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The dataset generation failed
Error code:   DatasetGenerationError
Exception:    ArrowNotImplementedError
Message:      Cannot write struct type 'arguments' with no child field to Parquet. Consider adding a dummy child field.
Traceback:    Traceback (most recent call last):
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1831, in _prepare_split_single
                  writer.write_table(table)
                File "/usr/local/lib/python3.12/site-packages/datasets/arrow_writer.py", line 712, in write_table
                  self._build_writer(inferred_schema=pa_table.schema)
                File "/usr/local/lib/python3.12/site-packages/datasets/arrow_writer.py", line 757, in _build_writer
                  self.pa_writer = pq.ParquetWriter(
                                   ^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/pyarrow/parquet/core.py", line 1070, in __init__
                  self.writer = _parquet.ParquetWriter(
                                ^^^^^^^^^^^^^^^^^^^^^^^
                File "pyarrow/_parquet.pyx", line 2363, in pyarrow._parquet.ParquetWriter.__cinit__
                File "pyarrow/error.pxi", line 155, in pyarrow.lib.pyarrow_internal_check_status
                File "pyarrow/error.pxi", line 92, in pyarrow.lib.check_status
              pyarrow.lib.ArrowNotImplementedError: Cannot write struct type 'arguments' with no child field to Parquet. Consider adding a dummy child field.
              
              During handling of the above exception, another exception occurred:
              
              Traceback (most recent call last):
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1847, in _prepare_split_single
                  num_examples, num_bytes = writer.finalize()
                                            ^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/arrow_writer.py", line 731, in finalize
                  self._build_writer(self.schema)
                File "/usr/local/lib/python3.12/site-packages/datasets/arrow_writer.py", line 757, in _build_writer
                  self.pa_writer = pq.ParquetWriter(
                                   ^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/pyarrow/parquet/core.py", line 1070, in __init__
                  self.writer = _parquet.ParquetWriter(
                                ^^^^^^^^^^^^^^^^^^^^^^^
                File "pyarrow/_parquet.pyx", line 2363, in pyarrow._parquet.ParquetWriter.__cinit__
                File "pyarrow/error.pxi", line 155, in pyarrow.lib.pyarrow_internal_check_status
                File "pyarrow/error.pxi", line 92, in pyarrow.lib.check_status
              pyarrow.lib.ArrowNotImplementedError: Cannot write struct type 'arguments' with no child field to Parquet. Consider adding a dummy child field.
              
              The above exception was the direct cause of the following exception:
              
              Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1339, in compute_config_parquet_and_info_response
                  parquet_operations = convert_to_parquet(builder)
                                       ^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 972, in convert_to_parquet
                  builder.download_and_prepare(
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 894, in download_and_prepare
                  self._download_and_prepare(
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 970, in _download_and_prepare
                  self._prepare_split(split_generator, **prepare_split_kwargs)
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1702, in _prepare_split
                  for job_id, done, content in self._prepare_split_single(
                                               ^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1858, in _prepare_split_single
                  raise DatasetGenerationError("An error occurred while generating the dataset") from e
              datasets.exceptions.DatasetGenerationError: An error occurred while generating the dataset

