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Add a Python-based concurrent runner that executes multiple Qwen CLI tasks
across different models in parallel using isolated git worktrees.
Features:
- Execute N tasks × M models concurrently with configurable concurrency
- Create isolated git worktrees for each run under ~/.qwen/worktrees
- Real-time progress display with Rich library
- Capture stdout, stderr, and OpenAI API logs per run
- Atomic JSON tracking of all runs with status and metadata
- Automatic cleanup of worktrees after each run
Structure:
- runner.py: Main implementation with asyncio
- requirements.txt: Python dependencies
- README.md: Documentation and usage
- config.example.json: Configuration template
- examples/: Toy example with sample config and project
Usage:
python runner.py config.json
Each run creates an isolated output directory:
outputs/{run_id}/
├── stdout.txt
├── stderr.txt
└── logs/openai-*.json
Co-authored-by: Qwen-Coder <qwen-coder@alibabacloud.com>
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2 lines
30 B
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rich>=13.0.0
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aiofiles>=23.0.0
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