Media
检测并调整人声相对伴奏的电平，并返回可解释的响度报告。
用三种语言从你的代码中调用此工具。
# 1) Request a presigned URL → returns { uploadUrl, storageKey }
curl -X POST 'https://api.elysiatools.com/api/upload/presign/audio-vocal-instrumental-balance' \
-H 'Content-Type: application/json' \
-d '{"filename":"audioFile.ext","contentType":"application/octet-stream","size":12345}'
curl -X POST 'https://api.elysiatools.com/api/upload/presign/audio-vocal-instrumental-balance' \
-H 'Content-Type: application/json' \
-d '{"filename":"vocalFile.ext","contentType":"application/octet-stream","size":12345}'
curl -X POST 'https://api.elysiatools.com/api/upload/presign/audio-vocal-instrumental-balance' \
-H 'Content-Type: application/json' \
-d '{"filename":"instrumentalFile.ext","contentType":"application/octet-stream","size":12345}'
# 2) PUT the file bytes directly to the presigned uploadUrl
curl -X PUT '<presigned uploadUrl>' \
--data-binary @/path/to/file.ext
# 3) Call the tool, passing the returned storageKey for each file field
curl -X POST 'https://api.elysiatools.com/zh/api/tools/audio-vocal-instrumental-balance' \
-F 'audioFile=uploads/2026/01/01/your-tool-1700000000000-abc123.ext' \
-F 'vocalFile=tests/fixtures/audio-to-text-transcriber-english.flac' \
-F 'instrumentalFile=tests/fixtures/audio-to-text-transcriber-english.flac' \
-F 'sourceMode=stems' \
-F 'vocalOffsetDb=3' \
-F 'normalizeFinalLoudness=false' \
-F 'targetLufs=-16' \
-F 'outputFormat=mp3'以 JSON 形式 POST 提交输入参数。文件类型参数需先单独上传。
POST https://api.elysiatools.com/zh/api/tools/audio-vocal-instrumental-balance| 参数名 | 类型 | 必填 | 说明 |
|---|---|---|---|
| audioFile | file需先上传 | 否 | — |
| vocalFile | file需先上传 | 否 | — |
| instrumentalFile | file需先上传 | 否 | — |
| sourceMode | select | 否 | — |
| vocalOffsetDb | number | 否 | — |
| normalizeFinalLoudness | checkbox | 否 | — |
| targetLufs | number | 否 | — |
| outputFormat | select | 否 | — |
文件结果
{
"filePath": "/public/processing/randomid.ext",
"fileName": "output.ext",
"contentType": "application/octet-stream",
"size": 1024,
"metadata": {
"key": "value"
},
"error": "Error message (optional)",
"message": "Notification message (optional)"
}将此工具加入你的 Model Context Protocol 服务，让 AI 智能体可以列出并调用它。
将以下内容加入你的 MCP 客户端配置：
{
"mcpServers": {
"elysiatools-audio-vocal-instrumental-balance": {
"name": "audio-vocal-instrumental-balance",
"description": "检测并调整人声相对伴奏的电平，并返回可解释的响度报告。",
"baseUrl": "https://api.elysiatools.com/mcp/sse?toolId=audio-vocal-instrumental-balance",
"command": "",
"args": [],
"env": {},
"isActive": true,
"type": "sse"
}
}
}连接到 SSE 端点后，列出已开放的工具：
{
"jsonrpc": "2.0",
"id": 1,
"method": "tools/list"
}通过工具 id 调用，参数由其参数表构建：
{
"jsonrpc": "2.0",
"id": 2,
"method": "tools/call",
"params": {
"name": "audio-vocal-instrumental-balance",
"arguments": {
"audioFile": "https://example.com/file.ext",
"vocalFile": "tests/fixtures/audio-to-text-transcriber-english.flac",
"instrumentalFile": "tests/fixtures/audio-to-text-transcriber-english.flac",
"sourceMode": "stems",
"vocalOffsetDb": 3,
"normalizeFinalLoudness": false,
"targetLufs": -16,
"outputFormat": "mp3"
}
}
}有问题或反馈？请联系 [email protected]