hermes · spark · shootout

← hermes-4-70b-fp8

anomaly-detection-ranking

general timeout 38 turns 2240s 38 tool calls

reconstructed
TBLite drops the in‑progress transcript when it kills a timing‑out task. The events below were captured turn‑by‑turn by the agent‑loop patch and pieced back together — full content, reasoning, and tool calls are all real; they just came from a different stream than the other tasks.

turn 1 · tool · search_files 
{"total_count": 0}
turn 1 · assistant 26.0s api 
→ search_files({"pattern": "sensor_train.csv", "target": "files", "path": "."})
turn 2 · tool · search_files 
{"total_count": 0}
turn 2 · assistant 14.3s api 
→ search_files({"pattern": "network_train.csv", "target": "files", "path": "."})
turn 3 · tool · search_files 
{"total_count": 0}
turn 3 · assistant 18.5s api 
→ search_files({"pattern": "movie_train.csv", "target": "files", "path": "."})
turn 4 · tool · search_files 
{"total_count": 0}
turn 4 · assistant 20.5s api 
→ search_files({"pattern": "news_train.csv", "target": "files", "path": "."})
turn 5 · tool · search_files 
{"total_count": 0}
turn 5 · assistant 19.9s api 
→ search_files({"pattern": "both_train.csv", "target": "files", "path": "."})
turn 6 · tool · search_files 
{"total_count": 0}
turn 6 · assistant 17.3s api 
→ search_files({"pattern": "sensor_test.csv", "target": "files", "path": "."})
turn 7 · tool · search_files 
{"total_count": 0}
turn 7 · assistant 14.8s api 
→ search_files({"pattern": "network_test.csv", "target": "files", "path": "."})
turn 8 · tool · search_files 
{"total_count": 0}
turn 8 · assistant 21.1s api 
→ search_files({"pattern": "movie_test.csv", "target": "files", "path": "."})
turn 9 · tool · search_files 
{"total_count": 0}
turn 9 · assistant 15.2s api 
→ search_files({"pattern": "news_test.csv", "target": "files", "path": "."})
turn 10 · tool · search_files 
{"total_count": 0}
turn 10 · assistant 15.1s api 
→ search_files({"pattern": "both_test.csv", "target": "files", "path": "."})
turn 11 · tool · terminal 
{"output": "/app\ntotal 8\ndrwxr-xr-x 2 root root 4096 Apr 22 00:31 .\ndrwxr-xr-x 1 root root 4096 Apr 22 00:31 ..", "exit_code": 0, "error": null}
turn 11 · assistant 10.4s api 
→ terminal({"command": "pwd && ls -la"})
turn 12 · tool · terminal 
{"output": "", "exit_code": 0, "error": null}
turn 12 · assistant 13.1s api 
→ terminal({"command": "find . -name \"*.csv\" -type f"})
turn 13 · tool · terminal 
{"output": "/usr/share/distro-info/ubuntu.csv\n/usr/share/distro-info/debian.csv\n/usr/local/lib/python3.11/dist-packages/sklearn/datasets/data/linnerud_physiological.csv\n/usr/local/lib/python3.11/dist-packages/sklearn/datasets/data/wine_data.csv\n/usr/local/lib/python3.11/dist-packages/sklearn/datasets/data/boston_house_prices.csv\n/usr/local/lib/python3.11/dist-packages/sklearn/datasets/data/iris.csv\n/usr/local/lib/python3.11/dist-packages/sklearn/datasets/data/linnerud_exercise.csv\n/usr/local/lib/python3.11/dist-packages/sklearn/datasets/data/breast_cancer.csv\n/usr/local/lib/python3.11/dist-packages/numpy/random/tests/data/mt19937-testset-1.csv\n/usr/local/lib/python3.11/dist-packages/numpy/random/tests/data/sfc64-testset-2.csv", "exit_code": 0, "error": null}
turn 13 · assistant 21.5s api 
→ terminal({"command": "find / -name \"*.csv\" -type f 2>/dev/null | head -10"})
turn 14 · tool · search_files 
