("wss://api.elevenlabs.io/v1/speech-to-text/realtime");
url.searchParams.set("model_id", this.config.ELEVENLABS_STT_MODEL);
url.searchParams.set("language_code", this.config.BOT_DEFAULT_LANGUAGE);
url.searchParams.set("audio_format", "pcm_16000");
url.searchParams.set("commit_strategy", "manual");
url.searchParams.set("include_timestamps", "false");
url.searchParams.set("include_language_detection", "false");
url.searchParams.set("enable_logging", "false");
return await new Promise<string | null>((resolve, reject) => {
const socket = new WebSocket(url, {
headers: {
"xi-api-key": this.config.ELEVENLABS_API_KEY,
},
});
let settled = false;
let lastTranscript = "";
const timeout = setTimeout(() => {
finish(lastTranscript || null);
}, 15_000);
const finish = (result: string | null, error?: Error) => {
if (settled) {
return;
}
settled = true;
clearTimeout(timeout);
try {
socket.close();
} catch {
// Ignore close race.
}
if (error) {
reject(error);
return;
}
resolve(result);
};
socket.on("message", (raw) => {
let message: ElevenLabsMessage;
try {
message = JSON.parse(raw.toString()) as ElevenLabsMessage;
} catch (error) {
finish(null, error as Error);
return;
}
switch (message.message_type) {
case "session_started":
socket.send(
JSON.stringify({
message_type: "input_audio_chunk",
audio_base_64: pcm16MonoAudio.toString("base64"),
commit: true,
sample_rate: 16000,
}),
);
return;
case "partial_transcript":
return;
case "committed_transcript":
case "committed_transcript_with_timestamps": {
const transcript = message.text?.trim() ?? "";
if (transcript.length > 0) {
lastTranscript = transcript;
finish(transcript);
}
return;
}
default:
if (!message.message_type?.endsWith("error") && !message.message_type) {
return;
}
if (message.message_type && NON_FATAL_ERROR_TYPES.has(message.message_type)) {
finish(null);
return;
}
finish(
null,
new Error(message.error ?? `ElevenLabs STT error: ${message.message_type ?? "unknown"}`),
);
}
});
socket.on("error", (error) => {
finish(null, error as Error);
});
socket.on("close", () => {
if (!settled) {
finish(lastTranscript || null);
}
});
});
}
}

View File

@@ -1,78 +0,0 @@
import { Readable } from "node:stream";
import prism from "prism-media";
import type { AssistantRuntimeConfig } from "../config.js";
import { resolveFfmpegPath } from "../audio/ffmpeg-path.js";
export interface PreparedSpeechAudio {
stream: Readable;
dispose: () => void;
}
export class ElevenLabsTtsService {
constructor(private readonly config: AssistantRuntimeConfig) {
const resolvedFfmpegPath = resolveFfmpegPath();
if (resolvedFfmpegPath && !process.env.FFMPEG_PATH) {
process.env.FFMPEG_PATH = resolvedFfmpegPath;
}
}
async preparePlayback(text: string, signal?: AbortSignal): Promise<PreparedSpeechAudio> {
const url = new URL(`https://api.elevenlabs.io/v1/text-to-speech/${this.config.ELEVENLABS_VOICE_ID}/stream`);
url.searchParams.set("output_format", "mp3_44100_128");
url.searchParams.set("enable_logging", "false");
const response = await fetch(url, {
method: "POST",
headers: {
"Content-Type": "application/json",
"xi-api-key": this.config.ELEVENLABS_API_KEY,
},
body: JSON.stringify({
text,
model_id: this.config.ELEVENLABS_TTS_MODEL,
language_code: this.config.BOT_DEFAULT_LANGUAGE,
voice_settings: {
stability: 0.35,
similarity_boost: 0.75,
speed: 1.05,
},
}),
signal,
});
if (!response.ok || !response.body) {
throw new Error(`ElevenLabs TTS request failed with status ${response.status}`);
}
const input = Readable.fromWeb(response.body as never);
const ffmpeg = new prism.FFmpeg({
args: [
"-analyzeduration",
"0",
"-loglevel",
"0",
"-i",
"pipe:0",
"-f",
"s16le",
"-ar",
"48000",
"-ac",
"2",
"pipe:1",
],
});
input.pipe(ffmpeg);
return {
stream: ffmpeg,
dispose: () => {
input.destroy();
ffmpeg.destroy();
},
};
}
}

