Adjust pydoc markdown config so methods shown with classes

README.md

@@ -326,3 +326,4 @@ Here's a list of organizations who use Haystack. Don't hesitate to send a PR to
 - [Etalab](https://www.etalab.gouv.fr/)
 - [Infineon](https://www.infineon.com/)
 - [Sooth.ai](https://sooth.ai/)
+

docs/_src/api/api/crawler.md

@@ -24,7 +24,7 @@ Crawl texts from a website so that we can use them later in Haystack as a corpus
 
 <a id="crawler.Crawler.__init__"></a>
 
-#### \_\_init\_\_
+#### Crawler.\_\_init\_\_
 
 ```python
 def __init__(output_dir: str, urls: Optional[List[str]] = None, crawler_depth: int = 1, filter_urls: Optional[List] = None, overwrite_existing_files=True, id_hash_keys: Optional[List[str]] = None)
@@ -49,7 +49,7 @@ In this case the id will be generated by using the content and the defined metad
 
 <a id="crawler.Crawler.crawl"></a>
 
-#### crawl
+#### Crawler.crawl
 
 ```python
 def crawl(output_dir: Union[str, Path, None] = None, urls: Optional[List[str]] = None, crawler_depth: Optional[int] = None, filter_urls: Optional[List] = None, overwrite_existing_files: Optional[bool] = None, id_hash_keys: Optional[List[str]] = None) -> List[Path]
@@ -83,7 +83,7 @@ List of paths where the crawled webpages got stored
 
 <a id="crawler.Crawler.run"></a>
 
-#### run
+#### Crawler.run
 
 ```python
 def run(output_dir: Union[str, Path, None] = None, urls: Optional[List[str]] = None, crawler_depth: Optional[int] = None, filter_urls: Optional[List] = None, overwrite_existing_files: Optional[bool] = None, return_documents: Optional[bool] = False, id_hash_keys: Optional[List[str]] = None) -> Tuple[Dict, str]

docs/_src/api/api/document_classifier.md

@@ -12,7 +12,7 @@ class BaseDocumentClassifier(BaseComponent)
 
 <a id="base.BaseDocumentClassifier.timing"></a>
 
-#### timing
+#### BaseDocumentClassifier.timing
 
 ```python
 def timing(fn, attr_name)
@@ -81,7 +81,7 @@ With this document_classifier, you can directly get predictions via predict()
 
 <a id="transformers.TransformersDocumentClassifier.__init__"></a>
 
-#### \_\_init\_\_
+#### TransformersDocumentClassifier.\_\_init\_\_
 
 ```python
 def __init__(model_name_or_path: str = "bhadresh-savani/distilbert-base-uncased-emotion", model_version: Optional[str] = None, tokenizer: Optional[str] = None, use_gpu: bool = True, return_all_scores: bool = False, task: str = "text-classification", labels: Optional[List[str]] = None, batch_size: int = -1, classification_field: str = None)
@@ -119,7 +119,7 @@ or an entailment.
 
 <a id="transformers.TransformersDocumentClassifier.predict"></a>
 
-#### predict
+#### TransformersDocumentClassifier.predict
 
 ```python
 def predict(documents: List[Document]) -> List[Document]

docs/_src/api/api/evaluation.md

@@ -22,7 +22,7 @@ Please use pipeline.eval() instead.
 
 <a id="evaluator.EvalDocuments.__init__"></a>
 
-#### \_\_init\_\_
+#### EvalDocuments.\_\_init\_\_
 
 ```python
 def __init__(debug: bool = False, open_domain: bool = True, top_k: int = 10)
@@ -37,7 +37,7 @@ When False, correct retrieval is evaluated based on document_id.
 
 <a id="evaluator.EvalDocuments.run"></a>
 
-#### run
+#### EvalDocuments.run
 
 ```python
 def run(documents: List[Document], labels: List[Label], top_k: Optional[int] = None)
@@ -47,7 +47,7 @@ Run this node on one sample and its labels
 