{"total_count": 1, "files": ["/workdir/data/sensor_train.csv"]}
turn 14 · assistant 15.4s api 
→ search_files({"pattern": "sensor_train.csv", "target": "files", "path": "/"})
turn 15 · tool · search_files 
{"total_count": 1, "files": ["/workdir/data/sensor_test.csv"]}
turn 15 · assistant 15.2s api 
→ search_files({"pattern": "sensor_test.csv", "target": "files", "path": "/"})
turn 16 · tool · search_files 
{"total_count": 1, "files": ["/workdir/data/network_train.csv"]}
turn 16 · assistant 14.7s api 
→ search_files({"pattern": "network_train.csv", "target": "files", "path": "/"})
turn 17 · tool · search_files 
{"total_count": 1, "files": ["/workdir/data/network_test.csv"]}
turn 17 · assistant 14.6s api 
→ search_files({"pattern": "network_test.csv", "target": "files", "path": "/"})
turn 18 · tool · search_files 
{"total_count": 1, "files": ["/workdir/data/movie_train.csv"]}
turn 18 · assistant 15.0s api 
→ search_files({"pattern": "movie_train.csv", "target": "files", "path": "/"})
turn 19 · tool · search_files 
{"total_count": 1, "files": ["/workdir/data/movie_test.csv"]}
turn 19 · assistant 19.1s api 
→ search_files({"pattern": "movie_test.csv", "target": "files", "path": "/"})
turn 20 · tool · search_files 
{"total_count": 1, "files": ["/workdir/data/news_train.csv"]}
turn 20 · assistant 16.2s api 
→ search_files({"pattern": "news_train.csv", "target": "files", "path": "/"})
turn 21 · tool · search_files 
{"total_count": 1, "files": ["/workdir/data/news_test.csv"]}
turn 21 · assistant 19.1s api 
→ search_files({"pattern": "news_test.csv", "target": "files", "path": "/"})
turn 22 · tool · search_files 
{"total_count": 1, "files": ["/workdir/data/both_train.csv"]}
turn 22 · assistant 20.1s api 
→ search_files({"pattern": "both_train.csv", "target": "files", "path": "/"})
turn 23 · tool · search_files 
{"total_count": 1, "files": ["/workdir/data/both_test.csv"]}
turn 23 · assistant 16.5s api 
→ search_files({"pattern": "both_test.csv", "target": "files", "path": "/"})
turn 24 · tool · terminal 
{"output": "total 12\ndrwxr-xr-x 1 root root 4096 Mar  4 09:08 .\ndrwxr-xr-x 1 root root 4096 Apr 22 00:31 ..\ndrwxr-xr-x 2 root root 4096 Mar  4 09:08 data", "exit_code": 0, "error": null}
turn 24 · assistant 43.2s api 
→ terminal({"command": "cd /workdir && ls -la"})
turn 25 · tool · terminal 
{"output": "total 80\ndrwxr-xr-x 2 root root  4096 Mar  4 09:08 .\ndrwxr-xr-x 1 root root  4096 Mar  4 09:08 ..\n-rw-rw-r-- 1 root root   216 Mar  4 09:05 both_test.csv\n-rw-rw-r-- 1 root root   250 Mar  4 09:05 both_train.csv\n-rw-rw-r-- 1 root root   285 Mar  4 09:05 movie_test.csv\n-rw-rw-r-- 1 root root   343 Mar  4 09:05 movie_train.csv\n-rw-rw-r-- 1 root root  8381 Mar  4 09:05 network_test.csv\n-rw-rw-r-- 1 root root 17323 Mar  4 09:05 network_train.csv\n-rw-rw-r-- 1 root root   221 Mar  4 09:05 news_test.csv\n-rw-rw-r-- 1 root root   261 Mar  4 09:05 news_train.csv\n-rw-rw-r-- 1 root root  3978 Mar  4 09:05 sensor_test.csv\n-rw-rw-r-- 1 root root  8329 Mar  4 09:05 sensor_train.csv", "exit_code": 0, "error": null}
turn 25 · assistant 27.2s api 
→ terminal({"command": "cd /workdir && ls -la data/"})
turn 26 · tool · read_file 
{"content": "     1|timestamp,value,label\n     2|2025-06-01 00:00:00,0.1764052345967664,0\n     3|2025-06-01 01:00:00,0.08999489010740067,0\n     4|2025-06-01 02:00:00,0.19770721505740207,0\n     5|2025-06-01 03:00:00,0.373527452393745,0\n     6|", "total_lines": 201, "file_size": 8329, "truncated": true, "hint": "Use offset=6 to continue reading (showing 1-5 of 201 lines)", "is_binary": false, "is_image": false}
