Compare commits
14 Commits
| Author | SHA1 | Date | |
|---|---|---|---|
| a07f069ad0 | |||
| da15d299e6 | |||
| 7ef7c3f676 | |||
| 4143d00de7 | |||
| 0360f2493d | |||
| 0172887877 | |||
| 8f89f5e3cf | |||
| 5bd41f8c6a | |||
| e4399e1b7b | |||
| ad1ee48763 | |||
| 3ed206923f | |||
| 22d5427e86 | |||
| 43b53164c0 | |||
| 575fbac099 |
@@ -75,6 +75,7 @@ A TypeScript library that provides a unified interface for working with multiple
|
||||
|
||||
#### Instructions
|
||||
1. Install the package: `npm i @ztimson/ai-utils`
|
||||
2. For speaker diarization: `pip install pyannote.audio`
|
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|
||||
</details>
|
||||
|
||||
@@ -90,8 +91,9 @@ A TypeScript library that provides a unified interface for working with multiple
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|
||||
#### Instructions
|
||||
1. Install the dependencies: `npm i`
|
||||
2. Build library: `npm build`
|
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3. Run unit tests: `npm test`
|
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2. For speaker diarization: `pip install pyannote.audio`
|
||||
3. Build library: `npm build`
|
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4. Run unit tests: `npm test`
|
||||
|
||||
</details>
|
||||
|
||||
|
||||
337
package-lock.json
generated
337
package-lock.json
generated
@@ -1,12 +1,12 @@
|
||||
{
|
||||
"name": "@ztimson/ai-utils",
|
||||
"version": "0.4.0",
|
||||
"version": "0.6.4",
|
||||
"lockfileVersion": 3,
|
||||
"requires": true,
|
||||
"packages": {
|
||||
"": {
|
||||
"name": "@ztimson/ai-utils",
|
||||
"version": "0.4.0",
|
||||
"version": "0.6.4",
|
||||
"license": "MIT",
|
||||
"dependencies": {
|
||||
"@anthropic-ai/sdk": "^0.67.0",
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||||
@@ -16,7 +16,8 @@
|
||||
"@ztimson/utils": "^0.27.9",
|
||||
"cheerio": "^1.2.0",
|
||||
"openai": "^6.6.0",
|
||||
"tesseract.js": "^6.0.1"
|
||||
"tesseract.js": "^6.0.1",
|
||||
"wavefile": "^11.0.0"
|
||||
},
|
||||
"devDependencies": {
|
||||
"@types/node": "^24.8.1",
|
||||
@@ -106,9 +107,9 @@
|
||||
}
|
||||
},
|
||||
"node_modules/@esbuild/aix-ppc64": {
|
||||
"version": "0.27.2",
|
||||
"resolved": "https://registry.npmjs.org/@esbuild/aix-ppc64/-/aix-ppc64-0.27.2.tgz",
|
||||
"integrity": "sha512-GZMB+a0mOMZs4MpDbj8RJp4cw+w1WV5NYD6xzgvzUJ5Ek2jerwfO2eADyI6ExDSUED+1X8aMbegahsJi+8mgpw==",
|
||||
"version": "0.27.3",
|
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"resolved": "https://registry.npmjs.org/@esbuild/aix-ppc64/-/aix-ppc64-0.27.3.tgz",
|
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"integrity": "sha512-9fJMTNFTWZMh5qwrBItuziu834eOCUcEqymSH7pY+zoMVEZg3gcPuBNxH1EvfVYe9h0x/Ptw8KBzv7qxb7l8dg==",
|
||||
"cpu": [
|
||||
"ppc64"
|
||||
],
|
||||
@@ -123,9 +124,9 @@
|
||||
}
|
||||
},
|
||||
"node_modules/@esbuild/android-arm": {
|
||||
"version": "0.27.2",
|
||||
"resolved": "https://registry.npmjs.org/@esbuild/android-arm/-/android-arm-0.27.2.tgz",
|
||||
"integrity": "sha512-DVNI8jlPa7Ujbr1yjU2PfUSRtAUZPG9I1RwW4F4xFB1Imiu2on0ADiI/c3td+KmDtVKNbi+nffGDQMfcIMkwIA==",
|
||||
"version": "0.27.3",
|
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"resolved": "https://registry.npmjs.org/@esbuild/android-arm/-/android-arm-0.27.3.tgz",
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"integrity": "sha512-i5D1hPY7GIQmXlXhs2w8AWHhenb00+GxjxRncS2ZM7YNVGNfaMxgzSGuO8o8SJzRc/oZwU2bcScvVERk03QhzA==",
|
||||
"cpu": [
|
||||
"arm"
|
||||
],
|
||||
@@ -140,9 +141,9 @@
|
||||
}
|
||||
},
|
||||
"node_modules/@esbuild/android-arm64": {
|
||||
"version": "0.27.2",
|
||||
"resolved": "https://registry.npmjs.org/@esbuild/android-arm64/-/android-arm64-0.27.2.tgz",
|
||||
"integrity": "sha512-pvz8ZZ7ot/RBphf8fv60ljmaoydPU12VuXHImtAs0XhLLw+EXBi2BLe3OYSBslR4rryHvweW5gmkKFwTiFy6KA==",
|
||||
"version": "0.27.3",
|
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"resolved": "https://registry.npmjs.org/@esbuild/android-arm64/-/android-arm64-0.27.3.tgz",
|
||||
"integrity": "sha512-YdghPYUmj/FX2SYKJ0OZxf+iaKgMsKHVPF1MAq/P8WirnSpCStzKJFjOjzsW0QQ7oIAiccHdcqjbHmJxRb/dmg==",
|
||||
"cpu": [
|
||||
"arm64"
|
||||
],
|
||||
@@ -157,9 +158,9 @@
|
||||
}
|
||||
},
|
||||
"node_modules/@esbuild/android-x64": {
|
||||
"version": "0.27.2",
|
||||
"resolved": "https://registry.npmjs.org/@esbuild/android-x64/-/android-x64-0.27.2.tgz",
|
||||
"integrity": "sha512-z8Ank4Byh4TJJOh4wpz8g2vDy75zFL0TlZlkUkEwYXuPSgX8yzep596n6mT7905kA9uHZsf/o2OJZubl2l3M7A==",
|
||||
"version": "0.27.3",
|
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"resolved": "https://registry.npmjs.org/@esbuild/android-x64/-/android-x64-0.27.3.tgz",
|
||||
"integrity": "sha512-IN/0BNTkHtk8lkOM8JWAYFg4ORxBkZQf9zXiEOfERX/CzxW3Vg1ewAhU7QSWQpVIzTW+b8Xy+lGzdYXV6UZObQ==",
|
||||
"cpu": [
|
||||
"x64"
|
||||
],
|
||||
@@ -174,9 +175,9 @@
|
||||
}
|
||||
},
|
||||
"node_modules/@esbuild/darwin-arm64": {
|
||||
"version": "0.27.2",
|
||||
"resolved": "https://registry.npmjs.org/@esbuild/darwin-arm64/-/darwin-arm64-0.27.2.tgz",
|
||||
"integrity": "sha512-davCD2Zc80nzDVRwXTcQP/28fiJbcOwvdolL0sOiOsbwBa72kegmVU0Wrh1MYrbuCL98Omp5dVhQFWRKR2ZAlg==",
|
||||
"version": "0.27.3",
|
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"resolved": "https://registry.npmjs.org/@esbuild/darwin-arm64/-/darwin-arm64-0.27.3.tgz",
|
||||