 <a id="evaluator.EvalDocuments.print"></a>
 
-#### print
+#### EvalDocuments.print
 
 ```python
 def print()
@@ -75,7 +75,7 @@ Please use pipeline.eval() instead.
 
 <a id="evaluator.EvalAnswers.__init__"></a>
 
-#### \_\_init\_\_
+#### EvalAnswers.\_\_init\_\_
 
 ```python
 def __init__(skip_incorrect_retrieval: bool = True, open_domain: bool = True, sas_model: str = None, debug: bool = False)
@@ -100,7 +100,7 @@ Models:
 
 <a id="evaluator.EvalAnswers.run"></a>
 
-#### run
+#### EvalAnswers.run
 
 ```python
 def run(labels: List[Label], answers: List[Answer], correct_retrieval: bool)
@@ -110,7 +110,7 @@ Run this node on one sample and its labels
 
 <a id="evaluator.EvalAnswers.print"></a>
 
-#### print
+#### EvalAnswers.print
 
 ```python
 def print(mode)

docs/_src/api/api/extractor.md

@@ -19,7 +19,7 @@ The entities extracted by this Node will populate Document.entities
 
 <a id="entity.EntityExtractor.run"></a>
 
-#### run
+#### EntityExtractor.run
 
 ```python
 def run(documents: Optional[Union[List[Document], List[dict]]] = None) -> Tuple[Dict, str]
@@ -29,7 +29,7 @@ This is the method called when this node is used in a pipeline
 
 <a id="entity.EntityExtractor.extract"></a>
 
-#### extract
+#### EntityExtractor.extract
 
 ```python
 def extract(text)

docs/_src/api/api/file_classifier.md

@@ -14,7 +14,7 @@ Route files in an Indexing Pipeline to corresponding file converters.
 
 <a id="file_type.FileTypeClassifier.__init__"></a>
 
-#### \_\_init\_\_
+#### FileTypeClassifier.\_\_init\_\_
 
 ```python
 def __init__(supported_types: List[str] = DEFAULT_TYPES)
@@ -33,7 +33,7 @@ also be rejected.
 
 <a id="file_type.FileTypeClassifier.run"></a>
 
-#### run
+#### FileTypeClassifier.run
 
 ```python
 def run(file_paths: Union[Path, List[Path], str, List[str], List[Union[Path, str]]])

docs/_src/api/api/file_converter.md

@@ -14,7 +14,7 @@ Base class for implementing file converts to transform input documents to text f
 
 <a id="base.BaseConverter.__init__"></a>
 
-#### \_\_init\_\_
+#### BaseConverter.\_\_init\_\_
 
 ```python
 def __init__(remove_numeric_tables: bool = False, valid_languages: Optional[List[str]] = None, id_hash_keys: Optional[List[str]] = None)
@@ -39,7 +39,7 @@ In this case the id will be generated by using the content and the defined metad
 
 <a id="base.BaseConverter.convert"></a>
 
-#### convert
+#### BaseConverter.convert
 
 ```python
 @abstractmethod
@@ -73,7 +73,7 @@ In this case the id will be generated by using the content and the defined metad
 
 <a id="base.BaseConverter.validate_language"></a>
 
-#### validate\_language
+#### BaseConverter.validate\_language
 
 ```python
 def validate_language(text: str, valid_languages: Optional[List[str]] = None) -> bool
@@ -129,7 +129,7 @@ class DocxToTextConverter(BaseConverter)
 
 <a id="docx.DocxToTextConverter.convert"></a>
 
-#### convert
+#### DocxToTextConverter.convert
 
 ```python
 def convert(file_path: Path, meta: Optional[Dict[str, str]] = None, remove_numeric_tables: Optional[bool] = None, valid_languages: Optional[List[str]] = None, encoding: Optional[str] = None, id_hash_keys: Optional[List[str]] = None) -> List[Document]
@@ -174,7 +174,7 @@ class ImageToTextConverter(BaseConverter)
 