turn 26 · assistant 18.4s api 
→ read_file({"path": "/workdir/data/sensor_train.csv", "limit": 5})
turn 27 · tool · read_file 
{"content": "     1|timestamp,value\n     2|2025-07-01 00:00:00,-0.03691818379424436\n     3|2025-07-01 01:00:00,0.04267937716580035\n     4|2025-07-01 02:00:00,0.2429045822110254\n     5|2025-07-01 03:00:00,0.26419570386732105\n     6|", "total_lines": 101, "file_size": 3978, "truncated": true, "hint": "Use offset=6 to continue reading (showing 1-5 of 101 lines)", "is_binary": false, "is_image": false}
turn 27 · assistant 75.3s api 
→ read_file({"path": "/workdir/data/sensor_test.csv", "limit": 5})
turn 28 · tool · read_file 
{"content": "     1|duration,src_bytes,dst_bytes,label\n     2|0.7715921102270875,678.8628473430318,317.62323797493787,0\n     3|1.3559782857324367,543.650985051199,317.5833105834754,0\n     4|0.04569901093577326,509.64974680720087,351.00924658527094,0\n     5|1.3205579031715804,313.6507296635509,511.9972396817492,0\n     6|", "total_lines": 301, "file_size": 17323, "truncated": true, "hint": "Use offset=6 to continue reading (showing 1-5 of 301 lines)", "is_binary": false, "is_image": false}
turn 28 · assistant 19.0s api 
→ read_file({"path": "/workdir/data/network_train.csv", "limit": 5})
turn 29 · tool · read_file 
{"content": "     1|duration,src_bytes,dst_bytes\n     2|0.15487364784339708,399.214118273482,279.62301309882633\n     3|2.4149948711451112,682.9472261810536,388.0051054981321\n     4|0.24535797593034656,252.27121160102337,402.1816194360473\n     5|0.045280645433363,507.239694486038,271.6502699133702\n     6|", "total_lines": 151, "file_size": 8381, "truncated": true, "hint": "Use offset=6 to continue reading (showing 1-5 of 151 lines)", "is_binary": false, "is_image": false}
turn 29 · assistant 15.2s api 
→ read_file({"path": "/workdir/data/network_test.csv", "limit": 5})
turn 30 · tool · read_file 
{"content": "     1|query_id,doc_id,year,relevance\n     2|q1,m1,2017,8\n     3|q1,m2,2016,7\n     4|q1,m3,2015,6\n     5|q1,m4,2014,5\n     6|", "total_lines": 25, "file_size": 343, "truncated": true, "hint": "Use offset=6 to continue reading (showing 1-5 of 25 lines)", "is_binary": false, "is_image": false}
turn 30 · assistant 14.6s api 
→ read_file({"path": "/workdir/data/movie_train.csv", "limit": 5})
turn 31 · tool · read_file 
{"content": "     1|query_id,doc_id,year\n     2|q1,m1,2017\n     3|q1,m2,2016\n     4|q1,m3,2015\n     5|q1,m4,2014\n     6|", "total_lines": 25, "file_size": 285, "truncated": true, "hint": "Use offset=6 to continue reading (showing 1-5 of 25 lines)", "is_binary": false, "is_image": false}
turn 31 · assistant 14.9s api 
→ read_file({"path": "/workdir/data/movie_test.csv", "limit": 5})
turn 32 · tool · read_file 
{"content": "     1|query_id,doc_id,length,relevance\n     2|nq1,nq1_a,100,5\n     3|nq1,nq1_b,90,4\n     4|nq1,nq1_c,80,3\n     5|nq1,nq1_d,70,2\n     6|", "total_lines": 16, "file_size": 261, "truncated": true, "hint": "Use offset=6 to continue reading (showing 1-5 of 16 lines)", "is_binary": false, "is_image": false}
turn 32 · assistant 14.7s api 
→ read_file({"path": "/workdir/data/news_train.csv", "limit": 5})
turn 33 · tool · read_file 