"integrity": "sha512-Re491k7ByTVRy0t3EKWajdLIr0gz2kKKfzafkth4Q8A5n1xTHrkqZgLLjFEHVD+AXdUGgQMq+Godfq45mGpCKg==",
|
||||
"cpu": [
|
||||
"arm64"
|
||||
],
|
||||
@@ -191,9 +192,9 @@
|
||||
}
|
||||
},
|
||||
"node_modules/@esbuild/darwin-x64": {
|
||||
"version": "0.27.2",
|
||||
"resolved": "https://registry.npmjs.org/@esbuild/darwin-x64/-/darwin-x64-0.27.2.tgz",
|
||||
"integrity": "sha512-ZxtijOmlQCBWGwbVmwOF/UCzuGIbUkqB1faQRf5akQmxRJ1ujusWsb3CVfk/9iZKr2L5SMU5wPBi1UWbvL+VQA==",
|
||||
"version": "0.27.3",
|
||||
"resolved": "https://registry.npmjs.org/@esbuild/darwin-x64/-/darwin-x64-0.27.3.tgz",
|
||||
"integrity": "sha512-vHk/hA7/1AckjGzRqi6wbo+jaShzRowYip6rt6q7VYEDX4LEy1pZfDpdxCBnGtl+A5zq8iXDcyuxwtv3hNtHFg==",
|
||||
"cpu": [
|
||||
"x64"
|
||||
],
|
||||
@@ -208,9 +209,9 @@
|
||||
}
|
||||
},
|
||||
"node_modules/@esbuild/freebsd-arm64": {
|
||||
"version": "0.27.2",
|
||||
"resolved": "https://registry.npmjs.org/@esbuild/freebsd-arm64/-/freebsd-arm64-0.27.2.tgz",
|
||||
"integrity": "sha512-lS/9CN+rgqQ9czogxlMcBMGd+l8Q3Nj1MFQwBZJyoEKI50XGxwuzznYdwcav6lpOGv5BqaZXqvBSiB/kJ5op+g==",
|
||||
"version": "0.27.3",
|
||||
"resolved": "https://registry.npmjs.org/@esbuild/freebsd-arm64/-/freebsd-arm64-0.27.3.tgz",
|
||||
"integrity": "sha512-ipTYM2fjt3kQAYOvo6vcxJx3nBYAzPjgTCk7QEgZG8AUO3ydUhvelmhrbOheMnGOlaSFUoHXB6un+A7q4ygY9w==",
|
||||
"cpu": [
|
||||
"arm64"
|
||||
],
|
||||
@@ -225,9 +226,9 @@
|
||||
}
|
||||
},
|
||||
"node_modules/@esbuild/freebsd-x64": {
|
||||
"version": "0.27.2",
|
||||
"resolved": "https://registry.npmjs.org/@esbuild/freebsd-x64/-/freebsd-x64-0.27.2.tgz",
|
||||
"integrity": "sha512-tAfqtNYb4YgPnJlEFu4c212HYjQWSO/w/h/lQaBK7RbwGIkBOuNKQI9tqWzx7Wtp7bTPaGC6MJvWI608P3wXYA==",
|
||||
"version": "0.27.3",
|
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"resolved": "https://registry.npmjs.org/@esbuild/freebsd-x64/-/freebsd-x64-0.27.3.tgz",
|
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"integrity": "sha512-dDk0X87T7mI6U3K9VjWtHOXqwAMJBNN2r7bejDsc+j03SEjtD9HrOl8gVFByeM0aJksoUuUVU9TBaZa2rgj0oA==",
|
||||
"cpu": [
|
||||
"x64"
|
||||
],
|
||||
@@ -242,9 +243,9 @@
|
||||
}
|
||||
},
|
||||
"node_modules/@esbuild/linux-arm": {
|
||||
"version": "0.27.2",
|
||||
"resolved": "https://registry.npmjs.org/@esbuild/linux-arm/-/linux-arm-0.27.2.tgz",
|
||||
"integrity": "sha512-vWfq4GaIMP9AIe4yj1ZUW18RDhx6EPQKjwe7n8BbIecFtCQG4CfHGaHuh7fdfq+y3LIA2vGS/o9ZBGVxIDi9hw==",
|
||||
"version": "0.27.3",
|
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"resolved": "https://registry.npmjs.org/@esbuild/linux-arm/-/linux-arm-0.27.3.tgz",
|
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"integrity": "sha512-s6nPv2QkSupJwLYyfS+gwdirm0ukyTFNl3KTgZEAiJDd+iHZcbTPPcWCcRYH+WlNbwChgH2QkE9NSlNrMT8Gfw==",
|
||||
"cpu": [
|
||||
"arm"
|
||||
],
|
||||
@@ -259,9 +260,9 @@
|
||||
}
|
||||
},
|
||||
"node_modules/@esbuild/linux-arm64": {
|
||||
"version": "0.27.2",
|
||||
"resolved": "https://registry.npmjs.org/@esbuild/linux-arm64/-/linux-arm64-0.27.2.tgz",
|
||||
"integrity": "sha512-hYxN8pr66NsCCiRFkHUAsxylNOcAQaxSSkHMMjcpx0si13t1LHFphxJZUiGwojB1a/Hd5OiPIqDdXONia6bhTw==",
|
||||
"version": "0.27.3",
|
||||
"resolved": "https://registry.npmjs.org/@esbuild/linux-arm64/-/linux-arm64-0.27.3.tgz",
|
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"integrity": "sha512-sZOuFz/xWnZ4KH3YfFrKCf1WyPZHakVzTiqji3WDc0BCl2kBwiJLCXpzLzUBLgmp4veFZdvN5ChW4Eq/8Fc2Fg==",
|
||||
"cpu": [
|
||||
"arm64"
|
||||
],
|
||||
@@ -276,9 +277,9 @@
|
||||
}
|
||||
},
|
||||
"node_modules/@esbuild/linux-ia32": {
|
||||
"version": "0.27.2",
|
||||
"resolved": "https://registry.npmjs.org/@esbuild/linux-ia32/-/linux-ia32-0.27.2.tgz",
|
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"integrity": "sha512-MJt5BRRSScPDwG2hLelYhAAKh9imjHK5+NE/tvnRLbIqUWa+0E9N4WNMjmp/kXXPHZGqPLxggwVhz7QP8CTR8w==",
|
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"version": "0.27.3",
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"resolved": "https://registry.npmjs.org/@esbuild/linux-ia32/-/linux-ia32-0.27.3.tgz",
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"integrity": "sha512-yGlQYjdxtLdh0a3jHjuwOrxQjOZYD/C9PfdbgJJF3TIZWnm/tMd/RcNiLngiu4iwcBAOezdnSLAwQDPqTmtTYg==",
|
||||
"cpu": [
|
||||
"ia32"
|
||||
],
|
||||
@@ -293,9 +294,9 @@
|
||||
}
|
||||
},
|
||||
"node_modules/@esbuild/linux-loong64": {
|
||||
"version": "0.27.2",
|
||||
"resolved": "https://registry.npmjs.org/@esbuild/linux-loong64/-/linux-loong64-0.27.2.tgz",
|
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"integrity": "sha512-lugyF1atnAT463aO6KPshVCJK5NgRnU4yb3FUumyVz+cGvZbontBgzeGFO1nF+dPueHD367a2ZXe1NtUkAjOtg==",
|
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"version": "0.27.3",
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"resolved": "https://registry.npmjs.org/@esbuild/linux-loong64/-/linux-loong64-0.27.3.tgz",
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"integrity": "sha512-WO60Sn8ly3gtzhyjATDgieJNet/KqsDlX5nRC5Y3oTFcS1l0KWba+SEa9Ja1GfDqSF1z6hif/SkpQJbL63cgOA==",
|
||||
"cpu": [
|
||||
"loong64"
|
||||
],
|
||||
@@ -310,9 +311,9 @@
|
||||
}
|
||||
},
|
||||
"node_modules/@esbuild/linux-mips64el": {
|
||||
"version": "0.27.2",
|
||||
"resolved": "https://registry.npmjs.org/@esbuild/linux-mips64el/-/linux-mips64el-0.27.2.tgz",
|
