Compare commits
15 Commits
| Author | SHA1 | Date | |
|---|---|---|---|
| 89619e211e | |||
| afc6653364 | |||
| 68e72445a2 | |||
| 1aa6cdf329 | |||
| d022a5ef4d | |||
| a1d438a20a | |||
| 52a9e3aaa4 | |||
| a7aec4ee29 | |||
| dda2d4c2a3 | |||
| 58e0e488e4 | |||
| 8dfcd06752 | |||
| 14f6cdd313 | |||
| 73d6ee0f2a | |||
| bee4085666 | |||
| 3b5c71de7c |
234
package-lock.json
generated
234
package-lock.json
generated
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"cpu": [
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"arm"
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],
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@@ -2517,9 +2557,9 @@
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"resolved": "https://registry.npmjs.org/lightningcss-linux-arm64-gnu/-/lightningcss-linux-arm64-gnu-1.32.0.tgz",
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"cpu": [
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"arm64"
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],
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@@ -2541,9 +2581,9 @@
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}
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},
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"node_modules/lightningcss-linux-arm64-musl": {
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"version": "1.32.0",
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"resolved": "https://registry.npmjs.org/lightningcss-linux-arm64-musl/-/lightningcss-linux-arm64-musl-1.32.0.tgz",
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"version": "1.33.0",
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"resolved": "https://registry.npmjs.org/lightningcss-linux-arm64-musl/-/lightningcss-linux-arm64-musl-1.33.0.tgz",
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"cpu": [
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"arm64"
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||||
],
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@@ -2565,9 +2605,9 @@
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}
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},
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||||
"node_modules/lightningcss-linux-x64-gnu": {
|
||||
"version": "1.32.0",
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"resolved": "https://registry.npmjs.org/lightningcss-linux-x64-gnu/-/lightningcss-linux-x64-gnu-1.32.0.tgz",
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"integrity": "sha512-V7Qr52IhZmdKPVr+Vtw8o+WLsQJYCTd8loIfpDaMRWGUZfBOYEJeyJIkqGIDMZPwPx24pUMfwSxxI8phr/MbOA==",
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"version": "1.33.0",
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"resolved": "https://registry.npmjs.org/lightningcss-linux-x64-gnu/-/lightningcss-linux-x64-gnu-1.33.0.tgz",
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"integrity": "sha512-ar+Ju7LmcN0Jo4FpL4hpFybwNG9/3A/Br5KW2n2jyODg3MEZXaDYADdemoNS+BDNfMgKvylJLj4S5tyRActuAg==",
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||||
"cpu": [
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"x64"
|
||||
],
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@@ -2589,9 +2629,9 @@
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||||
}
|
||||
},
|
||||
"node_modules/lightningcss-linux-x64-musl": {
|
||||
"version": "1.32.0",
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"resolved": "https://registry.npmjs.org/lightningcss-linux-x64-musl/-/lightningcss-linux-x64-musl-1.32.0.tgz",
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"integrity": "sha512-bYcLp+Vb0awsiXg/80uCRezCYHNg1/l3mt0gzHnWV9XP1W5sKa5/TCdGWaR/zBM2PeF/HbsQv/j2URNOiVuxWg==",
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"version": "1.33.0",
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"resolved": "https://registry.npmjs.org/lightningcss-linux-x64-musl/-/lightningcss-linux-x64-musl-1.33.0.tgz",
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"integrity": "sha512-RYiYbkokw0trfKqqzfF55lginwEPrD3OJDfTuJzFs1MK6iFnDenaz1fqLLtX4ITG3OktJQXOeTaw1awrBAlZPw==",
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||||
"cpu": [
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"x64"
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],
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@@ -2613,9 +2653,9 @@
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||||
}
|
||||
},
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||||
"node_modules/lightningcss-win32-arm64-msvc": {
|
||||
"version": "1.32.0",
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"resolved": "https://registry.npmjs.org/lightningcss-win32-arm64-msvc/-/lightningcss-win32-arm64-msvc-1.32.0.tgz",
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"integrity": "sha512-8SbC8BR40pS6baCM8sbtYDSwEVQd4JlFTOlaD3gWGHfThTcABnNDBda6eTZeqbofalIJhFx0qKzgHJmcPTnGdw==",
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"version": "1.33.0",
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"resolved": "https://registry.npmjs.org/lightningcss-win32-arm64-msvc/-/lightningcss-win32-arm64-msvc-1.33.0.tgz",
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"integrity": "sha512-1K+MPfLSFVpphzpdbfkhlWk6wBrTObBzS2T6db10PNOZgR9GoVsAWzwNyuhUYYbTp23j+4RrncfujZ4uAzXvwA==",
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||||
"cpu": [
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"arm64"
|
||||
],
|
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@@ -2634,9 +2674,9 @@
|
||||
}
|
||||
},
|
||||
"node_modules/lightningcss-win32-x64-msvc": {
|
||||
"version": "1.32.0",
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"resolved": "https://registry.npmjs.org/lightningcss-win32-x64-msvc/-/lightningcss-win32-x64-msvc-1.32.0.tgz",
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"integrity": "sha512-Amq9B/SoZYdDi1kFrojnoqPLxYhQ4Wo5XiL8EVJrVsB8ARoC1PWW6VGtT0WKCemjy8aC+louJnjS7U18x3b06Q==",
|
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"version": "1.33.0",
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"resolved": "https://registry.npmjs.org/lightningcss-win32-x64-msvc/-/lightningcss-win32-x64-msvc-1.33.0.tgz",
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"integrity": "sha512-OlEICDx/Xl0FqSp4bry8zFnCvGpig3Gl4gCquvYwHuqJKEC1+n9NgDniFvqHGmMv1ZkqDJrDqKKSykTDX+ehuA==",
|
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"cpu": [
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"x64"
|
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],
|
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@@ -2794,9 +2834,9 @@
|
||||
}
|
||||
},
|
||||
"node_modules/mdurl": {
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"version": "2.0.0",
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"resolved": "https://registry.npmjs.org/mdurl/-/mdurl-2.0.0.tgz",
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"integrity": "sha512-Lf+9+2r+Tdp5wXDXC4PcIBjTDtq4UKjCPMQhKIuzpJNW0b96kVqSwW0bT7FhRSfmAiFYgP+SCRvdrDozfh0U5w==",
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"version": "2.1.0",
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"resolved": "https://registry.npmjs.org/mdurl/-/mdurl-2.1.0.tgz",
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"integrity": "sha512-1+HBaOx0zi/dQWht8rNv9MYf9qqpqL/kxI0hXImU6Y547zM6Sni8BQibt7ifgMcYtQg41ao3Ivd6cnSM86inpg==",
|
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"dev": true,
|
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"license": "MIT"
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},
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@@ -2971,9 +3011,9 @@
|
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"license": "MIT"
|
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},
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"node_modules/nanoid": {
|
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"version": "3.3.15",
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"resolved": "https://registry.npmjs.org/nanoid/-/nanoid-3.3.15.tgz",
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"integrity": "sha512-y7Wygv/7mEOvxTuEQDB8StXdMRBWf1kR/tlhAzBRUFkB2jfcLOAxO/SHmOO2zgz1pVgK29/kyupn059/bCHdjA==",
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"version": "3.3.16",
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"resolved": "https://registry.npmjs.org/nanoid/-/nanoid-3.3.16.tgz",
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"integrity": "sha512-bzlKTyNJ7+LdGIIwy8ijFpIqEQIvafahV7eYykJ8Cvh42EdJeODoJ6gUJXpQJvej1BddH8OqTXZNE/KfbWAu8Q==",
|
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"dev": true,
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"funding": [
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{
|
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@@ -3092,9 +3132,9 @@
|
||||
"license": "MIT"
|
||||
},
|
||||
"node_modules/openai": {
|
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"version": "6.46.0",
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"resolved": "https://registry.npmjs.org/openai/-/openai-6.46.0.tgz",
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"integrity": "sha512-DFg6jEPT2RO+oAyXtddeUJU8zkGy1OQ1AjGzNIJUMQG03TTqvCpy9tBpQ+2VVVnvrl3E56F8GEin2JYtWpITtA==",
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"version": "6.49.0",
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"resolved": "https://registry.npmjs.org/openai/-/openai-6.49.0.tgz",
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"integrity": "sha512-aYCc0C6L864eR6WSYIwQGyXriw/nIyZx0ObvhzOEVuk0zoBDpynjSbrionWI7q65B5H8jJX0DXR9snEzM6bfPg==",
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"license": "Apache-2.0",
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"peerDependencies": {
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"@aws-sdk/credential-provider-node": ">=3.972.0 <4",
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@@ -3232,9 +3272,9 @@
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"license": "MIT"
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},
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"node_modules/postcss": {
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"version": "8.5.17",
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"resolved": "https://registry.npmjs.org/postcss/-/postcss-8.5.17.tgz",
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"integrity": "sha512-J7EF+8X+CzRPaJPOv9Ck2wNWJvGnnl3PcNPAdGg6GTLjyVpyQ0yATMSXRFRV01BviT/9Gwuc3rjEyJbDJG9a4w==",
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"version": "8.5.25",
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"resolved": "https://registry.npmjs.org/postcss/-/postcss-8.5.25.tgz",
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"integrity": "sha512-DTPx3RWSSnWyzLxQnlH0rJP+EW5ekl16ZU4/psbIhA0e53kJfdgaN5vKM+xP7yJtXVu+nfdVFmlgFDEKAe4Pyw==",
|
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"dev": true,
|
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"funding": [
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{
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@@ -3252,7 +3292,7 @@
|
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],
|
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"license": "MIT",
|
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"dependencies": {
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"nanoid": "^3.3.12",
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"nanoid": "^3.3.16",
|
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"picocolors": "^1.1.1",
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"source-map-js": "^1.2.1"
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},
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@@ -3787,9 +3827,9 @@
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"license": "MIT"
|
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},
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"node_modules/undici": {
|
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"version": "7.28.0",
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"resolved": "https://registry.npmjs.org/undici/-/undici-7.28.0.tgz",
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"integrity": "sha512-cRZYrTDwWznlnRiPjggAGxZXanty6M8RV1ff8Wm4LWXBp7/IG8v5DnOm74DtUBp9OONpK75YlPnIjQqX0dBDtA==",
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"version": "7.29.0",
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"resolved": "https://registry.npmjs.org/undici/-/undici-7.29.0.tgz",
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"integrity": "sha512-IDxfleLmmbSskfWSUATiN1nfn2rDuvnMOqb5CWR92iIfojA0Ud+ulOAAEQ57LPr9rWmsreUyf5lwyao+7GNNVw==",
|
||||
"license": "MIT",
|
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"engines": {
|
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"node": ">=20.18.1"
|
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@@ -3981,16 +4021,16 @@
|
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}
|
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},
|
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"node_modules/vite": {
|
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"version": "8.1.4",
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"resolved": "https://registry.npmjs.org/vite/-/vite-8.1.4.tgz",
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"integrity": "sha512-bTT9PsdWO+MQMNG9ZXIP/qM9wGh37DFxTV/sPq9cFpHr3w4jkgef032PkAL9jAqhk3Nz8NQw3O8n6/xFkqO4QQ==",
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"version": "8.1.5",
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"resolved": "https://registry.npmjs.org/vite/-/vite-8.1.5.tgz",
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"integrity": "sha512-7ULLwsCdYx/nRyrpiEwvqb5TFHrMVZyBt+rg/OAXT7rgj/z+DtTDyKFeLAdDkubDVDKD8jOsndmy7m55XcfUsw==",
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||||
"dev": true,
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"license": "MIT",
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"dependencies": {
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"lightningcss": "^1.32.0",
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"picomatch": "^4.0.5",
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"postcss": "^8.5.16",
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"rolldown": "~1.1.4",
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"postcss": "^8.5.17",
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"rolldown": "~1.1.5",
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"tinyglobby": "^0.2.17"
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},
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||||
"bin": {
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||||
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||||
@@ -1,6 +1,6 @@
|
||||
{
|
||||
"name": "@ztimson/ai-utils",
|
||||
"version": "1.2.3",
|
||||
"version": "1.3.3",
|
||||
"description": "AI Utility library",
|
||||
"author": "Zak Timson",
|
||||
"license": "MIT",
|
||||
|
||||
@@ -21,10 +21,10 @@ export class Anthropic extends LLMProvider {
|
||||
messages.push(<any>{timestamp, ...h});
|
||||
} else {
|
||||
const textContent = h.content?.filter((c: any) => c.type == 'text').map((c: any) => c.text).join('\n\n');
|
||||
if(textContent) messages.push({timestamp, role: h.role, content: textContent});
|
||||
if(textContent) messages.push({role: h.role, content: textContent, timestamp: timestamp});
|
||||
h.content.forEach((c: any) => {
|
||||
if(c.type == 'tool_use') {
|
||||
messages.push({timestamp, role: 'tool', id: c.id, name: c.name, args: c.input, content: undefined});
|
||||
messages.push({role: 'tool', id: c.id, name: c.name, args: c.input, timestamp: c.timestamp, content: undefined});
|
||||
} else if(c.type == 'tool_result') {
|
||||
const m: any = messages.findLast(m => (<any>m).id == c.tool_use_id);
|
||||
if(m) m[c.is_error ? 'error' : 'content'] = c.content;
|
||||
@@ -46,13 +46,16 @@ export class Anthropic extends LLMProvider {
