shitton

2026-05-13 10:18:54 +03:00
parent cd8d2683c0
commit c5b61ee3d8
38 changed files with 3929 additions and 3718 deletions
@@ -28,13 +28,8 @@
        "@types/fluent-ffmpeg": "^2.1.28",
        "@types/node": "^25.6.1",
        "@types/qrcode": "^1.5.6",
-        "@typescript-eslint/eslint-plugin": "^8.59.2",
+        "@typescript/native-preview": "^7.0.0-beta",
        "@typescript-eslint/parser": "^8.59.2",
        "drizzle-kit": "^0.31.10",
        "eslint": "^10.3.0",
        "tsx": "^4.21.0",
        "typescript": "^6.0.3",
        "typescript-eslint": "^8.59.2",
      },
    },
  },
@@ -99,30 +94,8 @@
    "@esbuild/win32-x64": ["@esbuild/win32-x64@0.25.12", "", { "os": "win32", "cpu": "x64" }, "sha512-alJC0uCZpTFrSL0CCDjcgleBXPnCrEAhTBILpeAp7M/OFgoqtAetfBzX0xM00MUsVVPpVjlPuMbREqnZCXaTnA=="],
    "@eslint-community/eslint-utils": ["@eslint-community/eslint-utils@4.9.1", "", { "dependencies": { "eslint-visitor-keys": "^3.4.3" }, "peerDependencies": { "eslint": "^6.0.0 || ^7.0.0 || >=8.0.0" } }, "sha512-phrYmNiYppR7znFEdqgfWHXR6NCkZEK7hwWDHZUjit/2/U0r6XvkDl0SYnoM51Hq7FhCGdLDT6zxCCOY1hexsQ=="],
    "@eslint-community/regexpp": ["@eslint-community/regexpp@4.12.2", "", {}, "sha512-EriSTlt5OC9/7SXkRSCAhfSxxoSUgBm33OH+IkwbdpgoqsSsUg7y3uh+IICI/Qg4BBWr3U2i39RpmycbxMq4ew=="],
    "@eslint/config-array": ["@eslint/config-array@0.23.5", "", { "dependencies": { "@eslint/object-schema": "^3.0.5", "debug": "^4.3.1", "minimatch": "^10.2.4" } }, "sha512-Y3kKLvC1dvTOT+oGlqNQ1XLqK6D1HU2YXPc52NmAlJZbMMWDzGYXMiPRJ8TYD39muD/OTjlZmNJ4ib7dvSrMBA=="],
    "@eslint/config-helpers": ["@eslint/config-helpers@0.5.5", "", { "dependencies": { "@eslint/core": "^1.2.1" } }, "sha512-eIJYKTCECbP/nsKaaruF6LW967mtbQbsw4JTtSVkUQc9MneSkbrgPJAbKl9nWr0ZeowV8BfsarBmPpBzGelA2w=="],
    "@eslint/core": ["@eslint/core@1.2.1", "", { "dependencies": { "@types/json-schema": "^7.0.15" } }, "sha512-MwcE1P+AZ4C6DWlpin/OmOA54mmIZ/+xZuJiQd4SyB29oAJjN30UW9wkKNptW2ctp4cEsvhlLY/CsQ1uoHDloQ=="],
    "@eslint/object-schema": ["@eslint/object-schema@3.0.5", "", {}, "sha512-vqTaUEgxzm+YDSdElad6PiRoX4t8VGDjCtt05zn4nU810UIx/uNEV7/lZJ6KwFThKZOzOxzXy48da+No7HZaMw=="],
    "@eslint/plugin-kit": ["@eslint/plugin-kit@0.7.1", "", { "dependencies": { "@eslint/core": "^1.2.1", "levn": "^0.4.1" } }, "sha512-rZAP3aVgB9ds9KOeUSL+zZ21hPmo8dh6fnIFwRQj5EAZl9gzR7wxYbYXYysAM8CTqGmUGyp2S4kUdV17MnGuWQ=="],
    "@google/genai": ["@google/genai@2.0.0", "", { "dependencies": { "google-auth-library": "^10.3.0", "p-retry": "^4.6.2", "protobufjs": "^7.5.4", "ws": "^8.18.0" }, "peerDependencies": { "@modelcontextprotocol/sdk": "^1.25.2" }, "optionalPeers": ["@modelcontextprotocol/sdk"] }, "sha512-6XpO+YbGutXkm5QgR7NZktISxSz0dw3pSs9NtCUQwvhJc1eyA3KhdKhE/0Uaxp3a6eul3LC0SKau1bXymjOKUg=="],
    "@humanfs/core": ["@humanfs/core@0.19.1", "", {}, "sha512-5DyQ4+1JEUzejeK1JGICcideyfUbGixgS9jNgex5nqkW+cY7WZhxBigmieN5Qnw9ZosSNVC9KQKyb+GUaGyKUA=="],
    "@humanfs/node": ["@humanfs/node@0.16.7", "", { "dependencies": { "@humanfs/core": "^0.19.1", "@humanwhocodes/retry": "^0.4.0" } }, "sha512-/zUx+yOsIrG4Y43Eh2peDeKCxlRt/gET6aHfaKpuq267qXdYDFViVHfMaLyygZOnl0kGWxFIgsBy8QFuTLUXEQ=="],
    "@humanwhocodes/module-importer": ["@humanwhocodes/module-importer@1.0.1", "", {}, "sha512-bxveV4V8v5Yb4ncFTT3rPSgZBOpCkjfK0y4oVVVJwIuDVBRMDXrPyXRL988i5ap9m9bnyEEjWfm5WkBmtffLfA=="],
    "@humanwhocodes/retry": ["@humanwhocodes/retry@0.4.3", "", {}, "sha512-bV0Tgo9K4hfPCek+aMAn81RppFKv2ySDQeMoSZuvTASywNTnVJCArCZE2FWqpvIatKu7VMRLWlR1EazvVhDyhQ=="],
    "@img/colour": ["@img/colour@1.0.0", "", {}, "sha512-A5P/LfWGFSl6nsckYtjw9da+19jB8hkJ6ACTGcDfEJ0aE+l2n2El7dsVM7UVHZQ9s2lmYMWlrS21YLy2IR1LUw=="],
    "@img/sharp-darwin-arm64": ["@img/sharp-darwin-arm64@0.34.5", "", { "optionalDependencies": { "@img/sharp-libvips-darwin-arm64": "1.2.4" }, "os": "darwin", "cpu": "arm64" }, "sha512-imtQ3WMJXbMY4fxb/Ndp6HBTNVtWCUI0WdobyheGf5+ad6xX8VIDO8u2xE4qc/fr08CKG/7dDseFtn6M6g/r3w=="],
@@ -253,14 +226,8 @@
    "@types/bun": ["@types/bun@1.3.13", "", { "dependencies": { "bun-types": "1.3.13" } }, "sha512-9fqXWk5YIHGGnUau9TEi+qdlTYDAnOj+xLCmSTwXfAIqXr2x4tytJb43E9uCvt09zJURKXwAtkoH4nLQfzeTXw=="],
    "@types/esrecurse": ["@types/esrecurse@4.3.1", "", {}, "sha512-xJBAbDifo5hpffDBuHl0Y8ywswbiAp/Wi7Y/GtAgSlZyIABppyurxVueOPE8LUQOxdlgi6Zqce7uoEpqNTeiUw=="],
    "@types/estree": ["@types/estree@1.0.8", "", {}, "sha512-dWHzHa2WqEXI/O1E9OjrocMTKJl2mSrEolh1Iomrv6U+JuNwaHXsXx9bLu5gG7BUWFIN0skIQJQ/L1rIex4X6w=="],
    "@types/fluent-ffmpeg": ["@types/fluent-ffmpeg@2.1.28", "", { "dependencies": { "@types/node": "*" } }, "sha512-5ovxsDwBcPfJ+eYs1I/ZpcYCnkce7pvH9AHSvrZllAp1ZPpTRDZAFjF3TRFbukxSgIYTTNYePbS0rKUmaxVbXw=="],
    "@types/json-schema": ["@types/json-schema@7.0.15", "", {}, "sha512-5+fP8P8MFNC+AyZCDxrB2pkZFPGzqQWUzpSeuuVLvm8VMcorNYavBqoFcxK8bQz4Qsbn4oUEEem4wDLfcysGHA=="],
    "@types/node": ["@types/node@25.6.1", "", { "dependencies": { "undici-types": "~7.19.0" } }, "sha512-coJCN8O1q4AGyyqCAUSP06P+SrMTu18BkEj3NVAK07q6QUneD2wzj3CLv9+yP+BMeZQlMvneXqqvDe3w+xcq7g=="],
    "@types/qrcode": ["@types/qrcode@1.5.6", "", { "dependencies": { "@types/node": "*" } }, "sha512-te7NQcV2BOvdj2b1hCAHzAoMNuj65kNBMz0KBaxM6c3VGBOhU0dURQKOtH8CFNI/dsKkwlv32p26qYQTWoB5bw=="],
@@ -269,34 +236,24 @@
    "@types/ws": ["@types/ws@8.18.1", "", { "dependencies": { "@types/node": "*" } }, "sha512-ThVF6DCVhA8kUGy+aazFQ4kXQ7E1Ty7A3ypFOe0IcJV8O/M511G99AW24irKrW56Wt44yG9+ij8FaqoBGkuBXg=="],
-    "@typescript-eslint/eslint-plugin": ["@typescript-eslint/eslint-plugin@8.59.2", "", { "dependencies": { "@eslint-community/regexpp": "^4.12.2", "@typescript-eslint/scope-manager": "8.59.2", "@typescript-eslint/type-utils": "8.59.2", "@typescript-eslint/utils": "8.59.2", "@typescript-eslint/visitor-keys": "8.59.2", "ignore": "^7.0.5", "natural-compare": "^1.4.0", "ts-api-utils": "^2.5.0" }, "peerDependencies": { "@typescript-eslint/parser": "^8.59.2", "eslint": "^8.57.0 || ^9.0.0 || ^10.0.0", "typescript": ">=4.8.4 <6.1.0" } }, "sha512-j/bwmkBvHUtPNxzuWe5z6BEk3q54YRyGlBXkSsmfoih7zNrBvl5A9A98anlp/7JbyZcWIJ8KXo/3Tq/DjFLtuQ=="],
+    "@typescript/native-preview": ["@typescript/native-preview@7.0.0-dev.20260421.2", "", { "optionalDependencies": { "@typescript/native-preview-darwin-arm64": "7.0.0-dev.20260421.2", "@typescript/native-preview-darwin-x64": "7.0.0-dev.20260421.2", "@typescript/native-preview-linux-arm": "7.0.0-dev.20260421.2", "@typescript/native-preview-linux-arm64": "7.0.0-dev.20260421.2", "@typescript/native-preview-linux-x64": "7.0.0-dev.20260421.2", "@typescript/native-preview-win32-arm64": "7.0.0-dev.20260421.2", "@typescript/native-preview-win32-x64": "7.0.0-dev.20260421.2" }, "bin": { "tsgo": "bin/tsgo.js" } }, "sha512-CmajHI25HpVWE9R1XFoxr+cphJPxoYD3eFioQtAvXYkMFKnLdICMS9pXre9Pybizb75ejRxjKD5/CVG055rEIg=="],
-    "@typescript-eslint/parser": ["@typescript-eslint/parser@8.59.2", "", { "dependencies": { "@typescript-eslint/scope-manager": "8.59.2", "@typescript-eslint/types": "8.59.2", "@typescript-eslint/typescript-estree": "8.59.2", "@typescript-eslint/visitor-keys": "8.59.2", "debug": "^4.4.3" }, "peerDependencies": { "eslint": "^8.57.0 || ^9.0.0 || ^10.0.0", "typescript": ">=4.8.4 <6.1.0" } }, "sha512-plR3pp6D+SSUn1HM7xvSkx12/DhoHInI2YF35KAcVFNZvlC0gtrWqx7Qq1oH2Ssgi0vlFRCTbP+DZc7B9+TtsQ=="],
+    "@typescript/native-preview-darwin-arm64": ["@typescript/native-preview-darwin-arm64@7.0.0-dev.20260421.2", "", { "os": "darwin", "cpu": "arm64" }, "sha512-fHv1r3ZmVo6zxuAIFmuX3w9QxbcauoG0SsWhmDwm6VmRubLlOJIcmTtlmV3JAb9oOnq8LuzZljzT7Q39fSMQDw=="],
-    "@typescript-eslint/project-service": ["@typescript-eslint/project-service@8.59.2", "", { "dependencies": { "@typescript-eslint/tsconfig-utils": "^8.59.2", "@typescript-eslint/types": "^8.59.2", "debug": "^4.4.3" }, "peerDependencies": { "typescript": ">=4.8.4 <6.1.0" } }, "sha512-+2hqvEkeyf/0FBor67duF0Ll7Ot8jyKzDQOSrxazF/danillRq2DwR9dLptsXpoZQqxE1UisSmoZewrlPas9Vw=="],
+    "@typescript/native-preview-darwin-x64": ["@typescript/native-preview-darwin-x64@7.0.0-dev.20260421.2", "", { "os": "darwin", "cpu": "x64" }, "sha512-KWTR6xbW9t+JS7D5DQIzo75pqVXVWUxF9PMv/+S6xsnOjCVd6g0ixHcFpFMJMKSUQpGPr8Z5f7b8ks6LHW01jg=="],
-    "@typescript-eslint/scope-manager": ["@typescript-eslint/scope-manager@8.59.2", "", { "dependencies": { "@typescript-eslint/types": "8.59.2", "@typescript-eslint/visitor-keys": "8.59.2" } }, "sha512-JzfyEpEtOU89CcFSwyNS3mu4MLvLSXqnmX05+aKBDM+TdR5jzcGOEBwxwGNxrEQ7p/z6kK2WyioCGBf2zZBnvg=="],
+    "@typescript/native-preview-linux-arm": ["@typescript/native-preview-linux-arm@7.0.0-dev.20260421.2", "", { "os": "linux", "cpu": "arm" }, "sha512-BWLQO3nemLDSV5PoE5GPHe1dU9Dth77Kv8/cle9Ujcp4LhPo0KincdPqFH/qKeU/xvW25mgFueflZ1nc4rKuww=="],
-    "@typescript-eslint/tsconfig-utils": ["@typescript-eslint/tsconfig-utils@8.59.2", "", { "peerDependencies": { "typescript": ">=4.8.4 <6.1.0" } }, "sha512-BKK4alN7oi4C/zv4VqHQ+uRU+lTa6JGIZ7s1juw7b3RHo9OfKB+bKX3u0iVZetdsUCBBkSbdWbarJbmN0fTeSw=="],
+    "@typescript/native-preview-linux-arm64": ["@typescript/native-preview-linux-arm64@7.0.0-dev.20260421.2", "", { "os": "linux", "cpu": "arm64" }, "sha512-VLMEuml3BhUb+jaL0TXQ4xvVODxJF+RhkI+tBWvlynsJI4khTXEiwWh+wPOJrsfBRYFRMXEu28Odl/HXkYze8w=="],
-    "@typescript-eslint/type-utils": ["@typescript-eslint/type-utils@8.59.2", "", { "dependencies": { "@typescript-eslint/types": "8.59.2", "@typescript-eslint/typescript-estree": "8.59.2", "@typescript-eslint/utils": "8.59.2", "debug": "^4.4.3", "ts-api-utils": "^2.5.0" }, "peerDependencies": { "eslint": "^8.57.0 || ^9.0.0 || ^10.0.0", "typescript": ">=4.8.4 <6.1.0" } }, "sha512-nhqaj1nmTdVVl/BP5omXNRGO38jn5iosis2vbdmupF2txCf8ylWT8lx+JlvMYYVqzGVKtjojUFoQ3JRWK+mfzQ=="],
+    "@typescript/native-preview-linux-x64": ["@typescript/native-preview-linux-x64@7.0.0-dev.20260421.2", "", { "os": "linux", "cpu": "x64" }, "sha512-qUrJWTB5/wv4wnRG0TRXElAxc2kykNiRNyEIEqBbLmzDlrcvAW7RRy8MXoY1ZyTiKGMu14itZ3x9oW6+blFpRw=="],
-    "@typescript-eslint/types": ["@typescript-eslint/types@8.59.2", "", {}, "sha512-e82GVOE8Ps3E++Egvb6Y3Dw0S10u8NkQ9KXmtRhCWJJ8kDhOJTvtMAWnFL16kB1583goCWXsr0NieKCZMs2/0Q=="],
+    "@typescript/native-preview-win32-arm64": ["@typescript/native-preview-win32-arm64@7.0.0-dev.20260421.2", "", { "os": "win32", "cpu": "arm64" }, "sha512-Rc6NsWlZmCs5YUKVzKgwoBOoRUGsPzct4BDMRX0csD1devLBBc4AbUXWKsJRbpwIAnqMO1ld4sNHEb+wXgfNHQ=="],
-    "@typescript-eslint/typescript-estree": ["@typescript-eslint/typescript-estree@8.59.2", "", { "dependencies": { "@typescript-eslint/project-service": "8.59.2", "@typescript-eslint/tsconfig-utils": "8.59.2", "@typescript-eslint/types": "8.59.2", "@typescript-eslint/visitor-keys": "8.59.2", "debug": "^4.4.3", "minimatch": "^10.2.2", "semver": "^7.7.3", "tinyglobby": "^0.2.15", "ts-api-utils": "^2.5.0" }, "peerDependencies": { "typescript": ">=4.8.4 <6.1.0" } }, "sha512-o0XPGNwcWw+FIwStOWn+BwBuEmL6QXP0rsvAFg7ET1dey1Nr6Wb1ac8p5HEsK0ygO/6mUxlk+YWQD9xcb/nnXg=="],
+    "@typescript/native-preview-win32-x64": ["@typescript/native-preview-win32-x64@7.0.0-dev.20260421.2", "", { "os": "win32", "cpu": "x64" }, "sha512-GQv1+dya1t6EqF2Cpsb+xoozovdX10JUSf6Kl/8xNkTapzmlHd+uMr+8ku3jIASTxoRGn0Mklgjj3MDKrOTuLg=="],
    "@typescript-eslint/utils": ["@typescript-eslint/utils@8.59.2", "", { "dependencies": { "@eslint-community/eslint-utils": "^4.9.1", "@typescript-eslint/scope-manager": "8.59.2", "@typescript-eslint/types": "8.59.2", "@typescript-eslint/typescript-estree": "8.59.2" }, "peerDependencies": { "eslint": "^8.57.0 || ^9.0.0 || ^10.0.0", "typescript": ">=4.8.4 <6.1.0" } }, "sha512-Juw3EinkXqjaffxz6roowvV7GZT/kET5vSKKZT6upl5TXdWkLkYmNPXwDDL2Vkt2DPn0nODIS4egC/0AGxKo/Q=="],
    "@typescript-eslint/visitor-keys": ["@typescript-eslint/visitor-keys@8.59.2", "", { "dependencies": { "@typescript-eslint/types": "8.59.2", "eslint-visitor-keys": "^5.0.0" } }, "sha512-NwjLUnGy8/Zfx23fl50tRC8rYaYnM52xNRYFAXvmiil9yh1+K6aRVQMnzW6gQB/1DLgWt977lYQn7C+wtgXZiA=="],
    "acorn": ["acorn@8.16.0", "", { "bin": { "acorn": "bin/acorn" } }, "sha512-UVJyE9MttOsBQIDKw1skb9nAwQuR5wuGD3+82K6JgJlm/Y+KI92oNsMNGZCYdDsVtRHSak0pcV5Dno5+4jh9sw=="],
    "acorn-jsx": ["acorn-jsx@5.3.2", "", { "peerDependencies": { "acorn": "^6.0.0 || ^7.0.0 || ^8.0.0" } }, "sha512-rq9s+JNhf0IChjtDXxllJ7g41oZk5SlXtp0LHwyA5cejwn7vKmKp4pPri6YEePv2PU65sAsegbXtIinmDFDXgQ=="],
    "agent-base": ["agent-base@7.1.4", "", {}, "sha512-MnA+YT8fwfJPgBx3m60MNqakm30XOkyIoH1y6huTQvC0PwZG7ki8NacLBcrPbNoo8vEZy7Jpuk7+jMO+CUovTQ=="],