{"content": "     1|query_id,doc_id,length\n     2|nq1,nq1_a,100\n     3|nq1,nq1_b,90\n     4|nq1,nq1_c,80\n     5|nq1,nq1_d,70\n     6|", "total_lines": 16, "file_size": 221, "truncated": true, "hint": "Use offset=6 to continue reading (showing 1-5 of 16 lines)", "is_binary": false, "is_image": false}
turn 33 · assistant 14.6s api 
→ read_file({"path": "/workdir/data/news_test.csv", "limit": 5})
turn 34 · tool · read_file 
{"content": "     1|query_id,doc_id,score,relevance,extra_empty\n     2|bq1,bq1_m1,10,5,0\n     3|bq1,bq1_m2,9,4,0\n     4|bq1,bq1_n1,8,3,0\n     5|bq1,bq1_n2,7,2,0\n     6|", "total_lines": 12, "file_size": 250, "truncated": true, "hint": "Use offset=6 to continue reading (showing 1-5 of 12 lines)", "is_binary": false, "is_image": false}
turn 34 · assistant 15.5s api 
→ read_file({"path": "/workdir/data/both_train.csv", "limit": 5})
turn 35 · tool · read_file 
{"content": "     1|query_id,doc_id,score,extra_empty\n     2|bq1,bq1_m1,10,0\n     3|bq1,bq1_m2,9,0\n     4|bq1,bq1_n1,8,0\n     5|bq1,bq1_n2,7,0\n     6|", "total_lines": 12, "file_size": 216, "truncated": true, "hint": "Use offset=6 to continue reading (showing 1-5 of 12 lines)", "is_binary": false, "is_image": false}
turn 35 · assistant 15.4s api 
→ read_file({"path": "/workdir/data/both_test.csv", "limit": 5})
turn 36 · tool · terminal 
{"output": "", "exit_code": -1, "error": "Foreground command uses '&' backgrounding. Use terminal(background=true) for long-lived processes, then run health checks and tests in follow-up terminal calls.", "status": "error"}
turn 36 · assistant 532.0s api 
→ terminal({"command": "cd /workdir && python3 -c \"\nimport pandas as pd\nimport numpy as np\n\n# Sensor anomaly detection\nsensor_train = pd.read_csv('data/sensor_train.csv')\nsensor_test = pd.read_csv('data/sensor_test.csv')\n\n# Calculate z-scores for sensor values\nmean = sensor_train['value'].mean()\nstd = sensor_train['value'].std()\nsensor_train['z_score'] = (sensor_train['value'] - mean) / std\n\n# …)
turn 37 · tool · terminal 
{"output": "", "exit_code": -1, "error": "Foreground command uses '&' backgrounding. Use terminal(background=true) for long-lived processes, then run health checks and tests in follow-up terminal calls.", "status": "error"}
turn 37 · assistant 506.7s api 
→ terminal({"command": "cd /workdir && python3 -c \"\nimport pandas as pd\nimport numpy as np\n\n# Sensor anomaly detection\nsensor_train = pd.read_csv('data/sensor_train.csv')\nsensor_test = pd.read_csv('data/sensor_test.csv')\n\n# Calculate z-scores for sensor values\nmean = sensor_train['value'].mean()\nstd = sensor_train['value'].std()\nsensor_train['z_score'] = (sensor_train['value'] - mean) / std\n\n# …)
turn 38 · tool · terminal 
{"output": "", "exit_code": -1, "error": "Foreground command uses '&' backgrounding. Use terminal(background=true) for long-lived processes, then run health checks and tests in follow-up terminal calls.", "status": "error"}
turn 38 · assistant 519.8s api 
→ terminal({"command": "cd /workdir && python3 -c \"\nimport pandas as pd\nimport numpy as np\n\n# Sensor anomaly detection\nsensor_train = pd.read_csv('data/sensor_train.csv')\nsensor_test = pd.read_csv('data/sensor_test.csv')\n\n# Calculate z-scores for sensor values\nmean = sensor_train['value'].mean()\nstd = sensor_train['value'].std()\nsensor_train['z_score'] = (sensor_train['value'] - mean) / std\n\n# …)