- Remove npm install and npm run build from worktree initialization
- Remove INITIALIZING status enum and related code
- Add keep_worktree config option (default: false)
- When keep_worktree is true, worktree is preserved for debugging
- Renumber execution steps after removing initialize step
Co-authored-by: Qwen-Coder <qwen-coder@alibabacloud.com>
- Add git diff capture after each run, saved as diff.patch
- Add session log collection from ~/.qwen/projects/{id}/chats/
- Store session logs in outputs/{run_id}/chats/ with original filename
- Add session_id field to track chat recording UUID
- Modify cwd in session logs to actual runner working directory
- Remove stdout_file/stderr_file from top-level, keep only in prompt_results
- Rename logs folder to openai-logs
- Add File Writer task example for testing file creation
Co-authored-by: Qwen-Coder <qwen-coder@alibabacloud.com>
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>