    "ajv": ["ajv@6.14.0", "", { "dependencies": { "fast-deep-equal": "^3.1.1", "fast-json-stable-stringify": "^2.0.0", "json-schema-traverse": "^0.4.1", "uri-js": "^4.2.2" } }, "sha512-IWrosm/yrn43eiKqkfkHis7QioDleaXQHdDVPKg0FSwwd/DuvyX79TZnFOnYpB7dcsFAMmtFztZuXPDvSePkFw=="],
    "ansi-regex": ["ansi-regex@5.0.1", "", {}, "sha512-quJQXlTSUGL2LH9SUXo8VwsY4soanhgo6LNSm84E1LBcE8s3O0wpdiRzyR9z/ZZJMlMWv37qOOb9pdJlMUEKFQ=="],
    "ansi-styles": ["ansi-styles@4.3.0", "", { "dependencies": { "color-convert": "^2.0.1" } }, "sha512-zbB9rCJAT1rbjiVDb2hqKFHNYLxgtk8NURxZ3IZwD3F6NtxbXZQCnnSi1Lkx+IDohdPlFp222wVALIheZJQSEg=="],
@@ -307,13 +264,13 @@
    "axios": ["axios@1.16.0", "", { "dependencies": { "follow-redirects": "^1.16.0", "form-data": "^4.0.5", "proxy-from-env": "^2.1.0" } }, "sha512-6hp5CwvTPlN2A31g5dxnwAX0orzM7pmCRDLnZSX772mv8WDqICwFjowHuPs04Mc8deIld1+ejhtaMn5vp6b+1w=="],
-    "balanced-match": ["balanced-match@4.0.4", "", {}, "sha512-BLrgEcRTwX2o6gGxGOCNyMvGSp35YofuYzw9h1IMTRmKqttAZZVU67bdb9Pr2vUHA8+j3i2tJfjO6C6+4myGTA=="],
+    "balanced-match": ["balanced-match@1.0.2", "", {}, "sha512-3oSeUO0TMV67hN1AmbXsK4yaqU7tjiHlbxRDZOpH0KW9+CeX4bRAaX0Anxt0tx2MrpRpWwQaPwIlISEJhYU5Pw=="],
    "base64-js": ["base64-js@1.5.1", "", {}, "sha512-AKpaYlHn8t4SVbOHCy+b5+KKgvR4vrsD8vbvrbiQJps7fKDTkjkDry6ji0rUJjC0kzbNePLwzxq8iypo41qeWA=="],
    "bignumber.js": ["bignumber.js@9.3.1", "", {}, "sha512-Ko0uX15oIUS7wJ3Rb30Fs6SkVbLmPBAKdlm7q9+ak9bbIeFf0MwuBsQV6z7+X768/cHsfg+WlysDWJcmthjsjQ=="],
-    "brace-expansion": ["brace-expansion@5.0.5", "", { "dependencies": { "balanced-match": "^4.0.2" } }, "sha512-VZznLgtwhn+Mact9tfiwx64fA9erHH/MCXEUfB/0bX/6Fz6ny5EGTXYltMocqg4xFAQZtnO3DHWWXi8RiuN7cQ=="],
+    "brace-expansion": ["brace-expansion@2.0.2", "", { "dependencies": { "balanced-match": "^1.0.0" } }, "sha512-Jt0vHyM+jmUBqojB7E1NIYadt0vI0Qxjxd2TErW94wDz+E2LAm5vKMXXwg6ZZBTHPuUlDgQHKXvjGBdfcF1ZDQ=="],
    "buffer-equal-constant-time": ["buffer-equal-constant-time@1.0.1", "", {}, "sha512-zRpUiDwd/xk6ADqPMATG8vc9VPrkck7T07OIx0gnjmJAnHnTVXNQG3vfvWNuiZIkwu9KrKdA1iJKfsfTVxE6NA=="],
@@ -341,8 +298,6 @@
    "decamelize": ["decamelize@1.2.0", "", {}, "sha512-z2S+W9X73hAUUki+N+9Za2lBlun89zigOyGrsax+KUQ6wKW4ZoWpEYBkGhQjwAjjDCkWxhY0VKEhk8wzY7F5cA=="],
    "deep-is": ["deep-is@0.1.4", "", {}, "sha512-oIPzksmTg4/MriiaYGO+okXDT7ztn/w3Eptv/+gSIdMdKsJo0u4CfYNFJPy+4SKMuCqGw2wxnA+URMg3t8a/bQ=="],
    "delayed-stream": ["delayed-stream@1.0.0", "", {}, "sha1-3zrhmayt+31ECqrgsp4icrJOxhk="],
    "detect-libc": ["detect-libc@2.1.2", "", {}, "sha512-Btj2BOOO83o3WyH59e8MgXsxEQVcarkUOpEYrubB0urwnN10yQ364rsiByU11nZlqWYZm05i/of7io4mzihBtQ=="],
@@ -373,43 +328,11 @@
    "esbuild": ["esbuild@0.25.12", "", { "optionalDependencies": { "@esbuild/aix-ppc64": "0.25.12", "@esbuild/android-arm": "0.25.12", "@esbuild/android-arm64": "0.25.12", "@esbuild/android-x64": "0.25.12", "@esbuild/darwin-arm64": "0.25.12", "@esbuild/darwin-x64": "0.25.12", "@esbuild/freebsd-arm64": "0.25.12", "@esbuild/freebsd-x64": "0.25.12", "@esbuild/linux-arm": "0.25.12", "@esbuild/linux-arm64": "0.25.12", "@esbuild/linux-ia32": "0.25.12", "@esbuild/linux-loong64": "0.25.12", "@esbuild/linux-mips64el": "0.25.12", "@esbuild/linux-ppc64": "0.25.12", "@esbuild/linux-riscv64": "0.25.12", "@esbuild/linux-s390x": "0.25.12", "@esbuild/linux-x64": "0.25.12", "@esbuild/netbsd-arm64": "0.25.12", "@esbuild/netbsd-x64": "0.25.12", "@esbuild/openbsd-arm64": "0.25.12", "@esbuild/openbsd-x64": "0.25.12", "@esbuild/openharmony-arm64": "0.25.12", "@esbuild/sunos-x64": "0.25.12", "@esbuild/win32-arm64": "0.25.12", "@esbuild/win32-ia32": "0.25.12", "@esbuild/win32-x64": "0.25.12" }, "bin": { "esbuild": "bin/esbuild" } }, "sha512-bbPBYYrtZbkt6Os6FiTLCTFxvq4tt3JKall1vRwshA3fdVztsLAatFaZobhkBC8/BrPetoa0oksYoKXoG4ryJg=="],
    "escape-string-regexp": ["escape-string-regexp@4.0.0", "", {}, "sha512-TtpcNJ3XAzx3Gq8sWRzJaVajRs0uVxA2YAkdb1jm2YkPz4G6egUFAyA3n5vtEIZefPk5Wa4UXbKuS5fKkJWdgA=="],
    "eslint": ["eslint@10.3.0", "", { "dependencies": { "@eslint-community/eslint-utils": "^4.8.0", "@eslint-community/regexpp": "^4.12.2", "@eslint/config-array": "^0.23.5", "@eslint/config-helpers": "^0.5.5", "@eslint/core": "^1.2.1", "@eslint/plugin-kit": "^0.7.1", "@humanfs/node": "^0.16.6", "@humanwhocodes/module-importer": "^1.0.1", "@humanwhocodes/retry": "^0.4.2", "@types/estree": "^1.0.6", "ajv": "^6.14.0", "cross-spawn": "^7.0.6", "debug": "^4.3.2", "escape-string-regexp": "^4.0.0", "eslint-scope": "^9.1.2", "eslint-visitor-keys": "^5.0.1", "espree": "^11.2.0", "esquery": "^1.7.0", "esutils": "^2.0.2", "fast-deep-equal": "^3.1.3", "file-entry-cache": "^8.0.0", "find-up": "^5.0.0", "glob-parent": "^6.0.2", "ignore": "^5.2.0", "imurmurhash": "^0.1.4", "is-glob": "^4.0.0", "json-stable-stringify-without-jsonify": "^1.0.1", "minimatch": "^10.2.4", "natural-compare": "^1.4.0", "optionator": "^0.9.3" }, "peerDependencies": { "jiti": "*" }, "optionalPeers": ["jiti"], "bin": { "eslint": "bin/eslint.js" } }, "sha512-XbEXaRva5cF0ZQB8w6MluHA0kZZfV2DuCMJ3ozyEOHLwDpZX2Lmm/7Pp0xdJmI0GL1W05VH5VwIFHEm1Vcw2gw=="],
    "eslint-scope": ["eslint-scope@9.1.2", "", { "dependencies": { "@types/esrecurse": "^4.3.1", "@types/estree": "^1.0.8", "esrecurse": "^4.3.0", "estraverse": "^5.2.0" } }, "sha512-xS90H51cKw0jltxmvmHy2Iai1LIqrfbw57b79w/J7MfvDfkIkFZ+kj6zC3BjtUwh150HsSSdxXZcsuv72miDFQ=="],
    "eslint-visitor-keys": ["eslint-visitor-keys@5.0.1", "", {}, "sha512-tD40eHxA35h0PEIZNeIjkHoDR4YjjJp34biM0mDvplBe//mB+IHCqHDGV7pxF+7MklTvighcCPPZC7ynWyjdTA=="],
    "espree": ["espree@11.2.0", "", { "dependencies": { "acorn": "^8.16.0", "acorn-jsx": "^5.3.2", "eslint-visitor-keys": "^5.0.1" } }, "sha512-7p3DrVEIopW1B1avAGLuCSh1jubc01H2JHc8B4qqGblmg5gI9yumBgACjWo4JlIc04ufug4xJ3SQI8HkS/Rgzw=="],
    "esquery": ["esquery@1.7.0", "", { "dependencies": { "estraverse": "^5.1.0" } }, "sha512-Ap6G0WQwcU/LHsvLwON1fAQX9Zp0A2Y6Y/cJBl9r/JbW90Zyg4/zbG6zzKa2OTALELarYHmKu0GhpM5EO+7T0g=="],
    "esrecurse": ["esrecurse@4.3.0", "", { "dependencies": { "estraverse": "^5.2.0" } }, "sha512-KmfKL3b6G+RXvP8N1vr3Tq1kL/oCFgn2NYXEtqP8/L3pKapUA4G8cFVaoF3SU323CD4XypR/ffioHmkti6/Tag=="],
    "estraverse": ["estraverse@5.3.0", "", {}, "sha512-MMdARuVEQziNTeJD8DgMqmhwR11BRQ/cBP+pLtYdSTnf3MIO8fFeiINEbX36ZdNlfU/7A9f3gUw49B3oQsvwBA=="],
    "esutils": ["esutils@2.0.3", "", {}, "sha512-kVscqXk4OCp68SZ0dkgEKVi6/8ij300KBWTJq32P/dYeWTSwK41WyTxalN1eRmA5Z9UU/LX9D7FWSmV9SAYx6g=="],
    "extend": ["extend@3.0.2", "", {}, "sha512-fjquC59cD7CyW6urNXK0FBufkZcoiGG80wTuPujX590cB5Ttln20E2UB4S/WARVqhXffZl2LNgS+gQdPIIim/g=="],
    "fast-deep-equal": ["fast-deep-equal@3.1.3", "", {}, "sha512-f3qQ9oQy9j2AhBe/H9VC91wLmKBCCU/gDOnKNAYG5hswO7BLKj09Hc5HYNz9cGI++xlpDCIgDaitVs03ATR84Q=="],
    "fast-json-stable-stringify": ["fast-json-stable-stringify@2.1.0", "", {}, "sha512-lhd/wF+Lk98HZoTCtlVraHtfh5XYijIjalXck7saUtuanSDyLMxnHhSXEDJqHxD7msR8D0uCmqlkwjCV8xvwHw=="],
    "fast-levenshtein": ["fast-levenshtein@2.0.6", "", {}, "sha512-DCXu6Ifhqcks7TZKY3Hxp3y6qphY5SJZmrWMDrKcERSOXWQdMhU9Ig/PYrzyw/ul9jOIyh0N4M0tbC5hodg8dw=="],
    "fdir": ["fdir@6.5.0", "", { "peerDependencies": { "picomatch": "^3 || ^4" }, "optionalPeers": ["picomatch"] }, "sha512-tIbYtZbucOs0BRGqPJkshJUYdL+SDH7dVM8gjy+ERp3WAUjLEFJE+02kanyHtwjWOnwrKYBiwAmM0p4kLJAnXg=="],
    "fetch-blob": ["fetch-blob@3.2.0", "", { "dependencies": { "node-domexception": "^1.0.0", "web-streams-polyfill": "^3.0.3" } }, "sha512-7yAQpD2UMJzLi1Dqv7qFYnPbaPx7ZfFK6PiIxQ4PfkGPyNyl2Ugx+a/umUonmKqjhM4DnfbMvdX6otXq83soQQ=="],
-    "file-entry-cache": ["file-entry-cache@8.0.0", "", { "dependencies": { "flat-cache": "^4.0.0" } }, "sha512-XXTUwCvisa5oacNGRP9SfNtYBNAMi+RPwBFmblZEF7N7swHYQS6/Zfk7SRwx4D5j3CH211YNRco1DEMNVfZCnQ=="],
+    "find-up": ["find-up@4.1.0", "", { "dependencies": { "locate-path": "^5.0.0", "path-exists": "^4.0.0" } }, "sha512-PpOwAdQ/YlXQ2vj8a3h8IipDuYRi3wceVQQGYWxNINccq40Anw7BlsEXCMbt1Zt+OLA6Fq9suIpIWD0OsnISlw=="],
    "find-up": ["find-up@5.0.0", "", { "dependencies": { "locate-path": "^6.0.0", "path-exists": "^4.0.0" } }, "sha512-78/PXT1wlLLDgTzDs7sjq9hzz0vXD+zn+7wypEe4fXQxCmdmqfGsEPQxmiCSQI3ajFV91bVSsvNtrJRiW6nGng=="],
    "flat-cache": ["flat-cache@4.0.1", "", { "dependencies": { "flatted": "^3.2.9", "keyv": "^4.5.4" } }, "sha512-f7ccFPK3SXFHpx15UIGyRJ/FJQctuKZ0zVuN3frBo4HnK3cay9VEW0R6yPYFHC0AgqhukPzKjq22t5DmAyqGyw=="],
    "flatted": ["flatted@3.3.3", "", {}, "sha512-GX+ysw4PBCz0PzosHDepZGANEuFCMLrnRTiEy9McGjmkCQYwRq4A/X786G/fjM/+OjsWSU1ZrY5qyARZmO/uwg=="],
    "fluent-ffmpeg": ["fluent-ffmpeg@2.1.3", "", { "dependencies": { "async": "^0.2.9", "which": "^1.1.1" } }, "sha512-Be3narBNt2s6bsaqP6Jzq91heDgOEaDCJAXcE3qcma/EJBSy5FB4cvO31XBInuAuKBx8Kptf8dkhjK0IOru39Q=="],
@@ -437,12 +360,10 @@
    "get-proto": ["get-proto@1.0.1", "", { "dependencies": { "dunder-proto": "^1.0.1", "es-object-atoms": "^1.0.0" } }, "sha512-sTSfBjoXBp89JvIKIefqw7U2CCebsc74kiY6awiGogKtoSGbgjYE/G/+l9sF3MWFPNc9IcoOC4ODfKHfxFmp0g=="],
-    "get-tsconfig": ["get-tsconfig@4.13.0", "", { "dependencies": { "resolve-pkg-maps": "^1.0.0" } }, "sha512-1VKTZJCwBrvbd+Wn3AOgQP/2Av+TfTCOlE4AcRJE72W1ksZXbAx8PPBR9RzgTeSPzlPMHrbANMH3LbltH73wxQ=="],
+    "get-tsconfig": ["get-tsconfig@4.14.0", "", { "dependencies": { "resolve-pkg-maps": "^1.0.0" } }, "sha512-yTb+8DXzDREzgvYmh6s9vHsSVCHeC0G3PI5bEXNBHtmshPnO+S5O7qgLEOn0I5QvMy6kpZN8K1NKGyilLb93wA=="],
    "glob": ["glob@10.5.0", "", { "dependencies": { "foreground-child": "^3.1.0", "jackspeak": "^3.1.2", "minimatch": "^9.0.4", "minipass": "^7.1.2", "package-json-from-dist": "^1.0.0", "path-scurry": "^1.11.1" }, "bin": { "glob": "dist/esm/bin.mjs" } }, "sha512-DfXN8DfhJ7NH3Oe7cFmu3NCu1wKbkReJ8TorzSAFbSKrlNaQSKfIzqYqVY8zlbs2NLBbWpRiU52GX2PbaBVNkg=="],
    "glob-parent": ["glob-parent@6.0.2", "", { "dependencies": { "is-glob": "^4.0.3" } }, "sha512-XxwI8EOhVQgWp6iDL+3b0r86f4d6AX6zSU55HfB4ydCEuXLXc5FcYeOu+nnGftS4TEju/11rt4KJPTMgbfmv4A=="],
    "google-auth-library": ["google-auth-library@10.5.0", "", { "dependencies": { "base64-js": "^1.3.0", "ecdsa-sig-formatter": "^1.0.11", "gaxios": "^7.0.0", "gcp-metadata": "^8.0.0", "google-logging-utils": "^1.0.0", "gtoken": "^8.0.0", "jws": "^4.0.0" } }, "sha512-7ABviyMOlX5hIVD60YOfHw4/CxOfBhyduaYB+wbFWCWoni4N7SLcV46hrVRktuBbZjFC9ONyqamZITN7q3n32w=="],
    "google-logging-utils": ["google-logging-utils@1.1.3", "", {}, "sha512-eAmLkjDjAFCVXg7A1unxHsLf961m6y17QFqXqAXGj/gVkKFrEICfStRfwUlGNfeCEjNRa32JEWOUTlYXPyyKvA=="],
@@ -461,16 +382,8 @@
    "https-proxy-agent": ["https-proxy-agent@7.0.6", "", { "dependencies": { "agent-base": "^7.1.2", "debug": "4" } }, "sha512-vK9P5/iUfdl95AI+JVyUuIcVtd4ofvtrOr3HNtM2yxC9bnMbEdp3x01OhQNnjb8IJYi38VlTE3mBXwcfvywuSw=="],
    "ignore": ["ignore@7.0.5", "", {}, "sha512-Hs59xBNfUIunMFgWAbGX5cq6893IbWg4KnrjbYwX3tx0ztorVgTDA6B2sxf8ejHJ4wz8BqGUMYlnzNBer5NvGg=="],
    "imurmurhash": ["imurmurhash@0.1.4", "", {}, "sha512-JmXMZ6wuvDmLiHEml9ykzqO6lwFbof0GG4IkcGaENdCRDDmMVnny7s5HsIgHCbaq0w2MyPhDqkhTUgS2LU2PHA=="],
    "is-extglob": ["is-extglob@2.1.1", "", {}, "sha512-SbKbANkN603Vi4jEZv49LeVJMn4yGwsbzZworEoyEiutsN3nJYdbO36zfhGJ6QEDpOZIFkDtnq5JRxmvl3jsoQ=="],
    "is-fullwidth-code-point": ["is-fullwidth-code-point@3.0.0", "", {}, "sha512-zymm5+u+sCsSWyD9qNaejV3DFvhCKclKdizYaJUuHA83RLjb7nSuGnddCHGv0hk+KY7BMAlsWeK4Ueg6EV6XQg=="],
    "is-glob": ["is-glob@4.0.3", "", { "dependencies": { "is-extglob": "^2.1.1" } }, "sha512-xelSayHH36ZgE7ZWhli7pW34hNbNl8Ojv5KVmkJD4hBdD3th8Tfk9vYasLM+mXWOZhFkgZfxhLSnrwRr4elSSg=="],
    "isexe": ["isexe@2.0.0", "", {}, "sha512-RHxMLp9lnKHGHRng9QFhRCMbYAcVpn69smSGcq3f36xjgVVWThj4qqLbTLlq7Ssj8B+fIQ1EuCEGI2lKsyQeIw=="],
    "jackspeak": ["jackspeak@3.4.3", "", { "dependencies": { "@isaacs/cliui": "^8.0.2" }, "optionalDependencies": { "@pkgjs/parseargs": "^0.11.0" } }, "sha512-OGlZQpz2yfahA/Rd1Y8Cd9SIEsqvXkLVoSw/cgwhnhFMDbsQFeZYoJJ7bIZBS9BcamUW96asq/npPWugM+RQBw=="],
@@ -479,25 +392,15 @@
    "json-bigint": ["json-bigint@1.0.0", "", { "dependencies": { "bignumber.js": "^9.0.0" } }, "sha512-SiPv/8VpZuWbvLSMtTDU8hEfrZWg/mH/nV/b4o0CYbSxu1UIQPLdwKOCIyLQX+VIPO5vrLX3i8qtqFyhdPSUSQ=="],
    "json-buffer": ["json-buffer@3.0.1", "", {}, "sha512-4bV5BfR2mqfQTJm+V5tPPdf+ZpuhiIvTuAB5g8kcrXOZpTT/QwwVRWBywX1ozr6lEuPdbHxwaJlm9G6mI2sfSQ=="],
    "json-schema-traverse": ["json-schema-traverse@0.4.1", "", {}, "sha512-xbbCH5dCYU5T8LcEhhuh7HJ88HXuW3qsI3Y0zOZFKfZEHcpWiHU/Jxzk629Brsab/mMiHQti9wMP+845RPe3Vg=="],
