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.sentencizer.Sentencizer object at 0x000001CA1A69DF00> (name: 'None').

[dalalBerrezoug]

i don't understand the error
my code:
def getSentences(text):
nlp = English()
nlp.add_pipe(nlp.create_pipe('sentencizer'))

document = nlp(text)
return [sent.string.strip() for sent in document.sents]

the error:

sentences = getSentences(text)
File "C:\Users***\PycharmProjects\tutospacy\main.py", line 8, in getSentences
nlp.add_pipe(nlp.create_pipe('sentencizer'))
File "C:\Python\Python39\lib\site-packages\spacy\language.py", line 749, in add_pipe
raise ValueError(err)
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.sentencizer.Sentencizer object at 0x000001CA1A69DF00> (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.

my Environment

• spaCy version: 3.0.5
• Platform: Windows-10-10.0.19041-SP0
• Python version: 3.9.4
• Pipelines: en_core_web_sm (3.0.0)

[polm]

The way add_pipe works changed in v3. Your code is using the v2 style, but like the error says you need to change it. Your code should look like this:

nlp.add_pipe('sentencizer')

[greybraun]

Nice to meet you @polm.
Excuse me, can you fix my problem?
I can't compile this code.
import cov_bsv
nlp = cov_bsv.load()
got this error:

[polm]

Please open a new thread, paste errors as text, not images, and explain what cov_bsv is.

[greybraun]

I wanted to load model on this site.
https://spacy.io/universe/project/cov-bsv

simple code:
import cov_bsv # model
nlp = cov_bsv.load() # load model

error you have seen occoured on second line.

And, thank you for your reply.

[polm]

Please open a new thread.

[greybraun]

Please open a new thread.
Excuse me, can we discuss on skype? Mine: live:.cid.8eae674c7e1e7d0c

[Polindem]

[polm]

Uh, not really sure what your error has to do with this one, but if it's a textacy issue maybe you should ask on their repo?

[Manan-3000]

Giving me the same kind of error in my code
def train_model(train_data):
if 'ner' not in nlp.pipe_names:
ner = nlp.create_pipe('ner')
nlp.add_pipe(ner, last = True)

for _, annotation in train_data:
    for ent in annotation['entities']:
        ner.add_label(ent[2])
        

other_pipes = [pipe for pipe in nlp.pipe_names if pipe != 'ner']
with nlp.disable_pipes(*other_pipes):  # only train NER
    optimizer = nlp.begin_training()
    for itn in range(10):
        print("Starting iteration " + str(itn))
        random.shuffle(train_data)
        losses = {}
        index = 0
        for text, annotations in train_data:
            try:
                nlp.update(
                    [text],  # batch of texts
                    [annotations],  # batch of annotations
                    drop=0.2,  # dropout - make it harder to memorise data
                    sgd=optimizer,  # callable to update weights
                    losses=losses)
            except Exception as e:
                pass
            
        print(losses)

The error:
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.ner.EntityRecognizer object at 0x00000260D46BB040> (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.

[svlandeg]

The error message actually fully explains what you need to do to fix this:

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