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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 3 new columns ({'url', 'name', 'symbol'}) and 7 missing columns ({'embed_model', 'chunk_size_words', 'overlap_words', 'chunks', 'device', 'run_id', 'total_chunks'}).

This happened while the json dataset builder was generating data using

hf://datasets/eksakstri/nifty50-rag-data/nifty50_companies.json (at revision 57bdc207d45c1088426eae70e17dc36101844fd7), ['hf://datasets/eksakstri/nifty50-rag-data@57bdc207d45c1088426eae70e17dc36101844fd7/chunk_metadata.json', 'hf://datasets/eksakstri/nifty50-rag-data@57bdc207d45c1088426eae70e17dc36101844fd7/nifty50_companies.json', 'hf://datasets/eksakstri/nifty50-rag-data@57bdc207d45c1088426eae70e17dc36101844fd7/nifty50_market_summary.json', 'hf://datasets/eksakstri/nifty50-rag-data@57bdc207d45c1088426eae70e17dc36101844fd7/nifty50_snapshot.json'], ['hf://datasets/eksakstri/nifty50-rag-data@57bdc207d45c1088426eae70e17dc36101844fd7/chunk_metadata.json', 'hf://datasets/eksakstri/nifty50-rag-data@57bdc207d45c1088426eae70e17dc36101844fd7/nifty50_companies.json', 'hf://datasets/eksakstri/nifty50-rag-data@57bdc207d45c1088426eae70e17dc36101844fd7/nifty50_market_summary.json', 'hf://datasets/eksakstri/nifty50-rag-data@57bdc207d45c1088426eae70e17dc36101844fd7/nifty50_snapshot.json']

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 "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1837, in _prepare_split_single
                  writer.write_table(table)
                  ~~~~~~~~~~~~~~~~~~^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/arrow_writer.py", line 765, in write_table
                  self._write_table(pa_table, writer_batch_size=writer_batch_size)
                  ~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/arrow_writer.py", line 773, in _write_table
                  pa_table = table_cast(pa_table, self._schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2369, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2297, in cast_table_to_schema
                  raise CastError(
                  ...<3 lines>...
                  )
              datasets.table.CastError: Couldn't cast
              symbol: string
              name: string
              url: string
              to
              {'run_id': Value('string'), 'embed_model': Value('string'), 'device': Value('string'), 'chunk_size_words': Value('int64'), 'overlap_words': Value('int64'), 'total_chunks': Value('int64'), 'chunks': {'char_count': Value('int64'), 'chunk_index': Value('int64'), 'chunk_total': Value('int64'), 'company': Value('string'), 'faiss_id': Value('int64'), 'ingested_at': Value('string'), 'pdf_file': Value('string'), 'pdf_path': Value('string'), 'run_id': Value('string')}}
              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 1369, in compute_config_parquet_and_info_response
                  parquet_operations, partial, estimated_dataset_info = stream_convert_to_parquet(
                                                                        ~~~~~~~~~~~~~~~~~~~~~~~~~^
                      builder, max_dataset_size_bytes=max_dataset_size_bytes
                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                  )
                  ^
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 948, in stream_convert_to_parquet
                  builder._prepare_split(split_generator=splits_generators[split], file_format="parquet")
                  ~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1683, in _prepare_split
                  for job_id, done, content in self._prepare_split_single(
                                               ~~~~~~~~~~~~~~~~~~~~~~~~~~^
                      gen_kwargs=gen_kwargs, job_id=job_id, **_prepare_split_args
                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                  ):
                  ^
                File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1839, in _prepare_split_single
                  raise DatasetGenerationCastError.from_cast_error(
                  ...<4 lines>...
                  )
              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 3 new columns ({'url', 'name', 'symbol'}) and 7 missing columns ({'embed_model', 'chunk_size_words', 'overlap_words', 'chunks', 'device', 'run_id', 'total_chunks'}).