    "json-stable-stringify-without-jsonify": ["json-stable-stringify-without-jsonify@1.0.1", "", {}, "sha512-Bdboy+l7tA3OGW6FjyFHWkP5LuByj1Tk33Ljyq0axyzdk9//JSi2u3fP1QSmd1KNwq6VOKYGlAu87CisVir6Pw=="],
    "jsonfile": ["jsonfile@5.0.0", "", { "dependencies": { "universalify": "^0.1.2" }, "optionalDependencies": { "graceful-fs": "^4.1.6" } }, "sha512-NQRZ5CRo74MhMMC3/3r5g2k4fjodJ/wh8MxjFbCViWKFjxrnudWSY5vomh+23ZaXzAS7J3fBZIR2dV6WbmfM0w=="],
    "jwa": ["jwa@2.0.1", "", { "dependencies": { "buffer-equal-constant-time": "^1.0.1", "ecdsa-sig-formatter": "1.0.11", "safe-buffer": "^5.0.1" } }, "sha512-hRF04fqJIP8Abbkq5NKGN0Bbr3JxlQ+qhZufXVr0DvujKy93ZCbXZMHDL4EOtodSbCWxOqR8MS1tXA5hwqCXDg=="],
    "jws": ["jws@4.0.1", "", { "dependencies": { "jwa": "^2.0.1", "safe-buffer": "^5.0.1" } }, "sha512-EKI/M/yqPncGUUh44xz0PxSidXFr/+r0pA70+gIYhjv+et7yxM+s29Y+VGDkovRofQem0fs7Uvf4+YmAdyRduA=="],
    "keyv": ["keyv@4.5.4", "", { "dependencies": { "json-buffer": "3.0.1" } }, "sha512-oxVHkHR/EJf2CNXnWxRLW6mg7JyCCUcG0DtEGmL2ctUo1PNTin1PUil+r/+4r5MpVgC/fn1kjsx7mjSujKqIpw=="],
    "levn": ["levn@0.4.1", "", { "dependencies": { "prelude-ls": "^1.2.1", "type-check": "~0.4.0" } }, "sha512-+bT2uH4E5LGE7h/n3evcS/sQlJXCpIp6ym8OWJ5eV6+67Dsql/LaaT7qJBAt2rzfoa/5QBGBhxDix1dMt2kQKQ=="],
    "libsql": ["libsql@0.5.29", "", { "dependencies": { "@neon-rs/load": "^0.0.4", "detect-libc": "2.0.2" }, "optionalDependencies": { "@libsql/darwin-arm64": "0.5.29", "@libsql/darwin-x64": "0.5.29", "@libsql/linux-arm-gnueabihf": "0.5.29", "@libsql/linux-arm-musleabihf": "0.5.29", "@libsql/linux-arm64-gnu": "0.5.29", "@libsql/linux-arm64-musl": "0.5.29", "@libsql/linux-x64-gnu": "0.5.29", "@libsql/linux-x64-musl": "0.5.29", "@libsql/win32-x64-msvc": "0.5.29" }, "os": [ "linux", "win32", "darwin", ], "cpu": [ "arm", "x64", "arm64", ] }, "sha512-8lMP8iMgiBzzoNbAPQ59qdVcj6UaE/Vnm+fiwX4doX4Narook0a4GPKWBEv+CR8a1OwbfkgL18uBfBjWdF0Fzg=="],
-    "locate-path": ["locate-path@6.0.0", "", { "dependencies": { "p-locate": "^5.0.0" } }, "sha512-iPZK6eYjbxRu3uB4/WZ3EsEIMJFMqAoopl3R+zuq0UjcAm/MO6KCweDgPfP3elTztoKP3KtnVHxTn2NHBSDVUw=="],
+    "locate-path": ["locate-path@5.0.0", "", { "dependencies": { "p-locate": "^4.1.0" } }, "sha512-t7hw9pI+WvuwNJXwk5zVHpyhIqzg2qTlklJOf0mVxGSbe3Fp2VieZcduNYjaLDoy6p9uGpQEGWG87WpMKlNq8g=="],
    "long": ["long@5.3.2", "", {}, "sha512-mNAgZ1GmyNhD7AuqnTG3/VQ26o760+ZYBPKjPvugO8+nLbYfX6TVpJPseBvopbdY+qpZ/lKUnmEc1LeZYS3QAA=="],
@@ -509,14 +412,12 @@
    "mime-types": ["mime-types@2.1.29", "", { "dependencies": { "mime-db": "1.46.0" } }, "sha512-Y/jMt/S5sR9OaqteJtslsFZKWOIIqMACsJSiHghlCAyhf7jfVYjKBmLiX8OgpWeW+fjJ2b+Az69aPFPkUOY6xQ=="],
-    "minimatch": ["minimatch@10.2.5", "", { "dependencies": { "brace-expansion": "^5.0.5" } }, "sha512-MULkVLfKGYDFYejP07QOurDLLQpcjk7Fw+7jXS2R2czRQzR56yHRveU5NDJEOviH+hETZKSkIk5c+T23GjFUMg=="],
+    "minimatch": ["minimatch@9.0.5", "", { "dependencies": { "brace-expansion": "^2.0.1" } }, "sha512-G6T0ZX48xgozx7587koeX9Ys2NYy6Gmv//P89sEte9V9whIapMNF4idKxnW2QtCcLiTWlb/wfCabAtAFWhhBow=="],
    "minipass": ["minipass@7.1.2", "", {}, "sha512-qOOzS1cBTWYF4BH8fVePDBOO9iptMnGUEZwNc/cMWnTV2nVLZ7VoNWEPHkYczZA0pdoA7dl6e7FL659nX9S2aw=="],
    "ms": ["ms@2.1.3", "", {}, "sha512-6FlzubTLZG3J2a/NVCAleEhjzq5oxgHyaCU9yYXvcLsvoVaHJq/s5xXI6/XXP6tz7R9xAOtHnSO/tXtF3WRTlA=="],
    "natural-compare": ["natural-compare@1.4.0", "", {}, "sha512-OWND8ei3VtNC9h7V60qff3SVobHr996CTwgxubgyQYEpg290h9J0buyECNNJexkFm5sOajh5G116RYA1c8ZMSw=="],
    "node-domexception": ["node-domexception@1.0.0", "", {}, "sha512-/jKZoMpw0F8GRwl4/eLROPA3cfcXtLApP0QzLmUT/HuPCZWyB7IY9ZrMeKw2O/nFIqPQB3PVM9aYm0F312AXDQ=="],
    "node-fetch": ["node-fetch@3.3.2", "", { "dependencies": { "data-uri-to-buffer": "^4.0.0", "fetch-blob": "^3.1.4", "formdata-polyfill": "^4.0.10" } }, "sha512-dRB78srN/l6gqWulah9SrxeYnxeddIG30+GOqK/9OlLVyLg3HPnr6SqOWTWOXKRwC2eGYCkZ59NNuSgvSrpgOA=="],
@@ -525,11 +426,9 @@
    "openai": ["openai@6.37.0", "", { "peerDependencies": { "ws": "^8.18.0", "zod": "^3.25 || ^4.0" }, "optionalPeers": ["ws", "zod"], "bin": { "openai": "bin/cli" } }, "sha512-0H5dEGFmmLv6KSd0W1w2nyL8WsLkX6yoLeQpU+dZAOuGcany5qkYQMmj35ZrKgb6yiyYqpUzFOpR8mZQkgqeEQ=="],
-    "optionator": ["optionator@0.9.4", "", { "dependencies": { "deep-is": "^0.1.3", "fast-levenshtein": "^2.0.6", "levn": "^0.4.1", "prelude-ls": "^1.2.1", "type-check": "^0.4.0", "word-wrap": "^1.2.5" } }, "sha512-6IpQ7mKUxRcZNLIObR0hz7lxsapSSIYNZJwXPGeF0mTVqGKFIXj1DQcMoT22S3ROcLyY/rz0PWaWZ9ayWmad9g=="],
+    "p-limit": ["p-limit@2.3.0", "", { "dependencies": { "p-try": "^2.0.0" } }, "sha512-//88mFWSJx8lxCzwdAABTJL2MyWB12+eIY7MDL2SqLmAkeKU9qxRvWuSyTjm3FUmpBEMuFfckAIqEaVGUDxb6w=="],
-    "p-limit": ["p-limit@3.1.0", "", { "dependencies": { "yocto-queue": "^0.1.0" } }, "sha512-TYOanM3wGwNGsZN2cVTYPArw454xnXj5qmWF1bEoAc4+cU/ol7GVh7odevjp1FNHduHc3KZMcFduxU5Xc6uJRQ=="],
+    "p-locate": ["p-locate@4.1.0", "", { "dependencies": { "p-limit": "^2.2.0" } }, "sha512-R79ZZ/0wAxKGu3oYMlz8jy/kbhsNrS7SKZ7PxEHBgJ5+F2mtFW2fK2cOtBh1cHYkQsbzFV7I+EoRKe6Yt0oK7A=="],
    "p-locate": ["p-locate@5.0.0", "", { "dependencies": { "p-limit": "^3.0.2" } }, "sha512-LaNjtRWUBY++zB5nE/NwcaoMylSPk+S+ZHNB1TzdbMJMny6dynpAGt7X/tl/QYq3TIeE6nxHppbo2LGymrG5Pw=="],
    "p-retry": ["p-retry@4.6.2", "", { "dependencies": { "@types/retry": "0.12.0", "retry": "^0.13.1" } }, "sha512-312Id396EbJdvRONlngUx0NydfrIQ5lsYu0znKVUzVvArzEIt08V1qhtyESbGVd1FGX7UKtiFp5uwKZdM8wIuQ=="],
@@ -543,20 +442,14 @@
    "path-scurry": ["path-scurry@1.11.1", "", { "dependencies": { "lru-cache": "^10.2.0", "minipass": "^5.0.0 || ^6.0.2 || ^7.0.0" } }, "sha512-Xa4Nw17FS9ApQFJ9umLiJS4orGjm7ZzwUrwamcGQuHSzDyth9boKDaycYdDcZDuqYATXw4HFXgaqWTctW/v1HA=="],
    "picomatch": ["picomatch@4.0.3", "", {}, "sha512-5gTmgEY/sqK6gFXLIsQNH19lWb4ebPDLA4SdLP7dsWkIXHWlG66oPuVvXSGFPppYZz8ZDZq0dYYrbHfBCVUb1Q=="],
    "pngjs": ["pngjs@5.0.0", "", {}, "sha512-40QW5YalBNfQo5yRYmiw7Yz6TKKVr3h6970B2YE+3fQpsWcrbj1PzJgxeJ19DRQjhMbKPIuMY8rFaXc8moolVw=="],
    "prelude-ls": ["prelude-ls@1.2.1", "", {}, "sha512-vkcDPrRZo1QZLbn5RLGPpg/WmIQ65qoWWhcGKf/b5eplkkarX0m9z8ppCat4mlOqUsWpyNuYgO3VRyrYHSzX5g=="],
    "promise-limit": ["promise-limit@2.7.0", "", {}, "sha512-7nJ6v5lnJsXwGprnGXga4wx6d1POjvi5Qmf1ivTRxTjH4Z/9Czja/UCMLVmB9N93GeWOU93XaFaEt6jbuoagNw=="],
    "protobufjs": ["protobufjs@7.5.4", "", { "dependencies": { "@protobufjs/aspromise": "^1.1.2", "@protobufjs/base64": "^1.1.2", "@protobufjs/codegen": "^2.0.4", "@protobufjs/eventemitter": "^1.1.0", "@protobufjs/fetch": "^1.1.0", "@protobufjs/float": "^1.0.2", "@protobufjs/inquire": "^1.1.0", "@protobufjs/path": "^1.1.2", "@protobufjs/pool": "^1.1.0", "@protobufjs/utf8": "^1.1.0", "@types/node": ">=13.7.0", "long": "^5.0.0" } }, "sha512-CvexbZtbov6jW2eXAvLukXjXUW1TzFaivC46BpWc/3BpcCysb5Vffu+B3XHMm8lVEuy2Mm4XGex8hBSg1yapPg=="],
    "proxy-from-env": ["proxy-from-env@2.1.0", "", {}, "sha512-cJ+oHTW1VAEa8cJslgmUZrc+sjRKgAKl3Zyse6+PV38hZe/V6Z14TbCuXcan9F9ghlz4QrFr2c92TNF82UkYHA=="],
    "punycode": ["punycode@2.3.1", "", {}, "sha512-vYt7UD1U9Wg6138shLtLOvdAu+8DsC/ilFtEVHcH+wydcSpNE20AfSOduf6MkRFahL5FY7X1oU7nKVZFtfq8Fg=="],
    "qrcode": ["qrcode@1.5.4", "", { "dependencies": { "dijkstrajs": "^1.0.1", "pngjs": "^5.0.0", "yargs": "^15.3.1" }, "bin": { "qrcode": "bin/qrcode" } }, "sha512-1ca71Zgiu6ORjHqFBDpnSMTR2ReToX4l1Au1VFLyVeBTFavzQnv5JxMFr3ukHVKpSrSA2MCk0lNJSykjUfz7Zg=="],
    "require-directory": ["require-directory@2.1.1", "", {}, "sha512-fGxEI7+wsG9xrvdjsrlmL22OMTTiHRwAMroiEeMgq8gzoLC/PQr7RsRDSTLUg/bZAZtF+TVIkHc6/4RIKrui+Q=="],
@@ -597,10 +490,6 @@
    "systeminformation": ["systeminformation@5.31.6", "", { "os": "!aix", "bin": { "systeminformation": "lib/cli.js" } }, "sha512-Uv2b2uGGM6ns+26czgW2cYRabYdnswM0ddSOOlryHOaelzsmDSet1iM/NT7VOYxW8x/BW+HkY+b1Ve2pLTSGSA=="],
    "tinyglobby": ["tinyglobby@0.2.15", "", { "dependencies": { "fdir": "^6.5.0", "picomatch": "^4.0.3" } }, "sha512-j2Zq4NyQYG5XMST4cbs02Ak8iJUdxRM0XI5QyxXuZOzKOINmWurp3smXu3y5wDcJrptwpSjgXHzIQxR0omXljQ=="],
    "ts-api-utils": ["ts-api-utils@2.5.0", "", { "peerDependencies": { "typescript": ">=4.8.4" } }, "sha512-OJ/ibxhPlqrMM0UiNHJ/0CKQkoKF243/AEmplt3qpRgkW8VG7IfOS41h7V8TjITqdByHzrjcS/2si+y4lIh8NA=="],
    "tslib": ["tslib@2.8.1", "", {}, "sha512-oJFu94HQb+KVduSUQL7wnpmqnfmLsOA/nAh6b6EH0wCEoK0/mPeXU6c3wKDV83MkOuHPRHtSXKKU99IBazS/2w=="],
    "tsx": ["tsx@4.21.0", "", { "dependencies": { "esbuild": "~0.27.0", "get-tsconfig": "^4.7.5" }, "optionalDependencies": { "fsevents": "~2.3.3" }, "bin": { "tsx": "dist/cli.mjs" } }, "sha512-5C1sg4USs1lfG0GFb2RLXsdpXqBSEhAaA/0kPL01wxzpMqLILNxIxIOKiILz+cdg/pLnOUxFYOR5yhHU666wbw=="],
@@ -609,20 +498,12 @@
    "twemoji-parser": ["twemoji-parser@14.0.0", "", {}, "sha512-9DUOTGLOWs0pFWnh1p6NF+C3CkQ96PWmEFwhOVmT3WbecRC+68AIqpsnJXygfkFcp4aXbOp8Dwbhh/HQgvoRxA=="],
    "type-check": ["type-check@0.4.0", "", { "dependencies": { "prelude-ls": "^1.2.1" } }, "sha512-XleUoc9uwGXqjWwXaUTZAmzMcFZ5858QA2vvx1Ur5xIcixXIP+8LnFDgRplU30us6teqdlskFfu+ae4K79Ooew=="],
    "typescript": ["typescript@6.0.3", "", { "bin": { "tsc": "bin/tsc", "tsserver": "bin/tsserver" } }, "sha512-y2TvuxSZPDyQakkFRPZHKFm+KKVqIisdg9/CZwm9ftvKXLP8NRWj38/ODjNbr43SsoXqNuAisEf1GdCxqWcdBw=="],
    "typescript-eslint": ["typescript-eslint@8.59.2", "", { "dependencies": { "@typescript-eslint/eslint-plugin": "8.59.2", "@typescript-eslint/parser": "8.59.2", "@typescript-eslint/typescript-estree": "8.59.2", "@typescript-eslint/utils": "8.59.2" }, "peerDependencies": { "eslint": "^8.57.0 || ^9.0.0 || ^10.0.0", "typescript": ">=4.8.4 <6.1.0" } }, "sha512-pJw051uomb3ZeCzGTpRb8RbEqB5Y4WWet8gl/GcTlU35BSx0PVdZ86/bqkQCyKKuraVQEK7r6kBHQXF+fBhkoQ=="],
    "typescript-telegram-bot-api": ["typescript-telegram-bot-api@0.16.0", "", { "dependencies": { "axios": "^1.7.7", "form-data": "^4.0.1" } }, "sha512-NaAjXucQiZ87U8La/IMaWDOghbMlJzfMbU4rG8ppFpgPOvEwat/zfN5BM+J2QDvKVGN87qJ+1nELnkm3ctSLnQ=="],
    "undici-types": ["undici-types@7.19.2", "", {}, "sha512-qYVnV5OEm2AW8cJMCpdV20CDyaN3g0AjDlOGf1OW4iaDEx8MwdtChUp4zu4H0VP3nDRF/8RKWH+IPp9uW0YGZg=="],
    "universalify": ["universalify@0.1.2", "", {}, "sha512-rBJeI5CXAlmy1pV+617WB9J63U6XcazHHF2f2dbJix4XzpUF0RS3Zbj0FGIOCAva5P/d/GBOYaACQ1w+0azUkg=="],
    "uri-js": ["uri-js@4.4.1", "", { "dependencies": { "punycode": "^2.1.0" } }, "sha512-7rKUyy33Q1yc98pQ1DAmLtwX109F7TIfWlW1Ydo8Wl1ii1SeHieeh0HHfPeL2fMXK6z0s8ecKs9frCuLJvndBg=="],
    "web-streams-polyfill": ["web-streams-polyfill@3.3.3", "", {}, "sha512-d2JWLCivmZYTSIoge9MsgFCZrt571BikcWGYkjC1khllbTeDlGqZ2D8vD8E/lJa8WGWbb7Plm8/XJYV7IJHZZw=="],
    "whatwg-fetch": ["whatwg-fetch@3.6.20", "", {}, "sha512-EqhiFU6daOA8kpjOWTL0olhVOF3i7OrFzSYiGsEMB8GcXS+RrzauAERX65xMeNWVqxA6HXH2m69Z9LaKKdisfg=="],
@@ -631,8 +512,6 @@
    "which-module": ["which-module@2.0.1", "", {}, "sha512-iBdZ57RDvnOR9AGBhML2vFZf7h8vmBjhoaZqODJBFWHVtKkDmKuHai3cx5PgVMrX5YDNp27AofYbAwctSS+vhQ=="],
    "word-wrap": ["word-wrap@1.2.5", "", {}, "sha512-BN22B5eaMMI9UMtjrGd5g5eCYPpCPDUy0FJXbYsaT5zYxjFOckS53SQDE3pWkVoWpHXVb3BrYcEN4Twa55B5cA=="],
    "wrap-ansi": ["wrap-ansi@6.2.0", "", { "dependencies": { "ansi-styles": "^4.0.0", "string-width": "^4.1.0", "strip-ansi": "^6.0.0" } }, "sha512-r6lPcBGxZXlIcymEu7InxDMhdW0KDxpLgoFLcguasxCaJ/SOIZwINatK9KY/tf+ZrlywOKU0UDj3ATXUBfxJXA=="],
    "wrap-ansi-cjs": ["wrap-ansi@7.0.0", "", { "dependencies": { "ansi-styles": "^4.0.0", "string-width": "^4.1.0", "strip-ansi": "^6.0.0" } }, "sha512-YVGIj2kamLSTxw6NsZjoBxfSwsn0ycdesmc4p+Q21c5zPuZ1pl+NfxVdxPtdHvmNVOQ6XSYG4AUtyt/Fi7D16Q=="],
@@ -645,18 +524,12 @@
    "yargs-parser": ["yargs-parser@18.1.3", "", { "dependencies": { "camelcase": "^5.0.0", "decamelize": "^1.2.0" } }, "sha512-o50j0JeToy/4K6OZcaQmW6lyXXKhq7csREXcDwk2omFPJEwUNOVtJKvmDr9EI1fAJZUyZcRF7kxGBWmRXudrCQ=="],
    "yocto-queue": ["yocto-queue@0.1.0", "", {}, "sha512-rVksvsnNCdJ/ohGc6xgPwyN8eheCxsiLM8mxuE/t/mOVqJewPuO1miLpTHQiRgTKCLexL4MeAFVagts7HmNZ2Q=="],
    "zod": ["zod@4.4.3", "", {}, "sha512-ytENFjIJFl2UwYglde2jchW2Hwm4GJFLDiSXWdTrJQBIN9Fcyp7n4DhxJEiWNAJMV1/BqWfW/kkg71UDcHJyTQ=="],
    "zod-to-json-schema": ["zod-to-json-schema@3.25.1", "", { "peerDependencies": { "zod": "^3.25 || ^4" } }, "sha512-pM/SU9d3YAggzi6MtR4h7ruuQlqKtad8e9S0fmxcMi+ueAK5Korys/aWcV9LIIHTVbj01NdzxcnXSN+O74ZIVA=="],