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"integrity": "sha512-nlP2I6ArEBewvJ2gjrrkESEZkB5mIoaTswuqNFRv/WYd+ATtUpe9Y09RnJvgvdag7he0OWgEZWhviS1OTOKixw==",
|
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"version": "0.27.3",
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"resolved": "https://registry.npmjs.org/@esbuild/linux-mips64el/-/linux-mips64el-0.27.3.tgz",
|
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"integrity": "sha512-APsymYA6sGcZ4pD6k+UxbDjOFSvPWyZhjaiPyl/f79xKxwTnrn5QUnXR5prvetuaSMsb4jgeHewIDCIWljrSxw==",
|
||||
"cpu": [
|
||||
"mips64el"
|
||||
],
|
||||
@@ -327,9 +328,9 @@
|
||||
}
|
||||
},
|
||||
"node_modules/@esbuild/linux-ppc64": {
|
||||
"version": "0.27.2",
|
||||
"resolved": "https://registry.npmjs.org/@esbuild/linux-ppc64/-/linux-ppc64-0.27.2.tgz",
|
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"integrity": "sha512-C92gnpey7tUQONqg1n6dKVbx3vphKtTHJaNG2Ok9lGwbZil6DrfyecMsp9CrmXGQJmZ7iiVXvvZH6Ml5hL6XdQ==",
|
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"version": "0.27.3",
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"resolved": "https://registry.npmjs.org/@esbuild/linux-ppc64/-/linux-ppc64-0.27.3.tgz",
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|
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"cpu": [
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"ppc64"
|
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],
|
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@@ -344,9 +345,9 @@
|
||||
}
|
||||
},
|
||||
"node_modules/@esbuild/linux-riscv64": {
|
||||
"version": "0.27.2",
|
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"resolved": "https://registry.npmjs.org/@esbuild/linux-riscv64/-/linux-riscv64-0.27.2.tgz",
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"integrity": "sha512-B5BOmojNtUyN8AXlK0QJyvjEZkWwy/FKvakkTDCziX95AowLZKR6aCDhG7LeF7uMCXEJqwa8Bejz5LTPYm8AvA==",
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"version": "0.27.3",
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"resolved": "https://registry.npmjs.org/@esbuild/linux-riscv64/-/linux-riscv64-0.27.3.tgz",
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"cpu": [
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"riscv64"
|
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],
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@@ -361,9 +362,9 @@
|
||||
}
|
||||
},
|
||||
"node_modules/@esbuild/linux-s390x": {
|
||||
"version": "0.27.2",
|
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"resolved": "https://registry.npmjs.org/@esbuild/linux-s390x/-/linux-s390x-0.27.2.tgz",
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"integrity": "sha512-p4bm9+wsPwup5Z8f4EpfN63qNagQ47Ua2znaqGH6bqLlmJ4bx97Y9JdqxgGZ6Y8xVTixUnEkoKSHcpRlDnNr5w==",
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"version": "0.27.3",
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"resolved": "https://registry.npmjs.org/@esbuild/linux-s390x/-/linux-s390x-0.27.3.tgz",
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"cpu": [
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"s390x"
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@@ -378,9 +379,9 @@
|
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|
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},
|
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"node_modules/@esbuild/linux-x64": {
|
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"version": "0.27.2",
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"resolved": "https://registry.npmjs.org/@esbuild/linux-x64/-/linux-x64-0.27.2.tgz",
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"version": "0.27.3",
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"cpu": [
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"x64"
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],
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@@ -395,9 +396,9 @@
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}
|
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},
|
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"node_modules/@esbuild/netbsd-arm64": {
|
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"version": "0.27.2",
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"resolved": "https://registry.npmjs.org/@esbuild/netbsd-arm64/-/netbsd-arm64-0.27.2.tgz",
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"version": "0.27.3",
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"resolved": "https://registry.npmjs.org/@esbuild/netbsd-arm64/-/netbsd-arm64-0.27.3.tgz",
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"cpu": [
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@@ -412,9 +413,9 @@
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"node_modules/@esbuild/netbsd-x64": {
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"version": "0.27.2",
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@@ -429,9 +430,9 @@
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@@ -446,9 +447,9 @@
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@@ -463,9 +464,9 @@
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@@ -480,9 +481,9 @@
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@@ -497,9 +498,9 @@
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@@ -514,9 +515,9 @@
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@@ -531,9 +532,9 @@
