[teamai] Push 87 resource(s) from XingfenD
This commit is contained in:
+324
@@ -0,0 +1,324 @@
|
||||
# TTS Providers
|
||||
|
||||
`synthesize-audio.sh` 是 provider-agnostic 的 runner —— 它自己不知道
|
||||
怎么调任何 TTS,只知道循环 `audio-segments.json`、跳过已存在文件、
|
||||
打印进度。
|
||||
|
||||
**每个 provider 是这个目录下的一个 `.sh` 文件**,定义一个
|
||||
`tts_synthesize` 函数(必需),以及可选的 `tts_check` 和
|
||||
`tts_install_help`。runner 根据 `PRESENTATION_TTS` 环境变量加载对应文件。
|
||||
|
||||
---
|
||||
|
||||
## 怎么用
|
||||
|
||||
```bash
|
||||
# 默认(minimax)
|
||||
npm run synthesize-audio
|
||||
|
||||
# 换 provider
|
||||
PRESENTATION_TTS=openai npm run synthesize-audio
|
||||
npm run synthesize-audio -- --provider=elevenlabs
|
||||
|
||||
# 指定音色(每个 provider 自己解析)
|
||||
PRESENTATION_TTS_VOICE=alloy npm run synthesize-audio
|
||||
npm run synthesize-audio -- --voice=zh-CN-YunxiNeural
|
||||
|
||||
# 强制全部重合成
|
||||
npm run synthesize-audio -- --force
|
||||
```
|
||||
|
||||
`--provider` 和 `--voice` 的命令行参数会覆盖 env var。
|
||||
|
||||
---
|
||||
|
||||
## 内置 provider
|
||||
|
||||
| 文件 | 后端 | 鉴权 | 备注 |
|
||||
|---|---|---|---|
|
||||
| `minimax.sh` | MiniMax `mmx` CLI | `mmx auth login --api-key` | **默认**;中文口播质量稳 |
|
||||
| `openai.sh` | OpenAI Audio Speech API | `OPENAI_API_KEY` env var | curl-based;多数 agent 已有 key |
|
||||
|
||||
只内置这两个 —— 我们不替你做更多技术选型。其它后端的代码片段在下面,
|
||||
复制到 `tts-providers/<name>.sh` 即可启用。
|
||||
|
||||
---
|
||||
|
||||
## 怎么加你自己的 TTS
|
||||
|
||||
1. 在这个目录建 `<name>.sh`(小写、kebab-case)
|
||||
2. 实现 `tts_synthesize text out_path [voice]`(必需)
|
||||
3. 可选实现 `tts_check`(启动前校验环境)和 `tts_install_help`(失败时打印怎么修)
|
||||
4. `PRESENTATION_TTS=<name> npm run synthesize-audio`
|
||||
|
||||
---
|
||||
|
||||
## 三函数契约
|
||||
|
||||
### `tts_synthesize <text> <out_path> [<voice>]` (required)
|
||||
|
||||
把一段文字写成 mp3 / 任意 web 可播的音频文件到 `<out_path>`。
|
||||
|
||||
| 参数 | 说明 |
|
||||
|---|---|
|
||||
| `$1` | 要合成的文本(已是 UTF-8 字符串,可能包含中英文混排和标点) |
|
||||
| `$2` | 目标文件绝对路径(runner 已 `mkdir -p` 它的父目录),扩展名 `.mp3` |
|
||||
| `$3` | 音色 id(可能为空字符串,provider 自行决定默认) |
|
||||
|
||||
成功 → exit 0 并把音频写到 `$2`。失败 → 非零退出(runner 会标 FAILED 继续下一段,不会终止全局合成)。
|
||||
|
||||
> 如果 backend 只能出 wav / ogg,自己在函数末尾用 `ffmpeg` 转一下:
|
||||
> `ffmpeg -y -i tmp.wav -codec:a libmp3lame -qscale:a 2 "$out" >/dev/null 2>&1`
|
||||
|
||||
### `tts_check` (optional)
|
||||
|
||||
启动时被 runner 调一次(不是每段)。检查 CLI 是否装、API key 是否设、auth 是否通。
|
||||
未就绪 return 非零,runner 会立刻终止并打印 `tts_install_help`。
|
||||
|
||||
### `tts_install_help` (optional)
|
||||
|
||||
`tts_check` 失败时被 runner 调,往 stderr 打印怎么装 / 怎么登录 / 在哪拿 key。
|
||||
|
||||
---
|
||||
|
||||
## 常见 TTS 后端的现成片段
|
||||
|
||||
下面**不是**内置 provider —— 是你自己写 `tts-providers/<name>.sh` 时
|
||||
可以**直接抄过去**的代码片段。复制 → 保存为 `<name>.sh` → 调通了
|
||||
就 `PRESENTATION_TTS=<name>` 用。
|
||||
|
||||
> 大多数云 TTS 的 API key 通过环境变量传入(例如 `OPENAI_API_KEY`、
|
||||
> `ELEVENLABS_API_KEY`)。把 `export` 加到你的 shell rc,或在
|
||||
> 同目录放一个 git-ignored 的 `.env` 文件并 `set -a; source .env; set +a`。
|
||||
|
||||
### OpenAI TTS
|
||||
|
||||
**已内置** —— 直接看 [`openai.sh`](./openai.sh)。
|
||||
该文件也是写 HTTP-based provider 的**官方参考实现**:jq 构造 JSON
|
||||
payload、curl `-fsS` 提交、可选 base URL(接 Azure-OpenAI / 代理)、
|
||||
可选 model env var、空音色 fallback 到默认值。新接 REST API 的
|
||||
provider 直接抄它起手最快。
|
||||
|
||||
启用:
|
||||
|
||||
```bash
|
||||
export OPENAI_API_KEY=sk-...