|
||||
i++;
|
||||
}
|
||||
}
|
||||
return history.map(({timestamp, ...h}) => h);
|
||||
return history;
|
||||
}
|
||||
|
||||
ask(message: string, options: LLMRequest = {}): AbortablePromise<string | any> {
|
||||
const controller = new AbortController();
|
||||
return Object.assign(new Promise<any>(async (res) => {
|
||||
let history = this.fromStandard([...options.history || [], {role: 'user', content: message, timestamp: Date.now()}]);
|
||||
let history = this.fromStandard([
|
||||
...(options.history || []).filter(h => h.role !== 'system'),
|
||||
{role: 'user', content: message, timestamp: Date.now()}
|
||||
]);
|
||||
const tools = options.tools || this.ai.options.llm?.tools || [];
|
||||
const requestParams: any = {
|
||||
model: options.model || this.model,
|
||||
@@ -83,8 +86,9 @@ export class Anthropic extends LLMProvider {
|
||||
};
|
||||
}
|
||||
|
||||
let resp: any, isFirstMessage = true;
|
||||
let resp: any, terminal = false;
|
||||
do {
|
||||
requestParams.messages = history.map(({timestamp, ...m}) => m);
|
||||
resp = await this.client.messages.create(requestParams).catch(err => {
|
||||
err.message += `\n\nMessages:\n${JSON.stringify(history, null, 2)}`;
|
||||
throw err;
|
||||
@@ -92,8 +96,6 @@ export class Anthropic extends LLMProvider {
|
||||
|
||||
// Streaming mode
|
||||
if(options.stream) {
|
||||
if(!isFirstMessage) options.stream({text: '\n\n'});
|
||||
else isFirstMessage = false;
|
||||
resp.content = [];
|
||||
for await (const chunk of resp) {
|
||||
if(controller.signal.aborted) break;
|
||||
@@ -113,7 +115,7 @@ export class Anthropic extends LLMProvider {
|
||||
}
|
||||
} else if(chunk.type === 'content_block_stop') {
|
||||
const last = resp.content.at(-1);
|
||||
if(last.input != null) last.input = last.input ? JSONAttemptParse(last.input, {}) : {};
|
||||
if(last?.input != null) last.input = last.input ? JSONAttemptParse(last.input, {}) : {};
|
||||
} else if(chunk.type === 'message_stop') {
|
||||
break;
|
||||
}
|
||||
@@ -123,32 +125,43 @@ export class Anthropic extends LLMProvider {
|
||||
// Run tools
|
||||
const toolCalls = resp.content.filter((c: any) => c.type === 'tool_use');
|
||||
if(toolCalls.length && !controller.signal.aborted) {
|
||||
history.push({role: 'assistant', content: resp.content});
|
||||
history.push({role: 'assistant', content: resp.content, timestamp: Date.now()});
|
||||
const results = await Promise.all(toolCalls.map(async (toolCall: any) => {
|
||||
const tool = tools.find(findByProp('name', toolCall.name));
|
||||
if(options.stream) options.stream({tool: toolCall.name});
|
||||
if(!tool) return {tool_use_id: toolCall.id, is_error: true, content: 'Tool not found'};
|
||||
try {
|
||||
const result = await tool.fn(toolCall.input, options?.stream, this.ai);
|
||||
// Wrap stream so a tool's `done` ends turn gracefully
|
||||
const toolStream = options.stream && ((chunk: any) => {
|
||||
if(chunk.done) { terminal = true; return; }
|
||||
options.stream!(chunk);
|
||||
});
|
||||
const result = await tool.fn(toolCall.input, toolStream, this.ai, toolCall.id);
|
||||
return {type: 'tool_result', tool_use_id: toolCall.id, content: typeof result == 'object' ? JSONSanitize(result) : result};
|
||||
} catch (err: any) {
|
||||
return {type: 'tool_result', tool_use_id: toolCall.id, is_error: true, content: err?.message || err?.toString() || 'Unknown'};
|
||||
}
|
||||
}));
|
||||
history.push({role: 'user', content: results});
|
||||
history.push({role: 'user', content: results, timestamp: Date.now()});
|
||||
requestParams.messages = history;
|
||||
}
|
||||
} while (!controller.signal.aborted && resp.content.some((c: any) => c.type === 'tool_use'));
|
||||
} while (!terminal && !controller.signal.aborted && resp.content.some((c: any) => c.type === 'tool_use'));
|
||||
|
||||
const textContent = resp.content.filter((c: any) => c.type == 'text').map((c: any) => c.text).join('\n\n');
|
||||
history.push({role: 'assistant', content: textContent});
|
||||
if(!terminal) {
|
||||
const textContent = resp.content.filter((c: any) => c.type == 'text').map((c: any) => c.text).join('\n\n');
|
||||
history.push({role: 'assistant', content: textContent.trim(), timestamp: Date.now()});
|
||||
}
|
||||
history = this.toStandard(history);
|
||||
|
||||
if(options.stream) options.stream({done: true});
|
||||
if(options.history) options.history.splice(0, options.history.length, ...history);
|
||||
if(options.stream) options.stream({done: true});
|
||||
|
||||
const turnStart = history.map(h => h.role).lastIndexOf('user');
|
||||
const finalContent = history.slice(turnStart + 1).reduce((str, h) => {
|
||||
if(h.role === 'assistant') return str + (h.content || '');
|
||||
if(h.role === 'tool') return str + `<tool>${h.name}</tool>\n\n`;
|
||||
return str;
|
||||
}, '').trim();
|
||||
|
||||
// Return parsed JSON if schema provided
|
||||
const finalContent = history.at(-1)?.content;
|
||||
res(options.schema ? JSONAttemptParse(finalContent, finalContent) : finalContent);
|
||||
}), {abort: () => controller.abort()});
|
||||
}
|
||||
|
||||
205
src/llm.ts
205
src/llm.ts
@@ -1,3 +1,4 @@
|
||||
import {snakeCase} from '@ztimson/utils';
|
||||
import {AbortablePromise, Ai} from './ai.ts';
|
||||
import {Anthropic} from './antrhopic.ts';
|
||||
import {OpenAi} from './open-ai.ts';
|
||||
@@ -6,11 +7,24 @@ import {AiTool, AiToolArg} from './tools.ts';
|
||||
import {fileURLToPath} from 'url';
|
||||
import {dirname, join} from 'path';
|
||||
import {spawn} from 'node:child_process';
|
||||
import {Memory, MemoryCache, MemoryManager} from './memory.ts';
|
||||
import {Memory, MemoryCache, MemoryManager, MemoryOptions} from './memory.ts';
|
||||
|
||||
export type AnthropicConfig = {proto: 'anthropic', token: string};
|
||||
export type OpenAiConfig = {proto: 'openai', host?: string, token: string};
|
||||
|
||||
export type Agent = {
|
||||
name: string;
|
||||
description?: string;
|
||||
model?: string | null;
|
||||
temperature?: number;
|
||||
system: string;
|
||||
delegate?: boolean;
|
||||
skills?: Skill[] | null;
|
||||
tools?: AiTool[] | null;
|
||||
mcp?: McpServer[] | null;
|
||||
agents?: string[] | null;
|
||||
}
|
||||
|
||||
export type LLMMessage = {
|
||||
/** Message originator */
|
||||
role: 'assistant' | 'system' | 'user';
|
||||
@@ -55,13 +69,17 @@ export type LLMRequest = {
|
||||
/** Compress old messages in the chat to free up context */
|
||||
compress?: {max: number; min: number};
|
||||
/** User's memory documents - RAG injected automatically each turn */
|
||||
memory?: Memory[] | MemoryCache;
|
||||
memory?: Memory[] | MemoryCache | MemoryOptions;
|
||||
/** Model to use for memory operations */
|
||||
memoryModel?: string;
|
||||
/** Skill documents the AI can browse and read on demand */
|
||||
skills?: Skill[];
|
||||
/** MCP servers to connect and expose as tools */
|
||||
mcp?: McpServer[];
|
||||
/** Subagents exposed as delegatable/wrapped tools */
|
||||
agents?: Agent[];
|
||||
/** @internal recursion guard for nested agent delegation */
|
||||
_agentDepth?: number;
|
||||
}
|
||||
|
||||
export type McpServer = {
|
||||
@@ -82,6 +100,7 @@ export type Skill = {
|
||||
content: string;
|
||||
}
|
||||
|
||||
const MAX_AGENT_DEPTH = 5;
|
||||
|
||||
class LLM {
|
||||
private memoryManager!: MemoryManager;
|
||||
@@ -99,6 +118,59 @@ class LLM {
|
||||
this.memoryManager = new MemoryManager(this);
|
||||
}
|
||||
|
||||
/**
|
||||
* Wrap agents as tools. Nested delegation is opt-in only (empty by default, like
|
||||
* tools/skills/mcp) and an agent can never call itself even if explicitly whitelisted.
|
||||
* Delegate results are queued in `pending` and spliced into history by `ask()` after
|
||||
* the provider's own end-of-turn history sync has already run.
|
||||
*/
|
||||
private setupAgent(agents: Agent[] = [], allAgents: Agent[], pending: Map<string, any>, aborts: (() => void)[], depth = 0): AiTool[] {
|
||||
return agents.map(a => {
|
||||
const toolName = `${a.delegate ? '' : 'sub'}agent_${snakeCase(a.name)}`;
|
||||
return {
|
||||
name: toolName,
|
||||
description: `${a.delegate ? 'Delegate to ' : ''}Subagent: ${a.description || a.name}`,
|
||||
args: {
|
||||
context: {type: 'string', description: 'Summary of related messages, samples, files, etc...', required: true},
|
||||
instructions: {type: 'string', description: 'Detailed instructions for subagent to complete', required: true},
|
||||
},
|
||||
fn: async (args: any, stream: any, ai: any, id?: string) => {
|
||||
if(depth >= MAX_AGENT_DEPTH) return 'Max agent delegation depth exceeded';
|
||||
const subHistory: LLMMessage[] = [];
|
||||
|
||||
// Opt-in only, self always excluded regardless of whitelist
|
||||
const nested = (a.agents || [])
|
||||
.map(name => allAgents.find(x => x.name === name))
|
||||
.filter((x): x is Agent => !!x && x.name !== a.name);
|
||||
|
||||
const request = this.ask(`${args.instructions}${args.context ? `\n\n<context>${args.context}</context>` : ''}`, {
|
||||
system: `You are a specialized subagent. ${a.delegate ? 'Your output streams directly to the user for the remainder of this turn.' : 'You are wrapped in a tool call that will be analysis by an LLM'}
|
||||
As a subagent, focus on executing your task completely using available tools and returning only the final result - no commentary, questions, or dialogue.
|
||||
|
||||
${a.system}`,
|
||||
model: a.model || undefined,
|
||||
temperature: a.temperature,
|
||||
stream: a.delegate ? stream : undefined,
|
||||
history: subHistory,
|
||||
mcp: a.mcp || undefined,
|
||||
skills: a.skills || undefined,
|
||||
tools: a.tools || undefined,
|
||||
agents: nested,
|
||||
_agentDepth: depth + 1,
|
||||
} as any);
|
||||
aborts.push(request.abort);
|
||||
const resp = await request;
|
||||
|
||||
if(a.delegate) {
|
||||
pending.set(<string>id, {resp, subHistory});
|
||||
return '';
|
||||
}
|
||||
return resp;
|
||||
}
|
||||
};
|
||||
});
|
||||
}
|
||||
|
||||
private async setupMcp(servers: McpServer[] = []): Promise<{prompt: string, tools: AiTool[]}> {
|
||||
if(!servers?.length) return {prompt: '', tools: []};
|
||||
const allTools: AiTool[] = [];
|
||||
@@ -143,7 +215,7 @@ class LLM {
|
||||
return {
|
||||
prompt: `You have access to the following skill documents, use \`read_skill\` to access them:\n${list}`,
|
||||
tools: [{
|
||||
name: 'read_skill',
|
||||
name: 'skill_read',
|
||||
description: 'Read the full content of a skill/knowledge document',
|
||||
args: {
|
||||
name: {type: 'string', description: 'Exact skill name', required: true}
|
||||
@@ -167,8 +239,16 @@ class LLM {
|
||||
}
|
||||
const m = options.model || this.defaultModel;
|
||||
if(!this.models[m]) throw new Error(`Model does not exist: ${m}`);
|
||||
let abort = () => {};
|
||||
return Object.assign(new Promise<string>(async res => {
|
||||
let request: AbortablePromise<string> | null = null;
|
||||
let aborted = false;
|
||||
const nestedAborts: (() => void)[] = [];
|
||||
const abort = () => {
|
||||
aborted = true;
|
||||
request?.abort?.();
|
||||
nestedAborts.forEach(a => a());
|
||||
};
|
||||
|
||||
const promise = (async () => {
|
||||
let tools: AiTool[] = options.tools || this.ai.options.llm?.tools || [];
|
||||
const prompts: string[] = [];
|
||||
let history = options.history || [];
|
||||
@@ -189,48 +269,95 @@ class LLM {
|
||||
tools.push(...s.tools);
|
||||
}
|
||||
|
||||
// Agents
|
||||
const agents = options.agents || this.ai.options?.llm?.agents;
|
||||
const pendingDelegates = new Map<string, any>();
|
||||
if(agents?.length) tools.push(...this.setupAgent(agents, agents, pendingDelegates, nestedAborts, options._agentDepth || 0));
|
||||
|
||||
// Memory
|
||||
if (options.memory) {
|
||||
const mems = options.memory instanceof MemoryCache ? options.memory.memories : options.memory;
|
||||
const relevant = await this.memoryManager.recollect(message, options.memory, 5);
|
||||
prompts.unshift(`You have access to the following memory files:
|
||||
const mem = MemoryManager.normalize(options.memory);
|
||||
if(mem) {
|
||||
const mems = mem.memory instanceof MemoryCache ? mem.memory.memories : mem.memory;
|
||||
if(mems.length) {
|
||||
if(mem.inject) {
|
||||
const pool = 15; // candidates considered, cheap since only refs are listed
|
||||
const budget = mem.maxTokens ?? 2000; // actual content injected
|
||||
const relevant = await this.memoryManager.recollect(message, mem.memory, pool);
|
||||
|
||||
let used = 0;
|
||||
const preloaded: typeof relevant = [];
|
||||
const listed: typeof relevant = [];
|
||||
for(const r of relevant) {
|
||||
const t = this.estimateTokens(r.content);
|
||||
if(used + t <= budget || preloaded.length === 0) {
|
||||
preloaded.push(r);
|
||||
used += t;
|
||||
} else listed.push(r);
|
||||
}
|
||||
|
||||
prompts.unshift(`You have access to the following memory files:
|
||||
${mems.map(m => `- ${m.name}: ${m.description}`).join('\n')}
|
||||
${relevant.length ? `
|
||||
${preloaded.length ? `
|
||||
Relevant memories have been preloaded:
|
||||
${relevant.map(r => `
|
||||
${preloaded.map(r => `
|
||||
**${r.name}**
|
||||
${r.description}
|
||||
${r.content}
|
||||
`).join('\n---\n')}
|
||||
` : ''}${listed.length ? `
|
||||
Also relevant but not preloaded (use \`memory_recall\`): ${listed.map(r => r.name).join(', ')}
|
||||
` : ''}`.trim());
|
||||
tools.push(this.memoryManager.tools.read(options.memory));
|
||||
}
|
||||
if(mem.tool) tools.push(this.memoryManager.tools.read(mem.memory));
|
||||
}
|
||||
}
|
||||
|
||||
if(aborted) throw Object.assign(new Error('Aborted'), {name: 'AbortError'});
|
||||
|
||||
prompts.unshift(options.system || this.ai.options.llm?.system || '');
|
||||
const resp = await this.models[m].ask(message, {...options, tools, system: prompts.filter(Boolean).join('\n\n')});
|
||||
request = this.models[m].ask(message, {...options, tools, system: prompts.filter(Boolean).join('\n\n')});
|
||||
let resp = await request;
|
||||
|
||||
// Spice delegated agents response into history
|
||||
let lastDelegateResp: string | null = null;
|
||||
if(pendingDelegates.size) {
|
||||
for(let i = 0; i < history.length; i++) {
|
||||
const h: any = history[i];
|
||||
if(h.role !== 'tool' || !pendingDelegates.has(h.id)) continue;
|
||||
const {resp: delegateResp, subHistory} = pendingDelegates.get(h.id)!;
|
||||
pendingDelegates.delete(h.id);
|
||||
const insert: LLMMessage[] = [...subHistory.filter(sh => sh.role === 'tool'), {role: 'assistant', content: delegateResp, timestamp: Date.now()}];
|
||||
history.splice(i + 1, 0, ...insert);
|
||||
lastDelegateResp = delegateResp;
|
||||
i += insert.length;
|
||||
}
|
||||
}
|
||||
|
||||
// If the orchestrator added no commentary of its own, its answer IS the delegate's answer
|
||||
if(typeof resp === 'string' && !resp.trim() && lastDelegateResp !== null) resp = lastDelegateResp;
|
||||
|
||||
// Trim memory injections from history
|
||||
if(options.memory) {
|
||||
history.splice(0, history.length, ...history.filter(h => h.role !== 'tool' || h.name !== 'recall'));
|
||||
}
|
||||
if(mem?.tool) history.splice(0, history.length, ...history.filter(h => h.role !== 'tool' || h.name !== 'memory_recall'));
|
||||
|
||||
// Auto-memorize before compressing
|
||||
if(options.compress && this.estimateTokens(history) >= options.compress.max) {
|
||||
if(options.memory) await this.memoryManager.memorize(history, options.memory, {model: options.memoryModel || this.defaultModel, ...options});
|
||||
if(mem?.update) await this.memoryManager.memorize(history, mem.memory, {model: options.memoryModel || this.defaultModel, ...options});
|
||||
const compressed = await this.compressHistory(history, options.compress.max, options.compress.min, options);
|
||||
if(options.history) options.history.splice(0, options.history.length, ...compressed);
|
||||
}
|
||||
|
||||
return res(resp);
|
||||
}), {abort});
|
||||
return resp;
|
||||
})();
|
||||
|
||||
return Object.assign(promise, {abort});
|
||||
}
|
||||
|
||||
/**
|
||||
* Digest full conversation history into memory documents.