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@@ -567,9 +568,9 @@
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@@ -587,9 +588,9 @@
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@@ -599,10 +600,10 @@
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@@ -625,13 +626,13 @@
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@@ -1261,9 +1262,9 @@
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@@ -1503,9 +1504,9 @@
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@@ -1577,15 +1578,15 @@
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@@ -1604,14 +1605,14 @@
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@@ -1651,9 +1652,9 @@
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@@ -1837,9 +1838,9 @@
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@@ -2183,9 +2184,9 @@
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@@ -2491,9 +2492,9 @@
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@@ -2504,32 +2505,32 @@
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"@esbuild/android-x64": "0.27.2",
|
||||
"@esbuild/darwin-arm64": "0.27.2",
|
||||
"@esbuild/darwin-x64": "0.27.2",
|
||||
"@esbuild/freebsd-arm64": "0.27.2",
|
||||
"@esbuild/freebsd-x64": "0.27.2",
|
||||
"@esbuild/linux-arm": "0.27.2",
|
||||
"@esbuild/linux-arm64": "0.27.2",
|
||||
"@esbuild/linux-ia32": "0.27.2",
|
||||
"@esbuild/linux-loong64": "0.27.2",
|
||||
"@esbuild/linux-mips64el": "0.27.2",
|
||||
"@esbuild/linux-ppc64": "0.27.2",
|
||||
"@esbuild/linux-riscv64": "0.27.2",
|
||||
"@esbuild/linux-s390x": "0.27.2",
|
||||
"@esbuild/linux-x64": "0.27.2",
|
||||
"@esbuild/netbsd-arm64": "0.27.2",
|
||||
"@esbuild/netbsd-x64": "0.27.2",
|
||||
"@esbuild/openbsd-arm64": "0.27.2",
|
||||
"@esbuild/openbsd-x64": "0.27.2",
|
||||
"@esbuild/openharmony-arm64": "0.27.2",
|
||||
"@esbuild/sunos-x64": "0.27.2",
|
||||
"@esbuild/win32-arm64": "0.27.2",
|
||||
"@esbuild/win32-ia32": "0.27.2",
|
||||
"@esbuild/win32-x64": "0.27.2"
|
||||
"@esbuild/aix-ppc64": "0.27.3",
|
||||
"@esbuild/android-arm": "0.27.3",
|
||||
"@esbuild/android-arm64": "0.27.3",
|
||||
"@esbuild/android-x64": "0.27.3",
|
||||
"@esbuild/darwin-arm64": "0.27.3",
|
||||
"@esbuild/darwin-x64": "0.27.3",
|
||||
"@esbuild/freebsd-arm64": "0.27.3",
|
||||
"@esbuild/freebsd-x64": "0.27.3",
|
||||
"@esbuild/linux-arm": "0.27.3",
|
||||
"@esbuild/linux-arm64": "0.27.3",
|
||||
"@esbuild/linux-ia32": "0.27.3",
|
||||
"@esbuild/linux-loong64": "0.27.3",
|
||||
"@esbuild/linux-mips64el": "0.27.3",
|
||||
"@esbuild/linux-ppc64": "0.27.3",
|
||||
"@esbuild/linux-riscv64": "0.27.3",
|
||||
"@esbuild/linux-s390x": "0.27.3",
|
||||
"@esbuild/linux-x64": "0.27.3",
|
||||
"@esbuild/netbsd-arm64": "0.27.3",
|
||||
"@esbuild/netbsd-x64": "0.27.3",
|
||||
"@esbuild/openbsd-arm64": "0.27.3",
|
||||
"@esbuild/openbsd-x64": "0.27.3",
|
||||
"@esbuild/openharmony-arm64": "0.27.3",
|
||||
"@esbuild/sunos-x64": "0.27.3",
|
||||
"@esbuild/win32-arm64": "0.27.3",
|
||||
"@esbuild/win32-ia32": "0.27.3",
|
||||
"@esbuild/win32-x64": "0.27.3"
|
||||
}
|
||||
},
|
||||
"node_modules/escalade": {
|
||||
@@ -3102,9 +3103,9 @@
|
||||
}
|
||||
},
|
||||
"node_modules/markdown-it": {
|
||||
"version": "14.1.0",
|
||||
"resolved": "https://registry.npmjs.org/markdown-it/-/markdown-it-14.1.0.tgz",
|
||||
"integrity": "sha512-a54IwgWPaeBCAAsv13YgmALOF1elABB08FxO9i+r4VFk5Vl4pKokRPeX8u5TCgSsPi6ec1otfLjdOpVcgbpshg==",
|
||||
"version": "14.1.1",
|
||||
"resolved": "https://registry.npmjs.org/markdown-it/-/markdown-it-14.1.1.tgz",
|
||||
"integrity": "sha512-BuU2qnTti9YKgK5N+IeMubp14ZUKUUw7yeJbkjtosvHiP0AZ5c8IAgEMk79D0eC8F23r4Ac/q8cAIFdm2FtyoA==",
|
||||
"dev": true,
|
||||
"license": "MIT",
|
||||
"dependencies": {
|
||||
@@ -3509,9 +3510,9 @@
|
||||
}
|
||||
},
|
||||
"node_modules/openai": {
|
||||
"version": "6.17.0",
|
||||
"resolved": "https://registry.npmjs.org/openai/-/openai-6.17.0.tgz",
|
||||
"integrity": "sha512-NHRpPEUPzAvFOAFs9+9pC6+HCw/iWsYsKCMPXH5Kw7BpMxqd8g/A07/1o7Gx2TWtCnzevVRyKMRFqyiHyAlqcA==",
|
||||
"version": "6.21.0",
|
||||
"resolved": "https://registry.npmjs.org/openai/-/openai-6.21.0.tgz",
|
||||
"integrity": "sha512-26dQFi76dB8IiN/WKGQOV+yKKTTlRCxQjoi2WLt0kMcH8pvxVyvfdBDkld5GTl7W1qvBpwVOtFcsqktj3fBRpA==",
|
||||
"license": "Apache-2.0",
|
||||
"bin": {
|
||||
"openai": "bin/cli"
|
||||
@@ -3994,9 +3995,9 @@
|
||||
"license": "MIT"
|
||||
},
|
||||
"node_modules/semver": {
|
||||
"version": "7.7.3",
|
||||
"resolved": "https://registry.npmjs.org/semver/-/semver-7.7.3.tgz",
|
||||
"integrity": "sha512-SdsKMrI9TdgjdweUSR9MweHA4EJ8YxHn8DFaDisvhVlUOe4BF1tLD7GAj0lIqWVl+dPb/rExr0Btby5loQm20Q==",
|
||||
"version": "7.7.4",
|
||||
"resolved": "https://registry.npmjs.org/semver/-/semver-7.7.4.tgz",
|
||||
"integrity": "sha512-vFKC2IEtQnVhpT78h1Yp8wzwrf8CM+MzKMHGJZfBtzhZNycRFnXsHk6E5TxIkkMsgNS7mdX3AGB7x2QM2di4lA==",
|
||||
"license": "ISC",
|
||||
"bin": {
|
||||
"semver": "bin/semver.js"
|
||||
@@ -4403,9 +4404,9 @@
|
||||
"license": "MIT"
|
||||
},
|
||||
"node_modules/undici": {
|
||||
"version": "7.19.2",
|
||||
"resolved": "https://registry.npmjs.org/undici/-/undici-7.19.2.tgz",
|
||||
"integrity": "sha512-4VQSpGEGsWzk0VYxyB/wVX/Q7qf9t5znLRgs0dzszr9w9Fej/8RVNQ+S20vdXSAyra/bJ7ZQfGv6ZMj7UEbzSg==",
|
||||
"version": "7.21.0",
|
||||
"resolved": "https://registry.npmjs.org/undici/-/undici-7.21.0.tgz",
|
||||
