| schema_version = "1.2" | |
| artifacts = [] | |
| [task] | |
| name = "smoldataenvs-train/0001_137_1137361_qa_2" | |
| description = "What is the total number of check-ins recorded in the New York City dataset?" | |
| authors = [] | |
| keywords = ["smoldataenvs", "data-analysis", "kaggle"] | |
| [metadata] | |
| source_dataset = "jupyter-agent/jupyter-agent-dataset" | |
| source_row_id = "0001/137/1137361.ipynb_qa_2" | |
| kaggle_dataset_name = "chetanism/foursquare-nyc-and-tokyo-checkin-dataset" | |
| gold_answer = "227428" | |
| reward_mode_initial = "numeric" | |
| package_tier = 1 | |
| difficulty_level = 1 | |
| difficulty = "easy" | |
| difficulty_tier = "easy" | |
| [environment] | |
| build_timeout_sec = 600.0 | |
| os = "linux" | |
| cpus = 1 | |
| memory_mb = 1024 | |
| storage_mb = 5120 | |
| gpus = 0 | |
| allow_internet = true | |
| mcp_servers = [] | |
| # Pre-agent hook: Harbor runs the command AFTER container start and BEFORE the | |
| # agent setup begins. We use it to pull this task's bucket prefix into | |
| # /home/user/input/. See environment/pull_bucket.py. | |
| [environment.healthcheck] | |
| command = "python3 /opt/pull_bucket.py && [ -n \"$(ls /home/user/input)\" ]" | |
| interval_sec = 2.0 | |
| timeout_sec = 180.0 | |
| start_period_sec = 5.0 | |
| start_interval_sec = 2.0 | |
| retries = 30 | |
| [environment.env] | |
| HF_BUCKET = "AdithyaSK/jupyter-agent-kaggle-all" | |
| BUCKET_PREFIX = "chetanism__foursquare-nyc-and-tokyo-checkin-dataset" | |
| HF_TOKEN = "${HF_TOKEN}" | |
| KAGGLE_DATASET_NAME = "chetanism/foursquare-nyc-and-tokyo-checkin-dataset" | |
| [verifier] | |
| timeout_sec = 120.0 | |
| [verifier.env] | |
| EXPECTED_ANSWER = "227428" | |
| QUESTION = "What is the total number of check-ins recorded in the New York City dataset?" | |
| REWARD_MODE = "numeric" | |
| ATOL = "0.0" | |
| RTOL = "0.0" | |
| [agent] | |
| # Capped at 600s (10 min) to kill the long-tail stuck-agent cases without | |
| # cutting off legitimate complex trials. Median Phase B trial is 60-120s; | |
| # legitimate L4/L5 tasks can hit 200-300s; anything past 600s is almost | |
| # certainly a stuck agent loop. | |
| timeout_sec = 600.0 | |
| [solution.env] | |