spaCy官方classy classification示例报错：组件工厂未找到的解决咨询

问题 #

我正在学习使用spaCy，现在想要学习classy classification，但spaCy官方网页上展示的classy示例无法正常运行。以下是我使用的代码以及出现的错误信息：

import spacy

data = {
    "furniture": ["This text is about chairs.",
               "Couches, benches and televisions.",
               "I really need to get a new sofa."],
    "kitchen": ["There also exist things like fridges.",
                "I hope to be getting a new stove today.",
                "Do you also have some ovens."]
}

# see github repo for examples on sentence-transformers and Huggingface
nlp = spacy.load('en_core_web_md')
nlp.add_pipe("classy_classification", 
    config={
        "data": data,
        "model": "spacy"
    }
)

print(nlp("I am looking for kitchen appliances.")._.cats)

错误信息：

File "C:\Users\vidrr\AppData\Local\Programs\Python\Python312\Lib\site-packages\spacy\language.py", line 821, in add_pipe
    pipe_component = self.create_pipe(
                     ^^^^^^^^^^^^^^^^^
  File "C:\Users\vidrr\AppData\Local\Programs\Python\Python312\Lib\site-packages\spacy\language.py", line 690, in create_pipe
    raise ValueError(err)
ValueError: [E002] Can't find factory for 'classy_classification' for language English (en). This usually happens when spaCy calls `nlp.create_pipe` with a custom component name that's not registered on the current language class. If you're using a custom component, make sure you've added the decorator `@Language.component` (for function components) or `@Language.factory` (for class components).

Available factories: attribute_ruler, tok2vec, merge_noun_chunks, merge_entities, merge_subtokens, token_splitter, doc_cleaner, parser, beam_parser, lemmatizer, trainable_lemmatizer, entity_linker, entity_ruler, tagger, morphologizer, ner, beam_ner, senter, sentencizer, spancat, spancat_singlelabel, span_finder, future_entity_ruler, span_ruler, textcat, textcat_multilabel, en.lemmatizer

解决方法 #

• 安装对应第三方库
  classy_classification不是spaCy内置组件，需要单独安装配套库。在终端执行命令：

pip install spacy-classy-classification

• 修改代码导入组件
  安装完成后，在代码中导入该库，它会自动完成组件注册。修改后的代码如下：

import spacy
import spacy_classy_classification  # 新增该行，注册classy_classification组件

data = {
    "furniture": ["This text is about chairs.",
               "Couches, benches and televisions.",
               "I really need to get a new sofa."],
    "kitchen": ["There also exist things like fridges.",
                "I hope to be getting a new stove today.",
                "Do you also have some ovens."]
}

nlp = spacy.load('en_core_web_md')
nlp.add_pipe("classy_classification", 
    config={
        "data": data,
        "model": "spacy"
    }
)

print(nlp("I am looking for kitchen appliances.")._.cats)

• 运行验证
  执行修改后的代码，即可正常加载组件并输出分类结果。

内容的提问来源于stack exchange，提问作者David Ramirez