"integrity": "sha512-Hn2tCQpoDt1wv23a68Ctc8Cr/BHpUSfaPYrkajTXOS9IKpxVRx/X5m1K2YkbK2ipgZgxXSgsUinl3x+2YdSSfg==",
|
||||
"license": "MIT",
|
||||
"engines": {
|
||||
"node": ">=20.18.1"
|
||||
@@ -4667,6 +4668,18 @@
|
||||
"integrity": "sha512-zksaLKM2fVlnB5jQQDqKXXwYHLQUVH9es+5TOOHwGOVJOCeRBCiPjwSg+3tN2AdTCzjgli4jijCH290kXb/zWQ==",
|
||||
"license": "Apache-2.0"
|
||||
},
|
||||
"node_modules/wavefile": {
|
||||
"version": "11.0.0",
|
||||
"resolved": "https://registry.npmjs.org/wavefile/-/wavefile-11.0.0.tgz",
|
||||
"integrity": "sha512-/OBiAALgWU24IG7sC84cDO/KfFuvajWc5Uec0oV2zrpOOZZDgGdOwHwgEzOrwh8jkubBk7PtZfQBIcI1OaE5Ng==",
|
||||
"license": "MIT",
|
||||
"bin": {
|
||||
"wavefile": "bin/wavefile.js"
|
||||
},
|
||||
"engines": {
|
||||
"node": ">=8"
|
||||
}
|
||||
},
|
||||
"node_modules/webidl-conversions": {
|
||||
"version": "3.0.1",
|
||||
"resolved": "https://registry.npmjs.org/webidl-conversions/-/webidl-conversions-3.0.1.tgz",
|
||||
|
||||
@@ -1,6 +1,6 @@
|
||||
{
|
||||
"name": "@ztimson/ai-utils",
|
||||
"version": "0.6.1",
|
||||
"version": "0.7.3",
|
||||
"description": "AI Utility library",
|
||||
"author": "Zak Timson",
|
||||
"license": "MIT",
|
||||
@@ -32,7 +32,8 @@
|
||||
"@ztimson/utils": "^0.27.9",
|
||||
"cheerio": "^1.2.0",
|
||||
"openai": "^6.6.0",
|
||||
"tesseract.js": "^6.0.1"
|
||||
"tesseract.js": "^6.0.1",
|
||||
"wavefile": "^11.0.0"
|
||||
},
|
||||
"devDependencies": {
|
||||
"@types/node": "^24.8.1",
|
||||
|
||||
@@ -8,6 +8,8 @@ export type AbortablePromise<T> = Promise<T> & {
|
||||
};
|
||||
|
||||
export type AiOptions = {
|
||||
/** Token to pull models from hugging face */
|
||||
hfToken?: string;
|
||||
/** Path to models */
|
||||
path?: string;
|
||||
/** ASR model: whisper-tiny, whisper-base */
|
||||
|
||||
134
src/asr.ts
Normal file
134
src/asr.ts
Normal file
@@ -0,0 +1,134 @@
|
||||
import { pipeline } from '@xenova/transformers';
|
||||
import { parentPort } from 'worker_threads';
|
||||
import { spawn } from 'node:child_process';
|
||||
import { execSync } from 'node:child_process';
|
||||
import { mkdtempSync, rmSync, readFileSync } from 'node:fs';
|
||||
import { join } from 'node:path';
|
||||
import { tmpdir } from 'node:os';
|
||||
import wavefile from 'wavefile';
|
||||
|
||||
let whisperPipeline: any;
|
||||
|
||||
export async function canDiarization(): Promise<boolean> {
|
||||
return new Promise((resolve) => {
|
||||
const proc = spawn('python', ['-c', 'import pyannote.audio']);
|
||||
proc.on('close', (code: number) => resolve(code === 0));
|
||||
proc.on('error', () => resolve(false));
|
||||
});
|
||||
}
|
||||
|
||||
async function runDiarization(audioPath: string, dir: string, token: string): Promise<any[]> {
|
||||
const script = `
|
||||
import sys
|
||||
import json
|
||||
import os
|
||||
from pyannote.audio import Pipeline
|
||||
|
||||
os.environ['TORCH_HOME'] = r"${dir}"
|
||||
pipeline = Pipeline.from_pretrained("pyannote/speaker-diarization-3.1", token="${token}")
|
||||
output = pipeline(sys.argv[1])
|
||||
|
||||
segments = []
|
||||
for turn, speaker in output.speaker_diarization:
|
||||
segments.append({"start": turn.start, "end": turn.end, "speaker": speaker})
|
||||
|
||||
print(json.dumps(segments))
|
||||
`;
|
||||
|
||||
return new Promise((resolve, reject) => {
|
||||
let output = '';
|
||||
const proc = spawn('python', ['-c', script, audioPath]);
|
||||
proc.stdout.on('data', (data: Buffer) => output += data.toString());
|
||||
proc.stderr.on('data', (data: Buffer) => console.error(data.toString()));
|
||||
proc.on('close', (code: number) => {
|
||||
if(code === 0) {
|
||||
try {
|
||||
resolve(JSON.parse(output));
|
||||
} catch (err) {
|
||||
reject(new Error('Failed to parse diarization output'));
|
||||
}
|
||||
} else {
|
||||
reject(new Error(`Python process exited with code ${code}`));
|
||||
}
|
||||
});
|
||||
proc.on('error', reject);
|
||||
});
|
||||
}
|
||||
|
||||
function combineSpeakerTranscript(chunks: any[], speakers: any[]): string {
|
||||
const speakerMap = new Map();
|
||||
let speakerCount = 0;
|
||||
speakers.forEach((seg: any) => {
|
||||
if(!speakerMap.has(seg.speaker)) speakerMap.set(seg.speaker, ++speakerCount);
|
||||
});
|
||||
|
||||
const lines: string[] = [];
|
||||
let currentSpeaker = -1;
|
||||
let currentText = '';
|
||||
chunks.forEach((chunk: any) => {
|
||||
const time = chunk.timestamp[0];
|
||||
const speaker = speakers.find((s: any) => time >= s.start && time <= s.end);
|
||||
const speakerNum = speaker ? speakerMap.get(speaker.speaker) : 1;
|
||||
if (speakerNum !== currentSpeaker) {
|
||||
if(currentText) lines.push(`[Speaker ${currentSpeaker}]: ${currentText.trim()}`);
|
||||
currentSpeaker = speakerNum;
|
||||
currentText = chunk.text;
|
||||
} else {
|
||||
currentText += chunk.text;
|
||||
}
|
||||
});
|
||||
if(currentText) lines.push(`[Speaker ${currentSpeaker}]: ${currentText.trim()}`);
|
||||
return lines.join('\n');
|
||||
}
|
||||
|
||||
function prepareAudioBuffer(file: string): [string, Float32Array] {
|
||||
let wav: any, tmp;
|
||||
try {
|
||||
wav = new wavefile.WaveFile(readFileSync(file));
|
||||
} catch(err) {
|
||||
tmp = join(mkdtempSync(join(tmpdir(), 'audio-')), 'converted.wav');
|
||||
execSync(`ffmpeg -i "${file}" -ar 16000 -ac 1 -f wav "${tmp}"`, { stdio: 'ignore' });
|
||||
wav = new wavefile.WaveFile(readFileSync(tmp));
|
||||
} finally {
|