    "@esbuild-kit/core-utils/esbuild": ["esbuild@0.18.20", "", { "optionalDependencies": { "@esbuild/android-arm": "0.18.20", "@esbuild/android-arm64": "0.18.20", "@esbuild/android-x64": "0.18.20", "@esbuild/darwin-arm64": "0.18.20", "@esbuild/darwin-x64": "0.18.20", "@esbuild/freebsd-arm64": "0.18.20", "@esbuild/freebsd-x64": "0.18.20", "@esbuild/linux-arm": "0.18.20", "@esbuild/linux-arm64": "0.18.20", "@esbuild/linux-ia32": "0.18.20", "@esbuild/linux-loong64": "0.18.20", "@esbuild/linux-mips64el": "0.18.20", "@esbuild/linux-ppc64": "0.18.20", "@esbuild/linux-riscv64": "0.18.20", "@esbuild/linux-s390x": "0.18.20", "@esbuild/linux-x64": "0.18.20", "@esbuild/netbsd-x64": "0.18.20", "@esbuild/openbsd-x64": "0.18.20", "@esbuild/sunos-x64": "0.18.20", "@esbuild/win32-arm64": "0.18.20", "@esbuild/win32-ia32": "0.18.20", "@esbuild/win32-x64": "0.18.20" }, "bin": { "esbuild": "bin/esbuild" } }, "sha512-ceqxoedUrcayh7Y7ZX6NdbbDzGROiyVBgC4PriJThBKSVPWnnFHZAkfI1lJT8QFkOwH4qOS2SJkS4wvpGl8BpA=="],
    "@esbuild-kit/esm-loader/get-tsconfig": ["get-tsconfig@4.14.0", "", { "dependencies": { "resolve-pkg-maps": "^1.0.0" } }, "sha512-yTb+8DXzDREzgvYmh6s9vHsSVCHeC0G3PI5bEXNBHtmshPnO+S5O7qgLEOn0I5QvMy6kpZN8K1NKGyilLb93wA=="],
    "@eslint-community/eslint-utils/eslint-visitor-keys": ["eslint-visitor-keys@3.4.3", "", {}, "sha512-wpc+LXeiyiisxPlEkUzU6svyS1frIO3Mgxj1fdy7Pm8Ygzguax2N3Fa/D/ag1WqbOprdI+uY6wMUl8/a2G+iag=="],
    "@isaacs/cliui/string-width": ["string-width@5.1.2", "", { "dependencies": { "eastasianwidth": "^0.2.0", "emoji-regex": "^9.2.2", "strip-ansi": "^7.0.1" } }, "sha512-HnLOCR3vjcY8beoNLtcjZ5/nxn2afmME6lhrDrebokqMap+XbeW8n9TXpPDOqdGK5qcI3oT0GKTW6wC7EMiVqA=="],
    "@isaacs/cliui/strip-ansi": ["strip-ansi@7.1.2", "", { "dependencies": { "ansi-regex": "^6.0.1" } }, "sha512-gmBGslpoQJtgnMAvOVqGZpEz9dyoKTCzy2nfz/n8aIFhN/jCE/rCmcxabB6jOOHV+0WNnylOxaxBQPSvcWklhA=="],
@@ -673,18 +546,12 @@
    "@types/ws/@types/node": ["@types/node@25.0.3", "", { "dependencies": { "undici-types": "~7.16.0" } }, "sha512-W609buLVRVmeW693xKfzHeIV6nJGGz98uCPfeXI1ELMLXVeKYZ9m15fAMSaUPBHYLGFsVRcMmSCksQOrZV9BYA=="],
    "@typescript-eslint/typescript-estree/semver": ["semver@7.7.4", "", { "bin": { "semver": "bin/semver.js" } }, "sha512-vFKC2IEtQnVhpT78h1Yp8wzwrf8CM+MzKMHGJZfBtzhZNycRFnXsHk6E5TxIkkMsgNS7mdX3AGB7x2QM2di4lA=="],
    "bun-types/@types/node": ["@types/node@25.6.0", "", { "dependencies": { "undici-types": "~7.19.0" } }, "sha512-+qIYRKdNYJwY3vRCZMdJbPLJAtGjQBudzZzdzwQYkEPQd+PJGixUL5QfvCLDaULoLv+RhT3LDkwEfKaAkgSmNQ=="],
    "cross-spawn/which": ["which@2.0.2", "", { "dependencies": { "isexe": "^2.0.0" }, "bin": { "node-which": "./bin/node-which" } }, "sha512-BLI3Tl1TW3Pvl70l3yq3Y64i+awpwXqsGBYWkkqMtnbXgrMD+yj7rhW0kuEDxzJaYXGjEW5ogapKNMEKNMjibA=="],
    "eslint/ignore": ["ignore@5.3.2", "", {}, "sha512-hsBTNUqQTDwkWtcdYI2i06Y/nUBEsNEDJKjWdigLvegy8kDuJAS8uRlpkkcQpyEXL0Z/pjDy5HBmMjRCJ2gq+g=="],
    "fs-extra/jsonfile": ["jsonfile@4.0.0", "", { "optionalDependencies": { "graceful-fs": "^4.1.6" } }, "sha512-m6F1R3z8jjlf2imQHS2Qez5sjKWQzbuuhuJ/FKYFRZvPE3PuHcSMVZzfsLhGVOkfd20obL5SWEBew5ShlquNxg=="],
    "glob/minimatch": ["minimatch@9.0.5", "", { "dependencies": { "brace-expansion": "^2.0.1" } }, "sha512-G6T0ZX48xgozx7587koeX9Ys2NYy6Gmv//P89sEte9V9whIapMNF4idKxnW2QtCcLiTWlb/wfCabAtAFWhhBow=="],
    "libsql/detect-libc": ["detect-libc@2.0.2", "", {}, "sha512-UX6sGumvvqSaXgdKGUsgZWqcUyIXZ/vZTrlRT/iobiKhGL0zL4d3osHj3uqllWJK+i+sixDS/3COVEOFbupFyw=="],
    "protobufjs/@types/node": ["@types/node@25.0.10", "", { "dependencies": { "undici-types": "~7.16.0" } }, "sha512-zWW5KPngR/yvakJgGOmZ5vTBemDoSqF3AcV/LrO5u5wTWyEAVVh+IT39G4gtyAkh3CtTZs8aX/yRM82OfzHJRg=="],
@@ -695,7 +562,7 @@
    "tsx/esbuild": ["esbuild@0.27.2", "", { "optionalDependencies": { "@esbuild/aix-ppc64": "0.27.2", "@esbuild/android-arm": "0.27.2", "@esbuild/android-arm64": "0.27.2", "@esbuild/android-x64": "0.27.2", "@esbuild/darwin-arm64": "0.27.2", "@esbuild/darwin-x64": "0.27.2", "@esbuild/freebsd-arm64": "0.27.2", "@esbuild/freebsd-x64": "0.27.2", "@esbuild/linux-arm": "0.27.2", "@esbuild/linux-arm64": "0.27.2", "@esbuild/linux-ia32": "0.27.2", "@esbuild/linux-loong64": "0.27.2", "@esbuild/linux-mips64el": "0.27.2", "@esbuild/linux-ppc64": "0.27.2", "@esbuild/linux-riscv64": "0.27.2", "@esbuild/linux-s390x": "0.27.2", "@esbuild/linux-x64": "0.27.2", "@esbuild/netbsd-arm64": "0.27.2", "@esbuild/netbsd-x64": "0.27.2", "@esbuild/openbsd-arm64": "0.27.2", "@esbuild/openbsd-x64": "0.27.2", "@esbuild/openharmony-arm64": "0.27.2", "@esbuild/sunos-x64": "0.27.2", "@esbuild/win32-arm64": "0.27.2", "@esbuild/win32-ia32": "0.27.2", "@esbuild/win32-x64": "0.27.2" }, "bin": { "esbuild": "bin/esbuild" } }, "sha512-HyNQImnsOC7X9PMNaCIeAm4ISCQXs5a5YasTXVliKv4uuBo1dKrG0A+uQS8M5eXjVMnLg3WgXaKvprHlFJQffw=="],
-    "yargs/find-up": ["find-up@4.1.0", "", { "dependencies": { "locate-path": "^5.0.0", "path-exists": "^4.0.0" } }, "sha512-PpOwAdQ/YlXQ2vj8a3h8IipDuYRi3wceVQQGYWxNINccq40Anw7BlsEXCMbt1Zt+OLA6Fq9suIpIWD0OsnISlw=="],
+    "tsx/get-tsconfig": ["get-tsconfig@4.13.0", "", { "dependencies": { "resolve-pkg-maps": "^1.0.0" } }, "sha512-1VKTZJCwBrvbd+Wn3AOgQP/2Av+TfTCOlE4AcRJE72W1ksZXbAx8PPBR9RzgTeSPzlPMHrbANMH3LbltH73wxQ=="],
    "@esbuild-kit/core-utils/esbuild/@esbuild/android-arm": ["@esbuild/android-arm@0.18.20", "", { "os": "android", "cpu": "arm" }, "sha512-fyi7TDI/ijKKNZTUJAQqiG5T7YjJXgnzkURqmGj13C6dCqckZBLdl4h7bkhHt/t0WP+zO9/zwroDvANaOqO5Sw=="],
@@ -753,8 +620,6 @@
    "@types/ws/@types/node/undici-types": ["undici-types@7.16.0", "", {}, "sha512-Zz+aZWSj8LE6zoxD+xrjh4VfkIG8Ya6LvYkZqtUQGJPZjYl53ypCaUwWqo7eI0x66KBGeRo+mlBEkMSeSZ38Nw=="],
    "glob/minimatch/brace-expansion": ["brace-expansion@2.0.2", "", { "dependencies": { "balanced-match": "^1.0.0" } }, "sha512-Jt0vHyM+jmUBqojB7E1NIYadt0vI0Qxjxd2TErW94wDz+E2LAm5vKMXXwg6ZZBTHPuUlDgQHKXvjGBdfcF1ZDQ=="],
    "protobufjs/@types/node/undici-types": ["undici-types@7.16.0", "", {}, "sha512-Zz+aZWSj8LE6zoxD+xrjh4VfkIG8Ya6LvYkZqtUQGJPZjYl53ypCaUwWqo7eI0x66KBGeRo+mlBEkMSeSZ38Nw=="],
    "tsx/esbuild/@esbuild/aix-ppc64": ["@esbuild/aix-ppc64@0.27.2", "", { "os": "aix", "cpu": "ppc64" }, "sha512-GZMB+a0mOMZs4MpDbj8RJp4cw+w1WV5NYD6xzgvzUJ5Ek2jerwfO2eADyI6ExDSUED+1X8aMbegahsJi+8mgpw=="],
@@ -808,13 +673,5 @@
    "tsx/esbuild/@esbuild/win32-ia32": ["@esbuild/win32-ia32@0.27.2", "", { "os": "win32", "cpu": "ia32" }, "sha512-Iuws0kxo4yusk7sw70Xa2E2imZU5HoixzxfGCdxwBdhiDgt9vX9VUCBhqcwY7/uh//78A1hMkkROMJq9l27oLQ=="],
    "tsx/esbuild/@esbuild/win32-x64": ["@esbuild/win32-x64@0.27.2", "", { "os": "win32", "cpu": "x64" }, "sha512-sRdU18mcKf7F+YgheI/zGf5alZatMUTKj/jNS6l744f9u3WFu4v7twcUI9vu4mknF4Y9aDlblIie0IM+5xxaqQ=="],
    "yargs/find-up/locate-path": ["locate-path@5.0.0", "", { "dependencies": { "p-locate": "^4.1.0" } }, "sha512-t7hw9pI+WvuwNJXwk5zVHpyhIqzg2qTlklJOf0mVxGSbe3Fp2VieZcduNYjaLDoy6p9uGpQEGWG87WpMKlNq8g=="],
    "glob/minimatch/brace-expansion/balanced-match": ["balanced-match@1.0.2", "", {}, "sha512-3oSeUO0TMV67hN1AmbXsK4yaqU7tjiHlbxRDZOpH0KW9+CeX4bRAaX0Anxt0tx2MrpRpWwQaPwIlISEJhYU5Pw=="],
    "yargs/find-up/locate-path/p-locate": ["p-locate@4.1.0", "", { "dependencies": { "p-limit": "^2.2.0" } }, "sha512-R79ZZ/0wAxKGu3oYMlz8jy/kbhsNrS7SKZ7PxEHBgJ5+F2mtFW2fK2cOtBh1cHYkQsbzFV7I+EoRKe6Yt0oK7A=="],
    "yargs/find-up/locate-path/p-locate/p-limit": ["p-limit@2.3.0", "", { "dependencies": { "p-try": "^2.0.0" } }, "sha512-//88mFWSJx8lxCzwdAABTJL2MyWB12+eIY7MDL2SqLmAkeKU9qxRvWuSyTjm3FUmpBEMuFfckAIqEaVGUDxb6w=="],
  }
 }
@@ -2,20 +2,18 @@
  "name": "tg-chat-bot",
  "main": "src/index.ts",
  "version": "1.0.0",
  "type": "module",
  "scripts": {
-    "build": "tsc -p tsconfig.build.json",
+    "build": "tsgo -p tsconfig.json",
    "lint": "eslint .",
    "start": "node dist/index.js",
-    "bun:start": "bun run dist/index.js"
+    "bun:start": "bun run src/index.ts"
  },
  "dependencies": {
    "@google/genai": "^2.0.0",
    "@mistralai/mistralai": "^2.2.1",
    "openai": "^6.37.0",
    "ollama": "^0.6.3",
    "typescript-telegram-bot-api": "^0.16.0",
    "@libsql/client": "^0.17.3",
    "@napi-rs/canvas": "^1.0.0",
    "axios": "^1.16.0",
@@ -34,12 +32,7 @@
    "@types/fluent-ffmpeg": "^2.1.28",
    "@types/node": "^25.6.1",
    "@types/qrcode": "^1.5.6",
    "@typescript-eslint/eslint-plugin": "^8.59.2",
    "@typescript-eslint/parser": "^8.59.2",
    "drizzle-kit": "^0.31.10",
-    "eslint": "^10.3.0",
+    "@typescript/native-preview": "^7.0.0-beta"
    "tsx": "^4.21.0",
    "typescript": "^6.0.3",
    "typescript-eslint": "^8.59.2"
  }
 }
@@ -0,0 +1,283 @@
 import {Message} from "typescript-telegram-bot-api";
 export type AiRunnerLogLevel = "trace" | "debug" | "info" | "success" | "warn" | "error";
 export type AiRunnerLogDetails = Record<string, unknown>;
 export type AiLogToolCallLike = {
    id: string;
    name: string;
    argumentsText: string;
 };
 const AI_RUNNER_LOG_PREFIX = "unified-ai-runner";
 const AI_RUNNER_LOG_MAX_STRING = 600;
 const AI_RUNNER_LOG_MAX_ARRAY = 8;
 const LOG_LEVEL_WEIGHT: Record<AiRunnerLogLevel, number> = {
    trace: 10,
    debug: 20,
    info: 30,
    success: 30,
    warn: 40,
    error: 50,
 };
 const AI_RUNNER_LOG_COLORS: Record<AiRunnerLogLevel | "reset" | "bold" | "dim" | "label" | "key" | "value", string> = {
    reset: "\x1b[0m",
    bold: "\x1b[1m",
    dim: "\x1b[2m",
    trace: "\x1b[90m",
    debug: "\x1b[90m",
    info: "\x1b[36m",
    success: "\x1b[32m",
    warn: "\x1b[33m",
    error: "\x1b[31m",
    label: "\x1b[35m",
    key: "\x1b[94m",
    value: "\x1b[97m",
 };
 function envBool(name: string, defaultValue: boolean): boolean {
    const value = process.env[name];
    if (value === undefined) return defaultValue;
    return !["0", "false", "no", "off"].includes(value.trim().toLowerCase());
 }
 function aiRunnerLogsEnabled(): boolean {
    return envBool("AI_RUNNER_LOGS", true) && envBool("AI_LOG_ENABLED", true);
 }
 function aiRunnerColorsEnabled(): boolean {
    return envBool("AI_RUNNER_LOG_COLORS", true) && !process.env.NO_COLOR;
 }
 function configuredMinLevel(): AiRunnerLogLevel {
    const raw = process.env.AI_LOG_LEVEL?.trim().toLowerCase();
    if (raw && raw in LOG_LEVEL_WEIGHT) return raw as AiRunnerLogLevel;
    return "debug";
 }
 function shouldWriteLevel(level: AiRunnerLogLevel): boolean {
    return LOG_LEVEL_WEIGHT[level] >= LOG_LEVEL_WEIGHT[configuredMinLevel()];
 }
 function paintAiLog(value: string, color: keyof typeof AI_RUNNER_LOG_COLORS): string {
    if (!aiRunnerColorsEnabled()) return value;
    return `${AI_RUNNER_LOG_COLORS[color]}${value}${AI_RUNNER_LOG_COLORS.reset}`;
 }
 function truncateAiLogString(value: string, max = AI_RUNNER_LOG_MAX_STRING): string {
    if (value.length <= max) return value;
    return `${value.slice(0, max)}… (+${value.length - max} chars)`;
 }
 function safeJsonParseObject(value?: string): Record<string, unknown> {
    if (!value?.trim()) return {};
    try {
        const parsed: unknown = JSON.parse(value);
        return parsed && typeof parsed === "object" && !Array.isArray(parsed)
            ? parsed as Record<string, unknown>
            : {};
    } catch {
        return {};
    }
 }
 function isSecretKey(keyPath: string): boolean {
    const normalized = keyPath.toLowerCase();
    return normalized.includes("token")
        || normalized.includes("secret")
        || normalized.includes("apikey")
        || normalized.includes("api_key")
        || normalized.includes("authorization")
        || normalized.endsWith(".key")
        || normalized === "key";
 }
 function isPromptKey(keyPath: string): boolean {
    const normalized = keyPath.toLowerCase();
    return normalized.includes("prompt") || normalized.includes("systemprompt");
 }
 function isTextPreviewKey(keyPath: string): boolean {
    const normalized = keyPath.toLowerCase();
    return normalized.includes("content")
        || normalized.includes("message")
        || normalized.includes("text")
        || normalized.includes("preview")
        || normalized.includes("input")
        || normalized.includes("output");
 }
 function isToolArgsKey(keyPath: string): boolean {
    const normalized = keyPath.toLowerCase();
    return normalized.endsWith("args")
        || normalized.endsWith("arguments")
        || normalized.includes("toolargs")
        || normalized.includes("tool_args");
 }
 function isDaoKey(keyPath: string): boolean {
    const normalized = keyPath.toLowerCase();
    return normalized.includes("dao")
        || normalized.includes("database")
        || normalized.includes("db.")
