Datasets:

Finish-him
/

msc-knowledge-base

Error code:   FeaturesError
Exception:    ArrowInvalid
Message:      Schema at index 1 was different: 
domains: struct<ai_agents: struct<docs: list<item: string>, count: int64>, development: struct<docs: list<item: string>, count: int64>, content_generation: struct<docs: list<item: string>, count: int64>, brand_identity: struct<docs: list<item: string>, count: int64>, audio_generation: struct<docs: list<item: string>, count: int64>, marketing_seo: struct<docs: list<item: string>, count: int64>, chatbot: struct<docs: list<item: string>, count: int64>, planning_admin: struct<docs: list<item: string>, count: int64>, animation_generation: struct<docs: list<item: string>, count: int64>>
domain_info: struct<marketing_seo: struct<name: string, description: string, keywords: list<item: string>, future_team: string, priority: int64>, ai_agents: struct<name: string, description: string, keywords: list<item: string>, future_team: string, priority: int64>, chatbot: struct<name: string, description: string, keywords: list<item: string>, future_team: string, priority: int64>, content_generation: struct<name: string, description: string, keywords: list<item: string>, future_team: string, priority: int64>, audio_generation: struct<name: string, description: string, keywords: list<item: string>, future_team: string, priority: int64>, animation_generation: struct<name: string, description: string, keywords: list<item: string>, future_team: string, priority: int64>, planning_admin: struct<name: string, description: string, keywords: list<item: string>, future_team: string, priority: int64>, brand_identity: struct<name: string, description: string, keywords: list<item: string>, future_team: string, priority: int64>, development: struct<name: string, description: string, keywords: list<item: string>, future_team: string, priority: int64>>
vs
metadata: struct<name: string, version: string, created_at: string, total_documents: int64, domains: list<item: string>, teams: list<item: string>>
documents: list<item: struct<id: string, title: string, filepath: string, msc_domains: list<item: string>, assigned_team: string, content_hash: string, stats: struct<word_count: int64, line_count: int64, char_count: int64, code_blocks: int64, headers: int64>, qa_pairs_count: int64, instructions_count: int64, definitions_count: int64, chunks_count: int64>>
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/split/first_rows.py", line 243, in compute_first_rows_from_streaming_response
                  iterable_dataset = iterable_dataset._resolve_features()
                                     ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 3496, in _resolve_features
                  features = _infer_features_from_batch(self.with_format(None)._head())
                                                        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2257, in _head
                  return next(iter(self.iter(batch_size=n)))
                         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2461, in iter
                  for key, example in iterator:
                                      ^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 1952, in __iter__
                  for key, pa_table in self._iter_arrow():
                                       ^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 1974, in _iter_arrow
                  yield from self.ex_iterable._iter_arrow()
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 563, in _iter_arrow
                  yield new_key, pa.Table.from_batches(chunks_buffer)
                                 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "pyarrow/table.pxi", line 5039, in pyarrow.lib.Table.from_batches
                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.ArrowInvalid: Schema at index 1 was different: 
              domains: struct<ai_agents: struct<docs: list<item: string>, count: int64>, development: struct<docs: list<item: string>, count: int64>, content_generation: struct<docs: list<item: string>, count: int64>, brand_identity: struct<docs: list<item: string>, count: int64>, audio_generation: struct<docs: list<item: string>, count: int64>, marketing_seo: struct<docs: list<item: string>, count: int64>, chatbot: struct<docs: list<item: string>, count: int64>, planning_admin: struct<docs: list<item: string>, count: int64>, animation_generation: struct<docs: list<item: string>, count: int64>>
              domain_info: struct<marketing_seo: struct<name: string, description: string, keywords: list<item: string>, future_team: string, priority: int64>, ai_agents: struct<name: string, description: string, keywords: list<item: string>, future_team: string, priority: int64>, chatbot: struct<name: string, description: string, keywords: list<item: string>, future_team: string, priority: int64>, content_generation: struct<name: string, description: string, keywords: list<item: string>, future_team: string, priority: int64>, audio_generation: struct<name: string, description: string, keywords: list<item: string>, future_team: string, priority: int64>, animation_generation: struct<name: string, description: string, keywords: list<item: string>, future_team: string, priority: int64>, planning_admin: struct<name: string, description: string, keywords: list<item: string>, future_team: string, priority: int64>, brand_identity: struct<name: string, description: string, keywords: list<item: string>, future_team: string, priority: int64>, development: struct<name: string, description: string, keywords: list<item: string>, future_team: string, priority: int64>>
              vs
              metadata: struct<name: string, version: string, created_at: string, total_documents: int64, domains: list<item: string>, teams: list<item: string>>
              documents: list<item: struct<id: string, title: string, filepath: string, msc_domains: list<item: string>, assigned_team: string, content_hash: string, stats: struct<word_count: int64, line_count: int64, char_count: int64, code_blocks: int64, headers: int64>, qa_pairs_count: int64, instructions_count: int64, definitions_count: int64, chunks_count: int64>>

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msc-knowledge-base

Base de conhecimento completa da MSC Marketing para RAG e fine-tuning

Sobre

Este dataset faz parte da infraestrutura de IA da MSC Marketing, uma empresa especializada em Marketing Digital e SEO.

Uso

from datasets import load_dataset

dataset = load_dataset("Finish-him/msc-knowledge-base")

Estrutura

Os arquivos incluídos neste dataset são:

msc_documents.json
domain_distribution.json
team_distribution.json

Licença

MIT License - MSC Marketing

Contato

Website: https://mscmarketing.group
GitHub: https://github.com/MSC-Consultoria

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msc-knowledge-base

Sobre

Uso

Estrutura

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Contato

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