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string
description
string
prompt
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mcp_config
dict
setup_tool
dict
evaluate_tool
dict
agent_config
dict
system_prompt
string
inspect_evals/bfcl - Sample 0
Task from inspect_evals/bfcl dataset, sample 0
I've been playing a game where rolling a six is somehow more likely than usual, and the chance of it happening on a single roll is 60%. I'm curious, if I roll the die 20 times, what are the odds that I'll get exactly five sixes?
{ "inspect": { "args": [ "run", "--rm", "-i", "--init", "-v", "/var/run/docker.sock:/var/run/docker.sock", "-v", "/home/genteki/.cache/inspect_evals:/root/.cache/inspect_evals", "hud-inspect:latest" ], "command": "docker" } }
{ "arguments": { "model": "claude-sonnet-4-20250514", "sample_id": "0", "task_name": "inspect_evals/bfcl" }, "name": "load_task" }
{ "arguments": {}, "name": "score_task" }
{ "agent_class": "server.agents.InspectAgent", "allowed_tools": [], "disallowed_tools": [ "_store_agent_message", "load_task", "score_task" ], "initial_screenshot": false }
You are a helpful AI assistant. Follow the instructions in the user messages carefully.
inspect_evals/bfcl - Sample 1
Task from inspect_evals/bfcl dataset, sample 1
During last night's basketball game, one of the star players was on fire, attempting a whopping 30 free throws. It's generally known that the average success rate for free throws hovers around 50%. I'm curious, with that success probability, what are the chances that the player made exactly 15 out of those 30 attempts?
{ "inspect": { "args": [ "run", "--rm", "-i", "--init", "-v", "/var/run/docker.sock:/var/run/docker.sock", "-v", "/home/genteki/.cache/inspect_evals:/root/.cache/inspect_evals", "hud-inspect:latest" ], "command": "docker" } }
{ "arguments": { "model": "claude-sonnet-4-20250514", "sample_id": "1", "task_name": "inspect_evals/bfcl" }, "name": "load_task" }
{ "arguments": {}, "name": "score_task" }
{ "agent_class": "server.agents.InspectAgent", "allowed_tools": [], "disallowed_tools": [ "_store_agent_message", "load_task", "score_task" ], "initial_screenshot": false }
You are a helpful AI assistant. Follow the instructions in the user messages carefully.
inspect_evals/bfcl - Sample 2
Task from inspect_evals/bfcl dataset, sample 2
I'm currently tweaking a machine learning model and I need to understand the similarity between two objects in my dataset. Their characteristics are expressed in the feature vectors [0.5, 0.7, 0.2, 0.9, 0.1] for the first object and [0.4, 0.6, 0.3, 0.8, 0.2] for the second one. Could you calculate the cosine similarity...
{ "inspect": { "args": [ "run", "--rm", "-i", "--init", "-v", "/var/run/docker.sock:/var/run/docker.sock", "-v", "/home/genteki/.cache/inspect_evals:/root/.cache/inspect_evals", "hud-inspect:latest" ], "command": "docker" } }
{ "arguments": { "model": "claude-sonnet-4-20250514", "sample_id": "2", "task_name": "inspect_evals/bfcl" }, "name": "load_task" }
{ "arguments": {}, "name": "score_task" }
{ "agent_class": "server.agents.InspectAgent", "allowed_tools": [], "disallowed_tools": [ "_store_agent_message", "load_task", "score_task" ], "initial_screenshot": false }
You are a helpful AI assistant. Follow the instructions in the user messages carefully.
inspect_evals/bfcl - Sample 3
Task from inspect_evals/bfcl dataset, sample 3
I'm working on a project that involves comparing the attributes of different entities to determine how similar they are. I have two entities represented by numerical arrays, and I need to use cosine similarity as a measure of similarity between them. The attributes for the first entity are [0.3, 0.8, 0.1, 0.6, 0.2], an...
{ "inspect": { "args": [ "run", "--rm", "-i", "--init", "-v", "/var/run/docker.sock:/var/run/docker.sock", "-v", "/home/genteki/.cache/inspect_evals:/root/.cache/inspect_evals", "hud-inspect:latest" ], "command": "docker" } }
{ "arguments": { "model": "claude-sonnet-4-20250514", "sample_id": "3", "task_name": "inspect_evals/bfcl" }, "name": "load_task" }
{ "arguments": {}, "name": "score_task" }
{ "agent_class": "server.agents.InspectAgent", "allowed_tools": [], "disallowed_tools": [ "_store_agent_message", "load_task", "score_task" ], "initial_screenshot": false }
You are a helpful AI assistant. Follow the instructions in the user messages carefully.
inspect_evals/bfcl - Sample 4
Task from inspect_evals/bfcl dataset, sample 4
I'm working on a physics experiment and need to calculate the density of an object I have. It weighs 50 kilograms and takes up a space of 10 cubic meters. Could you help me figure out its density?
{ "inspect": { "args": [ "run", "--rm", "-i", "--init", "-v", "/var/run/docker.sock:/var/run/docker.sock", "-v", "/home/genteki/.cache/inspect_evals:/root/.cache/inspect_evals", "hud-inspect:latest" ], "command": "docker" } }
{ "arguments": { "model": "claude-sonnet-4-20250514", "sample_id": "4", "task_name": "inspect_evals/bfcl" }, "name": "load_task" }
{ "arguments": {}, "name": "score_task" }
{ "agent_class": "server.agents.InspectAgent", "allowed_tools": [], "disallowed_tools": [ "_store_agent_message", "load_task", "score_task" ], "initial_screenshot": false }