|
||||
PRESENTATION_TTS=openai npm run synthesize-audio
|
||||
# 用 HD 模型 + 别的音色
|
||||
OPENAI_TTS_MODEL=tts-1-hd npm run synthesize-audio -- --provider=openai --voice=nova
|
||||
```
|
||||
|
||||
### ElevenLabs — `tts-providers/elevenlabs.sh`
|
||||
|
||||
```bash
|
||||
# Docs: https://elevenlabs.io/docs/api-reference/text-to-speech
|
||||
# Env: ELEVENLABS_API_KEY=...
|
||||
# Voice: pass voice ID; "Rachel" default is 21m00Tcm4TlvDq8ikWAM
|
||||
# Model: eleven_multilingual_v2 supports Chinese; eleven_turbo_v2_5 cheaper
|
||||
|
||||
tts_check() {
|
||||
command -v curl >/dev/null || { echo "✗ curl not found" >&2; return 1; }
|
||||
command -v jq >/dev/null || { echo "✗ jq not found" >&2; return 1; }
|
||||
[[ -n "${ELEVENLABS_API_KEY:-}" ]] || { echo "✗ ELEVENLABS_API_KEY not set" >&2; return 1; }
|
||||
}
|
||||
|
||||
tts_install_help() {
|
||||
cat <<'EOF' >&2
|
||||
Set your ElevenLabs key first:
|
||||
export ELEVENLABS_API_KEY=... # get one at https://elevenlabs.io
|
||||
EOF
|
||||
}
|
||||
|
||||
tts_synthesize() {
|
||||
local text="$1" out="$2" voice="${3:-21m00Tcm4TlvDq8ikWAM}"
|
||||
local payload
|
||||
payload=$(jq -n --arg t "$text" \
|
||||
'{text:$t, model_id:"eleven_multilingual_v2"}')
|
||||
|
||||
curl -fsS -o "$out" -X POST \
|
||||
"https://api.elevenlabs.io/v1/text-to-speech/$voice" \
|
||||
-H "xi-api-key: $ELEVENLABS_API_KEY" \
|
||||
-H "Content-Type: application/json" \
|
||||
-d "$payload"
|
||||
}
|
||||
```
|
||||
|
||||
### edge-tts — `tts-providers/edge-tts.sh`(免费 / 无 API key)
|
||||
|
||||
```bash
|
||||
# Docs: https://github.com/rany2/edge-tts
|
||||
# Install: pip install edge-tts
|
||||
# Voices: edge-tts --list-voices
|
||||
# zh-CN-YunxiNeural (男声)
|
||||
# zh-CN-XiaoxiaoNeural (女声)
|
||||
# en-US-AriaNeural (英文女声)
|
||||
# en-US-GuyNeural (英文男声)
|
||||
|
||||
tts_check() {
|
||||
command -v edge-tts >/dev/null || { echo "✗ edge-tts not found" >&2; return 1; }
|
||||
}
|
||||
|
||||
tts_install_help() {
|
||||
cat <<'EOF' >&2
|
||||
Install edge-tts (free, uses Microsoft Edge's TTS backend, no API key):
|
||||
pip install edge-tts
|
||||
List available voices:
|
||||
edge-tts --list-voices | less
|
||||
EOF
|
||||
}
|
||||
|
||||
tts_synthesize() {
|
||||
local text="$1" out="$2" voice="${3:-zh-CN-YunxiNeural}"
|
||||
edge-tts --text "$text" --voice "$voice" --write-media "$out" >/dev/null 2>&1
|
||||
}
|
||||
```
|
||||
|
||||
### macOS `say` — `tts-providers/say.sh`(离线 / 兜底)
|
||||
|
||||
```bash
|
||||
# 系统自带,零依赖,适合 CI 跑通流程 / 离线预览。
|
||||
# 中文音色:Tingting / Sinji / Meijia(看 `say -v ?` 全列表)
|
||||
# 输出是 aiff,要 ffmpeg 转 mp3(Auto 模式 audio 标签默认认 mp3)。
|
||||
|
||||
tts_check() {
|
||||
command -v say >/dev/null || { echo "✗ 'say' not available (macOS only)" >&2; return 1; }
|
||||
command -v ffmpeg >/dev/null || { echo "✗ ffmpeg not found (brew install ffmpeg)" >&2; return 1; }
|
||||
}
|
||||
|
||||
tts_install_help() {
|
||||
cat <<'EOF' >&2
|
||||
macOS-only provider. Needs ffmpeg for aiff→mp3:
|
||||
brew install ffmpeg
|
||||
List voices: say -v ?