              
              This happened while the json dataset builder was generating data using
              
              hf://datasets/eksakstri/nifty50-rag-data/nifty50_companies.json (at revision 57bdc207d45c1088426eae70e17dc36101844fd7), ['hf://datasets/eksakstri/nifty50-rag-data@57bdc207d45c1088426eae70e17dc36101844fd7/chunk_metadata.json', 'hf://datasets/eksakstri/nifty50-rag-data@57bdc207d45c1088426eae70e17dc36101844fd7/nifty50_companies.json', 'hf://datasets/eksakstri/nifty50-rag-data@57bdc207d45c1088426eae70e17dc36101844fd7/nifty50_market_summary.json', 'hf://datasets/eksakstri/nifty50-rag-data@57bdc207d45c1088426eae70e17dc36101844fd7/nifty50_snapshot.json'], ['hf://datasets/eksakstri/nifty50-rag-data@57bdc207d45c1088426eae70e17dc36101844fd7/chunk_metadata.json', 'hf://datasets/eksakstri/nifty50-rag-data@57bdc207d45c1088426eae70e17dc36101844fd7/nifty50_companies.json', 'hf://datasets/eksakstri/nifty50-rag-data@57bdc207d45c1088426eae70e17dc36101844fd7/nifty50_market_summary.json', 'hf://datasets/eksakstri/nifty50-rag-data@57bdc207d45c1088426eae70e17dc36101844fd7/nifty50_snapshot.json']
              
              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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run_id
string
embed_model
string
device
string
chunk_size_words
int64
overlap_words
int64
total_chunks
int64
chunks
dict
e357d42b-c9ae-46c3-ac13-9ff6f47ef4cd
all-MiniLM-L6-v2
cpu
500
50
61,128
{ "char_count": 3331, "chunk_index": 0, "chunk_total": 2, "company": "ADANIENT", "faiss_id": 0, "ingested_at": "2026-07-06 17:39:41.943468+00:00", "pdf_file": "ADANIENT_01042026184830_AELSEintimation01042026.pdf", "pdf_path": "ADANIENT\\pdfs\\ADANIENT_01042026184830_AELSEintimation01042026.pdf", "run_...
e357d42b-c9ae-46c3-ac13-9ff6f47ef4cd
all-MiniLM-L6-v2
cpu
500
50
61,128
{ "char_count": 1172, "chunk_index": 1, "chunk_total": 2, "company": "ADANIENT", "faiss_id": 1, "ingested_at": "2026-07-06 17:39:41.943488+00:00", "pdf_file": "ADANIENT_01042026184830_AELSEintimation01042026.pdf", "pdf_path": "ADANIENT\\pdfs\\ADANIENT_01042026184830_AELSEintimation01042026.pdf", "run_...
e357d42b-c9ae-46c3-ac13-9ff6f47ef4cd
all-MiniLM-L6-v2
cpu
500
50
61,128
{ "char_count": 3331, "chunk_index": 0, "chunk_total": 2, "company": "ADANIENT", "faiss_id": 2, "ingested_at": "2026-07-06 17:39:42.091269+00:00", "pdf_file": "ADANIENT_01042026184830_AELSEintimation01042026.pdf", "pdf_path": "ADANIENT\\pdfs\\ADANIENT_01042026184830_AELSEintimation01042026.pdf", "run_...
e357d42b-c9ae-46c3-ac13-9ff6f47ef4cd
all-MiniLM-L6-v2
cpu
500
50
61,128
{ "char_count": 1172, "chunk_index": 1, "chunk_total": 2, "company": "ADANIENT", "faiss_id": 3, "ingested_at": "2026-07-06 17:39:42.091294+00:00", "pdf_file": "ADANIENT_01042026184830_AELSEintimation01042026.pdf", "pdf_path": "ADANIENT\\pdfs\\ADANIENT_01042026184830_AELSEintimation01042026.pdf", "run_...
e357d42b-c9ae-46c3-ac13-9ff6f47ef4cd
all-MiniLM-L6-v2
cpu
500
50
61,128
{ "char_count": 3331, "chunk_index": 0, "chunk_total": 2, "company": "ADANIENT", "faiss_id": 4, "ingested_at": "2026-07-06 17:39:42.239922+00:00", "pdf_file": "ADANIENT_01042026185131_AELSEintimation01042026.pdf", "pdf_path": "ADANIENT\\pdfs\\ADANIENT_01042026185131_AELSEintimation01042026.pdf", "run_...
e357d42b-c9ae-46c3-ac13-9ff6f47ef4cd
all-MiniLM-L6-v2
cpu
500
50
61,128
{ "char_count": 1172, "chunk_index": 1, "chunk_total": 2, "company": "ADANIENT", "faiss_id": 5, "ingested_at": "2026-07-06 17:39:42.239942+00:00", "pdf_file": "ADANIENT_01042026185131_AELSEintimation01042026.pdf", "pdf_path": "ADANIENT\\pdfs\\ADANIENT_01042026185131_AELSEintimation01042026.pdf", "run_...