You are a helpful AI assistant. Follow the instructions in the user messages carefully.
inspect_evals/bfcl - Sample 5
Task from inspect_evals/bfcl dataset, sample 5
I've got this strange object we've come across in our scientific research. It's pretty hefty, weighing in at 120 kilograms, and it takes up about 30 cubic meters of space. Can you help me calculate its density?
{ "inspect": { "args": [ "run", "--rm", "-i", "--init", "-v", "/var/run/docker.sock:/var/run/docker.sock", "-v", "/home/genteki/.cache/inspect_evals:/root/.cache/inspect_evals", "hud-inspect:latest" ], "command": "docker" } }
{ "arguments": { "model": "claude-sonnet-4-20250514", "sample_id": "5", "task_name": "inspect_evals/bfcl" }, "name": "load_task" }
{ "arguments": {}, "name": "score_task" }
{ "agent_class": "server.agents.InspectAgent", "allowed_tools": [], "disallowed_tools": [ "_store_agent_message", "load_task", "score_task" ], "initial_screenshot": false }
You are a helpful AI assistant. Follow the instructions in the user messages carefully.
inspect_evals/bfcl - Sample 6
Task from inspect_evals/bfcl dataset, sample 6
During our advanced physics experiment, we've been tracking this unique object which initially was moving at 15 m/s. It's been accelerating at a rate of 9.8 m/s², and this has been going on for exactly 10 seconds. I need to calculate the total displacement of the object over this period. Can you help me with that?
{ "inspect": { "args": [ "run", "--rm", "-i", "--init", "-v", "/var/run/docker.sock:/var/run/docker.sock", "-v", "/home/genteki/.cache/inspect_evals:/root/.cache/inspect_evals", "hud-inspect:latest" ], "command": "docker" } }
{ "arguments": { "model": "claude-sonnet-4-20250514", "sample_id": "6", "task_name": "inspect_evals/bfcl" }, "name": "load_task" }
{ "arguments": {}, "name": "score_task" }
{ "agent_class": "server.agents.InspectAgent", "allowed_tools": [], "disallowed_tools": [ "_store_agent_message", "load_task", "score_task" ], "initial_screenshot": false }
You are a helpful AI assistant. Follow the instructions in the user messages carefully.
inspect_evals/bfcl - Sample 7
Task from inspect_evals/bfcl dataset, sample 7
During the high-speed chase, when the driver accelerated the vehicle, it was initially moving at 25 meters per second. With the sudden push on the gas pedal, the car accelerated at 15 meters per second squared, and this went on for 8 seconds. I need to calculate the displacement of the vehicle over that time. Can you p...
{ "inspect": { "args": [ "run", "--rm", "-i", "--init", "-v", "/var/run/docker.sock:/var/run/docker.sock", "-v", "/home/genteki/.cache/inspect_evals:/root/.cache/inspect_evals", "hud-inspect:latest" ], "command": "docker" } }
{ "arguments": { "model": "claude-sonnet-4-20250514", "sample_id": "7", "task_name": "inspect_evals/bfcl" }, "name": "load_task" }
{ "arguments": {}, "name": "score_task" }
{ "agent_class": "server.agents.InspectAgent", "allowed_tools": [], "disallowed_tools": [ "_store_agent_message", "load_task", "score_task" ], "initial_screenshot": false }
You are a helpful AI assistant. Follow the instructions in the user messages carefully.
inspect_evals/bfcl - Sample 8
Task from inspect_evals/bfcl dataset, sample 8
During our physics lab session, we're experimenting with electric fields and their effects on charged particles. We've placed a particle that carries a charge of 5 coulombs within a field where there's a voltage of 10 volts. I need to calculate the electrostatic potential energy for this scenario. Could you work that o...
{ "inspect": { "args": [ "run", "--rm", "-i", "--init", "-v", "/var/run/docker.sock:/var/run/docker.sock", "-v", "/home/genteki/.cache/inspect_evals:/root/.cache/inspect_evals", "hud-inspect:latest" ], "command": "docker" } }
{ "arguments": { "model": "claude-sonnet-4-20250514", "sample_id": "8", "task_name": "inspect_evals/bfcl" }, "name": "load_task" }
{ "arguments": {}, "name": "score_task" }
{ "agent_class": "server.agents.InspectAgent", "allowed_tools": [], "disallowed_tools": [ "_store_agent_message", "load_task", "score_task" ], "initial_screenshot": false }
You are a helpful AI assistant. Follow the instructions in the user messages carefully.
inspect_evals/bfcl - Sample 9
Task from inspect_evals/bfcl dataset, sample 9
I'm working on a physics simulation and I have a micro-particle here charged at 7.8 coulombs. It's placed in an electromagnetic field with a voltage of 15.2 volts. Can you calculate the electrostatic potential energy for this particle in the given field?
{ "inspect": { "args": [ "run", "--rm", "-i", "--init", "-v", "/var/run/docker.sock:/var/run/docker.sock", "-v", "/home/genteki/.cache/inspect_evals:/root/.cache/inspect_evals", "hud-inspect:latest" ], "command": "docker" } }
{ "arguments": { "model": "claude-sonnet-4-20250514", "sample_id": "9", "task_name": "inspect_evals/bfcl" }, "name": "load_task" }
{ "arguments": {}, "name": "score_task" }
{ "agent_class": "server.agents.InspectAgent", "allowed_tools": [], "disallowed_tools": [ "_store_agent_message", "load_task", "score_task" ], "initial_screenshot": false }
You are a helpful AI assistant. Follow the instructions in the user messages carefully.

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