|
||||
* Call on session end to persist the conversation.
|
||||
*/
|
||||
async updateMemory(history: LLMMessage[], memories: Memory[] | MemoryCache, options: LLMRequest = {}): Promise<void> {
|
||||
await this.memoryManager.memorize(history, memories, {model: this.defaultModel, ...options});
|
||||
async updateMemory(history: LLMMessage[], memories: Memory[] | MemoryCache, options: LLMRequest = {}): Promise<Memory[]> {
|
||||
return this.memoryManager.memorize(history, memories, {model: this.defaultModel, ...options});
|
||||
}
|
||||
|
||||
/**
|
||||
@@ -383,15 +510,33 @@ ${r.content}
|
||||
* @param {string} searchTerms Multiple search terms to check against target
|
||||
* @returns {{avg: number, max: number, similarities: number[]}} Similarity values 0-1: 0 = unique, 1 = identical
|
||||
*/
|
||||
fuzzyMatch(target: string, ...searchTerms: string[]) {
|
||||
if(searchTerms.length < 2) throw new Error('Requires at least 2 strings to compare');
|
||||
const vector = (text: string, dimensions: number = 10): number[] => {
|
||||
return text.toLowerCase().split('').map((char, index) =>
|
||||
(char.charCodeAt(0) * (index + 1)) % dimensions / dimensions).slice(0, dimensions);
|
||||
}
|
||||
const v = vector(target);
|
||||
const similarities = searchTerms.map(t => vector(t)).map(refVector => this.cosineSimilarity(v, refVector));
|
||||
return {avg: similarities.reduce((acc, s) => acc + s, 0) / similarities.length, max: Math.max(...similarities), similarities};
|
||||
fuzzyMatch(target, ...searchTerms) {
|
||||
if (searchTerms.length < 2) throw new Error('Requires at least 2 strings to compare');
|
||||
const levenshtein = (a, b) => {
|
||||
const m = a.length, n = b.length;
|
||||
if (!m) return n;
|
||||
if (!n) return m;
|
||||
const dp = Array.from({length: m + 1}, (_, i) => [i, ...Array(n).fill(0)]);
|
||||
for (let j = 0; j <= n; j++) dp[0][j] = j;
|
||||
for (let i = 1; i <= m; i++) {
|
||||
for (let j = 1; j <= n; j++) {
|
||||
dp[i][j] = a[i - 1] === b[j - 1]
|
||||
? dp[i - 1][j - 1]
|
||||
: 1 + Math.min(dp[i - 1][j - 1], dp[i - 1][j], dp[i][j - 1]);
|
||||
}
|
||||
}
|
||||
return dp[m][n];
|
||||
};
|
||||
const similarity = (a, b) => {
|
||||
a = a.toLowerCase(); b = b.toLowerCase();
|
||||
return 1 - levenshtein(a, b) / Math.max(a.length, b.length, 1);
|
||||
};
|
||||
const similarities = searchTerms.map(t => similarity(target, t));
|
||||
return {
|
||||
avg: similarities.reduce((acc, s) => acc + s, 0) / similarities.length,
|
||||
max: Math.max(...similarities),
|
||||
similarities
|
||||
};
|
||||
}
|
||||
|
||||
/**
|
||||
|
||||
803
src/memory.ts
803
src/memory.ts
@@ -1,92 +1,80 @@
|
||||
import {LLMRequest, LLMMessage} from './llm.ts';
|
||||
import {AiTool} from './tools.ts';
|
||||
import {KDTree, KDPoint} from './kd-tree.ts';
|
||||
|
||||
export type Memory = {
|
||||
name: string;
|
||||
description: string;
|
||||
content: string;
|
||||
embedding: number[];
|
||||
links: string[];
|
||||
backlinks: string[];
|
||||
}
|
||||
|
||||
type MemoryRef = {
|
||||
name: string;
|
||||
description: string;
|
||||
}
|
||||
|
||||
type FactBucket = {
|
||||
subject: string;
|
||||
facts: string[];
|
||||
}
|
||||
|
||||
export type MemoryNode = {
|
||||
name: string;
|
||||
missing: boolean;
|
||||
links: string[];
|
||||
backlinks: string[];
|
||||
}
|
||||
import {KDPoint, KDTree} from './kd-tree.ts';
|
||||
|
||||
export function buildMemoryGraph(memories: Memory[] | MemoryCache): MemoryNode[] {
|
||||
const mems = memories instanceof MemoryCache ? memories.memories : memories;
|
||||
const nameSet = new Set(mems.map(m => m.name));
|
||||
const ghosts = new Set<string>();
|
||||
|
||||
for (const m of mems) {
|
||||
for (const link of m.links) {
|
||||
const nodes: MemoryNode[] = mems.map(m => {
|
||||
const {links, backlinks} = extractMetadata(m.content);
|
||||
return {
|
||||
name: m.name,
|
||||
missing: false,
|
||||
links,
|
||||
backlinks,
|
||||
};
|
||||
});
|
||||
|
||||
for (const node of nodes) {
|
||||
for (const link of node.links) {
|
||||
if (!nameSet.has(link)) ghosts.add(link);
|
||||
}
|
||||
}
|
||||
|
||||
return [
|
||||
...mems.map(m => ({
|
||||
name: m.name,
|
||||
missing: false,
|
||||
links: m.links,
|
||||
backlinks: m.backlinks,
|
||||
})),
|
||||
...nodes,
|
||||
...[...ghosts].map(name => ({
|
||||
name,
|
||||
missing: true,
|
||||
links: [],
|
||||
backlinks: mems
|
||||
.filter(m => m.links.includes(name))
|
||||
.map(m => m.name),
|
||||
backlinks: nodes
|
||||
.filter(n => n.links.includes(name))
|
||||
.map(n => n.name),
|
||||
}))
|
||||
];
|
||||
}
|
||||
|
||||
function extractLinks(content: string): string[] {
|
||||
const matches = content.matchAll(/\[\[([^\]]+)\]\]/g);
|
||||
return [...new Set([...matches].map(m => m[1].trim()))];
|
||||
}
|
||||
export function renderMemoryGraph(nodes) {
|
||||
if (!nodes.length) return 'No memories yet.';
|
||||
|
||||
function rebuildBacklinks(memories: Memory[]): void {
|
||||
for (const m of memories) m.backlinks = [];
|
||||
for (const m of memories) {
|
||||
for (const link of m.links) {
|
||||
const target = memories.find(t => t.name === link);
|
||||
if (target) target.backlinks.push(m.name);
|
||||
}
|
||||
const groups = new Map();
|
||||
for (const node of nodes) {
|
||||
const [prefix, ...rest] = node.name.split('/');
|
||||
const group = rest.length ? prefix : 'Root';
|
||||
const label = rest.length ? rest.join('/') : node.name;
|
||||
if (!groups.has(group)) groups.set(group, []);
|
||||
groups.get(group).push({...node, label});
|
||||
}
|
||||
}
|
||||
|
||||
function cosineDistance(a: number[], b: number[]): number {
|
||||
let dot = 0, normA = 0, normB = 0;
|
||||
for (let i = 0; i < a.length; i++) {
|
||||
dot += a[i] * b[i];
|
||||
normA += a[i] * a[i];
|
||||
normB += b[i] * b[i];
|
||||
const ghostCount = nodes.filter(n => n.missing).length;
|
||||
const lines = [`Memory Graph (${nodes.length} nodes, ${ghostCount} ghost${ghostCount === 1 ? '' : 's'})`, ''];
|
||||
|
||||
for (const group of [...groups.keys()].sort()) {
|
||||
const items = groups.get(group).sort((a, b) => a.label.localeCompare(b.label));
|
||||
lines.push(`${group}/`);
|
||||
items.forEach((n, i) => {
|
||||
const last = i === items.length - 1;
|
||||
const branch = last ? '└─' : '├─';
|
||||
const pad = last ? ' ' : '│ ';
|
||||
const tag = n.missing ? ' (ghost)' : '';
|
||||
lines.push(` ${branch} ${n.label}${tag}`);
|
||||
if (n.links.length) lines.push(` ${pad} → ${n.links.join(', ')}`);
|
||||
if (n.backlinks.length) lines.push(` ${pad} ← ${n.backlinks.join(', ')}`);
|
||||
});
|
||||
lines.push('');
|
||||
}
|
||||
const denom = Math.sqrt(normA) * Math.sqrt(normB);
|
||||
return denom === 0 ? 1 : 1 - dot / denom;
|
||||
|
||||
return lines.join('\n').trimEnd();
|
||||
}
|
||||
|
||||
export class MemoryCache {
|
||||
private tree: KDTree<MemoryRef>;
|
||||
public memories: Memory[];
|
||||
|
||||
get length() { return this.memories.length; }
|
||||
|
||||
constructor(memories: Memory[]) {
|
||||
this.memories = memories;
|
||||
this.tree = this.buildTree();
|
||||
@@ -94,7 +82,7 @@ export class MemoryCache {
|
||||
|
||||
private buildTree(): KDTree<MemoryRef> {
|
||||
const embedded = this.memories.filter(m => m.embedding?.length);
|
||||
if(!embedded.length) return new KDTree<MemoryRef>(0);
|
||||
if (!embedded.length) return new KDTree<MemoryRef>(0);
|
||||
|
||||
const dims = embedded[0].embedding.length;
|
||||
const points: KDPoint<MemoryRef>[] = embedded.map(m => ({
|
||||
@@ -125,102 +113,370 @@ export class MemoryCache {
|
||||
this.rebuild();
|
||||
}
|
||||
|
||||
remove(name: string): void {
|
||||
const idx = this.memories.findIndex(m => m.name === name);
|
||||
if (idx !== -1) {
|
||||
this.memories.splice(idx, 1);
|
||||
this.rebuild();
|
||||
}
|
||||
}
|
||||
|
||||
rebuild(): void {
|
||||
this.tree = this.buildTree();
|
||||
}
|
||||
}
|
||||
|
||||
rebuildLinks(): void {
|
||||
rebuildBacklinks(this.memories);
|
||||
export type MemoryOptions = {
|
||||
/** Memory object */
|
||||
memory: Memory[] | MemoryCache;
|
||||
/** Inject N memories into the system prompt */
|
||||
inject?: boolean;
|
||||
/** expose recall tool to LLM */
|
||||
tool?: boolean;
|
||||
/** Update memory on compression */
|
||||
update?: boolean;
|
||||
/** Max context size of memories to inject to each call (removed immediately after use) */
|
||||
maxTokens?: number;
|
||||
}
|
||||
|
||||
export type Memory = {
|
||||
name: string;
|
||||
description: string;
|
||||
content: string;
|
||||
embedding: number[];
|
||||
}
|
||||
|
||||
export type MemoryRef = {
|
||||
name: string;
|
||||
description: string;
|
||||
}
|
||||
|
||||
export type FactBucket = {
|
||||
subject: string;
|
||||
facts: string[];
|
||||
}
|
||||
|
||||
export type MemoryNode = {
|
||||
name: string;
|
||||
missing: boolean;
|
||||
links: string[];
|
||||
backlinks: string[];
|
||||
}
|
||||
|
||||
function extractLinks(content: string): string[] {
|
||||
if(!content) return [];
|
||||
const matches = content.matchAll(/\[\[([^\]]+)\]\]/g);
|
||||
return [...new Set([...matches].map(m => m[1].trim()))];
|
||||
}
|
||||
|
||||
export function extractMetadata(content: string): {links: string[], backlinks: string[]} {
|
||||
const match = content.match(/^---\n([\s\S]*?)\n---/);
|
||||
if (!match) return {links: [], backlinks: []};
|
||||
|
||||
const fm = match[1];
|
||||
const getList = (key: string): string[] => {
|
||||
const m = fm.match(new RegExp(`^${key}:\\s*\\[(.*)\\]$`, 'm'));
|
||||
if (!m || !m[1].trim()) return [];
|
||||
return m[1].split(',').map(s => s.trim().replace(/^"|"$/g, '')).filter(Boolean);
|
||||
};
|
||||
|
||||
return {
|
||||
links: getList('links'),
|
||||
backlinks: getList('backlinks'),
|
||||
};
|
||||
}
|
||||
|
||||
function dedupeFacts(facts: string[]): string[] {
|
||||
const seen = new Map<string, string>();
|
||||
for (const f of facts) {
|
||||
const clean = f.trim();
|
||||
if (clean) seen.set(clean.toLowerCase(), clean);
|
||||
}
|
||||
return [...seen.values()];
|
||||
}
|
||||
|
||||
function cosineDistance(a: number[], b: number[]): number {
|
||||
let dot = 0, normA = 0, normB = 0;
|
||||
for (let i = 0; i < a.length; i++) {
|
||||
dot += a[i] * b[i];
|
||||
normA += a[i] * a[i];
|
||||
normB += b[i] * b[i];
|
||||
}
|
||||
const denom = Math.sqrt(normA) * Math.sqrt(normB);
|
||||
return denom === 0 ? 1 : 1 - dot / denom;
|
||||
}
|
||||
|
||||
function getWeekMonday(date: Date = new Date()): string {
|
||||
const d = new Date(Date.UTC(date.getFullYear(), date.getMonth(), date.getDate()));
|
||||
const day = d.getUTCDay();
|
||||
const diff = day === 0 ? -6 : 1 - day;
|
||||
d.setUTCDate(d.getUTCDate() + diff);
|
||||
return d.toISOString().slice(0, 10);
|
||||
}
|
||||
|
||||
function getWeekSunday(monday: string): string {
|
||||
const d = new Date(`${monday}T00:00:00Z`);
|
||||
d.setUTCDate(d.getUTCDate() + 6);
|
||||
return d.toISOString().slice(0, 10);
|
||||
}
|
||||
|
||||
export class MemoryManager {
|
||||
private recentlyTouched = new Map<string, number>();
|
||||
|
||||
private pendingMemorizations = new Map<string, {
|
||||
memories: Memory[] | MemoryCache,
|
||||
tempMemoryName: string,
|
||||
timestamp: number,
|
||||
}>();
|
||||
|
||||
private queues = new Map<string, {
|
||||
pending: string[],
|
||||
request: {abort?: () => void} | null,
|
||||
task: Promise<void>,
|
||||
}>();
|
||||
|
||||
tools = {
|
||||
read: (memories: Memory[] | MemoryCache): AiTool => ({
|
||||
name: 'read_memory',
|
||||
name: 'memory_recall',
|
||||
description: 'Read the full content of a memory document',
|
||||
args: {
|
||||
name: {type: 'string', description: 'Exact memory name', required: true},
|
||||
},
|
||||
fn:(args: any) => {
|
||||
fn: (args: any) => {
|
||||
const mems = memories instanceof MemoryCache ? memories.memories : memories;
|
||||
const mem = mems.find(m => m.name === args.name);
|
||||
if(!mem) return 'Document not found';
|
||||
return this.formatMemory(mem);
|
||||
}
|
||||
if (!mem) return 'Document not found';
|
||||
this.touch(mem.name);
|
||||
return mem.content;
|
||||
},
|
||||
}),
|
||||
|
||||
forget: (memories: Memory[] | MemoryCache): AiTool => ({
|
||||
name: 'memory_forget',
|
||||
description: 'Permanently delete a memory document and clean up all references to it',
|
||||
args: {
|
||||
name: {type: 'string', description: 'Exact memory name to forget', required: true}
|
||||
},
|
||||
fn: (args: any) => {
|
||||
const result = this.forget(args.name, memories);
|
||||
return result ? `Forgotten: ${args.name}` : `Not found: ${args.name}`;
|
||||
},
|
||||
}),
|
||||
};
|
||||
|
||||
constructor(private llm: any) {}
|
||||
|
||||
static normalize(m?: Memory[] | MemoryCache | MemoryOptions) {
|
||||
if(!m) return null;
|
||||