e357d42b-c9ae-46c3-ac13-9ff6f47ef4cd
all-MiniLM-L6-v2
cpu
500
50
61,128
{ "char_count": 3331, "chunk_index": 0, "chunk_total": 2, "company": "ADANIENT", "faiss_id": 6, "ingested_at": "2026-07-06 17:39:42.384591+00:00", "pdf_file": "ADANIENT_01042026185131_AELSEintimation01042026.pdf", "pdf_path": "ADANIENT\\pdfs\\ADANIENT_01042026185131_AELSEintimation01042026.pdf", "run_...
e357d42b-c9ae-46c3-ac13-9ff6f47ef4cd
all-MiniLM-L6-v2
cpu
500
50
61,128
{ "char_count": 1172, "chunk_index": 1, "chunk_total": 2, "company": "ADANIENT", "faiss_id": 7, "ingested_at": "2026-07-06 17:39:42.384610+00:00", "pdf_file": "ADANIENT_01042026185131_AELSEintimation01042026.pdf", "pdf_path": "ADANIENT\\pdfs\\ADANIENT_01042026185131_AELSEintimation01042026.pdf", "run_...
e357d42b-c9ae-46c3-ac13-9ff6f47ef4cd
all-MiniLM-L6-v2
cpu
500
50
61,128
{ "char_count": 3331, "chunk_index": 0, "chunk_total": 2, "company": "ADANIENT", "faiss_id": 8, "ingested_at": "2026-07-06 17:39:42.754905+00:00", "pdf_file": "ADANIENT_01042026185459_AELSEintimation01042026.pdf", "pdf_path": "ADANIENT\\pdfs\\ADANIENT_01042026185459_AELSEintimation01042026.pdf", "run_...
e357d42b-c9ae-46c3-ac13-9ff6f47ef4cd
all-MiniLM-L6-v2
cpu
500
50
61,128
{ "char_count": 1172, "chunk_index": 1, "chunk_total": 2, "company": "ADANIENT", "faiss_id": 9, "ingested_at": "2026-07-06 17:39:42.754942+00:00", "pdf_file": "ADANIENT_01042026185459_AELSEintimation01042026.pdf", "pdf_path": "ADANIENT\\pdfs\\ADANIENT_01042026185459_AELSEintimation01042026.pdf", "run_...
e357d42b-c9ae-46c3-ac13-9ff6f47ef4cd
all-MiniLM-L6-v2
cpu
500
50
61,128
{ "char_count": 3331, "chunk_index": 0, "chunk_total": 2, "company": "ADANIENT", "faiss_id": 10, "ingested_at": "2026-07-06 17:39:42.899646+00:00", "pdf_file": "ADANIENT_01042026185459_AELSEintimation01042026.pdf", "pdf_path": "ADANIENT\\pdfs\\ADANIENT_01042026185459_AELSEintimation01042026.pdf", "run...
e357d42b-c9ae-46c3-ac13-9ff6f47ef4cd
all-MiniLM-L6-v2
cpu
500
50
61,128
{ "char_count": 1172, "chunk_index": 1, "chunk_total": 2, "company": "ADANIENT", "faiss_id": 11, "ingested_at": "2026-07-06 17:39:42.899665+00:00", "pdf_file": "ADANIENT_01042026185459_AELSEintimation01042026.pdf", "pdf_path": "ADANIENT\\pdfs\\ADANIENT_01042026185459_AELSEintimation01042026.pdf", "run...
e357d42b-c9ae-46c3-ac13-9ff6f47ef4cd
all-MiniLM-L6-v2
cpu
500
50
61,128
{ "char_count": 1366, "chunk_index": 0, "chunk_total": 1, "company": "ADANIENT", "faiss_id": 12, "ingested_at": "2026-07-06 17:39:42.982368+00:00", "pdf_file": "ADANIENT_05062026201643_AELIntimation05062026.pdf", "pdf_path": "ADANIENT\\pdfs\\ADANIENT_05062026201643_AELIntimation05062026.pdf", "run_id"...
e357d42b-c9ae-46c3-ac13-9ff6f47ef4cd
all-MiniLM-L6-v2
cpu
500
50
61,128
{ "char_count": 1366, "chunk_index": 0, "chunk_total": 1, "company": "ADANIENT", "faiss_id": 13, "ingested_at": "2026-07-06 17:39:43.057227+00:00", "pdf_file": "ADANIENT_05062026201643_AELIntimation05062026.pdf", "pdf_path": "ADANIENT\\pdfs\\ADANIENT_05062026201643_AELIntimation05062026.pdf", "run_id"...