|
||||
EOF
|
||||
}
|
||||
|
||||
tts_synthesize() {
|
||||
local text="$1" out="$2" voice="${3:-Tingting}"
|
||||
local tmp
|
||||
tmp=$(mktemp -t tts).aiff
|
||||
say -v "$voice" -o "$tmp" "$text" \
|
||||
&& ffmpeg -y -i "$tmp" -codec:a libmp3lame -qscale:a 2 "$out" >/dev/null 2>&1
|
||||
local code=$?
|
||||
rm -f "$tmp"
|
||||
return $code
|
||||
}
|
||||
```
|
||||
|
||||
### Azure Speech — `tts-providers/azure.sh`
|
||||
|
||||
```bash
|
||||
# Docs: https://learn.microsoft.com/azure/ai-services/speech-service/rest-text-to-speech
|
||||
# Env: AZURE_SPEECH_KEY=... AZURE_SPEECH_REGION=eastus
|
||||
# SSML payload — Azure requires SSML, not plain JSON
|
||||
|
||||
tts_check() {
|
||||
command -v curl >/dev/null || { echo "✗ curl not found" >&2; return 1; }
|
||||
[[ -n "${AZURE_SPEECH_KEY:-}" ]] || { echo "✗ AZURE_SPEECH_KEY not set" >&2; return 1; }
|
||||
[[ -n "${AZURE_SPEECH_REGION:-}" ]] || { echo "✗ AZURE_SPEECH_REGION not set" >&2; return 1; }
|
||||
}
|
||||
|
||||
tts_install_help() {
|
||||
cat <<'EOF' >&2
|
||||
Set Azure Speech credentials:
|
||||
export AZURE_SPEECH_KEY=...
|
||||
export AZURE_SPEECH_REGION=eastus # or your resource's region
|
||||
EOF
|
||||
}
|
||||
|
||||
tts_synthesize() {
|
||||
local text="$1" out="$2" voice="${3:-zh-CN-YunxiNeural}"
|
||||
local lang="${voice%%-*}-${voice#*-}"; lang="${lang%%-*}-${lang#*-}" # "zh-CN"
|
||||
local ssml="<speak version='1.0' xml:lang='$lang'><voice xml:lang='$lang' name='$voice'>$(printf '%s' "$text" | sed 's/&/\&/g; s/</\</g; s/>/\>/g')</voice></speak>"
|
||||
|
||||
curl -fsS -o "$out" -X POST \
|
||||
"https://${AZURE_SPEECH_REGION}.tts.speech.microsoft.com/cognitiveservices/v1" \
|
||||
-H "Ocp-Apim-Subscription-Key: $AZURE_SPEECH_KEY" \
|
||||
-H "Content-Type: application/ssml+xml" \
|
||||
-H "X-Microsoft-OutputFormat: audio-24khz-48kbitrate-mono-mp3" \
|
||||
-H "User-Agent: web-video-presentation" \
|
||||
--data-binary "$ssml"