||||
wav.toBitDepth('32f');
|
||||
wav.toSampleRate(16000);
|
||||
const samples = wav.getSamples();
|
||||
if(Array.isArray(samples)) {
|
||||
const left = samples[0];
|
||||
const right = samples[1];
|
||||
const buffer = new Float32Array(left.length);
|
||||
for (let i = 0; i < left.length; i++) buffer[i] = (left[i] + right[i]) / 2;
|
||||
return [tmp || file, buffer];
|
||||
}
|
||||
return [tmp || file, samples];
|
||||
}
|
||||
}
|
||||
|
||||
parentPort?.on('message', async ({ file, speaker, model, modelDir, token }) => {
|
||||
try {
|
||||
if(!whisperPipeline) whisperPipeline = await pipeline('automatic-speech-recognition', `Xenova/${model}`, {cache_dir: modelDir, quantized: true});
|
||||
|
||||
// Prepare audio file
|
||||
const [f, buffer] = prepareAudioBuffer(file);
|
||||
|
||||
// Fetch transcript and speakers
|
||||
const hasDiarization = speaker && await canDiarization();
|
||||
const [transcript, speakers] = await Promise.all([
|
||||
whisperPipeline(buffer, {return_timestamps: speaker ? 'word' : false}),
|
||||
(!speaker || !token || !hasDiarization) ? Promise.resolve(): runDiarization(f, modelDir, token),
|
||||
]);
|
||||
if(file != f) rmSync(f, { recursive: true, force: true });
|
||||
|
||||
// Return any results / errors if no more processing required
|
||||
const text = transcript.text?.trim() || null;
|
||||
if(!speaker) return parentPort?.postMessage({ text });
|
||||
if(!token) return parentPort?.postMessage({ text, error: 'HuggingFace token required' });
|
||||
if(!hasDiarization) return parentPort?.postMessage({ text, error: 'Speaker diarization unavailable' });
|
||||
|
||||
// Combine transcript and speakers
|
||||
const combined = combineSpeakerTranscript(transcript.chunks || [], speakers || []);
|
||||
parentPort?.postMessage({ text: combined });
|
||||
} catch (err: any) {
|
||||
parentPort?.postMessage({ error: err.stack || err.message });
|
||||
}
|
||||
});
|
||||
145
src/audio.ts
145
src/audio.ts
@@ -1,115 +1,60 @@
|
||||
import { spawn } from 'node:child_process';
|
||||
import { pipeline } from '@xenova/transformers';
|
||||
import {fileURLToPath} from 'url';
|
||||
import {Worker} from 'worker_threads';
|
||||
import {AbortablePromise, Ai} from './ai.ts';
|
||||
import {canDiarization} from './asr.ts';
|
||||
import {dirname, join} from 'path';
|
||||
|
||||
export class Audio {
|
||||
private whisperPipeline: any;
|
||||
|
||||
constructor(private ai: Ai) {}
|
||||
|
||||
private combineSpeakerTranscript(chunks: any[], speakers: any[]): string {
|
||||
const speakerMap = new Map();
|
||||
let speakerCount = 0;
|
||||
speakers.forEach((seg: any) => {
|
||||
if(!speakerMap.has(seg.speaker)) speakerMap.set(seg.speaker, ++speakerCount);
|
||||
});
|
||||
|
||||
const lines: string[] = [];
|
||||
let currentSpeaker = -1;
|
||||
let currentText = '';
|
||||
chunks.forEach((chunk: any) => {
|
||||
const time = chunk.timestamp[0];
|
||||
const speaker = speakers.find((s: any) => time >= s.start && time <= s.end);
|
||||
const speakerNum = speaker ? speakerMap.get(speaker.speaker) : 1;
|
||||
if (speakerNum !== currentSpeaker) {
|
||||
if(currentText) lines.push(`[speaker ${currentSpeaker}]: ${currentText.trim()}`);
|
||||
currentSpeaker = speakerNum;
|
||||
currentText = chunk.text;
|
||||
} else {
|
||||
currentText += chunk.text;
|
||||
}
|
||||
});
|
||||
if(currentText) lines.push(`[speaker ${currentSpeaker}]: ${currentText.trim()}`);
|
||||
return lines.join('\n');
|
||||
}
|
||||
|
||||
async canDiarization(): Promise<boolean> {
|
||||
return new Promise((resolve) => {
|
||||
const proc = spawn('python3', ['-c', 'import pyannote.audio']);
|
||||
proc.on('close', (code: number) => resolve(code === 0));
|
||||
proc.on('error', () => resolve(false));
|
||||
});
|
||||
}
|
||||
|
||||
private async runDiarization(audioPath: string): Promise<any[]> {
|
||||
if(!await this.canDiarization()) throw new Error('Pyannote is not installed: pip install pyannote.audio');
|
||||
const script = `
|
||||
import sys
|
||||
import json
|
||||
from pyannote.audio import Pipeline
|
||||
|
||||
os.environ['TORCH_HOME'] = "${this.ai.options.path}"
|
||||
pipeline = Pipeline.from_pretrained("pyannote/speaker-diarization-3.1")
|
||||
diarization = pipeline(sys.argv[1])
|
||||
|
||||
segments = []
|
||||
for turn, _, speaker in diarization.itertracks(yield_label=True):
|
||||
segments.append({
|
||||
"start": turn.start,
|
||||
"end": turn.end,
|
||||
"speaker": speaker
|
||||
})
|
||||
|
||||
print(json.dumps(segments))
|
||||
`;
|
||||
|
||||
return new Promise((resolve, reject) => {
|
||||
let output = '';
|
||||
const proc = spawn('python3', ['-c', script, audioPath]);
|
||||
proc.stdout.on('data', (data: Buffer) => output += data.toString());
|
||||
proc.stderr.on('data', (data: Buffer) => console.error(data.toString()));
|
||||
proc.on('close', (code: number) => {
|
||||
if(code === 0) {
|
||||
try {
|
||||
resolve(JSON.parse(output));
|
||||
} catch (err) {
|
||||
reject(new Error('Failed to parse diarization output'));
|
||||
}
|
||||
} else {
|
||||
reject(new Error(`Python process exited with code ${code}`));
|
||||
}
|
||||
});
|
||||
|
||||
proc.on('error', reject);
|
||||
});
|
||||
}
|
||||
|
||||
asr(path: string, options: { model?: string; speaker?: boolean } = {}): AbortablePromise<string | null> {
|
||||