 <a id="image.ImageToTextConverter.__init__"></a>
 
-#### \_\_init\_\_
+#### ImageToTextConverter.\_\_init\_\_
 
 ```python
 def __init__(remove_numeric_tables: bool = False, valid_languages: Optional[List[str]] = ["eng"], id_hash_keys: Optional[List[str]] = None)
@@ -201,7 +201,7 @@ In this case the id will be generated by using the content and the defined metad
 
 <a id="image.ImageToTextConverter.convert"></a>
 
-#### convert
+#### ImageToTextConverter.convert
 
 ```python
 def convert(file_path: Union[Path, str], meta: Optional[Dict[str, str]] = None, remove_numeric_tables: Optional[bool] = None, valid_languages: Optional[List[str]] = None, encoding: Optional[str] = "utf-8", id_hash_keys: Optional[List[str]] = None) -> List[Document]
@@ -243,7 +243,7 @@ class MarkdownConverter(BaseConverter)
 
 <a id="markdown.MarkdownConverter.convert"></a>
 
-#### convert
+#### MarkdownConverter.convert
 
 ```python
 def convert(file_path: Path, meta: Optional[Dict[str, str]] = None, remove_numeric_tables: Optional[bool] = None, valid_languages: Optional[List[str]] = None, encoding: Optional[str] = "utf-8", id_hash_keys: Optional[List[str]] = None) -> List[Document]
@@ -265,7 +265,7 @@ In this case the id will be generated by using the content and the defined metad
 
 <a id="markdown.MarkdownConverter.markdown_to_text"></a>
 
-#### markdown\_to\_text
+#### MarkdownConverter.markdown\_to\_text
 
 ```python
 @staticmethod
@@ -292,7 +292,7 @@ class PDFToTextConverter(BaseConverter)
 
 <a id="pdf.PDFToTextConverter.__init__"></a>
 
-#### \_\_init\_\_
+#### PDFToTextConverter.\_\_init\_\_
 
 ```python
 def __init__(remove_numeric_tables: bool = False, valid_languages: Optional[List[str]] = None, id_hash_keys: Optional[List[str]] = None, encoding: Optional[str] = "UTF-8")
@@ -320,7 +320,7 @@ Defaults to "UTF-8" in order to support special characters (e.g. German Umlauts,
 
 <a id="pdf.PDFToTextConverter.convert"></a>
 
-#### convert
+#### PDFToTextConverter.convert
 
 ```python
 def convert(file_path: Path, meta: Optional[Dict[str, str]] = None, remove_numeric_tables: Optional[bool] = None, valid_languages: Optional[List[str]] = None, encoding: Optional[str] = None, id_hash_keys: Optional[List[str]] = None) -> List[Document]
@@ -360,7 +360,7 @@ class PDFToTextOCRConverter(BaseConverter)
 
 <a id="pdf.PDFToTextOCRConverter.__init__"></a>
 
-#### \_\_init\_\_
+#### PDFToTextOCRConverter.\_\_init\_\_
 
 ```python
 def __init__(remove_numeric_tables: bool = False, valid_languages: Optional[List[str]] = ["eng"], id_hash_keys: Optional[List[str]] = None)
@@ -387,7 +387,7 @@ In this case the id will be generated by using the content and the defined metad
 
 <a id="pdf.PDFToTextOCRConverter.convert"></a>
 
-#### convert
+#### PDFToTextOCRConverter.convert
 
 ```python
 def convert(file_path: Path, meta: Optional[Dict[str, str]] = None, remove_numeric_tables: Optional[bool] = None, valid_languages: Optional[List[str]] = None, encoding: Optional[str] = "UTF-8", id_hash_keys: Optional[List[str]] = None) -> List[Document]
@@ -432,7 +432,7 @@ class TikaConverter(BaseConverter)
 
 <a id="tika.TikaConverter.__init__"></a>
 
-#### \_\_init\_\_
+#### TikaConverter.\_\_init\_\_
 
 ```python
 def __init__(tika_url: str = "http://localhost:9998/tika", remove_numeric_tables: bool = False, valid_languages: Optional[List[str]] = None, id_hash_keys: Optional[List[str]] = None)
@@ -458,7 +458,7 @@ In this case the id will be generated by using the content and the defined metad
 
 <a id="tika.TikaConverter.convert"></a>
 
-#### convert
+#### TikaConverter.convert
 