e357d42b-c9ae-46c3-ac13-9ff6f47ef4cd
all-MiniLM-L6-v2
cpu
500
50
61,128
{ "char_count": 2997, "chunk_index": 0, "chunk_total": 1, "company": "ADANIENT", "faiss_id": 14, "ingested_at": "2026-07-06 17:39:43.204824+00:00", "pdf_file": "ADANIENT_06042026224408_Intimationconversion_PPtoFP_NonASBA.pdf", "pdf_path": "ADANIENT\\pdfs\\ADANIENT_06042026224408_Intimationconversion_PPt...
e357d42b-c9ae-46c3-ac13-9ff6f47ef4cd
all-MiniLM-L6-v2
cpu
500
50
61,128
{ "char_count": 2997, "chunk_index": 0, "chunk_total": 1, "company": "ADANIENT", "faiss_id": 15, "ingested_at": "2026-07-06 17:39:43.353899+00:00", "pdf_file": "ADANIENT_06042026224408_Intimationconversion_PPtoFP_NonASBA.pdf", "pdf_path": "ADANIENT\\pdfs\\ADANIENT_06042026224408_Intimationconversion_PPt...
e357d42b-c9ae-46c3-ac13-9ff6f47ef4cd
all-MiniLM-L6-v2
cpu
500
50
61,128
{ "char_count": 3213, "chunk_index": 0, "chunk_total": 2, "company": "ADANIENT", "faiss_id": 16, "ingested_at": "2026-07-06 17:39:43.587155+00:00", "pdf_file": "ADANIENT_08062026184256_AAHLAcquisitionAgreement.pdf", "pdf_path": "ADANIENT\\pdfs\\ADANIENT_08062026184256_AAHLAcquisitionAgreement.pdf", "r...
e357d42b-c9ae-46c3-ac13-9ff6f47ef4cd
all-MiniLM-L6-v2
cpu
500
50
61,128
{ "char_count": 2137, "chunk_index": 1, "chunk_total": 2, "company": "ADANIENT", "faiss_id": 17, "ingested_at": "2026-07-06 17:39:43.587197+00:00", "pdf_file": "ADANIENT_08062026184256_AAHLAcquisitionAgreement.pdf", "pdf_path": "ADANIENT\\pdfs\\ADANIENT_08062026184256_AAHLAcquisitionAgreement.pdf", "r...
e357d42b-c9ae-46c3-ac13-9ff6f47ef4cd
all-MiniLM-L6-v2
cpu
500
50
61,128
{ "char_count": 3213, "chunk_index": 0, "chunk_total": 2, "company": "ADANIENT", "faiss_id": 18, "ingested_at": "2026-07-06 17:39:43.822426+00:00", "pdf_file": "ADANIENT_08062026184256_AAHLAcquisitionAgreement.pdf", "pdf_path": "ADANIENT\\pdfs\\ADANIENT_08062026184256_AAHLAcquisitionAgreement.pdf", "r...
e357d42b-c9ae-46c3-ac13-9ff6f47ef4cd
all-MiniLM-L6-v2
cpu
500
50
61,128
{ "char_count": 2137, "chunk_index": 1, "chunk_total": 2, "company": "ADANIENT", "faiss_id": 19, "ingested_at": "2026-07-06 17:39:43.822445+00:00", "pdf_file": "ADANIENT_08062026184256_AAHLAcquisitionAgreement.pdf", "pdf_path": "ADANIENT\\pdfs\\ADANIENT_08062026184256_AAHLAcquisitionAgreement.pdf", "r...
e357d42b-c9ae-46c3-ac13-9ff6f47ef4cd
all-MiniLM-L6-v2
cpu
500
50
61,128
{ "char_count": 2064, "chunk_index": 0, "chunk_total": 1, "company": "ADANIENT", "faiss_id": 20, "ingested_at": "2026-07-06 17:39:43.925110+00:00", "pdf_file": "ADANIENT_10062026195747_AEL_Intimationofacquisitioncompletion.pdf", "pdf_path": "ADANIENT\\pdfs\\ADANIENT_10062026195747_AEL_Intimationofacquis...
e357d42b-c9ae-46c3-ac13-9ff6f47ef4cd
all-MiniLM-L6-v2
cpu
500
50
61,128
{ "char_count": 2064, "chunk_index": 0, "chunk_total": 1, "company": "ADANIENT", "faiss_id": 21, "ingested_at": "2026-07-06 17:39:44.023827+00:00", "pdf_file": "ADANIENT_10062026195747_AEL_Intimationofacquisitioncompletion.pdf", "pdf_path": "ADANIENT\\pdfs\\ADANIENT_10062026195747_AEL_Intimationofacquis...