43
src/services/local-stt.ts Normal file
View File

@@ -0,0 +1,43 @@
import type { AssistantRuntimeConfig } from "../config.js";
import type { Logger } from "../logger.js";
import { PythonJsonWorker } from "./python-json-worker.js";
import type { SttService } from "./stt.js";
interface TranscribeResult {
text?: string;
}
export class LocalFasterWhisperSttService implements SttService {
private readonly worker: PythonJsonWorker;
constructor(private readonly config: AssistantRuntimeConfig, logger: Logger) {
this.worker = new PythonJsonWorker(config, logger, "local_stt_worker.py", "local-stt", {
LOCAL_STT_MODEL: config.LOCAL_STT_MODEL,
LOCAL_STT_DEVICE: config.LOCAL_STT_DEVICE,
LOCAL_STT_COMPUTE_TYPE: config.LOCAL_STT_COMPUTE_TYPE,
LOCAL_STT_BEAM_SIZE: String(config.LOCAL_STT_BEAM_SIZE),
});
}
async warmup(): Promise<void> {
await this.worker.request("ping", {});
}
async transcribePcm16(pcm16MonoAudio: Buffer): Promise<string | null> {
if (pcm16MonoAudio.byteLength === 0) {
return null;
}
const result = await this.worker.request<TranscribeResult>("transcribe", {
audio_base64: pcm16MonoAudio.toString("base64"),
language: this.config.BOT_DEFAULT_LANGUAGE,
});
const transcript = result.text?.trim() ?? "";
return transcript.length > 0 ? transcript : null;
}
async destroy(): Promise<void> {
await this.worker.destroy();
}
}

94
src/services/local-tts.ts Normal file
View File

@@ -0,0 +1,94 @@
import { Readable } from "node:stream";
import prism from "prism-media";
import type { AssistantRuntimeConfig } from "../config.js";
import type { Logger } from "../logger.js";
import { resolveFfmpegPath } from "../audio/ffmpeg-path.js";
import { PythonJsonWorker } from "./python-json-worker.js";
import type { PreparedSpeechAudio, TtsService } from "./tts.js";
interface SynthesizeResult {
wav_base64?: string;
}
export class LocalMeloTtsService implements TtsService {
private readonly worker: PythonJsonWorker;
constructor(config: AssistantRuntimeConfig, logger: Logger) {
const resolvedFfmpegPath = resolveFfmpegPath();
if (resolvedFfmpegPath && !process.env.FFMPEG_PATH) {
process.env.FFMPEG_PATH = resolvedFfmpegPath;
}
this.worker = new PythonJsonWorker(config, logger, "local_tts_worker.py", "local-tts", {
LOCAL_TTS_LANGUAGE: config.LOCAL_TTS_LANGUAGE,
LOCAL_TTS_SPEAKER: config.LOCAL_TTS_SPEAKER,
LOCAL_TTS_DEVICE: config.LOCAL_TTS_DEVICE,
LOCAL_TTS_SPEED: String(config.LOCAL_TTS_SPEED),
});
}
async warmup(): Promise<void> {
await this.worker.request("ping", {});
}
async preparePlayback(text: string, signal?: AbortSignal): Promise<PreparedSpeechAudio> {
const result = await this.worker.request<SynthesizeResult>(
"synthesize",
{
text,
},
signal,
);
const wavBase64 = result.wav_base64;
if (!wavBase64) {
throw new Error("로컬 TTS가 빈 오디오를 반환했습니다.");
}
const input = Readable.from([Buffer.from(wavBase64, "base64")]);
const ffmpeg = new prism.FFmpeg({
args: [
"-analyzeduration",
"0",
"-loglevel",
"0",
"-i",
"pipe:0",
"-f",
"s16le",
"-ar",
"48000",
"-ac",
"2",
"pipe:1",
],
});
if (signal) {
signal.addEventListener(
"abort",
() => {
input.destroy();
ffmpeg.destroy();
},
{ once: true },
);
}
input.pipe(ffmpeg);
return {
stream: ffmpeg,
dispose: () => {
input.destroy();
ffmpeg.destroy();
},
};
}
async destroy(): Promise<void> {
await this.worker.destroy();
}
}