const raw = m instanceof MemoryCache || Array.isArray(m);
|
||||
return raw ? {memory: <Memory[] | MemoryCache>m, inject: true, tool: true, update: true} : {inject: true, tool: true, update: true, ...m};
|
||||
}
|
||||
|
||||
private async createTempMemory(conversation: string): Promise<Memory> {
|
||||
const timestamp = Date.now();
|
||||
const content = `---
|
||||
name: _temp_${timestamp}
|
||||
description: Temporary memory - processing in background
|
||||
tags: [_temporary]
|
||||
links: []
|
||||
backlinks: []
|
||||
modified: ${new Date().toISOString()}
|
||||
---
|
||||
|
||||
# Recent Conversation (Processing)
|
||||
|
||||
${conversation}`;
|
||||
const [e] = await this.llm.embedding(content);
|
||||
return {
|
||||
name: `_temp_${timestamp}`,
|
||||
description: 'Temporary memory - processing in background',
|
||||
content,
|
||||
embedding: e?.embedding || [],
|
||||
};
|
||||
}
|
||||
|
||||
private applyHeader(content: string, header: string): string {
|
||||
return `${header}\n\n${this.stripHeader(content)}`;
|
||||
}
|
||||
|
||||
private async backgroundMemorization(conversation: string, memories: Memory[] | MemoryCache, options: LLMRequest, tempName: string): Promise<void> {
|
||||
const mem = memories instanceof MemoryCache ? memories.memories : memories;
|
||||
const monday = getWeekMonday();
|
||||
const sunday = getWeekSunday(monday);
|
||||
const buckets = await this.factAgent(conversation, mem, options, monday);
|
||||
if(!buckets.length) return;
|
||||
const jobs = [...buckets].map(({subject, facts}) => {
|
||||
let node = mem.find(m => m.name === subject);
|
||||
if(!node) {
|
||||
node = {name: subject, description: '', content: '', embedding: [],};
|
||||
mem.push(node);
|
||||
}
|
||||
const week = subject.startsWith('Journal/') ? {monday, sunday} : undefined;
|
||||
return this.enqueue(node, facts, mem, options, tempName, week);
|
||||
});
|
||||
await Promise.all(jobs);
|
||||
}
|
||||
|
||||
private buildHeader(node: Memory, week?: {monday: string, sunday: string}, links: string[] = [], backlinks: string[] = []): string {
|
||||
const tags = node.name.split('/')[0]?.toLowerCase();
|
||||
const lines = [
|
||||
'---',
|
||||
`name: ${node.name}`,
|
||||
`description: ${node.description || ''}`,
|
||||
tags ? `tags: [${tags}]` : '',
|
||||
links.length ? `links: [${links.map(l => `"${l}"`).join(', ')}]` : 'links: []',
|
||||
backlinks.length ? `backlinks: [${backlinks.map(l => `"${l}"`).join(', ')}]` : 'backlinks: []',
|
||||
week ? `week: ${week.monday} – ${week.sunday}` : '',
|
||||
`modified: ${new Date().toISOString()}`,
|
||||
'---',
|
||||
].filter(Boolean);
|
||||
return lines.join('\n');
|
||||
}
|
||||
|
||||
private cosineSearch(query: number[], memories: Memory[], limit: number): MemoryRef[] {
|
||||
const scored = memories
|
||||
.filter(m => m.embedding?.length)
|
||||
.map(m => ({
|
||||
ref: {name: m.name, description: m.description},
|
||||
distance: cosineDistance(query, m.embedding)
|
||||
distance: cosineDistance(query, m.embedding),
|
||||
}))
|
||||
.sort((a, b) => a.distance - b.distance)
|
||||
.slice(0, limit);
|
||||
return scored.map(s => s.ref);
|
||||
}
|
||||
|
||||
private createNode(name: string, memories: Memory[]): Memory {
|
||||
const existing = memories.find(m => m.name === name);
|
||||
if(existing) return existing;
|
||||
return {
|
||||
name,
|
||||
description: '',
|
||||
content: '',
|
||||
embedding: [],
|
||||
links: [],
|
||||
backlinks: [],
|
||||
};
|
||||
}
|
||||
/**
|
||||
* Coalescing queue: if a doc is already compiling, abort the in-flight run, merge its
|
||||
* facts with the new ones and restart. Never blocks a pending update, never drops facts.
|
||||
*/
|
||||
private enqueue(node: Memory, facts: string[], memories: Memory[] | MemoryCache, options: LLMRequest, tempName: string, week?: {monday: string, sunday: string}): Promise<void> {
|
||||
const key = node.name;
|
||||
const existing = this.queues.get(key);
|
||||
if (existing) {
|
||||
existing.pending.push(...facts);
|
||||
existing.request?.abort?.();
|
||||
return existing.task;
|
||||
}
|
||||
|
||||
private formatMemory(mem: Memory): string {
|
||||
return [
|
||||
`# ${mem.name}`,
|
||||
mem.description ? `> ${mem.description}` : '',
|
||||
mem.links.length ? `**Links:** ${mem.links.map(l => `[[${l}]]`).join(', ')}` : '',
|
||||
mem.backlinks.length ? `**Referenced by:** ${mem.backlinks.map(l => `[[${l}]]`).join(', ')}` : '',
|
||||
'',
|
||||
mem.content,
|
||||
].filter(l => l !== undefined).join('\n');
|
||||
const entry: {pending: string[], request: {abort?: () => void} | null, task: Promise<void>} = {pending: [...facts], request: null, task: Promise.resolve()};
|
||||
this.queues.set(key, entry);
|
||||
const m = memories instanceof MemoryCache ? memories.memories : memories;
|
||||
entry.task = (async () => {
|
||||
while (entry.pending.length) {
|
||||
const batch = dedupeFacts(entry.pending.splice(0, entry.pending.length));
|
||||
const written = await this.docAgent(node, batch, m, options, tempName, week, entry);
|
||||
if (!written) entry.pending.unshift(...batch);
|
||||
}
|
||||
})().finally(() => {
|
||||
this.queues.delete(key);
|
||||
if(!this.queues.size && memories instanceof MemoryCache) memories.rebuild();
|
||||
});
|
||||
return entry.task;
|
||||
}
|
||||
|
||||
private listNodes(memories: Memory[]): MemoryRef[] {
|
||||
return memories.map(m => ({name: m.name, description: m.description}));
|
||||
}
|
||||
|
||||
decay() {
|
||||
for(const [name, ttl] of this.recentlyTouched) {
|
||||
if(ttl <= 1) this.recentlyTouched.delete(name);
|
||||
else this.recentlyTouched.set(name, ttl - 1);
|
||||
}
|
||||
}
|
||||
|
||||
forget(name: string, memories: Memory[] | MemoryCache): boolean {
|
||||
const mem = memories instanceof MemoryCache ? memories.memories : memories;
|
||||
const idx = mem.findIndex(m => m.name === name);
|
||||
if (idx === -1) return false;
|
||||
|
||||
for (const node of mem) {
|
||||
const {links, backlinks} = extractMetadata(node.content);
|
||||
const newBacklinks = backlinks.filter(b => b !== name);
|
||||
const newLinks = links.filter(l => l !== name);
|
||||
|
||||
if (newBacklinks.length !== backlinks.length || newLinks.length !== links.length) {
|
||||
node.content = this.updateFrontmatter(node.content, {
|
||||
links: newLinks,
|
||||
backlinks: newBacklinks,
|
||||
});
|
||||
}
|
||||
}
|
||||
|
||||
mem.splice(idx, 1);
|
||||
|
||||
if (memories instanceof MemoryCache) memories.rebuild();
|
||||
return true;
|
||||
}
|
||||
|
||||
getTouched(): string[] {
|
||||
return [...this.recentlyTouched.keys()];
|
||||
}
|
||||
|
||||
async memorize(history: LLMMessage[], memories: Memory[] | MemoryCache, options: LLMRequest): Promise<Memory[]> {
|
||||
const conversation = history
|
||||
.filter(h => h.role === 'user' || h.role === 'assistant')
|
||||
.map(h => `[${h.role}]: ${h.content}`).join('\n\n').trim();
|
||||
if(!conversation) return [];
|
||||
|
||||
const trackingId = `${Date.now()}_${Math.random()}`;
|
||||
const tempMemory = await this.createTempMemory(conversation);
|
||||
const mem = memories instanceof MemoryCache ? memories.memories : memories;
|
||||
mem.push(tempMemory);
|
||||
if (memories instanceof MemoryCache) memories.rebuild();
|
||||
this.pendingMemorizations.set(trackingId, {
|
||||
memories,
|
||||
tempMemoryName: tempMemory.name,
|
||||
timestamp: Date.now(),
|
||||
});
|
||||
|
||||
try {
|
||||
await this.backgroundMemorization(conversation, memories, options, tempMemory.name);
|
||||
const finalMem = memories instanceof MemoryCache ? memories.memories : memories;
|
||||
return finalMem.filter(m => !m.name.startsWith('_temp_'));
|
||||
} finally {
|
||||
const pending = this.pendingMemorizations.get(trackingId);
|
||||
if (pending) {
|
||||
const cleanMem = pending.memories instanceof MemoryCache
|
||||
? pending.memories.memories
|
||||
: pending.memories;
|
||||
const idx = cleanMem.findIndex(m => m.name === pending.tempMemoryName);
|
||||
if (idx !== -1) cleanMem.splice(idx, 1);
|
||||
if (pending.memories instanceof MemoryCache) pending.memories.rebuild();
|
||||
}
|
||||
this.pendingMemorizations.delete(trackingId);
|
||||
}
|
||||
}
|
||||
|
||||
async recollect(query: string, memories: Memory[] | MemoryCache, limit = 5, graphDepth = 1): Promise<Memory[]> {
|
||||
const mem: Memory[] = memories instanceof MemoryCache ? memories.memories : memories;
|
||||
if(!mem.length) return [];
|
||||
if (!mem.length) return [];
|
||||
|
||||
const [e] = await this.llm.embedding(query);
|
||||
if(!e) return [];
|
||||
if (!e) return [];
|
||||
|
||||
let vectorResults: MemoryRef[];
|
||||
if(memories instanceof MemoryCache) vectorResults = memories.search(e.embedding, limit);
|
||||
if (memories instanceof MemoryCache) vectorResults = memories.search(e.embedding, limit);
|
||||
else vectorResults = this.cosineSearch(e.embedding, mem, limit);
|
||||
const found = new Set<string>(vectorResults.map(r => r.name));
|
||||
|
||||
if(graphDepth > 0) {
|
||||
if (graphDepth > 0) {
|
||||
const frontier = [...found];
|
||||
for(let depth = 0; depth < graphDepth; depth++) {
|
||||
for (let depth = 0; depth < graphDepth; depth++) {
|
||||
const next: string[] = [];
|
||||
for(const name of frontier) {
|
||||
for (const name of frontier) {
|
||||
const node = mem.find(m => m.name === name);
|
||||
if(!node) continue;
|
||||
for(const link of node.links) {
|
||||
if(!found.has(link) && mem.find(m => m.name === link)) {
|
||||
if (!node) continue;
|
||||
const {links} = extractMetadata(node.content);
|
||||
for (const link of links) {
|
||||
if (!found.has(link) && mem.find(m => m.name === link)) {
|
||||
found.add(link);
|
||||
next.push(link);
|
||||
}
|
||||
}
|
||||
}
|
||||
frontier.splice(0, frontier.length, ...next);
|
||||
if(!frontier.length) break;
|
||||
if (!frontier.length) break;
|
||||
}
|
||||
}
|
||||
|
||||
@@ -230,272 +486,157 @@ export class MemoryManager {
|
||||
return ordered.map(n => mem.find(m => m.name === n)!).filter(Boolean);
|
||||
}
|
||||
|
||||
async memorize(history: LLMMessage[], memories: Memory[] | MemoryCache, options: LLMRequest): Promise<void> {
|
||||
const mem = memories instanceof MemoryCache ? memories.memories : memories;
|
||||
const conversation = history
|
||||
.filter(h => h.role === 'user' || h.role === 'assistant')
|
||||
.map(h => `[${h.role}]: ${h.content}`).join('\n\n').trim();
|
||||
|
||||
if(conversation) {
|
||||
const buckets = await this.factAgent(conversation, mem, options);
|
||||
if(buckets.length) {
|
||||
await Promise.all(buckets.map(async bucket => {
|
||||
const node = await this.organizingAgent(bucket, mem, options);
|
||||
if(!mem.find(m => m.name === node.name)) mem.push(node);
|
||||
await this.docAgent(node, bucket, mem, options);
|
||||
}));
|
||||
}
|
||||
}
|
||||
|
||||
// Auto-compress old journals
|
||||
const weekAgo = Date.now() - (7 * 24 * 60 * 60 * 1000);
|
||||
const oldDailies = mem.filter(m => {
|
||||
const journal = /^Journal\/(\d{4}-\d{2}-\d{2}$)/.exec(m.name);
|
||||
return journal && new Date(journal[1]).getTime() < weekAgo;
|
||||
});
|
||||
|
||||
if(oldDailies.length) {
|
||||
const byMonth = new Map<string, Memory[]>();
|
||||
for(const daily of oldDailies) {
|
||||
const match = daily.name.match(/^Journal\/(\d{4}-\d{2})-\d{2}$/);
|
||||
if(!match) continue;
|
||||
const monthKey = match[1];
|
||||
if(!byMonth.has(monthKey)) byMonth.set(monthKey, []);
|
||||
byMonth.get(monthKey)!.push(daily);
|
||||
}
|
||||
|
||||
for(const [monthKey, entries] of byMonth) {
|
||||
const monthlyPath = `Journal/${monthKey}`;
|
||||
let monthly = mem.find(m => m.name === monthlyPath);
|
||||
if(!monthly) {
|
||||
monthly = this.createNode(monthlyPath, mem);
|
||||
mem.push(monthly);
|
||||
}
|
||||
|
||||
const bucket: FactBucket = {
|
||||
subject: monthlyPath,
|
||||
facts: entries.flatMap(e => e.content.split('\n').filter(line => line.trim())),
|
||||
};
|
||||
|
||||
await this.docAgent(monthly, bucket, mem, options);
|
||||
for(const daily of entries) {
|
||||
const idx = mem.indexOf(daily);
|
||||
if(idx !== -1) mem.splice(idx, 1);
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
if (memories instanceof MemoryCache) {
|
||||
memories.rebuildLinks();
|
||||
memories.rebuild();
|
||||
} else {
|
||||
rebuildBacklinks(mem);
|
||||
}
|
||||
touch(name: string, ttl = 2) {
|
||||
this.recentlyTouched.set(name, ttl);
|
||||
}
|
||||
|
||||
private async docAgent(node: Memory, bucket: FactBucket, memories: Memory[], options: LLMRequest): Promise<void> {
|
||||
let finalContent = node.content;
|
||||
const isJournalCompression = node.name.match(/^Journal\/\d{4}-\d{2}$/);
|
||||
const systemPrompt = isJournalCompression
|
||||
? `You are a journal compressor. Condense the daily entries below into a monthly summary.