 ```python
 def convert(file_path: Path, meta: Optional[Dict[str, str]] = None, remove_numeric_tables: Optional[bool] = None, valid_languages: Optional[List[str]] = None, encoding: Optional[str] = None, id_hash_keys: Optional[List[str]] = None) -> List[Document]
@@ -502,7 +502,7 @@ class TextConverter(BaseConverter)
 
 <a id="txt.TextConverter.convert"></a>
 
-#### convert
+#### TextConverter.convert
 
 ```python
 def convert(file_path: Path, meta: Optional[Dict[str, str]] = None, remove_numeric_tables: Optional[bool] = None, valid_languages: Optional[List[str]] = None, encoding: Optional[str] = "utf-8", id_hash_keys: Optional[List[str]] = None) -> List[Document]

docs/_src/api/api/generator.md

@@ -14,7 +14,7 @@ Abstract class for Generators
 
 <a id="base.BaseGenerator.predict"></a>
 
-#### predict
+#### BaseGenerator.predict
 
 ```python
 @abstractmethod
@@ -87,7 +87,7 @@ i.e. the model can easily adjust to domain documents even after training has fin
 
 <a id="transformers.RAGenerator.__init__"></a>
 
-#### \_\_init\_\_
+#### RAGenerator.\_\_init\_\_
 
 ```python
 def __init__(model_name_or_path: str = "facebook/rag-token-nq", model_version: Optional[str] = None, retriever: Optional[DensePassageRetriever] = None, generator_type: str = "token", top_k: int = 2, max_length: int = 200, min_length: int = 2, num_beams: int = 2, embed_title: bool = True, prefix: Optional[str] = None, use_gpu: bool = True)
@@ -115,7 +115,7 @@ See https://huggingface.co/models for full list of available models.
 
 <a id="transformers.RAGenerator.predict"></a>
 
-#### predict
+#### RAGenerator.predict
 
 ```python
 def predict(query: str, documents: List[Document], top_k: Optional[int] = None) -> Dict
@@ -207,7 +207,7 @@ For a list of all text-generation models see https://huggingface.co/models?pipel
 
 <a id="transformers.Seq2SeqGenerator.__init__"></a>
 
-#### \_\_init\_\_
+#### Seq2SeqGenerator.\_\_init\_\_
 
 ```python
 def __init__(model_name_or_path: str, input_converter: Optional[Callable] = None, top_k: int = 1, max_length: int = 200, min_length: int = 2, num_beams: int = 8, use_gpu: bool = True)
@@ -229,7 +229,7 @@ top_k: Optional[int] = None) -> BatchEncoding:
 
 <a id="transformers.Seq2SeqGenerator.predict"></a>
 
-#### predict
+#### Seq2SeqGenerator.predict
 
 ```python
 def predict(query: str, documents: List[Document], top_k: Optional[int] = None) -> Dict

docs/_src/api/api/other.md

@@ -36,7 +36,7 @@ The node allows multiple join modes:
 
 <a id="join_docs.JoinDocuments.__init__"></a>
 
-#### \_\_init\_\_
+#### JoinDocuments.\_\_init\_\_
 
 ```python
 def __init__(join_mode: str = "concatenate", weights: Optional[List[float]] = None, top_k_join: Optional[int] = None)
@@ -67,7 +67,7 @@ A node to join `Answer`s produced by multiple `Reader` nodes.
 
 <a id="join_answers.JoinAnswers.__init__"></a>
 
-#### \_\_init\_\_
+#### JoinAnswers.\_\_init\_\_
 
 ```python
 def __init__(join_mode: str = "concatenate", weights: Optional[List[float]] = None, top_k_join: Optional[int] = None)
@@ -99,7 +99,7 @@ different nodes.
 
 <a id="route_documents.RouteDocuments.__init__"></a>
 
-#### \_\_init\_\_
+#### RouteDocuments.\_\_init\_\_
 
 ```python
 def __init__(split_by: str = "content_type", metadata_values: Optional[List[str]] = None)