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https://github.com/feder-cr/Jobs_Applier_AI_Agent.git
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feder-cr
c0005a91e3
Harbor (the harness of Terminal-Bench) runs each task in a new Dot: dots_harbor/ is its environment (the Dot is created through the API, the task's Dockerfile is replayed as dot, with apt through dot-install, and the task's root paths are moved under /home/dot/bench) and its agent (the instruction goes to the Dot as a task). Every call goes through bridge.ts, on the end-to-end run's outside driver. Harbor's registry datasets run the same way. tasks/, written by author.py from fixed seeds: shell, files, coding, data analysis, the computer's settings, questions with one answer, two long tasks, and what a Dot is for (its own automation, a careful cleanup, a request it must refuse). In Dots: the oracle scores 25/25 and doing nothing 0/25; the Dot with z-ai/glm-5.3-flash scored 23/25 in 9 minutes, 4 at a time (one miss was the grader's rounding, now fixed).
21 lines
511 B
JSON
21 lines
511 B
JSON
{
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"extends": "./tsconfig.base.json",
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"compilerOptions": {
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"allowImportingTsExtensions": true
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},
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"include": [
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"*.ts",
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"apps/*/src/**/*.ts",
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"apps/*/test/**/*.ts",
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"packages/*/src/**/*.ts",
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"packages/*/test/**/*.ts",
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"packages/*/scripts/**/*.ts",
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"guest/image-builder/src/**/*.ts",
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"guest/image-builder/test/**/*.ts",
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"tests/repo/**/*.ts",
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"tests/e2e/**/*.ts",
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"tests/bench/**/*.ts"
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],
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"exclude": ["node_modules", "apps/web", "invisible_engine_dots"]
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}
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