|
||||
private updateFrontmatter(content: string, updates: {links?: string[], backlinks?: string[]}): string {
|
||||
const match = content.match(/^---\n([\s\S]*?)\n---\n\n?([\s\S]*)$/);
|
||||
if (!match) return content;
|
||||
|
||||
Format:
|
||||
# ${node.name}
|
||||
const [, fm, body] = match;
|
||||
let newFm = fm;
|
||||
|
||||
## Themes
|
||||
(Recurring topics, moods, patterns)
|
||||
if (updates.links !== undefined) {
|
||||
const linksList = updates.links.length ? `[${updates.links.map(l => `"${l}"`).join(', ')}]` : '[]';
|
||||
newFm = newFm.replace(/^links:.*$/m, `links: ${linksList}`);
|
||||
}
|
||||
|
||||
## Key Events
|
||||
(Important moments, decisions, milestones)
|
||||
if (updates.backlinks !== undefined) {
|
||||
const backlinksList = updates.backlinks.length ? `[${updates.backlinks.map(l => `"${l}"`).join(', ')}]` : '[]';
|
||||
newFm = newFm.replace(/^backlinks:.*$/m, `backlinks: ${backlinksList}`);
|
||||
}
|
||||
|
||||
## Notable Conversations
|
||||
(Significant discussions or revelations)
|
||||
newFm = newFm.replace(/^modified:.*$/m, `modified: ${new Date().toISOString()}`);
|
||||
|
||||
Rules:
|
||||
- Use [[WikiLinks]] to reference permanent notes using full paths like [[People/Sarah]] or [[Projects/Website]]
|
||||
- Keep it concise but preserve emotional/temporal context
|
||||
- Discard filler but keep things the user vented about or cared about
|
||||
- If a fact belongs in a permanent note, link to it instead of duplicating
|
||||
return `---\n${newFm}\n---\n\n${body}`;
|
||||
}
|
||||
|
||||
Current monthly summary:
|
||||
\`\`\`markdown
|
||||
${node.content || '(empty — first compression for this month)'}
|
||||
\`\`\``
|
||||
: `You are a knowledge base editor. Integrate the provided facts into the document below.
|
||||
private stripHeader(content: string): string {
|
||||
return content.replace(/^---[\s\S]*?\n---\n?/, '').trimStart();
|
||||
}
|
||||
|
||||
private async docAgent(node: Memory, facts: string[], memories: Memory[], options: LLMRequest, tempName: string, week: {monday: string, sunday: string} | undefined, entry: {request: {abort?: () => void} | null}): Promise<boolean> {
|
||||
const {links: oldLinks} = extractMetadata(node.content);
|
||||
const currentBody = this.stripHeader(node.content);
|
||||
let update;
|
||||
try {
|
||||
for(let i = 0; i < 3 && !update?.content; i++) {
|
||||
const request = this.llm.ask(`New Facts:\n${facts.map(f => `- ${f}`).join('\n')}`, {
|
||||
model: options.model,
|
||||
temperature: 0.3,
|
||||
schema: {
|
||||
description: {type: 'string', description: 'One-line description of what this document covers, no formatting or emojis', required: true},
|
||||
content: {type: 'string', description: 'Rewritten document in markdown, without the frontmatter block', required: true},
|
||||
},
|
||||
system: `You are a knowledge base editor. Rewrite the current document below so it incorporates the new facts.
|
||||
|
||||
Formatting rules:
|
||||
- Use Obsidian-style markdown: # headings, **bold** for key terms, bullet lists for facts
|
||||
- Use Obsidian-style markdown: # headings, **bold** to add emphasis, __italics__ for titles, terms, etc, bullet & numbered lists for grouped 1D data and tables for 2D data
|
||||
- Link related concepts with [[WikiLink]] notation using full paths like [[People/Sarah]] or [[Projects/Website]]
|
||||
- You may create links to nodes that don't exist yet if the concept is important
|
||||
- Create links for specific entities (person, place, project, program) and abstract concepts (quantum mechanics, entropy) but skip generics (car, red, dog)
|
||||
- Keep the document concise, factual, and human-readable
|
||||
- Resolve any contradictions between old content and new facts (new facts win)
|
||||
- Do not add filler, preamble, or AI commentary — just clean knowledge documents
|
||||
|
||||
- Resolve contradictions: the new facts always win — delete the outdated statement entirely, never keep both
|
||||
- Later facts in the list override earlier ones
|
||||
- Do not add frontmatter blocks, filler, preamble, or AI commentary
|
||||
${week ? '- This is a weekly journal entry.\n' : ''}
|
||||
All nodes:
|
||||
${this.listNodes(memories).map(n => n.name).join(', ') || 'none'}
|
||||
|
||||
Current document:
|
||||
\`\`\`markdown
|
||||
${node.content || '(empty — this is a new document)'}
|
||||
\`\`\``;
|
||||
|
||||
await this.llm.ask(
|
||||
`New facts to integrate:\n${bucket.facts.map(f => `- ${f}`).join('\n')}`,
|
||||
{
|
||||
model: options.model,
|
||||
temperature: 0.3,
|
||||
system: systemPrompt,
|
||||
tools: [{
|
||||
name: 'update_document',
|
||||
description: 'Write the complete updated document content',
|
||||
args: {
|
||||
description: {type: 'string', description: 'One-line description of what this document covers, no formatting or emojis', required: true},
|
||||
content: {type: 'string', description: 'Fully updated document in markdown', required: true},
|
||||
},
|
||||
fn:(args: any) => {
|
||||
node.description = args.description;
|
||||
finalContent = args.content;
|
||||
return 'Saved';
|
||||
}
|
||||
}]
|
||||
${currentBody}
|
||||
\`\`\``}
|
||||
);
|
||||
entry.request = request;
|
||||
update = await request;
|
||||
}
|
||||
);
|
||||
|
||||
node.content = finalContent;
|
||||
node.links = extractLinks(finalContent);
|
||||
const needsEmbed = !node.embedding?.length || node.description !== memories.find(m => m.name === node.name)?.description;
|
||||
if (needsEmbed) {
|
||||
const [e] = await this.llm.embedding(node.description);
|
||||
if (e) node.embedding = e.embedding;
|
||||
} catch (err: any) {
|
||||
if (err?.name === 'AbortError') return false;
|
||||
throw err;
|
||||
} finally {
|
||||
entry.request = null;
|
||||
}
|
||||
|
||||
if(!update?.content) return false;
|
||||
const newLinks = extractLinks(update.content).filter(l => l !== node.name && l !== tempName);
|
||||
const newLinkSet = new Set(newLinks);
|
||||
const oldLinkSet = new Set(oldLinks);
|
||||
|
||||
for (const added of newLinkSet) {
|
||||
if (!oldLinkSet.has(added)) {
|
||||
const target = memories.find(m => m.name === added);
|
||||
if (target) {
|
||||
const {backlinks} = extractMetadata(target.content);
|
||||
if (!backlinks.includes(node.name)) {
|
||||
target.content = this.updateFrontmatter(target.content, {
|
||||
backlinks: [...backlinks, node.name],
|
||||
});
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
for (const removed of oldLinkSet) {
|
||||
if (!newLinkSet.has(removed)) {
|
||||
const target = memories.find(m => m.name === removed);
|
||||
if (target) {
|
||||
const {backlinks} = extractMetadata(target.content);
|
||||
target.content = this.updateFrontmatter(target.content, {
|
||||
backlinks: backlinks.filter(b => b !== node.name),
|
||||
});
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
const {backlinks} = extractMetadata(node.content);
|
||||
node.description = node.name !== 'Person/User' ? update.description : 'All information about the current user';
|
||||
node.content = this.applyHeader(update.content, this.buildHeader(node, week, newLinks, backlinks));
|
||||
const [e] = await this.llm.embedding(node.content);
|
||||
if(e) node.embedding = e.embedding;
|
||||
return true;
|
||||
}
|
||||
|
||||
private async factAgent(conversation: string, memories: Memory[], options: LLMRequest): Promise<FactBucket[]> {
|
||||
const buckets: FactBucket[] = [];
|
||||
const today = new Date().toISOString().split('T')[0];
|
||||
|
||||
private async factAgent(conversation: string, memories: Memory[], options: LLMRequest, weekKey: string): Promise<FactBucket[]> {
|
||||
const buckets = new Map<string, string[]>();
|
||||
await this.llm.ask(conversation, {
|
||||
model: options.model,
|
||||
temperature: 0.2,
|
||||
system: `You are a fact extractor. Analyze this conversation and extract facts worth remembering long-term.
|
||||
|
||||
Rules:
|
||||
- ONLY extract facts the USER explicitly stated about themselves, their work, or their projects
|
||||
- ONLY extract current facts the USER explicitly stated about themselves, their work, or their projects
|
||||
- ONLY extract decisions that were MADE during this conversation
|
||||
- DO NOT extract anything the AI said, its capabilities, or meta-conversation about the AI
|
||||
- DO NOT extract greetings, pleasantries, or generic exchanges
|
||||
- DO NOT extract deltas or changes in facts; ONLY the end fact
|
||||
- If nothing worth remembering was said, do not call any tools
|
||||
|
||||
**Organizational patterns:**
|
||||
- Journal entries use paths like: Journal/${today}
|
||||
- People use paths like: People/Name
|
||||
- Projects use paths like: Projects/Name
|
||||
- Personal info uses paths like: Personal/Goals, Personal/Tasks, etc.
|
||||
- General knowledge uses paths like: Biology/Topic, History/Topic, etc.
|
||||
|
||||
Learn from existing nodes and follow the same pattern when extracting.
|
||||
|
||||
Group facts by subject. For each group call \`extract_facts\` once with the FULL PATH.
|
||||
|
||||
Known nodes (name: description):
|
||||
${this.listNodes(memories).map(n => `- ${n.name}: ${n.description}`).join('\n') || 'None yet.'}`,
|
||||
tools: [{
|
||||
name: 'extract_facts',
|
||||
description: 'Submit a group of related facts for a specific subject',
|
||||
args: {
|
||||
subject: {type: 'string', description: 'Full path for the subject (e.g., "Journal/2025-01-27", "People/Sarah", "Projects/Website")', required: true},
|
||||
facts: {type: 'string', description: 'Comma-separated list of extracted facts', required: true},
|
||||
},
|
||||
fn: (args: any) => {
|
||||
buckets.push({
|
||||
subject: args.subject,
|
||||
facts: args.facts.split(',').map((f: string) => f.trim()).filter(Boolean),
|
||||
});
|
||||
return 'Recorded';
|
||||
}
|
||||
}]
|
||||
});
|
||||
|
||||
return buckets;
|
||||
}
|
||||
|
||||
private async organizingAgent(bucket: FactBucket, memories: Memory[], options: LLMRequest): Promise<Memory> {
|
||||
let candidates = this.listNodes(memories);
|
||||
let attempts = 0;
|
||||
const maxAttempts = 3;
|
||||
|
||||
while (attempts++ < maxAttempts) {
|
||||
let home = '', mode: string | null = null;
|
||||
|
||||
const resp = await this.llm.ask(`Subject: ${bucket.subject}\n\nFacts:\n${bucket.facts.map(f => `- ${f}`).join('\n')}`, {
|
||||
model: options.model,
|
||||
temperature: 0.1,
|
||||
system: `You are a knowledge organizer. Your job is to find the correct home for the supplied facts.
|
||||
|
||||
1. Review the facts and the node list below. Pick the most likely match or decide if a new node is needed.
|
||||
2. If you picked an existing node, use \`read\` to verify it's the right place.
|
||||
- After reading, call either \`confirm\` (correct node) or \`mismatched\` (wrong node).
|
||||
3. If none of the nodes match, call \`create\` to make a new node.
|
||||
|
||||
**Organizational patterns:**
|
||||
- Journal entries: Journal/YYYY-MM-DD
|
||||
- People: People/Name
|
||||
- Projects: Projects/Name
|
||||
- Personal: Personal/Goals, Personal/Tasks, etc.
|
||||
- Knowledge: Biology/Topic, History/Topic, etc.