        || normalized.includes("sql")
        || normalized.includes("chunk");
 }
 function shouldRedactKey(keyPath: string): boolean {
    if (isSecretKey(keyPath)) return true;
    if (isPromptKey(keyPath) && !envBool("AI_LOG_PROMPTS", false)) return true;
    if (isToolArgsKey(keyPath) && !envBool("AI_LOG_TOOL_ARGS", false)) return true;
    if (isDaoKey(keyPath) && !envBool("AI_LOG_DAO", false)) return true;
    if (isTextPreviewKey(keyPath) && !envBool("AI_LOG_TEXT_PREVIEW", false)) return true;
    return false;
 }
 function primitiveToLogValue(value: unknown): unknown {
    if (value instanceof Error) {
        return {
            name: value.name,
            message: value.message,
            stack: value.stack?.split("\n").slice(0, 6).join("\n"),
        };
    }
    if (typeof value === "string") return truncateAiLogString(value);
    if (typeof value === "number" || typeof value === "boolean" || value === null || value === undefined) return value;
    if (typeof value === "bigint") return value.toString();
    if (typeof value === "function") return `[Function ${value.name || "anonymous"}]`;
    if (Buffer.isBuffer(value)) return `<Buffer ${(value as {length: number}).length} bytes>`;
    return undefined;
 }
 export function flattenAiLogDetails(
    value: unknown,
    keyPath = "",
    depth = 0,
    seen = new WeakSet<object>(),
 ): Record<string, unknown> {
    if (keyPath && shouldRedactKey(keyPath)) {
        return {[keyPath]: "<redacted>"};
    }
    const primitive = primitiveToLogValue(value);
    if (primitive !== undefined || value === undefined) {
        return keyPath ? {[keyPath]: primitive} : {value: primitive};
    }
    if (typeof value !== "object" || value === null) {
        return keyPath ? {[keyPath]: String(value)} : {value: String(value)};
    }
    if (seen.has(value)) {
        return keyPath ? {[keyPath]: "[Circular]"} : {value: "[Circular]"};
    }
    seen.add(value);
    if (Array.isArray(value)) {
        if (depth >= 2) {
            return keyPath ? {[keyPath]: `[Array ${value.length}]`} : {value: `[Array ${value.length}]`};
        }
        const entries: Record<string, unknown> = {};
        value.slice(0, AI_RUNNER_LOG_MAX_ARRAY).forEach((item, index) => {
            Object.assign(entries, flattenAiLogDetails(item, keyPath ? `${keyPath}.${index}` : String(index), depth + 1, seen));
        });
        if (value.length > AI_RUNNER_LOG_MAX_ARRAY) {
            entries[keyPath ? `${keyPath}.__more` : "__more"] = value.length - AI_RUNNER_LOG_MAX_ARRAY;
        }
        return entries;
    }
    if (depth >= 3) {
        return keyPath ? {[keyPath]: "[Object]"} : {value: "[Object]"};
    }
    const entries: Record<string, unknown> = {};
    for (const [key, raw] of Object.entries(value as Record<string, unknown>)) {
        const childPath = keyPath ? `${keyPath}.${key}` : key;
        if ((key.toLowerCase() === "data" || key.toLowerCase() === "image_url" || key.toLowerCase().endsWith("b64")) && typeof raw === "string") {
            entries[childPath] = `<${raw.length} chars>`;
            continue;
        }
        Object.assign(entries, flattenAiLogDetails(raw, childPath, depth + 1, seen));
    }
    return entries;
 }
 export function redactLogValue(value: unknown): Record<string, unknown> {
    return flattenAiLogDetails(value);
 }
 function formatAiLogDetails(details?: AiRunnerLogDetails): string {
    if (!details || !Object.keys(details).length) return "";
    const flattened = flattenAiLogDetails(details);
    const chunks = Object.entries(flattened).map(([key, value]) => {
        const safeValue = typeof value === "string" ? value : JSON.stringify(value);
        return `${paintAiLog(key, "key")}=${paintAiLog(safeValue ?? "undefined", "value")}`;
    });
    return ` ${chunks.join(" ")}`;
 }
 export function aiLog(level: AiRunnerLogLevel, event: string, details?: AiRunnerLogDetails): void {
    if (!aiRunnerLogsEnabled() || !shouldWriteLevel(level)) return;
    const timestamp = paintAiLog(new Date().toISOString(), "dim");
    const prefix = paintAiLog(AI_RUNNER_LOG_PREFIX, "bold");
    const levelText = paintAiLog(level.toUpperCase().padEnd(7), level);
    const eventText = paintAiLog(event, "label");
    const line = `${timestamp} ${prefix} ${levelText} ${eventText}${formatAiLogDetails(details)}`;
    if (level === "error") {
        console.error(line);
    } else if (level === "warn") {
        console.warn(line);
    } else {
        console.log(line);
    }
 }
 export function aiLogDuration(startedAt: number): string {
    const ms = Date.now() - startedAt;
    if (ms < 1000) return `${ms}ms`;
    return `${(ms / 1000).toFixed(2)}s`;
 }
 export function aiLogToolCall(toolCall: AiLogToolCallLike): Record<string, unknown> {
    return {
        id: toolCall.id,
        name: toolCall.name,
        arguments: safeJsonParseObject(toolCall.argumentsText),
    };
 }
 export function aiLogMessageIdentity(msg: Message | undefined): Record<string, unknown> | undefined {
    if (!msg) return undefined;
    return {
        chatId: msg.chat?.id,
        chatType: msg.chat?.type,
        messageId: msg.message_id,
        fromId: msg.from?.id,
        username: msg.from?.username,
    };
 }
 export function aiLogProviderTarget(target: {provider: string; purpose?: string; model?: string; baseUrl?: string; apiKey?: string} | undefined): Record<string, unknown> | undefined {
    if (!target) return undefined;
    return {
        provider: target.provider,
        purpose: target.purpose,
        model: target.model,
        baseUrl: target.baseUrl,
        apiKey: target.apiKey,
    };
 }
@@ -207,7 +207,7 @@ export function createMistralClient(target: AiRuntimeTarget): Mistral {
 export function createOllamaClient(target: AiRuntimeTarget): Ollama {
    return new Ollama({
-        host: target.baseUrl?.endsWith(":11434") ? target.baseUrl : target.baseUrl + ":11434",
+        host: target.baseUrl,
        headers: target.apiKey ? {"Authorization": `Bearer ${target.apiKey}`} : undefined,
    });
 }
@@ -65,26 +65,5 @@ export function asMistralChatMessage(message: ChatMessage): MistralChatMessage {
 //     }
 // }
 /*
 const messages: any[] = ordered.map(part => {
            const content: any[] = [{
                type: "input_text",
                text: (Environment.USE_NAMES_IN_PROMPT && !part.bot ? `MESSAGE FROM USER \"${part.name}\":\n` : "") + part.content,
            }];
            if (!part.bot) {
                for (const image of part.images ?? []) {
                    content.push({type: "input_image", image_url: `data:image/jpeg;base64,${image}`, detail: "auto"});
                }
            }
            return {role: part.bot ? "assistant" : "user", content};
        });
        if (Environment.SYSTEM_PROMPT && Environment.USE_SYSTEM_PROMPT) {
            messages.unshift({role: "system", content: Environment.SYSTEM_PROMPT});
        }
        return {parts: messages, imageCount};
 */
 export type AiChatMessage = | OpenAIChatMessage | OllamaChatMessage | MistralChatMessage | GeminiMessage;
@@ -67,7 +67,7 @@ export type MistralContentChunk =
 export type MistralFunctionCall = {
    name: string;
-    arguments: { [k: string]: any } | string;
+    arguments: Record<string, unknown> | string;
 };
 export type MistralToolCall = {
@@ -1,3 +1,7 @@
-import {ResponseInputItem} from "openai/resources/responses/responses";
+import type {ResponseInputMessageContentList} from "openai/resources/responses/responses";
-export type OpenAIChatMessage = ResponseInputItem
+export type OpenAIChatMessage = {
    type: "message";
    role: "system" | "user" | "assistant";
    content: string | ResponseInputMessageContentList;
 };
@@ -295,26 +295,38 @@ export async function formatRuntimeModelInfo(
    );
 }
 type NamedModel = {
    id?: string;
    name?: string;
    model?: string;
 };
 type ModelListResponse = {
    models?: NamedModel[];
    data?: NamedModel[];
 };
 export async function listProviderModels(provider: AiProvider): Promise<string[]> {
    const target = resolveAiRuntimeTarget(provider, "chat", getRuntimeModel(provider));
    switch (provider) {
        case AiProvider.OLLAMA: {
            const ollama = createOllamaClient(target);
-            const result: any = await ollama.list();
+            const result = await ollama.list() as ModelListResponse;
-            return (result.models ?? []).map((m: any) => m.model || m.name).filter(Boolean);
+            return (result.models ?? []).map(m => m.model || m.name).filter((name): name is string => !!name);
        }
        case AiProvider.GEMINI: {
            const models: string[] = [];
            if (getGeminiApiMode(target) === "openai") {
                const geminiAi = createGeminiOpenAiClient(target);
-                const iterable: any = await geminiAi.models.list();
+                const iterable = await geminiAi.models.list() as AsyncIterable<NamedModel>;
                for await (const model of iterable) models.push(model.name || model.id || String(model));
                return models;
            }
            const geminiAi = createGoogleGenAiClient(target);
-            const iterable: any = await geminiAi.models.list();
+            const iterable = await geminiAi.models.list() as AsyncIterable<NamedModel>;
            for await (const model of iterable) {
                const name = model.name || model.id || String(model);
                models.push(String(name).replace(/^models\//, ""));
@@ -323,13 +335,14 @@ export async function listProviderModels(provider: AiProvider): Promise<string[]
        }
        case AiProvider.MISTRAL: {
            const mistralAi = createMistralClient(target);
-            const result: any = await mistralAi.models.list();
+            const result = await mistralAi.models.list() as ModelListResponse | NamedModel[];
-            return (result.data ?? result.models ?? result ?? []).map((m: any) => m.id || m.name || String(m)).filter(Boolean);
+            const items = Array.isArray(result) ? result : result.data ?? result.models ?? [];
            return items.map(m => m.id || m.name || String(m)).filter((name): name is string => !!name);
        }
        case AiProvider.OPENAI: {
            const openAi = createOpenAiClient(target);
-            const result: any = await openAi.models.list();
+            const result = await openAi.models.list() as ModelListResponse;
-            return (result.data ?? []).map((m: any) => m.id).filter(Boolean);
+            return (result.data ?? []).map(m => m.id).filter((id): id is string => !!id);
        }
    }
 }
@@ -7,11 +7,11 @@ export type AiRequestQueueTarget = {
    baseUrl?: string;
 };
-type QueueEntry<T> = {
+type QueueEntry = {
    target: AiRequestQueueTarget;
    queueKey: string;
-    run: () => Promise<T>;
+    run: () => Promise<unknown>;
-    resolve: (value: T | PromiseLike<T>) => void;
+    resolve: (value: unknown) => void;
    reject: (reason?: unknown) => void;
    onPositionChange: (requestsBefore: number) => Promise<void> | void;
    signal?: AbortSignal;
@@ -26,7 +26,7 @@ type EnqueueOptions<T> = {
 };
 class AiProviderRequestQueue {
-    private readonly waiting = new Map<string, Array<QueueEntry<any>>>();
+    private readonly waiting = new Map<string, QueueEntry[]>();
    private readonly active = new Map<string, number>();
    enqueue<T>(target: AiRequestQueueTarget, options: EnqueueOptions<T>): Promise<T> {
@@ -36,11 +36,11 @@ class AiProviderRequestQueue {
        return new Promise<T>((resolve, reject) => {
            const queueKey = this.queueKey(target);
-            const entry: QueueEntry<T> = {
+            const entry: QueueEntry = {
                target,
                queueKey,
                run: options.run,
-                resolve,
+                resolve: value => resolve(value as T),
                reject,
                onPositionChange: options.onPositionChange,
                signal: options.signal,
@@ -63,11 +63,11 @@ class AiProviderRequestQueue {
        });
    }
-    private getQueue(queueKey: string): Array<QueueEntry<any>> | undefined {
+    private getQueue(queueKey: string): QueueEntry[] | undefined {
        return this.waiting.get(queueKey);
    }
-    private getOrCreateQueue(queueKey: string): Array<QueueEntry<any>> {
+    private getOrCreateQueue(queueKey: string): QueueEntry[] {
        let queue = this.waiting.get(queueKey);
        if (!queue) {
            queue = [];
@@ -104,7 +104,7 @@ class AiProviderRequestQueue {
        ]);
    }
-    private removeWaitingEntry(entry: QueueEntry<any>): boolean {
+    private removeWaitingEntry(entry: QueueEntry): boolean {
        const queue = this.getQueue(entry.queueKey);
        if (!queue) return false;
@@ -147,7 +147,7 @@ class AiProviderRequestQueue {
        }
    }
-    private async runEntry(entry: QueueEntry<any>): Promise<void> {
+    private async runEntry(entry: QueueEntry): Promise<void> {
        try {
            entry.resolve(await entry.run());
        } catch (e) {
@@ -174,7 +174,7 @@ class AiProviderRequestQueue {
        }).catch(console.error);
    }
-    private deleteQueueIfIdle(queueKey: string, queue: Array<QueueEntry<any>>): void {
+    private deleteQueueIfIdle(queueKey: string, queue: QueueEntry[]): void {
        if (!queue.length && this.activeCount(queueKey) <= 0) {
            this.waiting.delete(queueKey);
        }
@@ -198,7 +198,7 @@ async function transcribeGeminiSpeech(audio: AiDownloadedFile, signal?: AbortSig
            temperature: 0,
            abortSignal: signal,
        },
-    });
+    }) as unknown as GeminiSpeechResponse;
    return {
        provider: AiProvider.GEMINI,
@@ -240,17 +240,19 @@ async function transcribeOllamaSpeech(audio: AiDownloadedFile, signal?: AbortSig
    };
 }
-function collectGeminiText(response: any): string {
+type GeminiSpeechResponse = {
-    if (typeof response?.text === "string") return response.text;
+    text?: string;
    candidates?: Array<{content?: {parts?: Array<{text?: string}>}}> ;
 };
-    const candidates = response?.candidates ?? [];
+function collectGeminiText(response: GeminiSpeechResponse): string {
-    const candidateText = candidates
+    if (typeof response.text === "string") return response.text;
-        .flatMap((candidate: any) => candidate?.content?.parts ?? [])
+
-        .map((part: any) => part?.text ?? "")
+    const candidateText = (response.candidates ?? [])
        .flatMap(candidate => candidate.content?.parts ?? [])
        .map(part => part.text ?? "")
        .join("");
    if (candidateText.trim()) return candidateText;
-    return (response?.candidates ?? [])
+    return "";
        .map((output: any) => typeof output === "string" ? output : output?.content?.parts?.[0]?.text ?? "")
        .join("");
 }
@@ -292,7 +292,7 @@ export class TelegramStreamMessage {
            }
            if (shouldRemoveKeyboard) await this.removeKeyboard();
            this.lastSent = next;
-        } catch (e: any) {
+        } catch (e: unknown) {
            if (shouldRemoveKeyboard && this.isMessageNotModified(e)) {
                await this.removeKeyboard();
                this.lastSent = next;
@@ -369,8 +369,9 @@ export class TelegramStreamMessage {
            if (result && result !== true) this.waitMessage = result;
            this.mediaMode = true;
            this.lastSent = next;
-        } catch (e: any) {
+        } catch (e: unknown) {
-            if (!String(e?.message ?? e).includes("message is not modified")) logError(e);
+            const message = e instanceof Error ? e.message : String(e);
            if (!message.includes("message is not modified")) logError(e);
        }
    }
@@ -171,7 +171,7 @@ async function synthesizeMistralSpeech(text: string, voice?: string): Promise<Sy
    if (target.model) request.model = target.model;
    if (voice || Environment.MISTRAL_TTS_VOICE_ID) request.voiceId = voice || Environment.MISTRAL_TTS_VOICE_ID;
-    const response: any = await mistralAi.audio.speech.complete(request);
+    const response = await mistralAi.audio.speech.complete(request) as unknown as {audioData?: string; audio_data?: string};
    const audioData = response?.audioData ?? response?.audio_data;
    if (typeof audioData !== "string" || !audioData.trim()) {
        throw new Error(Environment.mistralTtsNoAudioDataText);
@@ -192,7 +192,7 @@ async function synthesizeMistralSpeech(text: string, voice?: string): Promise<Sy
 async function synthesizeGeminiSpeech(text: string, voice?: string): Promise<SynthesizedSpeech> {
    const target = resolveAiRuntimeTarget(AiProvider.GEMINI, "textToSpeech");
    const geminiAi = createGoogleGenAiClient(target);
-    const response: any = await geminiAi.models.generateContent({
+    const response = await geminiAi.models.generateContent({
        model: target.model,
        contents: text,
        config: {
@@ -15,7 +15,15 @@ export function getOpenAITools(): AiTool[] {
    }));
 }
-export function getOpenAIResponsesTools(): any[] {
+export type OpenAiResponseTool = {
    type: "function";
    name: string;
    description?: string;
    parameters?: unknown;
    strict: false;
 };
 export function getOpenAIResponsesTools(): OpenAiResponseTool[] {
    return getTools().map(tool => ({
        type: "function",
        name: tool.function.name,
@@ -1,28 +1,5 @@
-/*
+
 interface Tool {
    type: string;
    function: {
        name?: string;
        description?: string;
        type?: string;
        parameters?: {
            type?: string;
            $defs?: any;
            items?: any;
            required?: string[];
            properties?: {
                [key: string]: {
                    type?: string | string[];
                    items?: any;
                    description?: string;
                    enum?: any[];
                };
            };
        };
    };
 }
 */
 export type AiToolParameters = {
    type: "object";
@@ -45,7 +22,7 @@ export type AiToolCall = {
    function: {
        name: string;
        arguments: {
-            [key: string]: any;
+            [key: string]: unknown;
        };
    };
 };
@@ -356,11 +356,12 @@ export async function webSearch(args?: Record<string, unknown>) {
            note: "Use returned URLs as sources. Do not invent facts that are not present in the snippets/results.",
        };
-    } catch (e: any) {
+    } catch (e: unknown) {
        logError(e);
-        const status = e?.response?.status;
+        const axiosLike = e as {response?: {status?: unknown; data?: unknown}};
-        const data = e?.response?.data;
+        const status = axiosLike.response?.status;
        const data = axiosLike.response?.data;
        return {
            ok: false,
@@ -327,8 +327,8 @@ async function assertNoSymlinkInPath(
            if (stat.isSymbolicLink()) {
                throw new Error("Symlinks are not allowed in file tool paths.");
            }
-        } catch (e: any) {
+        } catch (e: unknown) {
-            if (e?.code === "ENOENT" && options?.allowMissingTail) {
+            if ((e as NodeJS.ErrnoException).code === "ENOENT" && options?.allowMissingTail) {
                return;
            }
@@ -341,8 +341,8 @@ async function pathExists(absolutePath: string): Promise<boolean> {
    try {
        await fs.promises.lstat(absolutePath);
        return true;
-    } catch (e: any) {
+    } catch (e: unknown) {
-        if (e?.code === "ENOENT") return false;
+        if ((e as NodeJS.ErrnoException).code === "ENOENT") return false;
        throw e;
    }
 }
@@ -58,11 +58,11 @@ export const marketRatesToolPrompt = [
    "- When the user asks for all rates, group fiat currencies separately from crypto and gold.",
 ].join("\n");
-export async function getMarketRates(): Promise<any | undefined> {
+export async function getMarketRates(): Promise<unknown | undefined> {
    try {
        const response = await axios.get("https://apid.r00t.top/api/v2/currency/rates");
        return response.data;
-    } catch (e: any) {
+    } catch (e: unknown) {
        console.error("GET_MARKET_RATES", e);
        return undefined;
    }
@@ -692,7 +692,7 @@ function parsePythonInterpreterArgs(
    return {
        code,
-        stdin,
+        stdin: typeof stdin === "string" ? stdin : undefined,
        timeoutMs: timeoutMs === undefined ? undefined : Number(timeoutMs),
    };
 }
@@ -96,7 +96,7 @@ export async function loadOllamaModel(model: string, ollama: Ollama, contextLeng
            }
        });
        return true;
-    } catch (e: any) {
+    } catch (e: unknown) {
        console.error("Error loading Ollama model:", model);
        return false;
    }
@@ -42,7 +42,7 @@ export const weatherToolPrompt = [
    "If the city is missing or unclear, ask the user to specify it.",
 ].join("\n");
-export async function getWeather(args?: Record<string, unknown>): Promise<any | null> {
+export async function getWeather(args?: Record<string, unknown>): Promise<Record<string, unknown> | null> {
    console.log("getWeather()");
    try {
        const city = asNonEmptyString(args?.city);
@@ -137,7 +137,7 @@ export async function getWeather(args?: Record<string, unknown>): Promise<any |
                windSpeed: wind.speed,
            },
        };
-    } catch (e: any) {
+    } catch (e: unknown) {
        logError(e);
        return null;
    } finally {
@@ -0,0 +1,156 @@
 // Gemini provider runner extracted from unified-ai-runner.ts.
