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The dataset generation failed because of a cast error

Error code:   DatasetGenerationCastError
Exception:    DatasetGenerationCastError
Message:      An error occurred while generating the dataset

All the data files must have the same columns, but at some point there are 7 new columns ({'examples', 'seed_terms', 'domain', 'application_instruction', 'domain_expert_prompt', 'perspectives', 'topics'}) and 10 missing columns ({'self_intruct_num_generations', 'argilla_dataset_name', 'domain_expert_temperature', 'self_instruct_base_url', 'argilla_api_url', 'self_instruct_temperature', 'domain_expert_num_generations', 'self_instruct_max_new_tokens', 'domain_expert_base_url', 'domain_expert_max_new_tokens'}).

This happened while the json dataset builder was generating data using

hf://datasets/CLeach22/green_farming/seed_data.json (at revision ac021c9bf31cd18ba42b6c2469bccfe0c0a0e4ba)

Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 2011, in _prepare_split_single
                  writer.write_table(table)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 585, in write_table
                  pa_table = table_cast(pa_table, self._schema)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2302, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2256, in cast_table_to_schema
                  raise CastError(
              datasets.table.CastError: Couldn't cast
              domain: string
              perspectives: list<item: string>
                child 0, item: string
              topics: list<item: string>
                child 0, item: string
              examples: list<item: struct<question: string, answer: string>>
                child 0, item: struct<question: string, answer: string>
                    child 0, question: string
                    child 1, answer: string
              domain_expert_prompt: string
              application_instruction: string
              seed_terms: list<item: string>
                child 0, item: string
              to
              {'argilla_api_url': Value(dtype='string', id=None), 'argilla_dataset_name': Value(dtype='string', id=None), 'self_instruct_base_url': Value(dtype='string', id=None), 'domain_expert_base_url': Value(dtype='string', id=None), 'self_instruct_temperature': Value(dtype='float64', id=None), 'domain_expert_temperature': Value(dtype='float64', id=None), 'self_intruct_num_generations': Value(dtype='int64', id=None), 'domain_expert_num_generations': Value(dtype='int64', id=None), 'self_instruct_max_new_tokens': Value(dtype='int64', id=None), 'domain_expert_max_new_tokens': Value(dtype='int64', id=None)}
              because column names don't match
              
              During handling of the above exception, another exception occurred:
              
              Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1321, 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 935, in convert_to_parquet
                  builder.download_and_prepare(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1027, in download_and_prepare
                  self._download_and_prepare(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1122, in _download_and_prepare
                  self._prepare_split(split_generator, **prepare_split_kwargs)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1882, in _prepare_split
                  for job_id, done, content in self._prepare_split_single(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 2013, in _prepare_split_single
                  raise DatasetGenerationCastError.from_cast_error(
              datasets.exceptions.DatasetGenerationCastError: An error occurred while generating the dataset
              
              All the data files must have the same columns, but at some point there are 7 new columns ({'examples', 'seed_terms', 'domain', 'application_instruction', 'domain_expert_prompt', 'perspectives', 'topics'}) and 10 missing columns ({'self_intruct_num_generations', 'argilla_dataset_name', 'domain_expert_temperature', 'self_instruct_base_url', 'argilla_api_url', 'self_instruct_temperature', 'domain_expert_num_generations', 'self_instruct_max_new_tokens', 'domain_expert_base_url', 'domain_expert_max_new_tokens'}).
              
              This happened while the json dataset builder was generating data using
              
              hf://datasets/CLeach22/green_farming/seed_data.json (at revision ac021c9bf31cd18ba42b6c2469bccfe0c0a0e4ba)
              
              Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)

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argilla_api_url string	argilla_dataset_name string	self_instruct_base_url string	domain_expert_base_url string	self_instruct_temperature float64	domain_expert_temperature float64	self_intruct_num_generations int64	domain_expert_num_generations int64	self_instruct_max_new_tokens int64	domain_expert_max_new_tokens int64	domain string	perspectives sequence	topics sequence	examples list	domain_expert_prompt string	application_instruction string	seed_terms sequence
https://CLeach22-green-farming-argilla-space.hf.space	green_farming	https://api-inference.huggingface.co/models/microsoft/Phi-3-mini-4k-instruct	https://api-inference.huggingface.co/models/microsoft/Phi-3-mini-4k-instruct	0.9	0.9	2	2	2,096	2,096	null	null	null	null	null	null	null
null	null	null	null	null	null	null	null	null	null	green_farming	[ "Family Farming", "Industrial Farming" ]	[ "animal welfare", "soil quality" ]	[ { "question": "How do I measure soil quality?", "answer": "\n\nSoil quality is a complex concept that can be influenced by many factors, including physical, chemical, and biological properties. There are several methods to assess soil quality, and the choice of method depends on the specific goals and resources available. " } ]	You will be asked about family farming and agribusiness related topics, from different perspectives. Your answer should be logical and supported by facts, don't fabricate arguments. Try to gather a diverse point of view taking into account current theories in agronomy, biology, economics, anthropology and ecology.	AI assistant in the domain of green_farming. You will be asked about family farming and agribusiness related topics, from different perspectives. Your answer should be logical and supported by facts, don't fabricate arguments. Try to gather a diverse point of view taking into account current theories in agronomy, biology, economics, anthropology and ecology.Below are some examples of questions and answers that the AI assistant would generate: Examples: - Question: How do I measure soil quality? - Answer: Soil quality is a complex concept that can be influenced by many factors, including physical, chemical, and biological properties. There are several methods to assess soil quality, and the choice of method depends on the specific goals and resources available. - Question: How do I measure soil quality? - Answer: Soil quality is a complex concept that can be influenced by many factors, including physical, chemical, and biological properties. There are several methods to assess soil quality, and the choice of method depends on the specific goals and resources available.	[ "animal welfare from a Family Farming perspective", "animal welfare from a Industrial Farming perspective", "soil quality from a Family Farming perspective", "soil quality from a Industrial Farming perspective" ]

YAML Metadata Warning: empty or missing yaml metadata in repo card (https://huggingface.co/docs/hub/datasets-cards)

Domain Dataset Grower

This dataset was generated by distilabel as a domain specific dataset for the domain of farming. The dataset used this seed data to generate the samples. The seed data was define by a domain expert and the generated data can be reviewed in this Argilla space here: Argilla

If you want to define a domain specific seed dataset for your own domain, you can use the distilabel tool to generate the dataset, and seed your dataset here

green_farming

Domain: green_farming

Perspectives

Family Farming
Industrial Farming

Topics

animal welfare
soil quality

Examples

How do I measure soil quality?

Soil quality is a complex concept that can be influenced by many factors, including physical, chemical, and biological properties. There are several methods to assess soil quality, and the choice of method depends on the specific goals and resources available.

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