|
||||
When extracting facts, you MUST also decide the exact destination path:
|
||||
- Use an existing node name if the facts clearly belong there
|
||||
- All information primary about the user should go under "People/User"
|
||||
- When required, create a new path following collection/subject format (e.g., People/Sarah, Projects/Oxide)
|
||||
- For journal entries, use "Journal"
|
||||
|
||||
Available nodes:
|
||||
${candidates.map(n => `- ${n.name}: ${n.description}`).join('\n') || 'None — create a new node.'}`,
|
||||
tools: [{
|
||||
name: 'read',
|
||||
description: 'Read a node file to verify it is the right home for these facts',
|
||||
args: {name: {type: 'string', description: 'Exact node name (full path)', required: true}},
|
||||
fn: ({name}) => {
|
||||
const mem = memories.find(m => m.name === name);
|
||||
if (!mem) return 'Node not found';
|
||||
home = name;
|
||||
return this.formatMemory(mem);
|
||||
}
|
||||
}, {
|
||||
name: 'confirm',
|
||||
description: 'Confirm this is the correct node for the facts',
|
||||
args: {},
|
||||
fn: () => {
|
||||
mode = 'success';
|
||||
resp.abort();
|
||||
}
|
||||
}, {
|
||||
name: 'mismatched',
|
||||
description: 'This is not the node you are looking for',
|
||||
args: {},
|
||||
fn: () => {
|
||||
mode = 'failed';
|
||||
resp.abort();
|
||||
}
|
||||
}, {
|
||||
name: 'create',
|
||||
description: 'No existing node fits — create a new one',
|
||||
args: {
|
||||
name: {type: 'string', description: 'Full path for the new node (e.g., "People/Sarah", "Journal/2025-01-27")', required: true}
|
||||
},
|
||||
fn: ({name}) => {
|
||||
home = name;
|
||||
mode = 'create';
|
||||
resp.abort();
|
||||
}
|
||||
}]
|
||||
});
|
||||
|
||||
if(mode === 'create') {
|
||||
return this.createNode(home, memories);
|
||||
} else if (mode === 'failed') {
|
||||
candidates = candidates.filter(c => c.name !== home);
|
||||
if(!candidates.length) return this.createNode(bucket.subject, memories);
|
||||
} else if (mode === 'success') {
|
||||
const existing = memories.find(m => m.name === home);
|
||||
return existing || this.createNode(home, memories);
|
||||
}
|
||||
}
|
||||
return this.createNode(bucket.subject, memories);
|
||||
- Journal
|
||||
${this.listNodes(memories).filter(n => !n.name.includes('_temp_') && !n.name.includes('Journal')).map(n => `- ${n.name}: ${n.description}`).join('\n') || 'None yet.'}`,
|
||||
tools: [{
|
||||
name: 'facts_extract',
|
||||
description: 'Submit facts with their destination',
|
||||
args: {
|
||||
destination: {type: 'string', description: 'Exact existing node name OR new path (e.g. "People/Sarah", "Projects/Oxide")', required: true},
|
||||
facts: {type: 'string', description: 'Comma-separated facts', required: true},
|
||||
},
|
||||
fn: (args: any) => {
|
||||
const subject = args.destination.trim().toLowerCase() === 'journal'
|
||||
? `Journal/${weekKey}` : args.destination.trim();
|
||||
const facts = buckets.get(subject) ?? [];
|
||||
facts.push(...dedupeFacts(String(args.facts).split(',')));
|
||||
buckets.set(subject, facts);
|
||||
return 'Recorded';
|
||||
},
|
||||
}],
|
||||
});
|
||||
return buckets.entries().toArray().map(([subject, facts]) => ({subject, facts}));
|
||||
}
|
||||
}
|
||||
|
||||
@@ -20,20 +20,22 @@ export class OpenAi extends LLMProvider {
|
||||
for(let i = 0; i < history.length; i++) {
|
||||
const h = history[i];
|
||||
if(h.role === 'assistant' && h.tool_calls) {
|
||||
const tools = h.tool_calls.map((tc: any) => ({
|
||||
const items: any[] = [];
|
||||
if(h.content) items.push({role: 'assistant', content: h.content, timestamp: h.timestamp});
|
||||
items.push(...h.tool_calls.map((tc: any) => ({
|
||||
role: 'tool',
|
||||
id: tc.id,
|
||||
name: tc.function.name,
|
||||
args: JSONAttemptParse(tc.function.arguments, {}),
|
||||
timestamp: h.timestamp
|
||||
}));
|
||||
history.splice(i, 1, ...tools);
|
||||
i += tools.length - 1;
|
||||
} else if(h.role === 'tool' && h.content) {
|
||||
})));
|
||||
history.splice(i, 1, ...items);
|
||||
i += items.length - 1;
|
||||
} else if(h.role === 'tool') {
|
||||
const record = history.find(h2 => h.tool_call_id == h2.id);
|
||||
if(record) {
|
||||
if(h.content.includes('"error":')) record.error = h.content;
|
||||
else record.content = h.content;
|
||||
if(h.content?.includes('"error":')) record.error = h.content;
|
||||
else record.content = h.content || '';
|
||||
}
|
||||
history.splice(i, 1);
|
||||
i--;
|
||||
@@ -51,15 +53,16 @@ export class OpenAi extends LLMProvider {
|
||||
content: null,
|
||||
tool_calls: [{ id: h.id, type: 'function', function: { name: h.name, arguments: JSON.stringify(h.args) } }],
|
||||
refusal: null,
|
||||
annotations: []
|
||||
annotations: [],
|
||||
timestamp: h.timestamp,
|
||||
}, {
|
||||
role: 'tool',
|
||||
tool_call_id: h.id,
|
||||
content: h.error || h.content
|
||||
content: h.error || h.content,
|
||||
timestamp: h.timestamp,
|
||||
});
|
||||
} else {
|
||||
const {timestamp, ...rest} = h;
|
||||
result.push(rest);
|
||||
result.push(h);
|
||||
}
|
||||
return result;
|
||||
}, [] as any[]);
|
||||
@@ -68,11 +71,12 @@ export class OpenAi extends LLMProvider {
|
||||
ask(message: string, options: LLMRequest = {}): AbortablePromise<string | any> {
|
||||
const controller = new AbortController();
|
||||
return Object.assign(new Promise<any>(async (res, rej) => {
|
||||
if(options.system) {
|
||||
if(options.history?.[0]?.role != 'system') options.history?.splice(0, 0, {role: 'system', content: options.system, timestamp: Date.now()});
|
||||
else options.history[0].content = options.system;
|
||||
}
|
||||
let history = this.fromStandard([...options.history || [], {role: 'user', content: message, timestamp: Date.now()}]);
|
||||
const base = (options.history || []).filter(h => h.role !== 'system');
|
||||
let history = this.fromStandard([
|
||||
...(options.system ? [{role: <any>'system', content: options.system, timestamp: Date.now()}] : []),
|
||||
...base,
|
||||
{role: 'user', content: message, timestamp: Date.now()}
|
||||
]);
|
||||
const tools = options.tools || this.ai.options.llm?.tools || [];
|
||||
const requestParams: any = {
|
||||
model: options.model || this.model,
|
||||
@@ -106,24 +110,22 @@ export class OpenAi extends LLMProvider {
|
||||
};
|
||||
}
|
||||
|
||||
let resp: any, isFirstMessage = true;
|
||||
let resp: any, terminal = false;
|
||||
do {
|
||||
requestParams.messages = history.map(({timestamp, ...m}) => m);
|
||||
resp = await this.client.chat.completions.create(requestParams).catch(err => {
|
||||
err.message += `\n\nMessages:\n${JSON.stringify(history, null, 2)}`;
|
||||
throw err;
|
||||
});
|
||||
|
||||
if(options.stream) {
|
||||
if(!isFirstMessage) options.stream({text: '\n\n'});
|
||||
else isFirstMessage = false;
|
||||
resp.choices = [{message: {role: 'assistant', content: '', tool_calls: []}}];
|
||||
resp.choices = [{message: {role: 'assistant', content: '', tool_calls: [], timestamp: Date.now()}}];
|
||||
for await (const chunk of resp) {
|
||||
if(controller.signal.aborted) break;
|
||||
if(chunk.choices[0].delta.content) {
|
||||
resp.choices[0].message.content += chunk.choices[0].delta.content;
|
||||
options.stream({text: chunk.choices[0].delta.content});
|
||||
}
|
||||
|
||||
if(chunk.choices[0].delta.tool_calls) {
|
||||
for(const deltaTC of chunk.choices[0].delta.tool_calls) {
|
||||
const existing = resp.choices[0].message.tool_calls.find(tc => tc.index === deltaTC.index);
|
||||
@@ -158,29 +160,40 @@ export class OpenAi extends LLMProvider {
|
||||
const results = await Promise.all(toolCalls.map(async (toolCall: any) => {
|
||||
const tool = tools?.find(findByProp('name', toolCall.function.name));
|
||||
if(options.stream) options.stream({tool: toolCall.function.name});
|
||||
if(!tool) return {role: 'tool', tool_call_id: toolCall.id, content: '{"error": "Tool not found"}'};
|
||||
if(!tool) return {role: 'tool', tool_call_id: toolCall.id, content: '{"error": "Tool not found"}', timestamp: Date.now()};
|
||||
try {
|
||||
const args = JSONAttemptParse(toolCall.function.arguments, {});
|
||||
const result = await tool.fn(args, options.stream, this.ai);
|
||||
return {role: 'tool', tool_call_id: toolCall.id, content: typeof result == 'object' ? JSONSanitize(result) : result};
|
||||
// Wrap stream so a tool's `done` ends turn gracefully
|
||||
const toolStream = options.stream && ((chunk: any) => {
|
||||
if(chunk.done) { terminal = true; return; }
|
||||
options.stream!(chunk);
|
||||
});
|
||||
const result = await tool.fn(args, toolStream, this.ai, toolCall.id);
|
||||
return {role: 'tool', tool_call_id: toolCall.id, content: typeof result == 'object' ? JSONSanitize(result) : result, timestamp: Date.now()};
|
||||
} catch (err: any) {
|
||||
return {role: 'tool', tool_call_id: toolCall.id, content: JSONSanitize({error: err?.message || err?.toString() || 'Unknown'})};
|
||||
return {role: 'tool', tool_call_id: toolCall.id, content: JSONSanitize({error: err?.message || err?.toString() || 'Unknown'}), timestamp: Date.now()};
|
||||
}
|
||||
}));
|
||||
history.push(...results);
|
||||
requestParams.messages = history;
|
||||
}
|
||||
} while (!controller.signal.aborted && resp.choices?.[0]?.message?.tool_calls?.length);
|
||||
} while (!terminal && !controller.signal.aborted && resp.choices?.[0]?.message?.tool_calls?.length);
|
||||
|
||||
const textContent = resp.choices[0].message.content?.trim() || '';
|
||||
history.push({role: 'assistant', content: textContent});
|
||||
if(!terminal) {
|
||||
const textContent = resp.choices[0].message.content || '';
|
||||
history.push({role: 'assistant', content: textContent.trim(), timestamp: Date.now()});
|
||||
}
|
||||
history = this.toStandard(history);
|
||||
|
||||
if(options.history) options.history.splice(0, options.history.length, ...history.filter(h => h.role !== 'system'));
|
||||
if(options.stream) options.stream({done: true});
|
||||
if(options.history) options.history.splice(0, options.history.length, ...history);
|
||||
|
||||
// Return parsed JSON if schema provided
|
||||
const finalContent = history.at(-1)?.content;
|
||||
const turnStart = history.map(h => h.role).lastIndexOf('user');
|
||||
const finalContent = history.slice(turnStart + 1).reduce((str, h) => {
|
||||
if(h.role === 'assistant') return str + (h.content || '');
|
||||
if(h.role === 'tool') return str + `<tool>${h.name}</tool>\n\n`;
|
||||
return str;
|
||||
}, '').trim();
|
||||
|
||||
res(options.schema ? JSONAttemptParse(finalContent, finalContent) : finalContent);
|
||||
}), {abort: () => controller.abort()});
|
||||
}
|
||||
|
||||
@@ -1,5 +1,5 @@
|
||||
import {AbortablePromise} from './ai.ts';
|
||||
import {LLMMessage, LLMRequest} from './llm.ts';
|
||||
import {LLMRequest} from './llm.ts';
|
||||
|
||||
export abstract class LLMProvider {
|
||||
abstract ask(message: string, options: LLMRequest): AbortablePromise<string>;
|
||||
|
||||
671
src/tools.ts
671
src/tools.ts
@@ -41,7 +41,7 @@ export type AiTool = {
|
||||
/** Tool arguments */
|
||||
args?: AiToolArg,
|
||||
/** Callback function */
|
||||
fn: (args: any, stream: LLMRequest['stream'], ai: Ai) => any | Promise<any>,
|
||||
fn: (args: any, stream: LLMRequest['stream'], ai: Ai, toolId?: string) => any | Promise<any>,
|
||||
};
|
||||
|
||||
export function convertSchema(schema: any): any {
|
||||
@@ -91,20 +91,33 @@ export function convertSchema(schema: any): any {
|
||||
};
|
||||
}
|
||||
|
||||
export const CliTool: AiTool = {
|
||||
export const ExecCliTool: AiTool = {
|
||||
name: 'cli',
|
||||
description: 'Use the command line interface, returns any output',
|
||||
args: {command: {type: 'string', description: 'Command to run', required: true}},
|
||||
fn: (args: {command: string}) => $Sync`${args.command}`
|
||||
}
|
||||
|
||||
export const DateTimeTool: AiTool = {
|
||||
name: 'get_datetime',
|
||||
description: 'Get local/UTC date/time',
|
||||
export const ExecJSTool: AiTool = {
|
||||
name: 'exec_javascript',
|
||||
description: 'Execute commonjs javascript',
|
||||
args: {
|
||||
timezone: {type: 'string', description: 'Which timezone to return, defaults to local', enum: ['local', 'utc'], default: 'local'}
|
||||
code: {type: 'string', description: 'CommonJS javascript', required: true}
|
||||
},
|
||||
fn: ({timezone}) => new Date()[timezone === 'local' ? 'toString' : 'toUTCString']()
|
||||
fn: async (args: {code: string}) => {
|
||||
const c = consoleInterceptor(null);
|
||||
const resp = await Fn<any>({console: c}, args.code, true).catch((err: any) => c.output.error.push(err));
|
||||
return {...c.output, return: resp, stdout: undefined, stderr: undefined};
|
||||
}
|
||||
}
|
||||
|
||||
export const ExecPythonTool: AiTool = {
|
||||
name: 'exec_python',
|
||||
description: 'Execute commonjs javascript',
|
||||
args: {
|
||||
code: {type: 'string', description: 'CommonJS javascript', required: true}
|
||||
},
|
||||
fn: async (args: {code: string}) => ({result: $Sync`python -c "${args.code}"`})
|
||||
}
|
||||
|
||||
export const ExecTool: AiTool = {
|
||||
@@ -118,11 +131,11 @@ export const ExecTool: AiTool = {
|
||||
try {
|
||||
switch(args.language) {
|
||||
case 'cli':
|
||||
return await CliTool.fn({command: args.code}, stream, ai);
|
||||
return await ExecCliTool.fn({command: args.code}, stream, ai);
|
||||
case 'node':
|
||||
return await JSTool.fn({code: args.code}, stream, ai);
|
||||
return await ExecJSTool.fn({code: args.code}, stream, ai);
|
||||
case 'python':
|
||||
return await PythonTool.fn({code: args.code}, stream, ai);
|
||||