 import {getGeminiTools} from "./tool-mappers";
 import {TelegramStreamMessage} from "./telegram-stream-message";
 import {ToolRuntimeContext} from "./tools/runtime";
 import {GeminiMessage} from "./gemini-chat-message";
 import {createGoogleGenAiClient} from "./ai-runtime-target";
 import {aiLog, aiLogDuration, aiLogProviderTarget, aiLogToolCall} from "./ai-logger";
 import {AsyncIterableStream, GeminiFunctionCallLike, GeminiResponseLike, MAX_TOOL_ROUNDS, RuntimeConfigSnapshot, ToolCallData, ToolExecutionMemory, executeToolBatch, roundStatus, safeJsonParseObject, GeminiGenerationRequest} from "./unified-ai-runner.shared";
 function collectGeminiResponseText(response: GeminiResponseLike & { text?: string }): string {
    if (typeof response.text === "string") return response.text;
    return (response.candidates ?? [])
        .flatMap(candidate => candidate.content?.parts ?? [])
        .map(part => part.text ?? "")
        .join("");
 }
 function collectGeminiFunctionCalls(response: GeminiResponseLike): ToolCallData[] {
    const calls = response.functionCalls
        ?? (response.candidates ?? []).flatMap(candidate => {
            return (candidate.content?.parts ?? [])
                .map(part => part.functionCall)
                .filter((call): call is GeminiFunctionCallLike => !!call);
        });
    return (calls ?? []).map((call, index) => ({
        id: call.id ?? `gemini_${index}_${call.name ?? "call"}`,
        name: call.name ?? "",
        argumentsText: JSON.stringify(call.args ?? {}),
    })).filter((call: ToolCallData) => call.name);
 }
 function mergeGeminiFunctionCalls(existing: ToolCallData[], next: ToolCallData[]): ToolCallData[] {
    const merged = [...existing];
    for (const call of next) {
        const index = merged.findIndex(item => item.id === call.id);
        if (index === -1) {
            merged.push(call);
        } else {
            merged[index] = call;
        }
    }
    return merged;
 }
 function appendGeminiToolRound(messages: GeminiMessage[], calls: ToolCallData[], results: string[]): void {
    messages.push({
        role: "model",
        parts: calls.map(call => ({
            functionCall: {
                id: call.id,
                name: call.name,
                args: safeJsonParseObject(call.argumentsText),
            },
        })),
    });
    messages.push({
        role: "user",
        parts: calls.map((call, index) => ({
            functionResponse: {
                id: call.id,
                name: call.name,
                response: {result: results[index] ?? ""},
            },
        })),
    });
 }
 export async function runGemini(
    messages: GeminiMessage[],
    streamMessage: TelegramStreamMessage,
    signal: AbortSignal,
    stream: boolean,
    firstRoundStatus: string,
    config: RuntimeConfigSnapshot,
    toolContext: ToolRuntimeContext,
 ): Promise<void> {
    const runnerStartedAt = Date.now();
    const geminiAi = createGoogleGenAiClient(config.geminiChatTarget);
    aiLog("info", "gemini.run.start", {
        stream,
        target: aiLogProviderTarget(config.geminiChatTarget),
        inputMessages: messages.length,
        hasToolInputFiles: !!toolContext.pythonInputFiles?.length,
    });
    const toolMemory: ToolExecutionMemory = new Map();
    for (let round = 0; round < MAX_TOOL_ROUNDS; round++) {
        const roundStartedAt = Date.now();
        aiLog("debug", "gemini.round.start", {round, messages: messages.length, stream});
        if (signal.aborted) throw new Error("Aborted");
        streamMessage.setStatus(roundStatus(round, firstRoundStatus) ?? "");
        await streamMessage.flush();
        const request: GeminiGenerationRequest = {
            model: config.geminiChatTarget.model,
            contents: messages,
            config: {
                tools: getGeminiTools(),
                temperature: messages.length <= 2 ? 0 : 0.6,
                abortSignal: signal,
            },
        };
        if (!stream) {
            const response = await geminiAi.models.generateContent(request) as unknown as GeminiResponseLike & {
                text?: string
            };
            const text = collectGeminiResponseText(response);
            streamMessage.append(text);
            const calls = collectGeminiFunctionCalls(response);
            aiLog(calls.length ? "info" : "success", calls.length ? "gemini.tool_calls" : "gemini.run.done", {
                round,
                duration: calls.length ? aiLogDuration(roundStartedAt) : aiLogDuration(runnerStartedAt),
                textChars: text.length,
                calls: calls.map(aiLogToolCall),
            });
            if (!calls.length) return;
            appendGeminiToolRound(messages, calls, await executeToolBatch(calls, streamMessage, toolContext, toolMemory));
            continue;
        }
        const response = await geminiAi.models.generateContentStream(request) as unknown as AsyncIterableStream<GeminiResponseLike & {
            text?: string
        }>;
        aiLog("debug", "gemini.stream.open", {round});
        let calls: ToolCallData[] = [];
        const roundTextStart = streamMessage.getText().length;
        for await (const chunk of response) {
            if (signal.aborted) throw new Error("Aborted");
            streamMessage.append(collectGeminiResponseText(chunk));
            calls = mergeGeminiFunctionCalls(calls, collectGeminiFunctionCalls(chunk));
        }
        aiLog(calls.length ? "info" : "success", calls.length ? "gemini.tool_calls" : "gemini.run.done", {
            round,
            duration: calls.length ? aiLogDuration(roundStartedAt) : aiLogDuration(runnerStartedAt),
            textChars: streamMessage.getText().slice(roundTextStart).length,
            calls: calls.map(aiLogToolCall),
        });
        if (!calls.length) return;
        appendGeminiToolRound(messages, calls, await executeToolBatch(calls, streamMessage, toolContext, toolMemory));
    }
 }
 export class GeminiProviderRunner {
    static run = runGemini;
 }
@@ -0,0 +1,137 @@
 // Mistral provider runner extracted from unified-ai-runner.ts.
 import {Environment} from "../common/environment";
 import {getMistralTools} from "./tool-mappers";
 import {TelegramStreamMessage} from "./telegram-stream-message";
 import {ToolRuntimeContext} from "./tools/runtime";
 import {MistralChatMessage} from "./mistral-chat-message";
 import {createMistralClient} from "./ai-runtime-target";
 import {aiLog, aiLogDuration, aiLogProviderTarget, aiLogToolCall} from "./ai-logger";
 import {MAX_TOOL_ROUNDS, MistralDeltaLike, MistralDocumentReference, RuntimeConfigSnapshot, StreamingToolCallAccumulator, ToolCallData, ToolExecutionMemory, contentFromMistralDelta, executeToolBatch, mistralToolCalls, normalizeMistralToolCalls, roundStatus} from "./unified-ai-runner.shared";
 export async function runMistral(
    messages: MistralChatMessage[],
    documents: MistralDocumentReference[],
    streamMessage: TelegramStreamMessage,
    signal: AbortSignal,
    stream: boolean,
    firstRoundStatus: string,
    config: RuntimeConfigSnapshot,
    toolContext: ToolRuntimeContext,
 ): Promise<void> {
    const runnerStartedAt = Date.now();
    const mistralAi = createMistralClient(config.mistralChatTarget);
    aiLog("info", "mistral.run.start", {
        stream,
        target: aiLogProviderTarget(config.mistralChatTarget),
        inputMessages: messages.length,
        documents: documents.length,
        hasToolInputFiles: !!toolContext.pythonInputFiles?.length,
    });
    const toolMemory: ToolExecutionMemory = new Map();
    for (let round = 0; round < MAX_TOOL_ROUNDS; round++) {
        const roundStartedAt = Date.now();
        aiLog("debug", "mistral.round.start", {round, messages: messages.length, stream});
        if (signal.aborted) throw new Error("Aborted");
        streamMessage.setStatus(roundStatus(round, firstRoundStatus) ?? "");
        await streamMessage.flush();
        if (!stream) {
            const request = {
                model: config.mistralChatTarget.model,
                messages,
                tools: getMistralTools(),
                documents: documents
            } as unknown as Parameters<typeof mistralAi.chat.complete>[0];
            const response = await mistralAi.chat.complete(request, {signal});
            const msg = response.choices?.[0]?.message;
            const text = typeof msg?.content === "string" ? msg.content : JSON.stringify(msg?.content ?? "");
            streamMessage.append(text);
            const calls = normalizeMistralToolCalls(mistralToolCalls(msg));
            aiLog(calls.length ? "info" : "success", calls.length ? "mistral.tool_calls" : "mistral.run.done", {
                round,
                duration: calls.length ? aiLogDuration(roundStartedAt) : aiLogDuration(runnerStartedAt),
                textChars: text.length,
                calls: calls.map(aiLogToolCall),
            });
            if (!calls.length) return;
            messages.push({
                role: "assistant",
                content: text,
                toolCalls: calls.map(call => ({
                    id: call.id,
                    function: {name: call.name, arguments: call.argumentsText},
                })),
            });
            const toolResults = await executeToolBatch(calls, streamMessage, toolContext, toolMemory);
            for (const [index, call] of calls.entries()) {
                messages.push({
                    role: "tool",
                    name: call.name,
                    toolCallId: call.id,
                    content: toolResults[index] ?? "",
                });
            }
            continue;
        }
        const request = {
            model: config.mistralChatTarget.model,
            messages,
            tools: getMistralTools(),
            documents: documents
        } as unknown as Parameters<typeof mistralAi.chat.stream>[0];
        const streamResponse = await mistralAi.chat.stream(request, {signal});
        aiLog("debug", "mistral.stream.open", {round});
        let calls: ToolCallData[] = [];
        const roundTextStart = streamMessage.getText().length;
        const toolCallAccumulator = new StreamingToolCallAccumulator("mistral_stream", round);
        for await (const event of streamResponse) {
            if (signal.aborted) throw new Error("Aborted");
            const choice = event.data?.choices?.[0];
            const delta = choice?.delta;
            const mistralDelta = delta as MistralDeltaLike;
            streamMessage.append(contentFromMistralDelta(mistralDelta));
            const rawDeltaCalls = mistralToolCalls(mistralDelta);
            if (rawDeltaCalls.length) {
                calls = toolCallAccumulator.add(rawDeltaCalls);
                streamMessage.setStatus(Environment.getUseToolText(calls));
                await streamMessage.flush();
            }
        }
        aiLog(calls.length ? "info" : "success", calls.length ? "mistral.tool_calls" : "mistral.run.done", {
            round,
            duration: calls.length ? aiLogDuration(roundStartedAt) : aiLogDuration(runnerStartedAt),
            textChars: streamMessage.getText().slice(roundTextStart).length,
            calls: calls.map(aiLogToolCall),
        });
        if (!calls.length) return;
        const roundText = streamMessage.getText().slice(roundTextStart);
        messages.push({
            role: "assistant",
            content: roundText,
            toolCalls: calls.map(c => ({id: c.id, function: {name: c.name, arguments: c.argumentsText}}))
        });
        const toolResults = await executeToolBatch(calls, streamMessage, toolContext, toolMemory);
        for (const [index, call] of calls.entries()) {
            messages.push({
                role: "tool",
                name: call.name,
                toolCallId: call.id,
                content: toolResults[index] ?? "",
            });
        }
    }
 }
 export class MistralProviderRunner {
    static run = runMistral;
 }
@@ -0,0 +1,404 @@
 // Ollama provider runner extracted from unified-ai-runner.ts.
 import {Message} from "typescript-telegram-bot-api";
 import * as fs from "node:fs";
 import path from "node:path";
 import {AiProvider} from "../model/ai-provider";
 import {Environment} from "../common/environment";
 import {bot, notesDir} from "../index";
 import {clamp, logError} from "../util/utils";
 import {getOllamaTools} from "./tool-mappers";
 import {TelegramStreamMessage} from "./telegram-stream-message";
 import {getModelCapabilities} from "./provider-model-runtime";
 import {ChatMessage} from "./chat-messages-types";
 import {ChatRequest, Tool} from "ollama";
 import {ToolRuntimeContext} from "./tools/runtime";
 import {enqueueTelegramApiCall} from "../util/telegram-api-queue";
 import {getCurrentDateTimeTool} from "./tools/datetime";
 import {getMarketRatesTool} from "./tools/market-rates";
 import {getWeatherTool} from "./tools/weather";
 import {loadOllamaModel, unloadAllOllamaModels} from "./tools/utils";
 import {createOllamaClient} from "./ai-runtime-target";
 import {GetNoteFileResult, GetNoteFileResultSchema} from "./tools/send-note-file";
 import {aiLog, aiLogDuration, aiLogMessageIdentity, aiLogProviderTarget, aiLogToolCall} from "./ai-logger";
 import {DEFAULT_OLLAMA_CONTEXT_SIZE, MAX_OLLAMA_CONTEXT_SIZE, MAX_TOOL_ROUNDS, MIN_OLLAMA_CONTEXT_SIZE, RuntimeConfigSnapshot, Think, ToolCallData, ToolExecutionMemory, allToolSchemaNames, appendOllamaToolResults, dedupeToolCalls, executeToolBatch, normalizeOllamaToolCalls, roundStatus, safeJsonParseObject, isRecord, isOllamaModelActive, OllamaToolCallLike} from "./unified-ai-runner.shared";
 import {latestUserTextFromOllamaMessages, looksLikeToolRankerJson, OllamaToolRanker} from "./unified-ai-runner.tool-ranker";
 export async function runOllama(
    msg: Message,
    messages: ChatMessage[],
    streamMessage: TelegramStreamMessage,
    signal: AbortSignal,
    stream: boolean,
    think: Think,
    firstRoundStatus: string,
    config: RuntimeConfigSnapshot,
    toolContext: ToolRuntimeContext,
    contextSize?: number,
 ): Promise<void> {
    const fromId = msg.from?.id;
    const runnerStartedAt = Date.now();
    const audioCount = messages.reduce((sum, m) => sum + (m.audioParts?.length || m.audios?.length || 0), 0);
    const videoNoteCount = messages.reduce((sum, m) => sum + (m.videoNotes?.length ?? 0), 0);
    const imageCount = messages.reduce((sum, m) => sum + (m.imageParts?.length || m.images?.length || 0), 0);
    const target = (audioCount || videoNoteCount) ? config.ollamaAudioTarget :
        imageCount ? config.ollamaVisionTarget :
            think ? config.ollamaThinkingTarget : config.ollamaChatTarget;
    const model = target.model;
    aiLog("info", "ollama.run.start", {
        stream,
        think,
        target: aiLogProviderTarget(target),
        requestedContextSize: contextSize,
        message: aiLogMessageIdentity(msg),
        counts: {messages: messages.length, images: imageCount, audio: audioCount, videoNotes: videoNoteCount},
        hasToolInputFiles: !!toolContext.pythonInputFiles?.length,
    });
    const ollama = createOllamaClient(target);
    const modelInfo = await ollama.show({model});
    const modelInfoMap = isRecord(modelInfo.model_info) ? modelInfo.model_info : {};
    const contextKey = Object.keys(modelInfoMap).find(k => k.endsWith(".context_length"));
    // @ts-ignore
    const rawMaxContextLength = contextKey ? modelInfoMap[contextKey] : undefined;
    const parsedMaxContextLength =
        typeof rawMaxContextLength === "number"
            ? rawMaxContextLength
            : typeof rawMaxContextLength === "string"
                ? Number(rawMaxContextLength)
                : DEFAULT_OLLAMA_CONTEXT_SIZE;
    const maxContextLength = Number.isFinite(parsedMaxContextLength)
        ? parsedMaxContextLength
        : DEFAULT_OLLAMA_CONTEXT_SIZE;
    const context = clamp(
        contextSize === -1 ? MAX_OLLAMA_CONTEXT_SIZE : contextSize ?? DEFAULT_OLLAMA_CONTEXT_SIZE,
        MIN_OLLAMA_CONTEXT_SIZE,
        maxContextLength ?? DEFAULT_OLLAMA_CONTEXT_SIZE
    );
    aiLog("debug", "ollama.context.resolved", {model, contextKey, maxContextLength, context});
    const modelsToLoad = [model];
    try {
        const activeModels = (await ollama.ps()).models.map(m => m.model);
        const oldSet = new Set(activeModels);
        const newSet = new Set(modelsToLoad);
        const added = modelsToLoad.filter(m => !oldSet.has(m));
        const removed = activeModels.filter(m => !newSet.has(m));
        const diff = [...added, ...removed];
        aiLog("debug", "ollama.models.active", {activeModels, requiredModels: modelsToLoad, added, removed});
        if (diff.length) {
            aiLog("info", "ollama.models.unload_extra", {keep: modelsToLoad, diff});
            await unloadAllOllamaModels(ollama, modelsToLoad);
        }
    } catch (e) {
        logError(e);
    }
    if (!(await isOllamaModelActive(ollama, target))) {
        const loadStartedAt = Date.now();
        aiLog("info", "ollama.model.load.start", {model, context});
        const currentStatus = streamMessage.getStatus();
        streamMessage.setStatus(Environment.getLoadingModelText(model));
        await streamMessage.flush();
        if (await loadOllamaModel(model, ollama, context)) {
            aiLog("success", "ollama.model.load.done", {model, duration: aiLogDuration(loadStartedAt)});
            streamMessage.setStatus(currentStatus ?? Environment.waitThinkText);
            await streamMessage.flush();
        }
    } else {
        aiLog("debug", "ollama.model.already_loaded", {model});
    }
    let interval: ReturnType<typeof setInterval> | null = null;
    if (!stream) {
        let typingInFlight = false;
        const applyTyping = async () => {
            if (typingInFlight) return;
            typingInFlight = true;
            try {
                await enqueueTelegramApiCall(
                    () => bot.sendChatAction({chat_id: msg.chat.id, action: "typing"}),
                    {method: "sendChatAction", chatId: msg.chat.id, chatType: msg.chat.type}
                ).catch(logError);
            } finally {
                typingInFlight = false;
            }
        };
        await applyTyping();
        interval = setInterval(() => {
            applyTyping().catch(logError);
        }, 5000);
    }
    const toolMemory: ToolExecutionMemory = new Map();
    try {
        for (let round = 0; round < MAX_TOOL_ROUNDS; round++) {
            const roundStartedAt = Date.now();
            aiLog("debug", "ollama.round.start", {
                round,
                context,
                messages: messages.length,
                stream,
                think: audioCount ? false : think,
            });
            const request: ChatRequest = {
                model: model,
                messages: messages,
                think: audioCount ? false : think,
                options: {
                    temperature: 0.6,
                    num_ctx: context,
                }
            };
            let activeToolNames: string[] = [];
            if ((await getModelCapabilities(AiProvider.OLLAMA, model, "tools"))?.tools?.supported) {
                const availableOllamaTools: Tool[] = fromId !== Environment.CREATOR_ID
                    ? [getCurrentDateTimeTool, getMarketRatesTool, getWeatherTool]
                    : getOllamaTools() as Tool[];
                aiLog("debug", "ollama.tools.available", {
                    round,
                    tools: allToolSchemaNames(availableOllamaTools),
                    rankerEnabled: !!config.ollamaToolRankerTarget,
                });
                const rankerSelection = await new OllamaToolRanker(config).selectTools({
                    userQuery: latestUserTextFromOllamaMessages(messages),
                    availableTools: availableOllamaTools,
                    round,
                    signal,
                });
                activeToolNames = rankerSelection.selectedNames;
                if (rankerSelection.tools.length > 0) {
                    request.tools = rankerSelection.tools;
                } else {
                    delete request.tools;
                }
                aiLog("debug", "ollama.tools.selected", {
                    round,
                    tools: activeToolNames,
                    count: activeToolNames.length,
                    usedRanker: rankerSelection.usedRanker,
                    missing: rankerSelection.missing,
                });
            }
            if (!stream) {
                const response = await ollama.chat({
                    ...request,
                    stream: false
                });
                const message = response.message;
                const rawContent = message?.content ?? "";
                const nativeCalls = dedupeToolCalls(
                    normalizeOllamaToolCalls(
                        message?.tool_calls as readonly OllamaToolCallLike[] | undefined,
                        round,
                    ),
                );
                const responseText = rawContent;
                if (looksLikeToolRankerJson(responseText)) {
                    aiLog("error", "ollama.response.looks_like_tool_ranker_json", {
                        round,
                        preview: responseText.slice(0, 800),
                        target: aiLogProviderTarget(target),
                    });
                    throw new Error("Ollama chat model returned tool-ranker JSON. Check that OLLAMA chat target and OLLAMA tools/ranker target are not mixed up.");
                }
                streamMessage.append(responseText);
                aiLog("debug", "ollama.response.received", {
                    round,
                    duration: aiLogDuration(roundStartedAt),
                    textChars: responseText.length,
                    nativeToolCallCount: nativeCalls.length,
                });
                if (!nativeCalls.length) {
                    aiLog("success", "ollama.run.done", {round, duration: aiLogDuration(runnerStartedAt)});
                    break;
                }
                const calls = nativeCalls;
                aiLog("info", "ollama.tool_calls", {
                    round,
                    calls: calls.map(aiLogToolCall),
                });
                messages.push({
                    role: "assistant",
                    content: responseText,
                    tool_calls: calls.map(c => ({
                        function: {
                            name: c.name,
                            arguments: safeJsonParseObject(c.argumentsText),
                        },
                    })),
                });
                appendOllamaToolResults(
                    messages,
                    calls,
                    await executeToolBatch(calls, streamMessage, toolContext, toolMemory),
                );
                continue;
            }
            const response = await ollama.chat({
                ...request,
                stream: true
            });
            aiLog("debug", "ollama.stream.open", {round});
            const calls: ToolCallData[] = [];
            const roundTextStart = streamMessage.getText().length;
            const abortOllamaResponse = () => response.abort?.();
            signal.addEventListener("abort", abortOllamaResponse, {once: true});
            if (signal.aborted) abortOllamaResponse();
            try {
                for await (const chunk of response) {
                    const localToolCalls: ToolCallData[] = [];
                    localToolCalls.push(...normalizeOllamaToolCalls(
                        chunk.message.tool_calls as readonly OllamaToolCallLike[] | undefined,
                        round,
                    ));
                    const newStatus = roundStatus(round, firstRoundStatus, chunk.message.content, localToolCalls, !!chunk.message.thinking);
                    const previousStatus = streamMessage.getStatus();
                    if (newStatus && newStatus !== Environment.waitThinkText) {
                        streamMessage.setStatus(newStatus);
                    } else {
                        streamMessage.clearStatus();
                    }
                    if (streamMessage.getStatus() !== previousStatus && previousStatus && newStatus !== Environment.waitThinkText) {
                        await streamMessage.flush();
                    }
                    if (signal.aborted) {
                        response.abort?.();
                        throw new Error("Aborted");
                    }
                    if (!(chunk.message?.thinking && streamMessage.getStatus() !== Environment.reasoningText)) {
                        streamMessage.append(chunk.message?.content ?? "");
                    }
                    calls.push(...normalizeOllamaToolCalls(
                        chunk.message?.tool_calls as readonly OllamaToolCallLike[] | undefined,
                        round,
                    ));
                    if (chunk.done) {
                        aiLog("debug", "ollama.stream.done", {
                            round,
                            duration: aiLogDuration(roundStartedAt),
                            textChars: streamMessage.getText().slice(roundTextStart).length,
                            toolCallCount: calls.length,
                        });
                        await streamMessage.flush(streamMessage.regenerateKeyboard(), true);
                    }
                }
            } finally {
                signal.removeEventListener("abort", abortOllamaResponse);
            }
            const streamedRoundText = streamMessage.getText().slice(roundTextStart);
            if (!calls.length && looksLikeToolRankerJson(streamedRoundText)) {
                streamMessage.replaceText(streamMessage.getText().slice(0, roundTextStart));
                aiLog("error", "ollama.response.looks_like_tool_ranker_json", {
                    round,
                    preview: streamedRoundText.slice(0, 800),
                    target: aiLogProviderTarget(target),
                });
                throw new Error("Ollama chat model returned tool-ranker JSON. Check that OLLAMA chat target and OLLAMA tools/ranker target are not mixed up.");
            }
            if (!calls.length) {
                aiLog("success", "ollama.run.done", {
                    round,
                    duration: aiLogDuration(runnerStartedAt),
                });
                break;
            }
            calls.splice(0, calls.length, ...dedupeToolCalls(calls));
            aiLog("info", "ollama.tool_calls", {
                round,
                calls: calls.map(aiLogToolCall),
            });
            const roundText = streamMessage.getText().slice(roundTextStart);
            messages.push({
                role: "assistant",
                content: roundText,
                tool_calls: calls.map(c => ({
                    function: {
                        name: c.name,
                        arguments: safeJsonParseObject(c.argumentsText),
                    },
                })),
            });
            const toolResults = await executeToolBatch(calls, streamMessage, toolContext, toolMemory);
            let successGetNoteFileResult: GetNoteFileResult | undefined = undefined;
            for (const toolResult of toolResults) {
                try {
                    const raw = JSON.parse(toolResult);
                    const res = GetNoteFileResultSchema.safeParse(raw);
                    if (res.success && res.data.success) {
                        successGetNoteFileResult = res.data;
                    }
                } catch {
                    // Not every tool result is JSON.
                }
            }
            if (successGetNoteFileResult && "attachment" in successGetNoteFileResult) {
                await bot.sendDocument({
                    chat_id: msg.chat.id,
                    reply_parameters: {
                        message_id: msg.message_id,
                    },
                    document: fs.createReadStream(path.join(notesDir, successGetNoteFileResult.attachment.relativePath)),
                }).catch(logError);
            }
            appendOllamaToolResults(messages, calls, toolResults);
        }
    } finally {
        if (interval) clearInterval(interval);
    }
 }
 export class OllamaProviderRunner {
    static run = runOllama;
 }
@@ -0,0 +1,426 @@
 // OpenAI and OpenAI-compatible provider runners extracted from unified-ai-runner.ts.
 import {Message} from "typescript-telegram-bot-api";
 import {Environment} from "../common/environment";
 import {getOpenAITools} from "./tool-mappers";
 import {TelegramStreamMessage} from "./telegram-stream-message";
 import {ToolRuntimeContext} from "./tools/runtime";
 import {OpenAIChatMessage} from "./openai-chat-message";
 import type {ResponseCreateParamsNonStreaming, ResponseCreateParamsStreaming, ResponseInputItem, ResponseStreamEvent} from "openai/resources/responses/responses";
 import type {ChatCompletionCreateParamsNonStreaming, ChatCompletionCreateParamsStreaming} from "openai/resources/chat/completions";
 import {createGeminiOpenAiClient, createOpenAiClient} from "./ai-runtime-target";
 import {aiLog, aiLogDuration, aiLogMessageIdentity, aiLogProviderTarget, aiLogToolCall} from "./ai-logger";
 import {AsyncIterableStream, MAX_TOOL_ROUNDS, OPENAI_IMAGE_PARTIALS, OpenAiChatCompletionResponseLike, OpenAiChatToolCallLike, OpenAiCompatibleChatMessage, OpenAiCompatibleContentPart, OpenAiResponseLike, OpenAiResponseOutputItem, RuntimeConfigSnapshot, ToolCallData, StreamingToolCallAccumulator, collectOpenAiResponseFunctionCalls, collectOpenAiResponseImages, collectOpenAiResponseText, executeToolBatch, getOpenAIResponsesToolsWithImage, openAiResponseItemCallId, safeJsonParseObject, showOpenAiGeneratedImage, ToolExecutionMemory, isRecord, roundStatus, OpenAiChatCompletionStreamChunkLike} from "./unified-ai-runner.shared";
 export async function runOpenAi(
    messages: OpenAIChatMessage[],
    streamMessage: TelegramStreamMessage,
    signal: AbortSignal,
    stream: boolean,
    firstRoundStatus: string,
    sourceMessage: Message,
    config: RuntimeConfigSnapshot,
    toolContext: ToolRuntimeContext,
 ): Promise<void> {
    // TODO: 13.05.2026: remove
    firstRoundStatus;
    const runnerStartedAt = Date.now();
    let responseInput: unknown[] = [...messages];
    const openAi = createOpenAiClient(config.openAiChatTarget);
    aiLog("info", "openai.run.start", {
        stream,
        target: aiLogProviderTarget(config.openAiChatTarget),
        imageTarget: aiLogProviderTarget(config.openAiImageTarget),
        inputMessages: messages.length,
        sourceMessage: aiLogMessageIdentity(sourceMessage),
        hasToolInputFiles: !!toolContext.pythonInputFiles?.length,
    });
    const toolMemory: ToolExecutionMemory = new Map();
    for (let round = 0; round < MAX_TOOL_ROUNDS; round++) {
        const roundStartedAt = Date.now();
        aiLog("debug", "openai.round.start", {round, inputItems: responseInput.length, stream});
        if (!stream) {
            const request: ResponseCreateParamsNonStreaming = {
                model: config.openAiChatTarget.model,
                input: responseInput as ResponseInputItem[],
                // TODO: 13.05.2026, Danil Nikolaev: fix
                tools: getOpenAIResponsesToolsWithImage(config) as any,
                instructions: config.systemPrompt,
            };
            const response = await openAi.responses.create(request, {signal}) as unknown as OpenAiResponseLike;
            const responseText = collectOpenAiResponseText(response);
            streamMessage.append(responseText);
            aiLog("debug", "openai.response.received", {
                round,
                duration: aiLogDuration(roundStartedAt),
                textChars: responseText.length,
                outputItems: response?.output?.length ?? 0,
            });
            const images = collectOpenAiResponseImages(response);
            if (images.length) {
                await showOpenAiGeneratedImage(
                    streamMessage,
                    sourceMessage,
                    images[images.length - 1],
                    `final_${round}`,
                    Environment.getImageGenDoneText(config.openAiImageTarget.model),
                    true,
                );
            }
            const calls = collectOpenAiResponseFunctionCalls(response);
            aiLog(calls.length ? "info" : "success", calls.length ? "openai.tool_calls" : "openai.run.done", {
                round,
                duration: calls.length ? aiLogDuration(roundStartedAt) : aiLogDuration(runnerStartedAt),
                calls: calls.map(call => ({
                    id: call.callId,
                    name: call.name,
                    arguments: safeJsonParseObject(call.argumentsText)
                })),
            });
            if (!calls.length) return;
            const toolCalls = calls.map(call => ({
                id: call.callId,
                name: call.name,
                argumentsText: call.argumentsText,
            }));
            const toolResults = await executeToolBatch(toolCalls, streamMessage, toolContext, toolMemory);
            const toolOutputs = calls.map((call, index) => ({
                type: "function_call_output" as const,
                call_id: call.callId,
                output: toolResults[index] ?? "",
            }));
            responseInput = [...responseInput, ...(response.output ?? []), ...toolOutputs];
            continue;
        }
        let completedResponse: OpenAiResponseLike | null = null;
        const request: ResponseCreateParamsStreaming = {
            model: config.openAiChatTarget.model,
            input: responseInput as ResponseInputItem[],
            stream: true,
            // TODO: 13.05.2026, Danil Nikolaev: fix
            tools: getOpenAIResponsesToolsWithImage(config) as any,
        };
        const response = await openAi.responses.create(request, {signal}) as unknown as AsyncIterableStream<ResponseStreamEvent>;
        aiLog("debug", "openai.stream.open", {round});
        let localToolCalls: ToolCallData[] = [];
        for await (const event of response) {
            if (signal.aborted) throw new Error("Aborted");
            switch (event.type) {
                case "response.output_text.delta":
                    streamMessage.append(event.delta ?? "");
                    break;
                case "response.image_generation_call.in_progress":
                    streamMessage.setStatus(Environment.startingImageGenText);
                    await streamMessage.flush();
                    break;
                case "response.image_generation_call.generating":
                    streamMessage.setStatus(Environment.imageGenText);
                    await streamMessage.flush();
                    break;
                case "response.image_generation_call.partial_image": {
                    const iteration = (event.partial_image_index ?? 0) + 1;
                    await showOpenAiGeneratedImage(
                        streamMessage,
                        sourceMessage,
                        event.partial_image_b64,
                        `partial_${round}_${iteration}`,
                        Environment.getPartialImageGenText(iteration, OPENAI_IMAGE_PARTIALS),
                        false,
                    );
                    break;
                }
                case "response.image_generation_call.completed":
                    streamMessage.setStatus(Environment.finalizingImageGenText);
                    await streamMessage.flush();
                    break;
                case "response.output_item.added":
                    if (event.item.type === "function_call" && event.item.name) {
                        const item = event.item as OpenAiResponseOutputItem & { id?: string };
                        localToolCalls.push({
                            id: openAiResponseItemCallId(item),
                            name: item.name ?? "",
                            argumentsText: item.arguments ?? "{}",
                        });
                        aiLog("info", "openai.stream.tool_call.added", {
                            round,
                            toolCalls: localToolCalls.map(aiLogToolCall)
                        });
                        streamMessage.setStatus(Environment.getUseToolText(localToolCalls));
                        await streamMessage.flush();
                    }
                    break;
                case "response.output_item.done":
                    if (event.item.type === "function_call" && event.item.name) {
                        const item = event.item as OpenAiResponseOutputItem & { id?: string };
                        const itemId = openAiResponseItemCallId(item);
                        const index = localToolCalls.findIndex(c => c.id === itemId);
                        if (index !== -1) {
                            localToolCalls.splice(index, 1);
                            if (localToolCalls.length === 0) {
                                streamMessage.clearStatus();
                            } else {
                                streamMessage.setStatus(Environment.getUseToolText(localToolCalls));
                            }
                            await streamMessage.flush();
                        }
                    }
