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Even after adding the config file for pyreparser lib the interpreter is showing error message
C:\B.Tech\Project 6th Sem\Smart Resume Analyser.venv\Lib\site-packages\spacy\util.py:918: UserWarning: [W094] Model 'en_training' (0.0.0) specifies an under-constrained spaCy vers
ion requirement: >=2.1.4. This can lead to compatibility problems with older versions, or as new spaCy versions are released, because the model may say it's compatible when it's not. Consider changing the "spacy_version" in your meta.json to a version range, with a lower and upper pin. For example: >=3.7.4,<3.8.0
warnings.warn(warn_msg)
2024-05-13 21:00:03.767 Uncaught app exception
Traceback (most recent call last):
File "C:\B.Tech\Project 6th Sem\Smart Resume Analyser.venv\Lib\site-packages\streamlit\runtime\scriptrunner\script_runner.py", line 600, in run_script
exec(code, module.dict)
File "C:\B.Tech\Project 6th Sem\Smart Resume Analyser\App.py", line 436, in
run()
File "C:\B.Tech\Project 6th Sem\Smart Resume Analyser\App.py", line 151, in run
resume_data = ResumeParser(save_image_path).get_extracted_data()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "C:\B.Tech\Project 6th Sem\Smart Resume Analyser.venv\Lib\site-packages\pyresparser\resume_parser.py", line 21, in init
custom_nlp = spacy.load(os.path.dirname(os.path.abspath(file)))
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "C:\B.Tech\Project 6th Sem\Smart Resume Analyser.venv\Lib\site-packages\spacy_init.py", line 51, in load
return util.load_model(
^^^^^^^^^^^^^^^^
File "C:\B.Tech\Project 6th Sem\Smart Resume Analyser.venv\Lib\site-packages\spacy\util.py", line 467, in load_model
return load_model_from_path(Path(name), **kwargs) # type: ignore[arg-type]
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "C:\B.Tech\Project 6th Sem\Smart Resume Analyser.venv\Lib\site-packages\spacy\util.py", line 539, in load_model_from_path
nlp = load_model_from_config(
^^^^^^^^^^^^^^^^^^^^^^^
File "C:\B.Tech\Project 6th Sem\Smart Resume Analyser.venv\Lib\site-packages\spacy\util.py", line 587, in load_model_from_config
nlp = lang_cls.from_config(
^^^^^^^^^^^^^^^^^^^^^
File "C:\B.Tech\Project 6th Sem\Smart Resume Analyser.venv\Lib\site-packages\spacy\language.py", line 1830, in from_config
resolved_nlp = registry.resolve(
^^^^^^^^^^^^^^^^^
File "C:\B.Tech\Project 6th Sem\Smart Resume Analyser.venv\Lib\site-packages\confection_init_.py", line 759, in resolve
resolved, _ = cls.make(
^^^^^^^^^^
File "C:\B.Tech\Project 6th Sem\Smart Resume Analyser.venv\Lib\site-packages\confection_init.py", line 808, in _make
filled, _, resolved = cls.fill(
^^^^^^^^^^
File "C:\B.Tech\Project 6th Sem\Smart Resume Analyser.venv\Lib\site-packages\confection_init.py", line 929, in _fill
raise ConfigValidationError(
confection.ConfigValidationError:
Config validation error
disabled field required
tokenizer field required
before_creation field required
after_creation field required
after_pipeline_creation field required
batch_size field required
{'lang': 'en', 'pipeline': ['tok2vec', 'tagger', 'parser', 'ner'], 'vectors': {'@vectors': 'spacy.Vectors.v1'}}
The text was updated successfully, but these errors were encountered:
Even after adding the config file for pyreparser lib the interpreter is showing error message
C:\B.Tech\Project 6th Sem\Smart Resume Analyser.venv\Lib\site-packages\spacy\util.py:918: UserWarning: [W094] Model 'en_training' (0.0.0) specifies an under-constrained spaCy vers
ion requirement: >=2.1.4. This can lead to compatibility problems with older versions, or as new spaCy versions are released, because the model may say it's compatible when it's not. Consider changing the "spacy_version" in your meta.json to a version range, with a lower and upper pin. For example: >=3.7.4,<3.8.0
warnings.warn(warn_msg)
2024-05-13 21:00:03.767 Uncaught app exception
Traceback (most recent call last):
File "C:\B.Tech\Project 6th Sem\Smart Resume Analyser.venv\Lib\site-packages\streamlit\runtime\scriptrunner\script_runner.py", line 600, in run_script
exec(code, module.dict)
File "C:\B.Tech\Project 6th Sem\Smart Resume Analyser\App.py", line 436, in
run()
File "C:\B.Tech\Project 6th Sem\Smart Resume Analyser\App.py", line 151, in run
resume_data = ResumeParser(save_image_path).get_extracted_data()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "C:\B.Tech\Project 6th Sem\Smart Resume Analyser.venv\Lib\site-packages\pyresparser\resume_parser.py", line 21, in init
custom_nlp = spacy.load(os.path.dirname(os.path.abspath(file)))
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "C:\B.Tech\Project 6th Sem\Smart Resume Analyser.venv\Lib\site-packages\spacy_init.py", line 51, in load
return util.load_model(
^^^^^^^^^^^^^^^^
File "C:\B.Tech\Project 6th Sem\Smart Resume Analyser.venv\Lib\site-packages\spacy\util.py", line 467, in load_model
return load_model_from_path(Path(name), **kwargs) # type: ignore[arg-type]
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "C:\B.Tech\Project 6th Sem\Smart Resume Analyser.venv\Lib\site-packages\spacy\util.py", line 539, in load_model_from_path
nlp = load_model_from_config(
^^^^^^^^^^^^^^^^^^^^^^^
File "C:\B.Tech\Project 6th Sem\Smart Resume Analyser.venv\Lib\site-packages\spacy\util.py", line 587, in load_model_from_config
nlp = lang_cls.from_config(
^^^^^^^^^^^^^^^^^^^^^
File "C:\B.Tech\Project 6th Sem\Smart Resume Analyser.venv\Lib\site-packages\spacy\language.py", line 1830, in from_config
resolved_nlp = registry.resolve(
^^^^^^^^^^^^^^^^^
File "C:\B.Tech\Project 6th Sem\Smart Resume Analyser.venv\Lib\site-packages\confection_init_.py", line 759, in resolve
resolved, _ = cls.make(
^^^^^^^^^^
File "C:\B.Tech\Project 6th Sem\Smart Resume Analyser.venv\Lib\site-packages\confection_init.py", line 808, in _make
filled, _, resolved = cls.fill(
^^^^^^^^^^
File "C:\B.Tech\Project 6th Sem\Smart Resume Analyser.venv\Lib\site-packages\confection_init.py", line 929, in _fill
raise ConfigValidationError(
confection.ConfigValidationError:
Config validation error
disabled field required
tokenizer field required
before_creation field required
after_creation field required
after_pipeline_creation field required
batch_size field required
{'lang': 'en', 'pipeline': ['tok2vec', 'tagger', 'parser', 'ner'], 'vectors': {'@vectors': 'spacy.Vectors.v1'}}
The text was updated successfully, but these errors were encountered: