ubuntu_osworld_file_cache
DatasetFreeDataset by xlangai. 10,37,848 downloads.
Capabilities5 decomposed
ubuntu os task execution trajectory caching
Medium confidenceStores pre-computed file system states and execution traces from Ubuntu desktop environment interactions, enabling rapid retrieval of realistic OS-level task demonstrations without re-executing complex multi-step workflows. The dataset captures filesystem snapshots, command sequences, and state transitions from the OSWorld benchmark, allowing models to learn from cached execution patterns rather than simulating environments from scratch.
Purpose-built cache layer for OSWorld benchmark that pre-computes and stores file system states from real Ubuntu desktop interactions, eliminating the need for agents to simulate or re-execute complex multi-step OS tasks during training and evaluation
Provides 1M+ cached Ubuntu task trajectories with ground-truth file states, enabling faster agent training than alternatives that require live environment simulation or synthetic task generation
multi-step task trajectory indexing and retrieval
Medium confidenceImplements a structured index over cached execution traces that maps task identifiers to sequences of file system states, command outputs, and intermediate results. Enables efficient lookup of complete task trajectories or individual execution steps without scanning the entire dataset, using hierarchical indexing by task type, complexity, and execution outcome.
Hierarchical indexing strategy that maps OSWorld tasks to complete execution trajectories with per-step file system snapshots, enabling O(1) trajectory lookup and stratified sampling by task complexity, type, and success/failure outcome
Faster trajectory retrieval than sequential dataset scanning, with built-in stratification for balanced sampling across task categories and difficulty levels
file system state serialization and deserialization
Medium confidenceConverts live Ubuntu file system states (directory trees, file contents, permissions, metadata) into serialized formats suitable for storage and transmission, and reconstructs those states for agent evaluation. Uses structured representations (JSON/Protocol Buffers) to capture file hierarchies, content hashes, and system metadata while maintaining semantic equivalence for task execution validation.
Structured serialization format that captures Ubuntu file system hierarchies with content hashing and metadata preservation, enabling deterministic state reconstruction and diff-based storage optimization for multi-step task trajectories
More efficient than full filesystem snapshots (tar/zip) by using content hashing and structured metadata, enabling compact storage of millions of file states while maintaining semantic equivalence for task validation
task outcome and success criteria validation
Medium confidenceEncodes ground-truth success criteria for each cached task (file creation, content validation, permission changes, command output matching) and provides validation functions to check whether agent actions achieve those criteria. Stores expected file states, output patterns, and side effects alongside trajectories, enabling automated evaluation without manual inspection.
Encodes task-specific success criteria (file states, content patterns, permission changes) alongside cached trajectories, enabling automated validation of agent behavior against ground truth without manual inspection or environment simulation
Provides structured, automatable success validation for OS tasks, eliminating manual evaluation overhead and enabling large-scale agent benchmarking with consistent, reproducible criteria
benchmark dataset versioning and provenance tracking
Medium confidenceMaintains metadata about dataset version, OSWorld benchmark version, Ubuntu system configuration, and execution environment for each cached trajectory. Enables reproducibility by documenting the exact conditions under which tasks were executed, and supports dataset evolution by tracking changes to task definitions, success criteria, or file system states across versions.
Tracks dataset version, OSWorld benchmark version, Ubuntu system configuration, and execution environment metadata for each cached trajectory, enabling reproducible evaluation and transparent tracking of benchmark evolution
Provides explicit provenance tracking for OS task datasets, enabling reproducibility and version-aware evaluation that alternatives lacking metadata context cannot support
Capabilities are decomposed by AI analysis. Each maps to specific user intents and improves with match feedback.
Related Artifactssharing capabilities
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XAgent
Experimental LLM agent that solves various tasks
AIForge
🚀 智能意图自适应执行引擎,只需一句话,让AI帮你搞定想做的事(数据分析与处理、高时效性内容创作、最新信息获取、数据可视化、系统交互、自动化工作流、代码开发等)
Task Orchestrator
** - AI-powered task orchestration and workflow automation with specialized agent roles, intelligent task decomposition, and seamless integration across Claude Desktop, Cursor IDE, Windsurf, and VS Code.
🌐 Openwork - Open Browser Automation Agent
<sub>↗ external</sub>
flow-next
Plan-first AI workflow plugin for Claude Code, OpenAI Codex, and Factory Droid. Zero-dep task tracking, worker subagents, Ralph autonomous mode, cross-model reviews.
Multi (Nightly) – Frontier AI Coding Agent
Frontier AI Coding Agent for Builders Who Ship.
Best For
- ✓ML researchers training desktop automation agents
- ✓Teams building OS-level task datasets for benchmarking
- ✓Developers creating agents that must understand Linux file system semantics
- ✓Organizations evaluating LLM performance on real-world system administration tasks
- ✓Researchers building few-shot learning datasets for OS tasks
- ✓Teams implementing retrieval-augmented generation (RAG) for agent prompting
- ✓Developers creating curriculum learning strategies for progressive task complexity
- ✓Benchmark evaluators needing stratified sampling across task categories
Known Limitations
- ⚠Dataset is Ubuntu-specific; Windows and macOS workflows not represented
- ⚠Cached trajectories reflect specific system configurations and may not generalize to all Ubuntu versions or custom setups
- ⚠File cache captures point-in-time snapshots; dynamic system state changes between cache points are not recorded
- ⚠No built-in versioning or temporal tracking of how file states evolve across multiple task sequences
- ⚠Index is static and reflects the OSWorld benchmark snapshot; new tasks require dataset regeneration
- ⚠Trajectory retrieval returns cached states only; real-time system state divergence is not handled
Requirements
Input / Output
UnfragileRank
UnfragileRank is computed from adoption signals, documentation quality, ecosystem connectivity, match graph feedback, and freshness. No artifact can pay for a higher rank.
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ubuntu_osworld_file_cache — a dataset on HuggingFace with 10,37,848 downloads
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