return await ExecPythonTool.fn({code: args.code}, stream, ai);
|
||||
default:
|
||||
throw new Error(`Unsupported language: ${args.language}`);
|
||||
}
|
||||
@@ -132,8 +145,483 @@ export const ExecTool: AiTool = {
|
||||
}
|
||||
}
|
||||
|
||||
export const FetchTool: AiTool = {
|
||||
name: 'fetch',
|
||||
export const FsDeleteTool = (whitelist: null | string[] = null): AiTool => {
|
||||
return {
|
||||
name: 'fs_delete',
|
||||
description: 'Delete a file or directory',
|
||||
args: {
|
||||
path: {type: 'string', description: 'Path to file or directory', required: true},
|
||||
recursive: {type: 'boolean', description: 'Delete all children', required: false}
|
||||
},
|
||||
fn: async ({path, recursive = false}) => {
|
||||
const {existsSync, rmSync} = await import('fs');
|
||||
const normalizePath = p => p.replace(/\\/g, '/');
|
||||
|
||||
path = normalizePath(path);
|
||||
if(whitelist && !whitelist.some(p => path.startsWith(p))) return {error: 'Permission denied'};
|
||||
if(!existsSync(path)) return {error: 'Path does not exist'};
|
||||
|
||||
rmSync(path, {recursive, force: true});
|
||||
return {success: true, path};
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
export const FsMoveTool = (whitelist: null | string[] = null): AiTool => {
|
||||
return {
|
||||
name: 'fs_move',
|
||||
description: 'Move or rename a file or directory',
|
||||
args: {
|
||||
source: {type: 'string', description: 'Path to source file or directory', required: true},
|
||||
destination: {type: 'string', description: 'Path to destination file or directory', required: true}
|
||||
},
|
||||
fn: async ({source, destination}) => {
|
||||
const {existsSync, renameSync} = await import('fs');
|
||||
const normalizePath = p => p.replace(/\\/g, '/');
|
||||
|
||||
source = normalizePath(source);
|
||||
destination = normalizePath(destination);
|
||||
if(whitelist && !whitelist.some(p => source.startsWith(p) && destination.startsWith(p))) return {error: 'Permission denied'};
|
||||
|
||||
if(!existsSync(source)) return {error: 'Source path does not exist'};
|
||||
if(existsSync(destination)) return {error: 'Destination path already exists'};
|
||||
|
||||
renameSync(source, destination);
|
||||
return {success: true, source, destination};
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
export const FsReadTool = (whitelist: null | string[] = null): AiTool => {
|
||||
return {
|
||||
name: 'fs_read',
|
||||
description: 'Read the contents of a provided path. Works with files and directories',
|
||||
args: {path: {type: 'string', description: 'Path to file or directory', required: true}},
|
||||
fn: async ({path}) => {
|
||||
const {existsSync, lstatSync, readdirSync, readFileSync} = await import('fs');
|
||||
const {join} = await import('path');
|
||||
const normalizePath = p => p.replace(/\\/g, '/');
|
||||
|
||||
path = normalizePath(path);
|
||||
if(whitelist && !whitelist.some(p => path.startsWith(p))) return {error: 'Permission denied'};
|
||||
|
||||
if(!existsSync(path)) return {error: 'Path does not exist'};
|
||||
const stats = lstatSync(path);
|
||||
if(stats.isDirectory()) {
|
||||
const children = readdirSync(path).map(name => {
|
||||
const childPath = normalizePath(join(path, name));
|
||||
const childStats = lstatSync(childPath);
|
||||
return {name, type: childStats.isDirectory() ? 'directory' : 'file', size: childStats.size};
|
||||
});
|
||||
return {type: 'directory', children};
|
||||
}
|
||||
const content = readFileSync(path, 'utf-8');
|
||||
return {type: 'file', content};
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
export const FsSearchTool = (whitelist: null | string[] = null): AiTool => {
|
||||
return {
|
||||
name: 'fs_search',
|
||||
description: 'Scan a directory for matching glob patterns (e.g. "**/*.js", "src/**/*.test.ts")',
|
||||
args: {
|
||||
pattern: {type: 'string', description: 'Glob pattern to match against paths', required: true},
|
||||
root: {type: 'string', description: 'Directory to search from', required: false, default: '.'}
|
||||
},
|
||||
fn: async ({pattern, root = '.'}) => {
|
||||
const {existsSync, lstatSync, readdirSync} = await import('fs');
|
||||
const {join, relative} = await import('path');
|
||||
const normalizePath = p => p.replace(/\\/g, '/');
|
||||
|
||||
root = normalizePath(root);
|
||||
if(!existsSync(root)) return {error: 'Root path does not exist'};
|
||||
if(!lstatSync(root).isDirectory()) return {error: 'Root path is not a directory'};
|
||||
|
||||
if(whitelist && !whitelist.some(p => root.startsWith(p))) return {error: 'Permission denied'};
|
||||
|
||||
const globToRegex = (glob) => {
|
||||
let re = '';
|
||||
for(let i = 0; i < glob.length; i++) {
|
||||
const c = glob[i];
|
||||
if(c === '*') {
|
||||
if(glob[i + 1] === '*') {
|
||||
const isSlash = glob[i + 2] === '/';
|
||||
re += '.*';
|
||||
i += isSlash ? 2 : 1;
|
||||
} else {
|
||||
re += '[^/]*';
|
||||
}
|
||||
} else if(c === '?') {
|
||||
re += '[^/]';
|
||||
} else if('.+^$(){}|[]\\'.includes(c)) {
|
||||
re += '\\' + c;
|
||||
} else {
|
||||
re += c;
|
||||
}
|
||||
}
|
||||
return new RegExp('^' + re + '$');
|
||||
};
|
||||
const regex = globToRegex(pattern);
|
||||
|
||||
const results: any = [];
|
||||
const walk = (dir) => {
|
||||
for(const name of readdirSync(dir)) {
|
||||
const fullPath = normalizePath(join(dir, name));
|
||||
const stats = lstatSync(fullPath);
|
||||
const relPath = normalizePath(relative(root, fullPath));
|
||||
if(regex.test(relPath)) {
|
||||
results.push({path: relPath, type: stats.isDirectory() ? 'directory' : 'file', size: stats.size});
|
||||
}
|
||||
if(stats.isDirectory()) walk(fullPath);
|
||||
}
|
||||
};
|
||||
walk(root);
|
||||
|
||||
return results;
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
export const FsWriteTool = (whitelist: null | string[] = null): AiTool => {
|
||||
return {
|
||||
name: 'fs_write',
|
||||
description: 'Create a directory, write content to a file or preform a find & replace',
|
||||
args: {
|
||||
path: {type: 'string', description: 'Path to file or directory', required: true},
|
||||
content: {type: 'string', description: 'Content to write or replace (Omit to create a directory)'},
|
||||
find: {type: 'string', description: 'Text or regex pattern to match (regex must match pattern: "/pattern/g")'}
|
||||
},
|
||||
fn: async ({path, content, find}) => {
|
||||
const {existsSync, mkdirSync, readFileSync, writeFileSync} = await import('fs');
|
||||
const {dirname} = await import('path');
|
||||
const normalizePath = p => p.replace(/\\/g, '/');
|
||||
|
||||
path = normalizePath(path);
|
||||
if(whitelist && !whitelist.some(p => path.startsWith(p))) return {error: 'Permission denied'};
|
||||
|
||||
if(content === undefined) {
|
||||
mkdirSync(path, {recursive: true});
|
||||
return {success: true, type: 'directory', path};
|
||||
}
|
||||
|
||||
const dir = normalizePath(dirname(path));
|
||||
if(!existsSync(dir)) mkdirSync(dir, {recursive: true});
|
||||
|
||||
if(find && existsSync(path)) {
|
||||
const existing = readFileSync(path, 'utf-8');
|
||||
const regexMatch = find.match(/^\/(.+)\/([gimuy]*)$/);
|
||||
const pattern = regexMatch ? new RegExp(regexMatch[1], regexMatch[2]) : find;
|
||||
|
||||
if(!existing.match(pattern)) return {error: 'Find pattern not found in file'};
|
||||
|
||||
const updated = existing.replace(pattern, content);
|
||||
writeFileSync(path, updated, 'utf-8');
|
||||
return {success: true, type: 'file', path, replaced: true, content: updated};
|
||||
}
|
||||
|
||||
writeFileSync(path, content, 'utf-8');
|
||||
return {success: true, type: 'file', path, content};
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
export const GetPathsTool: AiTool = {
|
||||
name: 'get_paths',
|
||||
description: 'Get the current working directory, and paths to the users home directory',
|
||||
fn: async () => {
|
||||
return {
|
||||
home: os.homedir(),
|
||||
cwd: process.cwd()
|
||||
};
|
||||
}
|
||||
}
|
||||
|
||||
export const GetDatetimeTool: AiTool = {
|
||||
name: 'get_datetime',
|
||||
description: 'Get local/UTC timestamp',
|
||||
args: {
|
||||
timezone: {type: 'string', description: 'Which timezone to return, defaults to local', enum: ['local', 'utc'], default: 'local'}
|
||||
},
|
||||
fn: ({timezone}) => new Date()[timezone === 'local' ? 'toString' : 'toUTCString']()
|
||||
}
|
||||
|
||||
export const GetDevice: AiTool = {
|
||||
name: 'get_device',
|
||||
description: 'Get comprehensive system information including hostname, specs, load, storage, and network status',
|
||||
args: {},
|
||||
fn: async () => {
|
||||
const platform = os.platform();
|
||||
const hostname = os.hostname();
|
||||
|
||||
// CPU Info
|
||||
const cpus = os.cpus();
|
||||
const cpuModel = cpus[0].model;
|
||||
const cpuCores = cpus.length;
|
||||
|
||||
// Memory Info
|
||||
const totalMem: any = (os.totalmem() / 1024 / 1024 / 1024).toFixed(2);
|
||||
const freeMem: any = (os.freemem() / 1024 / 1024 / 1024).toFixed(2);
|
||||
const usedMem: any = (totalMem - freeMem).toFixed(2);
|
||||
const memUsage: any = ((usedMem / totalMem) * 100).toFixed(1);
|
||||
|
||||
// Load Average (not available on Windows)
|
||||
const loadAvg = platform === 'win32' ? ['N/A', 'N/A', 'N/A'] : os.loadavg().map(l => l.toFixed(2));
|
||||
|
||||
// Storage Usage
|
||||
let storage = {};
|
||||
if(platform === 'win32') {
|
||||
const ps = $Sync`powershell "Get-PSDrive C | Select-Object Used,Free | ConvertTo-Json"`.trim();
|
||||
const drive = JSON.parse(ps);
|
||||
const used: any = (drive.Used / 1024 / 1024 / 1024).toFixed(2);
|
||||
const free: any = (drive.Free / 1024 / 1024 / 1024).toFixed(2);
|
||||
const total: any = (parseFloat(used) + parseFloat(free)).toFixed(2);
|
||||
const usage: any = ((used / total) * 100).toFixed(1);
|
||||
storage = {
|
||||
filesystem: 'C:',
|
||||
size: `${total} GB`,
|
||||
used: `${used} GB`,
|
||||
available: `${free} GB`,
|
||||
usage: `${usage}%`
|
||||
};
|
||||
} else {
|
||||
const df = $Sync`df -h / | tail -1`.trim();
|
||||
const s = df.split(/\s+/);
|
||||
storage = {
|
||||
filesystem: s[0],
|
||||
size: s[1],
|
||||
used: s[2],
|
||||
available: s[3],
|
||||
usage: s[4]
|
||||
};
|
||||
}
|
||||
|
||||
// Network Status
|
||||
const interfaces = os.networkInterfaces();
|
||||
const activeIfaces = Object.entries(interfaces)
|
||||
.filter(([name]) => name !== 'lo' && !name.includes('Loopback'))
|
||||
.map(([name, addrs]) => {
|
||||
const ipv4 = addrs?.find(a => a.family === 'IPv4');
|
||||
return ipv4 ? {name, ip: ipv4.address} : null;
|
||||
})
|
||||
.filter(Boolean);
|
||||
|
||||
// Internet connectivity check
|
||||
let internet = false;
|
||||
try {
|
||||
if(platform === 'win32') {
|
||||
$Sync`powershell "Test-Connection -ComputerName 8.8.8.8 -Count 1 -Quiet"`;
|
||||
} else {
|
||||
$Sync`ping -c 1 -W 2 8.8.8.8 > /dev/null 2>&1`;
|
||||
}
|
||||
internet = true;
|
||||
} catch {}
|
||||
|
||||
// Uptime
|
||||
const uptime = os.uptime();
|
||||
const days = Math.floor(uptime / 86400);
|
||||
const hours = Math.floor((uptime % 86400) / 3600);
|
||||
const minutes = Math.floor((uptime % 3600) / 60);
|
||||
|
||||
return {
|
||||
hostname,
|
||||
cpu: {
|
||||
model: cpuModel,
|
||||
cores: cpuCores
|
||||
},
|
||||
memory: {
|
||||
total: `${totalMem} GB`,
|
||||
used: `${usedMem} GB`,
|
||||
free: `${freeMem} GB`,
|
||||
usage: `${memUsage}%`
|
||||
},
|
||||
load: {
|
||||
'1min': loadAvg[0],
|
||||
'5min': loadAvg[1],
|
||||
'15min': loadAvg[2]
|
||||
},
|
||||
storage,
|
||||
network: {
|
||||
interfaces: activeIfaces,
|
||||
internet: internet ? 'connected' : 'disconnected'
|
||||
},
|
||||
uptime: `${days}d ${hours}h ${minutes}m`,
|
||||
platform: `${os.type()} ${os.release()}`
|
||||
};
|
||||
}
|
||||
}
|
||||
|
||||
export const GetWikipediaTool: AiTool = {
|
||||
name: 'get_wikipedia',
|
||||
description: 'Search Wikipedia for matching articles',
|
||||
args: {
|
||||
query: {type: 'string', description: 'Search term or article title', required: true},
|
||||
mode: {type: 'string', description: 'search - look for articles, summary - intro of first found article (default), full - complete first found article', enum: ['search', 'summary', 'full'], default: 'summary'},
|
||||
ua: {type: 'string', description: 'User Agent'},
|
||||
},
|
||||
fn: async ({query, mode, ua}) => {
|
||||
class WikipediaClient {
|
||||
useragent = 'Mozilla/5.0 (Windows NT 10.0; Win64; x64)';
|
||||
|
||||
constructor(useragent: string) {
|
||||
this.useragent = useragent;
|
||||
}
|
||||
|
||||
async get(url) {
|
||||
const resp = await fetch(url, {headers: {'User-Agent': this.useragent}});
|
||||
return resp.json();
|
||||
}
|
||||
|
||||
api(params) {
|
||||
const qs = new URLSearchParams({...params, format: 'json', utf8: '1'}).toString();
|
||||
return this.get(`https://en.wikipedia.org/w/api.php?${qs}`);
|
||||
}
|
||||
|
||||
clean(text) {
|
||||
const cutoffs = ['== See also ==', '== References ==', '== Bibliography ==', '== External links =='];
|
||||
for (const marker of cutoffs) {
|
||||
const idx = text.indexOf(marker);
|
||||
if (idx !== -1) text = text.slice(0, idx);
|
||||
}
|
||||
|
||||
return text
|
||||
.replace(/^={4}\s*(.+?)\s*={4}$/gm, '#### $1')
|
||||
.replace(/^={3}\s*(.+?)\s*={3}$/gm, '### $1')
|
||||
.replace(/^={2}\s*(.+?)\s*={2}$/gm, '## $1')
|
||||
.replace(/\n{3,}/g, '\n\n')
|
||||
.replace(/ {2,}/g, ' ')
|
||||
.replace(/\[\d+]/g, '')
|
||||
.trim();
|
||||
}
|
||||
|
||||
async searchTitles(query: string, limit = 6) {
|
||||
