Análise de sentimentos em texto financeiros

[Apollo]

Ao execultar esse trecho:

modelo = spacy.blank('en')
categorias = modelo.create_pipe("textcat")
categorias.add_label('POSITIVO')
categorias.add_label('NEGATIVO')
modelo.add_pipe(categorias)
historico = []

Recebo esse Erro:

ValueError Traceback (most recent call last)
<ipython-input-80-40ace644a210> in <module>
3 categorias.add_label(‘POSITIVO’)
4 categorias.add_label(‘NEGATIVO’)
—-> 5 modelo.add_pipe(categorias)
6 historico = []

/usr/local/lib/python3.9/dist-packages/spacy/language.py in add_pipe(self, factory_name, name, before, after, first, last, source, config, raw_config, validate)
746 bad_val = repr(factory_name)
747 err = Errors.E966.format(component=bad_val, name=name)
–> 748 raise ValueError(err)
749 name = name if name is not None else factory_name
750 if name in self.component_names:

ValueError: [E966] nlp.add_pipe now takes the string name of the registered component factory, not a callable component. Expected string, but got <spacy.pipeline.textcat.TextCategorizer object at 0x7f6b92f0cd10> (name: ‘None’).

– If you created your component with nlp.create_pipe('name'): remove nlp.create_pipe and call nlp.add_pipe('name') instead.

– If you passed in a component like TextCategorizer(): call nlp.add_pipe with the string name instead, e.g. nlp.add_pipe('textcat').

– If you’re using a custom component: Add the decorator @Language.component (for function components) or @Language.factory (for class components / factories) to your custom component and assign it a name, e.g. @Language.component('your_name'). You can then run nlp.add_pipe('your_name') to add it to the pipeline.

[Fábio Spak]

Olá Apollo, você esta utilizando essa versão do Spacy: !pip install spacy==2.2.4 ?

Fabio

[Autor]

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