View File

@@ -0,0 +1,189 @@
import { spawn, type ChildProcessWithoutNullStreams } from "node:child_process";
import { createInterface } from "node:readline";
import path from "node:path";
import type { AssistantRuntimeConfig } from "../config.js";
import type { Logger } from "../logger.js";
import { resolveLocalAiCachePath, resolvePythonLaunch } from "../python-runtime.js";
interface WorkerRequest {
id: number;
method: string;
params: Record<string, unknown>;
}
interface WorkerResponse {
id: number;
ok: boolean;
result?: unknown;
error?: string;
}
export class PythonJsonWorker {
private child: ChildProcessWithoutNullStreams | null = null;
private nextId = 1;
private readonly pending = new Map<
number,
{
resolve: (value: unknown) => void;
reject: (error: Error) => void;
}
>();
constructor(
private readonly config: AssistantRuntimeConfig,
private readonly logger: Logger,
private readonly scriptName: string,
private readonly label: string,
private readonly workerEnv: Record<string, string>,
) {}
async request<T>(method: string, params: Record<string, unknown>, signal?: AbortSignal): Promise<T> {
const child = this.ensureStarted();
const id = this.nextId++;
return await new Promise<T>((resolve, reject) => {
if (signal?.aborted) {
reject(new Error(`${this.label} request aborted before start`));
return;
}
const abortHandler = () => {
this.pending.delete(id);
reject(new Error(`${this.label} request aborted`));
};
if (signal) {
signal.addEventListener("abort", abortHandler, { once: true });
}
this.pending.set(id, {
resolve: (value) => {
if (signal) {
signal.removeEventListener("abort", abortHandler);
}
resolve(value as T);
},
reject: (error) => {
if (signal) {
signal.removeEventListener("abort", abortHandler);
}
reject(error);
},
});
const message: WorkerRequest = {
id,
method,
params,
};
child.stdin.write(`${JSON.stringify(message)}\n`);
});
}
async destroy(): Promise<void> {
this.rejectAll(new Error(`${this.label} worker terminated`));
if (!this.child) {
return;
}
const child = this.child;
this.child = null;
child.kill("SIGTERM");
await new Promise<void>((resolve) => {
child.once("exit", () => resolve());
setTimeout(resolve, 1_500);
});
}
private ensureStarted(): ChildProcessWithoutNullStreams {
if (this.child) {
return this.child;
}
const launch = resolvePythonLaunch(this.config);
const scriptPath = path.resolve(process.cwd(), "python", this.scriptName);
const cachePath = resolveLocalAiCachePath(this.config);
const recentStderr: string[] = [];
const child = spawn(launch.command, [...launch.args, scriptPath], {
stdio: ["pipe", "pipe", "pipe"],
env: {
...process.env,
HF_HOME: cachePath,
TRANSFORMERS_CACHE: cachePath,
PYTHONIOENCODING: "utf-8",
BOT_DEFAULT_LANGUAGE: this.config.BOT_DEFAULT_LANGUAGE,
...this.workerEnv,
},
});
createInterface({
input: child.stdout,
crlfDelay: Number.POSITIVE_INFINITY,
}).on("line", (line) => {
if (!line.trim()) {
return;
}
let payload: WorkerResponse;
try {
payload = JSON.parse(line) as WorkerResponse;
} catch (error) {
this.logger.warn(`${this.label} stdout parse failed`, error);
return;
}
const pending = this.pending.get(payload.id);
if (!pending) {
return;
}
this.pending.delete(payload.id);
if (payload.ok) {
pending.resolve(payload.result);
return;
}
pending.reject(new Error(payload.error ?? `${this.label} worker error`));
});
child.stderr.on("data", (chunk: Buffer) => {
const text = chunk.toString().trim();
if (text.length > 0) {
recentStderr.push(text);
if (recentStderr.length > 20) {
recentStderr.shift();
}
this.logger.warn(`[${this.label}]`, text);
}
});
child.on("exit", (code, signal) => {
if (this.child === child) {
this.child = null;
}
const detail = recentStderr.length > 0 ? `\n${recentStderr.join("\n")}` : "";
this.rejectAll(new Error(`${this.label} worker exited code=${code ?? "null"} signal=${signal ?? "null"}${detail}`));
});
child.on("error", (error) => {
this.rejectAll(error as Error);
});
this.child = child;
return child;
}
private rejectAll(error: Error): void {
const pending = [...this.pending.values()];
this.pending.clear();
for (const item of pending) {
item.reject(error);
}
}
}