e357d42b-c9ae-46c3-ac13-9ff6f47ef4cd
all-MiniLM-L6-v2
cpu
500
50
61,128
{ "char_count": 3276, "chunk_index": 0, "chunk_total": 15, "company": "ADANIENT", "faiss_id": 22, "ingested_at": "2026-07-06 17:39:47.574999+00:00", "pdf_file": "ADANIENT_13052026185124_outcomeofRIcommittee13052026.pdf", "pdf_path": "ADANIENT\\pdfs\\ADANIENT_13052026185124_outcomeofRIcommittee13052026.p...
e357d42b-c9ae-46c3-ac13-9ff6f47ef4cd
all-MiniLM-L6-v2
cpu
500
50
61,128
{ "char_count": 2986, "chunk_index": 1, "chunk_total": 15, "company": "ADANIENT", "faiss_id": 23, "ingested_at": "2026-07-06 17:39:47.575038+00:00", "pdf_file": "ADANIENT_13052026185124_outcomeofRIcommittee13052026.pdf", "pdf_path": "ADANIENT\\pdfs\\ADANIENT_13052026185124_outcomeofRIcommittee13052026.p...
e357d42b-c9ae-46c3-ac13-9ff6f47ef4cd
all-MiniLM-L6-v2
cpu
500
50
61,128
{ "char_count": 2942, "chunk_index": 2, "chunk_total": 15, "company": "ADANIENT", "faiss_id": 24, "ingested_at": "2026-07-06 17:39:47.575064+00:00", "pdf_file": "ADANIENT_13052026185124_outcomeofRIcommittee13052026.pdf", "pdf_path": "ADANIENT\\pdfs\\ADANIENT_13052026185124_outcomeofRIcommittee13052026.p...
e357d42b-c9ae-46c3-ac13-9ff6f47ef4cd
all-MiniLM-L6-v2
cpu
500
50
61,128
{ "char_count": 3053, "chunk_index": 3, "chunk_total": 15, "company": "ADANIENT", "faiss_id": 25, "ingested_at": "2026-07-06 17:39:47.575088+00:00", "pdf_file": "ADANIENT_13052026185124_outcomeofRIcommittee13052026.pdf", "pdf_path": "ADANIENT\\pdfs\\ADANIENT_13052026185124_outcomeofRIcommittee13052026.p...
e357d42b-c9ae-46c3-ac13-9ff6f47ef4cd
all-MiniLM-L6-v2
cpu
500
50
61,128
{ "char_count": 3343, "chunk_index": 4, "chunk_total": 15, "company": "ADANIENT", "faiss_id": 26, "ingested_at": "2026-07-06 17:39:47.575112+00:00", "pdf_file": "ADANIENT_13052026185124_outcomeofRIcommittee13052026.pdf", "pdf_path": "ADANIENT\\pdfs\\ADANIENT_13052026185124_outcomeofRIcommittee13052026.p...
e357d42b-c9ae-46c3-ac13-9ff6f47ef4cd
all-MiniLM-L6-v2
cpu
500
50
61,128
{ "char_count": 3129, "chunk_index": 5, "chunk_total": 15, "company": "ADANIENT", "faiss_id": 27, "ingested_at": "2026-07-06 17:39:47.575140+00:00", "pdf_file": "ADANIENT_13052026185124_outcomeofRIcommittee13052026.pdf", "pdf_path": "ADANIENT\\pdfs\\ADANIENT_13052026185124_outcomeofRIcommittee13052026.p...
e357d42b-c9ae-46c3-ac13-9ff6f47ef4cd
all-MiniLM-L6-v2
cpu
500
50
61,128
{ "char_count": 3212, "chunk_index": 6, "chunk_total": 15, "company": "ADANIENT", "faiss_id": 28, "ingested_at": "2026-07-06 17:39:47.575164+00:00", "pdf_file": "ADANIENT_13052026185124_outcomeofRIcommittee13052026.pdf", "pdf_path": "ADANIENT\\pdfs\\ADANIENT_13052026185124_outcomeofRIcommittee13052026.p...
e357d42b-c9ae-46c3-ac13-9ff6f47ef4cd
all-MiniLM-L6-v2
cpu
500
50
61,128
{ "char_count": 3627, "chunk_index": 7, "chunk_total": 15, "company": "ADANIENT", "faiss_id": 29, "ingested_at": "2026-07-06 17:39:47.575188+00:00", "pdf_file": "ADANIENT_13052026185124_outcomeofRIcommittee13052026.pdf", "pdf_path": "ADANIENT\\pdfs\\ADANIENT_13052026185124_outcomeofRIcommittee13052026.p...
e357d42b-c9ae-46c3-ac13-9ff6f47ef4cd
all-MiniLM-L6-v2
cpu
500
50
61,128
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