diff --git a/.github/workflows/rest_api_tests.yml b/.github/workflows/rest_api_tests.yml
index f307f7224..8c74b05c2 100644
--- a/.github/workflows/rest_api_tests.yml
+++ b/.github/workflows/rest_api_tests.yml
@@ -27,7 +27,7 @@ jobs:
       - name: Install Black
         run: |
           pip install --upgrade pip
-          pip install black==22.6.0
+          pip install .[formatting]
 
       - name: Check status
         run: |
@@ -40,7 +40,7 @@ jobs:
             echo "# Either:"
             echo "# 1. Run Black locally before committing:"
             echo "# "
-            echo "#     pip install black==22.6.0"
+            echo "#     pip install .[formatting]"
             echo "#     black ."
             echo "# "
             echo "# 2. Install the pre-commit hook:"
diff --git a/.github/workflows/tests.yml b/.github/workflows/tests.yml
index 4061feff3..4e63c8b3b 100644
--- a/.github/workflows/tests.yml
+++ b/.github/workflows/tests.yml
@@ -39,13 +39,11 @@ jobs:
     - uses: actions/checkout@v3
 
     - uses: actions/setup-python@v4
-      with:
-        python-version: "3.8"
 
     - name: Install Black
       run: |
         pip install --upgrade pip
-        pip install black==22.6.0
+        pip install .[formatting]
 
     - name: Check status
       run: |
@@ -58,7 +56,7 @@ jobs:
           echo "# Either:"
           echo "# 1. Run Black locally before committing:"
           echo "# "
-          echo "#     pip install black==22.6.0"
+          echo "#     pip install .[formatting]"
           echo "#     black ."
           echo "# "
           echo "# 2. Install the pre-commit hook:"
diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml
index 839d828ce..4207b322f 100644
--- a/.pre-commit-config.yaml
+++ b/.pre-commit-config.yaml
@@ -16,7 +16,7 @@ repos:
     - id: no-commit-to-branch  # prevents committing to main
 
 - repo: https://github.com/psf/black
-  rev: 22.6.0  # IMPORTANT: keep this aligned with the black version in pyproject.toml
+  rev: 23.1.0
   hooks:
   - id: black-jupyter
 
diff --git a/haystack/document_stores/elasticsearch.py b/haystack/document_stores/elasticsearch.py
index b24ea44b6..52c6df2d9 100644
--- a/haystack/document_stores/elasticsearch.py
+++ b/haystack/document_stores/elasticsearch.py
@@ -207,7 +207,6 @@ class ElasticsearchDocumentStore(SearchEngineDocumentStore):
         timeout: int,
         use_system_proxy: bool,
     ) -> Elasticsearch:
-
         hosts = prepare_hosts(host, port)
 
         if (api_key or api_key_id) and not (api_key and api_key_id):
diff --git a/haystack/document_stores/pinecone.py b/haystack/document_stores/pinecone.py
index 07e1fd710..1531210e8 100644
--- a/haystack/document_stores/pinecone.py
+++ b/haystack/document_stores/pinecone.py
@@ -1196,7 +1196,6 @@ class PineconeDocumentStore(BaseDocumentStore):
         headers: Optional[Dict[str, str]] = None,
         return_embedding: Optional[bool] = None,
     ) -> List[Document]:
-
         if headers:
             raise NotImplementedError("PineconeDocumentStore does not support headers.")
 
@@ -1500,7 +1499,6 @@ class PineconeDocumentStore(BaseDocumentStore):
             # Extract Answer
             answer = None
             if label_meta.get("label-answer-answer") is not None:
-
                 # backwards compatibility: if legacy answer object with `document_id` is present, convert to `document_ids
                 if "label-answer-document-id" in label_meta:
                     document_id = label_meta["label-answer-document-id"]
diff --git a/haystack/document_stores/search_engine.py b/haystack/document_stores/search_engine.py
index 31851bc14..5d4a1a253 100644
--- a/haystack/document_stores/search_engine.py
+++ b/haystack/document_stores/search_engine.py
@@ -1062,7 +1062,6 @@ class SearchEngineDocumentStore(KeywordDocumentStore):
         custom_query: Optional[str],
         all_terms_must_match: bool,
     ) -> Dict[str, Any]:
-
         # Naive retrieval without BM25, only filtering
         if query is None:
             body = {"query": {"bool": {"must": {"match_all": {}}}}}  # type: Dict[str, Any]
diff --git a/haystack/document_stores/sql.py b/haystack/document_stores/sql.py
index 7b4d4ae50..edaf9a62b 100644
--- a/haystack/document_stores/sql.py
+++ b/haystack/document_stores/sql.py
@@ -41,7 +41,6 @@ Base = declarative_base()  # type: Any
 