|
||||
}
|
||||
```
|
||||
|
||||
### Google Cloud TTS — `tts-providers/gcloud.sh`
|
||||
|
||||
```bash
|
||||
# Docs: https://cloud.google.com/text-to-speech/docs/reference/rest
|
||||
# Auth: easiest is `gcloud auth application-default login`
|
||||
# (or set GOOGLE_APPLICATION_CREDENTIALS to a service-account json)
|
||||
# Voices: zh-CN-Wavenet-A / zh-CN-Neural2-A / en-US-Neural2-J etc.
|
||||
|
||||
tts_check() {
|
||||
command -v curl >/dev/null || { echo "✗ curl not found" >&2; return 1; }
|
||||
command -v jq >/dev/null || { echo "✗ jq not found" >&2; return 1; }
|
||||
command -v base64 >/dev/null || { echo "✗ base64 not found" >&2; return 1; }
|
||||
command -v gcloud >/dev/null || { echo "✗ gcloud not found" >&2; return 1; }
|
||||
gcloud auth application-default print-access-token >/dev/null 2>&1 || {
|
||||
echo "✗ gcloud is not authenticated (run: gcloud auth application-default login)" >&2
|
||||
return 1
|
||||
}
|
||||
}
|
||||
|
||||
tts_install_help() {
|
||||
cat <<'EOF' >&2
|
||||
Install gcloud SDK and authenticate:
|
||||
https://cloud.google.com/sdk/docs/install
|
||||
gcloud auth application-default login
|
||||
gcloud services enable texttospeech.googleapis.com
|
||||
EOF
|
||||
}
|
||||
|
||||
tts_synthesize() {
|
||||
local text="$1" out="$2" voice="${3:-zh-CN-Wavenet-A}"
|
||||
local lang="${voice%-*}"; lang="${lang%-*}" # "zh-CN"
|
||||
local token
|
||||
token=$(gcloud auth application-default print-access-token)
|
||||
|
||||
local payload
|
||||
payload=$(jq -n --arg t "$text" --arg v "$voice" --arg l "$lang" \
|
||||
'{input:{text:$t}, voice:{languageCode:$l, name:$v}, audioConfig:{audioEncoding:"MP3"}}')
|
||||
|
||||
curl -fsS -X POST https://texttospeech.googleapis.com/v1/text:synthesize \
|
||||
-H "Authorization: Bearer $token" \
|
||||
-H "Content-Type: application/json" \
|
||||
-d "$payload" \
|
||||
| jq -r '.audioContent' | base64 -d > "$out"
|
||||
}
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## 设计要点(自己写 provider 时记住)
|
||||
|
||||
1. **`set -e` 友好**:runner 用 `set -euo pipefail`,所以你的函数里要么明确处理失败,要么让命令自然非零退出。不要吞错误。
|
||||
|
||||
2. **静默成功,喧闹失败**:成功时不打印任何东西到 stdout(runner 自己打进度条);失败时往 stderr 打详细原因。把 CLI 工具的 stdout 重定向到 `/dev/null`,stderr 留着看。
|
||||
|
||||
3. **mp3 输出**:浏览器里 `<audio>` 标签最稳吃 mp3。能直接出 mp3 就出 mp3;非 mp3 后端在函数末尾加一步 ffmpeg。
|
||||
|
||||
4. **音色 fallback**:`$3` 可能是空字符串。给一个合理的默认值(你最常用的中文音色 / 英文音色),不要因为没传音色就报错。
|
||||
|
||||
5. **不要做并发**:runner 是串行的(避免 rate limit)。provider 函数也别在内部 fork 多线程。
|
||||
|
||||
6. **不要修改全局状态**:provider 文件被 `source` 进 runner 的 shell。别 `cd`、别改 `IFS`、别 `set -e/+e` 切换,否则会污染 runner。把局部变量都 `local`。
|
||||
|
||||
⚠️ 一个坑:runner 用 `set -u`,**macOS 默认 bash 3.2 在 `"${arr[@]}"` 展开空数组时会炸 `unbound variable`**。如果你的 provider 需要"可选 --voice 参数",**不要**用 `local args=(); [[ -n $voice ]] && args=(--voice $v); cmd "${args[@]}"` —— 直接写两个 if 分支调命令(看 `minimax.sh` 的写法)。
|
||||
|
||||
7. **API 长度上限**:单段大多数 API 都有上限(OpenAI ~4096 chars / MiniMax ~5000 / ElevenLabs ~5000)。Skill 的 narrations 单段一般 < 200 字符,正常不会撞到。如果你的 narration 撞到了,**先回去拆 step**——一个 step 的口播本来就不该这么长。
|
||||
|
||||
---
|
||||
|
||||
## 调试
|
||||
|
||||
```bash
|
||||
# 看 runner 怎么调你的 provider
|
||||
bash -x scripts/synthesize-audio.sh
|
||||
|
||||
# 跑单段试试,不动 audio-segments.json
|
||||
source scripts/tts-providers/<name>.sh
|
||||
tts_check && tts_synthesize "测试一下" /tmp/test.mp3 ""
|
||||
afplay /tmp/test.mp3 # macOS 播一下听听
|
||||
```
|
||||
|
||||
跑通了再 `npm run synthesize-audio`。
|
||||
Reference in New Issue
Block a user