                    break;
                case "response.function_call_arguments.delta":
                    break;
                case "response.function_call_arguments.done":
                    break;
                case "response.completed":
                    completedResponse = event.response as unknown as OpenAiResponseLike;
                    break;
                case "response.failed":
                    throw new Error(event.response?.error?.message ?? "OpenAI response failed");
                case "error":
                    throw new Error(event.message ?? event?.message ?? "OpenAI stream error");
            }
        }
        if (!completedResponse) throw new Error("OpenAI did not return the final response.completed event.");
        aiLog("debug", "openai.stream.completed", {
            round,
            duration: aiLogDuration(roundStartedAt),
            outputItems: completedResponse?.output?.length ?? 0,
        });
        const images = collectOpenAiResponseImages(completedResponse);
        if (images.length) {
            await showOpenAiGeneratedImage(
                streamMessage,
                sourceMessage,
                images[images.length - 1],
                `final_${round}`,
                Environment.getImageGenDoneText(config.openAiImageTarget.model),
                true,
            );
        }
        const calls = collectOpenAiResponseFunctionCalls(completedResponse);
        aiLog(calls.length ? "info" : "success", calls.length ? "openai.tool_calls" : "openai.run.done", {
            round,
            duration: calls.length ? aiLogDuration(roundStartedAt) : aiLogDuration(runnerStartedAt),
            calls: calls.map(call => ({
                id: call.callId,
                name: call.name,
                arguments: safeJsonParseObject(call.argumentsText)
            })),
        });
        if (!calls.length) return;
        const toolCalls = calls.map(call => ({
            id: call.callId,
            name: call.name,
            argumentsText: call.argumentsText,
        }));
        const toolResults = await executeToolBatch(toolCalls, streamMessage, toolContext, toolMemory);
        const toolOutputs = calls.map((call, index) => ({
            type: "function_call_output",
            call_id: call.callId,
            output: toolResults[index] ?? "",
        }));
        responseInput = [...responseInput, ...(completedResponse.output ?? []), ...toolOutputs];
    }
 }
 function openAiResponseContentToText(content: unknown): string {
    if (typeof content === "string") return content;
    if (!Array.isArray(content)) return "";
    return content.map(part => isRecord(part) ? part.text ?? part.content ?? part.refusal ?? "" : "").join("");
 }
 function openAiResponseMessagesToChatCompletions(messages: OpenAIChatMessage[]): OpenAiCompatibleChatMessage[] {
    return messages.map((message): OpenAiCompatibleChatMessage => {
        if (message.role === "system" || message.role === "assistant") {
            return {
                role: message.role,
                content: openAiResponseContentToText(message.content),
            };
        }
        const content = Array.isArray(message.content)
            ? message.content.map((part): OpenAiCompatibleContentPart => {
                if (isRecord(part) && part.type === "input_image") {
                    return {
                        type: "image_url",
                        image_url: {url: String(part.image_url ?? "")},
                    };
                }
                return {
                    type: "text",
                    text: isRecord(part) && typeof part.text === "string" ? part.text : "",
                };
            })
            : message.content;
        return {role: "user", content};
    });
 }
 function normalizeOpenAiChatToolCalls(toolCalls: OpenAiChatToolCallLike[] = []): ToolCallData[] {
    return toolCalls.map((call, i) => ({
        id: call.id || `openai_chat_${Date.now()}_${i}`,
        name: call.function?.name || call.name || "",
        argumentsText: typeof call.function?.arguments === "string"
            ? call.function.arguments
            : JSON.stringify(call.function?.arguments ?? call.arguments ?? {}),
    })).filter(call => call.name);
 }
 async function appendOpenAiChatToolResults(
    messages: OpenAiCompatibleChatMessage[],
    calls: ToolCallData[],
    results: string[],
 ): Promise<void> {
    for (const [index, call] of calls.entries()) {
        messages.push({
            role: "tool",
            tool_call_id: call.id,
            content: results[index] ?? "",
        });
    }
 }
 export async function runOpenAiCompatibleChat(
    messages: OpenAIChatMessage[],
    streamMessage: TelegramStreamMessage,
    signal: AbortSignal,
    stream: boolean,
    firstRoundStatus: string,
    config: RuntimeConfigSnapshot,
    toolContext: ToolRuntimeContext,
 ): Promise<void> {
    const runnerStartedAt = Date.now();
    const geminiOpenAi = createGeminiOpenAiClient(config.geminiChatTarget);
    const chatMessages = openAiResponseMessagesToChatCompletions(messages);
    const toolMemory: ToolExecutionMemory = new Map();
    aiLog("info", "openai_compatible.run.start", {
        stream,
        target: aiLogProviderTarget(config.geminiChatTarget),
        inputMessages: messages.length,
        chatMessages: chatMessages.length,
        hasToolInputFiles: !!toolContext.pythonInputFiles?.length,
    });
    for (let round = 0; round < MAX_TOOL_ROUNDS; round++) {
        const roundStartedAt = Date.now();
        aiLog("debug", "openai_compatible.round.start", {round, messages: chatMessages.length, stream});
        streamMessage.setStatus(roundStatus(round, firstRoundStatus) ?? "");
        await streamMessage.flush();
        if (!stream) {
            const request: ChatCompletionCreateParamsNonStreaming = {
                model: config.geminiChatTarget.model,
                messages: chatMessages,
                tools: getOpenAITools(),
                temperature: 0.6,
            };
            const response = await geminiOpenAi.chat.completions.create(request, {signal}) as unknown as OpenAiChatCompletionResponseLike;
            const message = response.choices?.[0]?.message;
            streamMessage.append(message?.content ?? "");
            const calls = normalizeOpenAiChatToolCalls(message?.tool_calls ?? []);
            aiLog(calls.length ? "info" : "success", calls.length ? "openai_compatible.tool_calls" : "openai_compatible.run.done", {
                round,
                duration: calls.length ? aiLogDuration(roundStartedAt) : aiLogDuration(runnerStartedAt),
                textChars: message?.content?.length ?? 0,
                calls: calls.map(aiLogToolCall),
            });
            if (!calls.length) return;
            chatMessages.push({
                role: "assistant",
                content: message?.content ?? "",
                tool_calls: calls.map(call => ({
                    id: call.id,
                    type: "function" as const,
                    function: {
                        name: call.name,
                        arguments: call.argumentsText,
                    },
                })),
            });
            await appendOpenAiChatToolResults(chatMessages, calls, await executeToolBatch(calls, streamMessage, toolContext, toolMemory));
            continue;
        }
        const request: ChatCompletionCreateParamsStreaming = {
            model: config.geminiChatTarget.model,
            messages: chatMessages,
            tools: getOpenAITools(),
            temperature: 0.6,
            stream: true,
        };
        const response = await geminiOpenAi.chat.completions.create(request, {signal}) as unknown as AsyncIterableStream<OpenAiChatCompletionStreamChunkLike>;
        aiLog("debug", "openai_compatible.stream.open", {round});
        // const streamToolCalls: OpenAiChatToolCallLike[] = [];
        const roundTextStart = streamMessage.getText().length;
        const toolCallAccumulator = new StreamingToolCallAccumulator("openai_chat_stream", round);
        let calls: ToolCallData[] = [];
        for await (const chunk of response) {
            if (signal.aborted) throw new Error("Aborted");
            const delta = chunk.choices?.[0]?.delta;
            streamMessage.append(delta?.content ?? "");
            if (delta?.tool_calls?.length) {
                calls = toolCallAccumulator.add(delta.tool_calls);
                streamMessage.setStatus(Environment.getUseToolText(calls));
                await streamMessage.flush();
            }
        }
        // const calls = collectOpenAiChatStreamToolCalls(streamToolCalls);
        aiLog(calls.length ? "info" : "success", calls.length ? "openai_compatible.tool_calls" : "openai_compatible.run.done", {
            round,
            duration: calls.length ? aiLogDuration(roundStartedAt) : aiLogDuration(runnerStartedAt),
            textChars: streamMessage.getText().slice(roundTextStart).length,
            calls: calls.map(aiLogToolCall),
        });
        if (!calls.length) return;
        const roundText = streamMessage.getText().slice(roundTextStart);
        chatMessages.push({
            role: "assistant",
            content: roundText,
            tool_calls: calls.map(call => ({
                id: call.id,
                type: "function",
                function: {
                    name: call.name,
                    arguments: call.argumentsText,
                },
            })),
        });
        await appendOpenAiChatToolResults(chatMessages, calls, await executeToolBatch(calls, streamMessage, toolContext, toolMemory));
    }
 }
 export class OpenAiProviderRunner {
    static run = runOpenAi;
 }
 export class OpenAiCompatibleProviderRunner {
    static run = runOpenAiCompatibleChat;
 }
@@ -0,0 +1,225 @@
 import {Tool} from "ollama";
 import {AiRuntimeTarget, createOllamaClient} from "./ai-runtime-target";
 import {aiLog, aiLogDuration, aiLogProviderTarget} from "./ai-logger";
 import {allToolSchemaNames, isRecord, JsonObject, RuntimeConfigSnapshot, safeJsonParseObject, toolSchemaNames} from "./unified-ai-runner.shared";
 type RankedToolStep = {
    t: string | string[];
    h?: string;
    from?: string;
 };
 type RankedToolPlan = {
    s?: RankedToolStep[];
    m?: string;
 };
 export type ToolRankerSelection = {
    tools: Tool[];
    selectedNames: string[];
    missing: string;
    raw: string;
    usedRanker: boolean;
 };
 export class OllamaToolRanker {
    constructor(private readonly config: RuntimeConfigSnapshot) {}
    async selectTools(args: {
        userQuery: string;
        availableTools: Tool[];
        round: number;
        signal: AbortSignal;
    }): Promise<ToolRankerSelection> {
        const {availableTools, round, signal, userQuery} = args;
        const target = this.config.ollamaToolRankerTarget;
        if (!availableTools.length) {
            return {tools: [], selectedNames: [], missing: "", raw: "", usedRanker: false};
        }
        // Ranker disabled/unconfigured: keep old behavior and expose all allowed tools.
        if (!target?.model) {
            return {
                tools: availableTools,
                selectedNames: allToolSchemaNames(availableTools),
                missing: "",
                raw: "",
                usedRanker: false,
            };
        }
        const startedAt = Date.now();
        const availableNames = new Set(allToolSchemaNames(availableTools));
        const prompt = this.config.rankerToolPrompt?.trim() || DEFAULT_TOOL_RANKER_PROMPT;
        const toolsForPrompt = availableTools.map(tool => ({
            names: toolSchemaNames(tool),
            schema: tool,
        }));
        aiLog("debug", "ollama.tool_ranker.start", {
            round,
            target: aiLogProviderTarget(target),
            queryChars: userQuery.length,
            availableTools: [...availableNames],
        });
        try {
            const ollama = createOllamaClient(target as AiRuntimeTarget);
            const response = await ollama.chat({
                model: target.model,
                messages: [
                    {role: "system", content: prompt},
                    {
                        role: "user",
                        content: JSON.stringify({
                            q: userQuery,
                            tools: toolsForPrompt,
                        }),
                    },
                ],
                stream: false,
                options: {
                    temperature: 0,
                    num_ctx: 8192,
                },
            });
            if (signal.aborted) throw new Error("Aborted");
            const raw = response.message?.content?.trim() ?? "";
            const plan = parseToolRankerPlan(raw);
            const selectedNames = normalizeToolRankerNames(plan, availableNames);
            const selectedNameSet = new Set(selectedNames);
            const tools = availableTools.filter(tool => toolSchemaNames(tool).some(name => selectedNameSet.has(name)));
            const missing = typeof plan?.m === "string" ? plan.m.trim() : "";
            aiLog("debug", "ollama.tool_ranker.done", {
                round,
                duration: aiLogDuration(startedAt),
                selectedNames,
                selectedCount: tools.length,
                missing,
                rawPreview: raw.slice(0, 800),
            });
            // Important: if the plan is valid and empty, use NO tools. Do not fall back to all tools.
            return {tools, selectedNames, missing, raw, usedRanker: true};
        } catch (error) {
            if (String(error).includes("Aborted")) throw error;
            aiLog("warn", "ollama.tool_ranker.failed.fallback_all_allowed", {
                round,
                target: aiLogProviderTarget(target),
                duration: aiLogDuration(startedAt),
                error,
            });
            // Ranker transport/model failure is different from "ranker returned empty plan".
            // In that case, preserve availability rather than silently disabling tools.
            return {
                tools: availableTools,
                selectedNames: allToolSchemaNames(availableTools),
                missing: "",
                raw: "",
                usedRanker: false,
            };
        }
    }
 }
 export function latestUserTextFromOllamaMessages(messages: readonly { role?: string; content?: unknown }[]): string {
    for (let i = messages.length - 1; i >= 0; i--) {
        const message = messages[i];
        if (message?.role !== "user") continue;
        if (typeof message.content === "string") return message.content;
        if (Array.isArray(message.content)) {
            return message.content
                .map(part => isRecord(part) && typeof part.text === "string" ? part.text : "")
                .filter(Boolean)
                .join("\n");
        }
    }
    return "";
 }
 export function looksLikeToolRankerJson(text: string): boolean {
    const parsed = safeJsonParseObject(extractJsonObjectText(text) ?? text);
    return Array.isArray(parsed.s) && typeof parsed.m === "string";
 }
 function parseToolRankerPlan(raw: string): RankedToolPlan | undefined {
    const jsonText = extractJsonObjectText(raw);
    if (!jsonText) return undefined;
    const parsed = safeJsonParseObject(jsonText) as JsonObject;
    if (!Array.isArray(parsed.s)) return undefined;
    return parsed as RankedToolPlan;
 }
 function normalizeToolRankerNames(plan: RankedToolPlan | undefined, availableNames: Set<string>): string[] {
    if (!plan?.s?.length) return [];
    const result: string[] = [];
    for (const step of plan.s) {
        const rawNames = Array.isArray(step.t) ? step.t : [step.t];
        for (const rawName of rawNames) {
            if (typeof rawName !== "string") continue;
            const name = rawName.trim();
            if (availableNames.has(name) && !result.includes(name)) {
                result.push(name);
            }
        }
    }
    return result;
 }
 function extractJsonObjectText(raw: string): string | undefined {
    const text = raw.trim()
        .replace(/^```(?:json)?\s*/i, "")
        .replace(/\s*```$/i, "")
        .trim();
    const start = text.indexOf("{");
    if (start === -1) return undefined;
    let depth = 0;
    let inString = false;
    let escaped = false;
    for (let i = start; i < text.length; i++) {
        const ch = text[i];
        if (escaped) {
            escaped = false;
            continue;
        }
        if (ch === "\\") {
            escaped = true;
            continue;
        }
        if (ch === '"') {
            inString = !inString;
            continue;
        }
        if (inString) continue;
        if (ch === "{") depth++;
        if (ch === "}") depth--;
        if (depth === 0) {
            return text.slice(start, i + 1);
        }
    }
    return undefined;
 }
 const DEFAULT_TOOL_RANKER_PROMPT = `You are a tool router. Return strict compact JSON only.
 Schema: {"s":[{"t":"tool_name","h":"short input hint","from":"previous_tool.output_or_empty"}],"m":""}
 Use tools only when they are needed. If no tool is needed, return {"s":[],"m":""}.
 Never answer the user. Never explain. Never use markdown.`;
@@ -96,8 +96,8 @@ export class AiCancel extends CallbackCommand {
                    {method: "editMessageText", chatId: message.chat.id, chatType: message.chat.type}
                );
-            if (result && result !== true) {
+            if (result) {
-                await MessageStore.put({...result, text: cancelledText} as Message);
+                await MessageStore.put({...(result as object), text: cancelledText} as Message);
            } else {
                await MessageStore.put({
                    chatId: message.chat.id,
@@ -21,8 +21,9 @@ export class Ae extends Command {
        try {
            let result = this.executeEvaluation(match);
            await oldSendMessage(msg, result).catch(async () => await errorPlaceholder(msg));
-        } catch (e: any) {
+        } catch (e: unknown) {
-            const text = e.message.toString();
+            const error = e instanceof Error ? e : new Error(String(e));
            const text = error.message.toString();
            if (text.includes("is not defined")) {
                await oldSendMessage(msg, Environment.variableNotDefinedText).catch(logError);
@@ -30,7 +31,7 @@ export class Ae extends Command {
            }
            logError(`${text}
-                * Stacktrace: ${e.stack}`);
+                * Stacktrace: ${error.stack}`);
            await oldSendMessage(msg, text).catch(logError);
        }
@@ -43,15 +44,16 @@ export class Ae extends Command {
            e = ((typeof e == "string") ? e : JSON.stringify(e));
            return e;
-        } catch (e: any) {
+        } catch (e: unknown) {
-            const text = e.message.toString();
+            const error = e instanceof Error ? e : new Error(String(e));
            const text = error.message.toString();
            if (text.includes("is not defined")) {
                return Environment.evaluationVariableNotDefinedText;
            }
            logError(`${text}
-                * Stacktrace: ${e.stack}`);
+                * Stacktrace: ${error.stack}`);
            return text;
        }
@@ -62,7 +62,7 @@ export class Distort extends Command {
                }),
                {method: "sendPhoto", chatId, chatType: msg.chat.type}
            );
-        } catch (e: any) {
+        } catch (e: unknown) {
            await oldReplyToMessage(
                msg, Environment.getDistortFailedText(e)
            ).catch(logError);
@@ -69,7 +69,7 @@ export class Qr extends Command {
                }),
                {method: "sendPhoto", chatId, chatType: msg.chat.type}
            );
-        } catch (e: any) {
+        } catch (e: unknown) {
            await replyToMessage({
                message: msg,
                text: Environment.getQrCodeFailedText(e)
@@ -1636,8 +1636,8 @@ export class Environment {
    private static getFileMtimeMs(filePath: string): number | undefined {
        try {
            return fs.statSync(filePath).mtimeMs;
-        } catch (e: any) {
+        } catch (e: unknown) {
-            if (e?.code === "ENOENT") {
+            if ((e as NodeJS.ErrnoException).code === "ENOENT") {
                return undefined;
            }
@@ -23,8 +23,8 @@ function normalizeLanguageCode(value: string | undefined | null): string | undef
 function readMtimeMs(filePath: string): number | undefined {
    try {
        return fs.statSync(filePath).mtimeMs;
-    } catch (e: any) {
+    } catch (e: unknown) {
-        if (e?.code === "ENOENT") return undefined;
+        if ((e as NodeJS.ErrnoException).code === "ENOENT") return undefined;
        throw e;
    }
 }
@@ -1,7 +1,6 @@
 export type OllamaRequest = {
    uuid: string;
-    // eslint-disable-next-line @typescript-eslint/no-explicit-any
+    stream: unknown;
    stream: any;
    done: boolean;
    fromId: number;
    chatId: number;
@@ -68,11 +68,12 @@ export class ShellCommandRunner {
            }
            return {stdout, stderr};
-        } catch (error: any) {
+        } catch (error: unknown) {
-            console.error("Error code:", error.code);
+            const err = error as Partial<Error & {code: unknown; stdout: string; stderr: string}>;
-            console.error("Stderr:", error.stderr);
+            console.error("Error code:", err.code);
            console.error("Stderr:", err.stderr);
-            return {stdout: error.stdout ?? null, stderr: error.stderr ?? error.message};
+            return {stdout: err.stdout ?? null, stderr: err.stderr ?? err.message ?? String(error)};
        }
    }
@@ -1,4 +1,5 @@
 import * as si from "systeminformation";
 import {redactLogValue} from "../ai/ai-logger";
 import {Command} from "../base/command";
 import {CallbackCommand} from "../base/callback-command";
 import {
@@ -65,7 +66,7 @@ export const ignoreIfMarkupFailed = (e: Error | TelegramError) => {
 };
 export const logError = (e: Error | TelegramError | string | unknown) => {
-    console.error(e);
+    console.error(redactLogValue(e));
 };
 export const errorPlaceholder = async (msg: Message) => {
@@ -307,13 +308,13 @@ export async function editMessageText(options: EditOptions, retries = 1) {
            }
        );
        return Promise.resolve(message);
-    } catch (e: any) {
+    } catch (e: unknown) {
        logError(e);
-        if (isMarkupFailed(e)) {
+        if (isMarkupFailed(e as Error | TelegramError)) {
            return Promise.resolve(true);
-        } else if (isTooManyRequests(e) && retries > 0) {
+        } else if (isTooManyRequests(e as Error | TelegramError) && retries > 0) {
-            const retryAfter = Number(e.message.split("retry after ")[1]) || 30;
+            const retryAfter = Number((e instanceof Error ? e.message : String(e)).split("retry after ")[1]) || 30;
            await delay(retryAfter * 1000);
            return editMessageText(options, retries - 1);
        } else {
@@ -1836,9 +1837,10 @@ export function startIntervalEditor(params: {
        try {
            await params.editFn(next);
            lastSent = next;
-        } catch (e: any) {
+        } catch (e: unknown) {
-            if ((e?.description ?? e?.message ?? "").includes("message is not modified")) return;
+            const description = e instanceof Error ? e.message : String(e);
-            logError("edit failed: " + e);
+            if (description.includes("message is not modified")) return;
            logError("edit failed: " + description);
        }
    };
@@ -1896,7 +1898,6 @@ type RuntimeInfo =
    | { runtime: "unknown"; version: string };
 export function getRuntimeInfo(): RuntimeInfo {
    // eslint-disable-next-line @typescript-eslint/no-explicit-any
    const v = process.versions ?? {};
    if (typeof v.bun === "string") {
@@ -1906,7 +1907,6 @@ export function getRuntimeInfo(): RuntimeInfo {
        return {runtime: "node", version: v.node};
    }
    // eslint-disable-next-line @typescript-eslint/no-explicit-any
    return {runtime: "unknown", version: String(process.version ?? "")};
 }
@@ -1957,7 +1957,6 @@ export async function imageToBase64(filePath: string, withMimeType: boolean = fa
    }
 }
 // eslint-disable-next-line @typescript-eslint/no-explicit-any
 export function ifTrue(exp?: string | number | boolean): boolean {
    if (!exp) return false;
@@ -1,24 +1,32 @@
 {
  "compilerOptions": {
    "target": "ES2022",
-    "module": "NodeNext",
+    "module": "ESNext",
-    "moduleResolution": "NodeNext", // Modern resolution
+    "moduleResolution": "Bundler",
-    "rootDir": "src",              // Limits scope
+    "rootDir": "src",
    "outDir": "dist",
-    "incremental": true,           // HUGE performance boost
+    "incremental": true,
-    "isolatedModules": true,       // Ensures compatibility with fast runners
+    "isolatedModules": true,
    "strict": true,
    "noUnusedLocals": true,
    "noUnusedParameters": true,
    "skipLibCheck": true,
    "esModuleInterop": true,
    "resolveJsonModule": true,
    "sourceMap": true,
    "emitDecoratorMetadata": true,
    "experimentalDecorators": true,
    "allowSyntheticDefaultImports": true,
    "types": [
      "node",
      "bun"
    ]
  },
-  "include": ["src/**/*.ts"],
+  "include": [
-  "exclude": ["node_modules", "dist"] // Explicitly exclude build artifacts
+    "src/**/*.ts"
  ],
  "exclude": [
    "node_modules",
    "dist"
  ]
 }