|
Download data/processed/RQ1/README.md from AINativeOps/AINativeBench: direct link, hf CLI and curl.
- Browser
- Download file 990 Bytes
-
https://huggingface.co/datasets/AINativeOps/AINativeBench/resolve/main/data/processed/RQ1/README.md
- Command line
-
hf download hf://datasets/AINativeOps/AINativeBench/data/processed/RQ1/README.md
-
curl -L -o README.md https://huggingface.co/datasets/AINativeOps/AINativeBench/resolve/main/data/processed/RQ1/README.md
990 Bytes
| # RQ1 | |
| This directory contains scripts and aggregated artifacts for **RQ1** evaluation. | |
| ## Structure | |
| Each subfolder corresponds to one task/project and orchestration variant: | |
| - `*-A2A`: A2A runs | |
| - `*-H_A2A`: hard-coded A2A baseline | |
| - `*-MCP`: MCP runs | |
| Typical contents of each subfolder: | |
| - `reference_trajectory.yaml`: reference (ground-truth) trajectory/config | |
| - `evaluate_trajectory*.py`: trajectory-metric evaluation (writes CSV) | |
| - `evaluate_success.py`: success-rate computation (writes JSON/CSV) | |
| - `analyze_retry_patterns.py`: retry/error pattern analysis (writes JSON/CSV) | |
| ## Radar charts | |
| - `generate_radar_charts.py`: generates radar charts from evaluation outputs. | |
| ## Usage | |
| Run scripts from within the corresponding subfolder, e.g.: | |
| ```bash | |
| python3 evaluate_trajectory.py --config reference_trajectory.yaml --output evaluation_results.csv | |
| python3 evaluate_success.py | |
| python3 analyze_retry_patterns.py | |
| ``` | |
| Then (from `RQ1/`): | |
| ```bash | |
| python3 generate_radar_charts.py | |
| ``` | |