const data = await this.api({action: 'query', list: 'search', srsearch: query, srlimit: limit, srprop: 'snippet'});
|
||||
return data.query?.search || [];
|
||||
}
|
||||
|
||||
async fetchExtract(title: string, introOnly = false) {
|
||||
const params: any = {action: 'query', prop: 'extracts', titles: title, explaintext: 1, redirects: 1};
|
||||
if(introOnly) params.exintro = 1;
|
||||
const data = await this.api(params);
|
||||
const page: any = Object.values(data.query?.pages || {})[0];
|
||||
return this.clean(page?.extract || '');
|
||||
}
|
||||
|
||||
pageUrl(title: string) {
|
||||
return `https://en.wikipedia.org/wiki/${encodeURIComponent(title.replace(/ /g, '_'))}`;
|
||||
}
|
||||
|
||||
stripHtml(text: string) {
|
||||
return text.replace(/<[^>]+>/g, '');
|
||||
}
|
||||
|
||||
async lookup(query: string, detail = 'summary') {
|
||||
const results = await this.searchTitles(query, 6);
|
||||
if(!results.length) return `❌ No Wikipedia articles found for "${query}"`;
|
||||
const title = results[0].title;
|
||||
const url = this.pageUrl(title);
|
||||
const introOnly = detail !== 'full';
|
||||
const content = await this.fetchExtract(title, introOnly);
|
||||
return `## ${title}\n🔗 ${url}\n\n${content}`;
|
||||
}
|
||||
|
||||
async search(query: string) {
|
||||
const results = await this.searchTitles(query, 8);
|
||||
if(!results.length) return `❌ No results for "${query}"`;
|
||||
const lines = [`### Search results for "${query}"\n`];
|
||||
for(let i = 0; i < results.length; i++) {
|
||||
const r = results[i];
|
||||
const snippet = this.stripHtml(r.snippet || '').trim();
|
||||
lines.push(`**${i + 1}. ${r.title}**\n${snippet}\n${this.pageUrl(r.title)}`);
|
||||
}
|
||||
return lines.join('\n\n');
|
||||
}
|
||||
}
|
||||
|
||||
const wiki = new WikipediaClient(ua);
|
||||
if(mode === 'search') return wiki.search(query);
|
||||
return wiki.lookup(query, mode || 'summary');
|
||||
}
|
||||
};
|
||||
|
||||
export const GeoCodeTool: AiTool = {
|
||||
name: 'geo_code',
|
||||
description: 'Converts coordinates to address OR vice versa',
|
||||
args: {
|
||||
query: {type: 'string', description: 'Search query - coordinates (lat,lon) or address string', required: true},
|
||||
},
|
||||
fn: async ({query}) => {
|
||||
const coordinates = /(-?\d+(?:\.\d+)?).*?,.*?(-?\d+(?:\.\d+)?)/.exec(query);
|
||||
if(coordinates) { // Geolocate
|
||||
const url = `https://nominatim.openstreetmap.org/reverse?format=json&lat=${encodeURIComponent(coordinates[1])}&lon=${encodeURIComponent(coordinates[2])}`;
|
||||
const response = await fetch(url, {headers: {'User-Agent': 'OpenSight/1.0', 'Accept-Language': 'en'}});
|
||||
const data = await response.json();
|
||||
if(data.display_name) return {address: data.display_name, mode: 'geolocate'};
|
||||
} else { // Geocode
|
||||
const url = `https://nominatim.openstreetmap.org/search?format=json&q=${encodeURIComponent(query)}`;
|
||||
const response = await fetch(url, {headers: {'User-Agent': 'OpenSight/1.0'}});
|
||||
const data = await response.json();
|
||||
if(data[0]) return {latitude: parseFloat(data[0].lat), longitude: parseFloat(data[0].lon), mode: 'geocode'};
|
||||
}
|
||||
return {error: 'Not found'};
|
||||
},
|
||||
}
|
||||
|
||||
export const GeoWeatherTool: AiTool = {
|
||||
name: 'geo_weather',
|
||||
description: 'Gets weather and air quality info for a location and time',
|
||||
args: {
|
||||
query: {type: 'string', description: 'Location - address or place name', required: true},
|
||||
day: {type: 'string', description: 'Date to retrieve (YYYY-MM-DD), defaults to today'},
|
||||
},
|
||||
fn: async ({query, day}) => {
|
||||
day = day || new Date().toISOString().slice(0, 10);
|
||||
|
||||
const geoUrl = `https://nominatim.openstreetmap.org/search?format=json&q=${encodeURIComponent(query)}`;
|
||||
const geoResponse = await fetch(geoUrl, {headers: {'User-Agent': 'OpenSight/1.0'}});
|
||||
const geoData = await geoResponse.json();
|
||||
if(!geoData[0]) return {error: 'Location not found'};
|
||||
|
||||
const lat = parseFloat(geoData[0].lat);
|
||||
const lon = parseFloat(geoData[0].lon);
|
||||
|
||||
const weatherUrl = `https://api.open-meteo.com/v1/forecast?latitude=${lat}&longitude=${lon}&start_date=${day}&end_date=${day}&daily=weathercode,temperature_2m_max,temperature_2m_min,apparent_temperature_max,apparent_temperature_min,precipitation_sum,precipitation_probability_max,windspeed_10m_max,winddirection_10m_dominant,uv_index_max,sunrise,sunset&timezone=auto`;
|
||||
const airUrl = `https://air-quality-api.open-meteo.com/v1/air-quality?latitude=${lat}&longitude=${lon}&start_date=${day}&end_date=${day}&hourly=us_aqi,european_aqi,pm10,pm2_5&timezone=auto`;
|
||||
|
||||
const [weatherResponse, airResponse] = await Promise.all([fetch(weatherUrl), fetch(airUrl)]);
|
||||
const weatherData = await weatherResponse.json();
|
||||
const airData = await airResponse.json();
|
||||
|
||||
const avg = arr => (arr && arr.length) ? arr.reduce((a, b) => a + b, 0) / arr.length : null;
|
||||
|
||||
return {
|
||||
location: geoData[0].display_name,
|
||||
latitude: lat,
|
||||
longitude: lon,
|
||||
elevation: weatherData.elevation,
|
||||
date: day,
|
||||
weatherCode: weatherData.daily?.weathercode?.[0],
|
||||
tempMax: weatherData.daily?.temperature_2m_max?.[0],
|
||||
tempMin: weatherData.daily?.temperature_2m_min?.[0],
|
||||
feelsLikeMax: weatherData.daily?.apparent_temperature_max?.[0],
|
||||
feelsLikeMin: weatherData.daily?.apparent_temperature_min?.[0],
|
||||
precipitation: weatherData.daily?.precipitation_sum?.[0],
|
||||
precipitationChance: weatherData.daily?.precipitation_probability_max?.[0],
|
||||
windSpeedMax: weatherData.daily?.windspeed_10m_max?.[0],
|
||||
windDirection: weatherData.daily?.winddirection_10m_dominant?.[0],
|
||||
uvIndexMax: weatherData.daily?.uv_index_max?.[0],
|
||||
sunrise: weatherData.daily?.sunrise?.[0],
|
||||
sunset: weatherData.daily?.sunset?.[0],
|
||||
usAqi: avg(airData.hourly?.us_aqi),
|
||||
europeanAqi: avg(airData.hourly?.european_aqi),
|
||||
pm10: avg(airData.hourly?.pm10),
|
||||
pm2_5: avg(airData.hourly?.pm2_5),
|
||||
};
|
||||
},
|
||||
}
|
||||
|
||||
export const WebFetchTool: AiTool = {
|
||||
name: 'web_fetch',
|
||||
description: 'Make HTTP request to URL',
|
||||
args: {
|
||||
url: {type: 'string', description: 'URL to fetch', required: true},
|
||||
@@ -149,30 +637,59 @@ export const FetchTool: AiTool = {
|
||||
}) => new Http({url: args.url, headers: args.headers}).request({method: args.method || 'GET', body: args.body})
|
||||
}
|
||||
|
||||
export const JSTool: AiTool = {
|
||||
name: 'exec_javascript',
|
||||
description: 'Execute commonjs javascript',
|
||||
args: {
|
||||
code: {type: 'string', description: 'CommonJS javascript', required: true}
|
||||
},
|
||||
fn: async (args: {code: string}) => {
|
||||
const c = consoleInterceptor(null);
|
||||
const resp = await Fn<any>({console: c}, args.code, true).catch((err: any) => c.output.error.push(err));
|
||||
return {...c.output, return: resp, stdout: undefined, stderr: undefined};
|
||||
export const WebFlareSolverTool = (host: string) => {
|
||||
return {
|
||||
name: 'web_flaresolverr',
|
||||
description: 'Use a flaresolverr proxy to bypass cloudflare bot detection',
|
||||
args: {
|
||||
url: {type: 'string', description: 'URL to fetch', required: true},
|
||||
cmd: {type: 'string', description: 'Flaresolverr cmd', enum: ['request.get', 'request.post'], default: 'request.get'},
|
||||
maxTimeout: {type: 'number', description: 'Fetch time limit', default: 60_000},
|
||||
postData: {type: 'object', description: 'Data to send during request.post requests'},
|
||||
},
|
||||
fn: async ({url, cmd, maxTimeout, postData}) => {
|
||||
function toFormUrlEncoded(obj, prefix = '') {
|
||||
const pairs: any = [];
|
||||
for (const key in obj) {
|
||||
if (!obj.hasOwnProperty(key)) continue;
|
||||
|
||||
const value = obj[key];
|
||||
const encodedKey = prefix
|
||||
? `${prefix}[${encodeURIComponent(key)}]`
|
||||
: encodeURIComponent(key);
|
||||
|
||||
if (value === null || value === undefined) {
|
||||
pairs.push(`${encodedKey}=`);
|
||||
} else if (typeof value === 'object' && !Array.isArray(value)) {
|
||||
pairs.push(toFormUrlEncoded(value, encodedKey));
|
||||
} else if (Array.isArray(value)) {
|
||||
value.forEach(item => {
|
||||
pairs.push(`${encodedKey}[]=${encodeURIComponent(item)}`);
|
||||
});
|
||||
} else {
|
||||
pairs.push(`${encodedKey}=${encodeURIComponent(value)}`);
|
||||
}
|
||||
}
|
||||
|
||||
return pairs.join('&');
|
||||
}
|
||||
|
||||
const res = await fetch(host + '/v1', {
|
||||
method: 'POST',
|
||||
headers: {'Content-Type': 'application/json'},
|
||||
body: JSON.stringify({cmd, url, maxTimeout, postData: postData ? toFormUrlEncoded(postData) : undefined}),
|
||||
});
|
||||
|
||||
if(!res.ok) throw new Error(`FlareSolverr HTTP error: ${res.status} ${res.statusText}`);
|
||||
const data = await res.json();
|
||||
if(data.status !== 'ok') throw new Error(`FlareSolverr error: ${data.message ?? data.status}`);
|
||||
return data.solution.response;
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
export const PythonTool: AiTool = {
|
||||
name: 'exec_python',
|
||||
description: 'Execute commonjs javascript',
|
||||
args: {
|
||||
code: {type: 'string', description: 'CommonJS javascript', required: true}
|
||||
},
|
||||
fn: async (args: {code: string}) => ({result: $Sync`python -c "${args.code}"`})
|
||||
}
|
||||
|
||||
export const ReadWebpageTool: AiTool = {
|
||||
name: 'read_webpage',
|
||||
export const WebReadTool: AiTool = {
|
||||
name: 'web_read',
|
||||
description: 'Extract clean content from webpages, or convert media/documents to accessible formats',
|
||||
args: {
|
||||
url: {type: 'string', description: 'URL to read', required: true},
|
||||
@@ -300,91 +817,3 @@ export const WebSearchTool: AiTool = {
|
||||
return results;
|
||||
}
|
||||
}
|
||||
|
||||
export const WikipediaTool: AiTool = {
|
||||
name: 'wikipedia_search',
|
||||
description: 'Search Wikipedia for matching articles',
|
||||
args: {
|
||||
query: {type: 'string', description: 'Search term or article title', required: true},
|
||||
mode: {type: 'string', description: 'search - look for articles, summary - intro of first found article (default), full - complete first found article', enum: ['search', 'summary', 'full'], default: 'summary'}
|
||||
},
|
||||
fn: async (args: {query: string, mode: 'search' | 'summary' | 'full'}) => {
|
||||
const UA = 'Mozilla/5.0 (Windows NT 10.0; Win64; x64)';
|
||||
|
||||
class WikipediaClient {
|
||||
async get(url: string) {
|
||||
const resp = await fetch(url, {headers: {'User-Agent': UA}});
|
||||
return resp.json();
|
||||
}
|
||||
|
||||
api(params: any) {
|
||||
const qs = new URLSearchParams({...params, format: 'json', utf8: '1'}).toString();
|
||||
return this.get(`https://en.wikipedia.org/w/api.php?${qs}`);
|
||||
}
|
||||
|
||||
clean(text: string) {
|
||||
const cutoffs = ['== See also ==', '== References ==', '== Bibliography ==', '== External links =='];
|
||||
for (const marker of cutoffs) {
|
||||
const idx = text.indexOf(marker);
|
||||
if (idx !== -1) text = text.slice(0, idx);
|
||||
}
|
||||
|
||||
return text
|
||||
.replace(/^={4}\s*(.+?)\s*={4}$/gm, '#### $1')
|
||||
.replace(/^={3}\s*(.+?)\s*={3}$/gm, '### $1')
|
||||
.replace(/^={2}\s*(.+?)\s*={2}$/gm, '## $1')
|
||||
.replace(/\n{3,}/g, '\n\n')
|
||||
.replace(/ {2,}/g, ' ')
|
||||
.replace(/\[\d+\]/g, '')
|
||||
.trim();
|
||||
}
|
||||
|
||||
async searchTitles(query: string, limit = 6) {
|
||||
const data = await this.api({action: 'query', list: 'search', srsearch: query, srlimit: limit, srprop: 'snippet'});
|
||||
return data.query?.search || [];
|
||||
}
|
||||
|
||||
async fetchExtract(title: string, introOnly = false) {
|
||||
const params: any = {action: 'query', prop: 'extracts', titles: title, explaintext: 1, redirects: 1};
|
||||
if(introOnly) params.exintro = 1;
|
||||
const data = await this.api(params);
|
||||
const page: any = Object.values(data.query?.pages || {})[0];
|
||||
return this.clean(page?.extract || '');
|
||||
}
|
||||
|
||||
pageUrl(title: string) {
|
||||
return `https://en.wikipedia.org/wiki/${encodeURIComponent(title.replace(/ /g, '_'))}`;
|
||||
}
|
||||
|
||||
stripHtml(text: string) {
|
||||
return text.replace(/<[^>]+>/g, '');
|
||||
}
|
||||
|
||||
async lookup(query: string, detail = 'summary') {
|
||||
const results = await this.searchTitles(query, 6);
|
||||
if(!results.length) return `❌ No Wikipedia articles found for "${query}"`;
|
||||
const title = results[0].title;
|
||||
const url = this.pageUrl(title);
|
||||
const introOnly = detail !== 'full';
|
||||
const content = await this.fetchExtract(title, introOnly);
|
||||
return `## ${title}\n🔗 ${url}\n\n${content}`;
|
||||
}
|
||||
|
||||
async search(query: string) {
|
||||
const results = await this.searchTitles(query, 8);
|
||||
if(!results.length) return `❌ No results for "${query}"`;
|
||||
const lines = [`### Search results for "${query}"\n`];
|
||||
for(let i = 0; i < results.length; i++) {
|
||||
const r = results[i];
|
||||
const snippet = this.stripHtml(r.snippet || '').trim();
|
||||
lines.push(`**${i + 1}. ${r.title}**\n${snippet}\n${this.pageUrl(r.title)}`);
|
||||
}
|
||||
return lines.join('\n\n');
|
||||
}
|
||||
}
|
||||
|
||||
const wiki = new WikipediaClient();
|
||||
if(args.mode == 'search') return wiki.search(args.query);
|
||||
return wiki.lookup(args.query, args.mode || 'summary');
|
||||
}
|
||||
};
|
||||
|
||||
Reference in New Issue
Block a user