asr(file: string, options: { model?: string; speaker?: boolean | 'id' } = {}): AbortablePromise<string | null> {
|
||||
const { model = this.ai.options.asr || 'whisper-base', speaker = false } = options;
|
||||
let aborted = false;
|
||||
const abort = () => { aborted = true; };
|
||||
|
||||
const p = new Promise<string | null>(async (resolve, reject) => {
|
||||
try {
|
||||
if(aborted) return resolve(null);
|
||||
if(!this.whisperPipeline) this.whisperPipeline = await pipeline('automatic-speech-recognition', `Xenova/${model}`, { cache_dir: this.ai.options.path, quantized: true });
|
||||
|
||||
// Transcript
|
||||
if(aborted) return resolve(null);
|
||||
const transcriptResult = await this.whisperPipeline(path, {return_timestamps: speaker ? 'word' : false, chunk_length_s: 30,});
|
||||
if(!speaker) return resolve(transcriptResult.text?.trim() || null);
|
||||
|
||||
// Speaker Diarization
|
||||
if(aborted) return resolve(null);
|
||||
const speakers = await this.runDiarization(path);
|
||||
if(aborted) return resolve(null);
|
||||
const combined = this.combineSpeakerTranscript(transcriptResult.chunks || [], speakers);
|
||||
resolve(combined);
|
||||
} catch (err) {
|
||||
reject(err);
|
||||
let p = new Promise<string | null>((resolve, reject) => {
|
||||
const worker = new Worker(join(dirname(fileURLToPath(import.meta.url)), 'asr.js'));
|
||||
const handleMessage = ({ text, warning, error }: any) => {
|
||||
worker.terminate();
|
||||
if(aborted) return;
|
||||
if(error) reject(new Error(error));
|
||||
else {
|
||||
if(warning) console.warn(warning);
|
||||
resolve(text);
|
||||
}
|
||||
};
|
||||
const handleError = (err: Error) => {
|
||||
worker.terminate();
|
||||
if(!aborted) reject(err);
|
||||
};
|
||||
worker.on('message', handleMessage);
|
||||
worker.on('error', handleError);
|
||||
worker.on('exit', (code) => {
|
||||
if(code !== 0 && !aborted) reject(new Error(`Worker exited with code ${code}`));
|
||||
});
|
||||
worker.postMessage({file, model, speaker, modelDir: this.ai.options.path, token: this.ai.options.hfToken});
|
||||
});
|
||||
|
||||
// Name speakers using AI
|
||||
if(options.speaker == 'id') {
|
||||
if(!this.ai.language.defaultModel) throw new Error('Configure an LLM for advanced ASR speaker detection');
|
||||
p = p.then(async transcript => {
|
||||
if(!transcript) return transcript;
|
||||
let chunks = this.ai.language.chunk(transcript, 500, 0);
|
||||
if(chunks.length > 4) chunks = [...chunks.slice(0, 3), <string>chunks.at(-1)];
|
||||
const names = await this.ai.language.json(chunks.join('\n'), '{1: "Detected Name"}', {
|
||||
system: 'Use this following transcript to identify speakers. Only identify speakers you are sure about',
|
||||
temperature: 0.1,
|
||||
});
|
||||
Object.entries(names).forEach(([speaker, name]) => {
|
||||
transcript = (<string>transcript).replaceAll(`[Speaker ${speaker}]`, `[${name}]`);
|
||||
});
|
||||
return transcript;
|
||||
})
|
||||
}
|
||||
|
||||
return Object.assign(p, { abort });
|
||||
}
|
||||
|
||||
canDiarization = canDiarization;
|
||||
}
|
||||
|
||||
@@ -3,12 +3,9 @@ import { parentPort } from 'worker_threads';
|
||||
|
||||
let embedder: any;
|
||||
|
||||
parentPort?.on('message', async ({ id, text, model, path }) => {
|
||||
if(!embedder) embedder = await pipeline('feature-extraction', 'Xenova/' + model, {
|
||||
quantized: true,
|
||||
cache_dir: path,
|
||||
});
|
||||
parentPort?.on('message', async ({text, model, modelDir }) => {
|
||||
if(!embedder) embedder = await pipeline('feature-extraction', 'Xenova/' + model, {quantized: true, cache_dir: modelDir});
|
||||
const output = await embedder(text, { pooling: 'mean', normalize: true });
|
||||
const embedding = Array.from(output.data);
|
||||
parentPort?.postMessage({ id, embedding });
|
||||
parentPort?.postMessage({embedding});
|
||||
});
|
||||
|
||||
@@ -1,5 +1,6 @@
|
||||
export * from './ai';
|
||||
export * from './antrhopic';
|
||||
export * from './asr';
|
||||
export * from './audio';
|
||||
export * from './embedder'
|
||||
export * from './llm';
|
||||
|
||||
74
src/llm.ts
74
src/llm.ts
@@ -75,22 +75,10 @@ export type LLMRequest = {
|
||||
}
|
||||
|
||||
class LLM {
|
||||
private embedWorker: Worker | null = null;
|
||||
private embedQueue = new Map<number, { resolve: (value: number[]) => void; reject: (error: any) => void }>();
|
||||
private embedId = 0;
|
||||
private models: {[model: string]: LLMProvider} = {};
|
||||
private defaultModel!: string;
|
||||
defaultModel!: string;
|
||||
models: {[model: string]: LLMProvider} = {};
|
||||
|
||||
constructor(public readonly ai: Ai) {
|
||||
this.embedWorker = new Worker(join(dirname(fileURLToPath(import.meta.url)), 'embedder.js'));
|
||||
this.embedWorker.on('message', ({ id, embedding }) => {
|
||||
const pending = this.embedQueue.get(id);
|
||||
if (pending) {
|
||||
pending.resolve(embedding);
|
||||
this.embedQueue.delete(id);
|
||||
}
|
||||
});
|
||||
|
||||
if(!ai.options.llm?.models) return;
|
||||
Object.entries(ai.options.llm.models).forEach(([model, config]) => {
|
||||
if(!this.defaultModel) this.defaultModel = model;
|
||||
@@ -196,7 +184,12 @@ class LLM {
|
||||
const system = history[0].role == 'system' ? history[0] : null,
|
||||
recent = keep == 0 ? [] : history.slice(-keep),
|
||||
process = (keep == 0 ? history : history.slice(0, -keep)).filter(h => h.role === 'assistant' || h.role === 'user');