4
src/services/stt.ts Normal file
View File

@@ -0,0 +1,4 @@
export interface SttService {
transcribePcm16(pcm16MonoAudio: Buffer): Promise<string | null>;
destroy?(): Promise<void>;
}

11
src/services/tts.ts Normal file
View File

@@ -0,0 +1,11 @@
import type { Readable } from "node:stream";
export interface PreparedSpeechAudio {
stream: Readable;
dispose: () => void;
}
export interface TtsService {
preparePlayback(text: string, signal?: AbortSignal): Promise<PreparedSpeechAudio>;
destroy?(): Promise<void>;
}

88
src/setup-local-ai.ts Normal file
View File

@@ -0,0 +1,88 @@
import { existsSync } from "node:fs";
import { mkdir } from "node:fs/promises";
import { spawn } from "node:child_process";
import path from "node:path";
import { loadConfig } from "./config.js";
import { resolveLocalAiCachePath, resolveLocalAiVenvPath, resolvePythonLaunch, resolveVenvPythonPath } from "./python-runtime.js";
async function run(command: string, args: string[], extraEnv?: NodeJS.ProcessEnv): Promise<void> {
await new Promise<void>((resolve, reject) => {
const child = spawn(command, args, {
stdio: "inherit",
env: {
...process.env,
...extraEnv,
},
});
child.on("exit", (code) => {
if (code === 0) {
resolve();
return;
}
reject(new Error(`${command} ${args.join(" ")} exited with code ${code ?? "null"}`));
});
child.on("error", reject);
});
}
async function ensurePip(pythonBin: string, env: NodeJS.ProcessEnv): Promise<void> {
await new Promise<void>((resolve, reject) => {
const child = spawn(pythonBin, ["-m", "pip", "--version"], {
stdio: "ignore",
env,
});
child.on("exit", (code) => {
if (code === 0) {
resolve();
return;
}
reject(new Error("pip missing"));
});
child.on("error", reject);
}).catch(async () => {
await run(pythonBin, ["-m", "ensurepip", "--upgrade"], env);
});
}
async function main(): Promise<void> {
const config = loadConfig();
const venvPath = resolveLocalAiVenvPath(config);
const venvPython = resolveVenvPythonPath(config);
const cachePath = resolveLocalAiCachePath(config);
const requirementsPath = path.resolve(process.cwd(), "python", "requirements.txt");
const baseEnv = {
HF_HOME: cachePath,
TRANSFORMERS_CACHE: cachePath,
PYTHONIOENCODING: "utf-8",
};
await mkdir(cachePath, { recursive: true });
if (!existsSync(venvPython)) {
const launch = resolvePythonLaunch(config, { preferVenv: false });
console.log(`기본 Python 확인: ${launch.command} ${launch.args.join(" ")}`.trim());
console.log(`가상환경 생성: ${venvPath}`);
await run(launch.command, [...launch.args, "-m", "venv", venvPath], baseEnv);
}
await ensurePip(venvPython, {
...process.env,
...baseEnv,
});
console.log("로컬 AI 의존성 설치를 시작합니다.");
await run(venvPython, ["-m", "pip", "install", "--upgrade", "pip", "setuptools", "wheel"], baseEnv);
await run(venvPython, ["-m", "pip", "install", "-r", requirementsPath], baseEnv);
console.log("설치가 끝났습니다.");
console.log("다음 순서:");
console.log("1. bun run devices");
console.log("2. bun run start:local");
}
void main().catch((error) => {
console.error(error instanceof Error ? error.message : String(error));
process.exit(1);
});