|
||||
const summary: any = await this.json(`Create the smallest summary possible, no more than 500 tokens. Create a list of NEW facts (split by subject [pro]noun and fact) about what you learned from this conversation that you didn't already know or get from a tool call or system prompt. Focus only on new information about people, topics, or facts. Avoid generating facts about the AI. Match this format: {summary: string, facts: [[subject, fact]]}\n\n${process.map(m => `${m.role}: ${m.content}`).join('\n\n')}`, {model: options?.model, temperature: options?.temperature || 0.3});
|
||||
|
||||
const summary: any = await this.json(process.map(m => `${m.role}: ${m.content}`).join('\n\n'), '{summary: string, facts: [[subject, fact]]}', {
|
||||
system: 'Create the smallest summary possible, no more than 500 tokens. Create a list of NEW facts (split by subject [pro]noun and fact) about what you learned from this conversation that you didn\'t already know or get from a tool call or system prompt. Focus only on new information about people, topics, or facts. Avoid generating facts about the AI.',
|
||||
model: options?.model,
|
||||
temperature: options?.temperature || 0.3
|
||||
});
|
||||
const timestamp = new Date();
|
||||
const memory = await Promise.all((summary?.facts || [])?.map(async ([owner, fact]: [string, string]) => {
|
||||
const e = await Promise.all([this.embedding(owner), this.embedding(`${owner}: ${fact}`)]);
|
||||
@@ -262,30 +255,37 @@ class LLM {
|
||||
/**
|
||||
* Create a vector representation of a string
|
||||
* @param {object | string} target Item that will be embedded (objects get converted)
|
||||
* @param {number} maxTokens Chunking size. More = better context, less = more specific (Search by paragraphs or lines)
|
||||
* @param {number} overlapTokens Includes previous X tokens to provide continuity to AI (In addition to max tokens)
|
||||
* @param {maxTokens?: number, overlapTokens?: number} opts Options for embedding such as chunk sizes
|
||||
* @returns {Promise<Awaited<{index: number, embedding: number[], text: string, tokens: number}>[]>} Chunked embeddings
|
||||
*/
|
||||
embedding(target: object | string, maxTokens = 500, overlapTokens = 50) {
|
||||
async embedding(target: object | string, opts: {maxTokens?: number, overlapTokens?: number} = {}) {
|
||||
let {maxTokens = 500, overlapTokens = 50} = opts;
|
||||
const embed = (text: string): Promise<number[]> => {
|
||||
return new Promise((resolve, reject) => {
|
||||
const id = this.embedId++;
|
||||
this.embedQueue.set(id, { resolve, reject });
|
||||
this.embedWorker?.postMessage({
|
||||
id,
|
||||
text,
|
||||
model: this.ai.options?.embedder || 'bge-small-en-v1.5',
|
||||
path: this.ai.options.path
|
||||
const worker = new Worker(join(dirname(fileURLToPath(import.meta.url)), 'embedder.js'));
|
||||
const handleMessage = ({ embedding }: any) => {
|
||||
worker.terminate();
|
||||
resolve(embedding);
|
||||
};
|
||||
const handleError = (err: Error) => {
|
||||
worker.terminate();
|
||||
reject(err);
|
||||
};
|
||||
worker.on('message', handleMessage);
|
||||
worker.on('error', handleError);
|
||||
worker.on('exit', (code) => {
|
||||
if(code !== 0) reject(new Error(`Worker exited with code ${code}`));
|
||||
});
|
||||
worker.postMessage({text, model: this.ai.options?.embedder || 'bge-small-en-v1.5', modelDir: this.ai.options.path});
|
||||
});
|
||||
};
|
||||
const chunks = this.chunk(target, maxTokens, overlapTokens);
|
||||
return Promise.all(chunks.map(async (text, index) => ({
|
||||
index,
|
||||
embedding: await embed(text),
|
||||
text,
|
||||
tokens: this.estimateTokens(text),
|
||||
})));
|
||||
const chunks = this.chunk(target, maxTokens, overlapTokens), results: any[] = [];
|
||||
for(let i = 0; i < chunks.length; i++) {
|
||||
const text= chunks[i];
|
||||
const embedding = await embed(text);
|
||||
results.push({index: i, embedding, text, tokens: this.estimateTokens(text)});
|
||||
}
|
||||
return results;
|
||||
}
|
||||
|
||||
/**
|
||||
@@ -317,12 +317,16 @@ class LLM {
|
||||
|
||||
/**
|
||||
* Ask a question with JSON response
|
||||
* @param {string} message Question
|
||||
* @param {string} text Text to process
|
||||
* @param {string} schema JSON schema the AI should match
|
||||
* @param {LLMRequest} options Configuration options and chat history
|
||||
* @returns {Promise<{} | {} | RegExpExecArray | null>}
|
||||
*/
|
||||
async json(message: string, options?: LLMRequest): Promise<any> {
|
||||
let resp = await this.ask(message, {system: 'Respond using a JSON blob matching any provided examples', ...options});
|
||||
async json(text: string, schema: string, options?: LLMRequest): Promise<any> {
|
||||
let resp = await this.ask(text, {...options, system: (options?.system ? `${options.system}\n` : '') + `Only respond using a JSON code block matching this schema:
|
||||
\`\`\`json
|
||||
${schema}
|
||||
\`\`\``});
|
||||
if(!resp) return {};
|
||||
const codeBlock = /```(?:.+)?\s*([\s\S]*?)```/.exec(resp);
|
||||
const jsonStr = codeBlock ? codeBlock[1].trim() : resp;
|
||||
|
||||
@@ -6,6 +6,7 @@ export default defineConfig({
|
||||
build: {
|
||||
lib: {
|
||||
entry: {
|
||||
asr: './src/asr.ts',
|
||||
index: './src/index.ts',
|
||||
embedder: './src/embedder.ts',
|
||||
},
|
||||
|
||||
Reference in New Issue
Block a user