 
 class ArrayType(TypeDecorator):
-
     impl = String
     cache_ok = True
 
@@ -624,7 +623,6 @@ class SQLDocumentStore(BaseDocumentStore):
         headers: Optional[Dict[str, str]] = None,
         scale_score: bool = True,
     ) -> List[Document]:
-
         raise NotImplementedError(
             "SQLDocumentStore is currently not supporting embedding queries. "
             "Change the query type (e.g. by choosing a different retriever) "
diff --git a/haystack/document_stores/weaviate.py b/haystack/document_stores/weaviate.py
index b7a1733c8..b30505d64 100644
--- a/haystack/document_stores/weaviate.py
+++ b/haystack/document_stores/weaviate.py
@@ -972,7 +972,6 @@ class WeaviateDocumentStore(KeywordDocumentStore):
             properties.append("_additional {id, distance, vector}")
 
         if query is None:
-
             # Retrieval via custom query, no BM25
             if custom_query:
                 query_output = self.weaviate_client.query.raw(custom_query)
diff --git a/haystack/modeling/data_handler/processor.py b/haystack/modeling/data_handler/processor.py
index c33257988..9055180b7 100644
--- a/haystack/modeling/data_handler/processor.py
+++ b/haystack/modeling/data_handler/processor.py
@@ -1896,7 +1896,6 @@ class TextClassificationProcessor(Processor):
         for dictionary, input_ids, segment_ids, padding_mask, tokens in zip(
             dicts, input_ids_batch, segment_ids_batch, padding_masks_batch, tokens_batch
         ):
-
             tokenized = {}
             if debug:
                 tokenized["tokens"] = tokens
@@ -1974,7 +1973,6 @@ class InferenceProcessor(TextClassificationProcessor):
     """
 
     def __init__(self, tokenizer, max_seq_len, **kwargs):
-
         super(InferenceProcessor, self).__init__(
             tokenizer=tokenizer,
             max_seq_len=max_seq_len,
diff --git a/haystack/modeling/data_handler/samples.py b/haystack/modeling/data_handler/samples.py
index b529a7c7f..ebc3d5d2f 100644
--- a/haystack/modeling/data_handler/samples.py
+++ b/haystack/modeling/data_handler/samples.py
@@ -32,7 +32,6 @@ class Sample:
         self.tokenized = tokenized
 
     def __str__(self):
-
         if self.clear_text:
             clear_text_str = "\n \t".join([k + ": " + str(v) for k, v in self.clear_text.items()])
             if len(clear_text_str) > 3000:
diff --git a/haystack/modeling/evaluation/metrics.py b/haystack/modeling/evaluation/metrics.py
index 6421e1f8f..31498d3a0 100644
--- a/haystack/modeling/evaluation/metrics.py
+++ b/haystack/modeling/evaluation/metrics.py
@@ -144,7 +144,7 @@ def squad_EM(preds, labels):
     """
     n_docs = len(preds)
     n_correct = 0
-    for (pred, label) in zip(preds, labels):
+    for pred, label in zip(preds, labels):
         qa_candidate = pred[0][0]
         pred_start = qa_candidate.offset_answer_start
         pred_end = qa_candidate.offset_answer_end
@@ -160,7 +160,7 @@ def top_n_EM(preds, labels):
     """
     n_docs = len(preds)
     n_correct = 0
-    for (pred, label) in zip(preds, labels):
+    for pred, label in zip(preds, labels):
         qa_candidates = pred[0]
         for qa_candidate in qa_candidates:
             pred_start = qa_candidate.offset_answer_start
@@ -178,7 +178,7 @@ def squad_EM_start(preds, labels):
     """
     n_docs = len(preds)
     n_correct = 0
-    for (pred, label) in zip(preds, labels):
+    for pred, label in zip(preds, labels):
         qa_candidate = pred[0][0]
         pred_start = qa_candidate.offset_answer_start
         curr_labels = label
@@ -245,7 +245,7 @@ def metrics_per_bin(preds, labels, num_bins: int = 10):
     pred_bins = [[] for _ in range(num_bins)]  # type: List
     label_bins = [[] for _ in range(num_bins)]  # type: List
     count_per_bin = [0] * num_bins
-    for (pred, label) in zip(preds, labels):
+    for pred, label in zip(preds, labels):
         current_score = pred[0][0].confidence
         if current_score >= 1.0:
             current_score = 0.9999
diff --git a/haystack/modeling/infer.py b/haystack/modeling/infer.py
index 62ba50948..fa591904b 100644
--- a/haystack/modeling/infer.py
+++ b/haystack/modeling/infer.py
@@ -402,7 +402,6 @@ class Inferencer:
         unaggregated_preds_all = []
 
         for batch in tqdm(data_loader, desc="Inferencing Samples", unit=" Batches", disable=self.disable_tqdm):
-
             batch = {key: batch[key].to(self.devices[0]) for key in batch}
 
             # get logits
diff --git a/haystack/modeling/model/biadaptive_model.py b/haystack/modeling/model/biadaptive_model.py
index 6e47db69f..3d12376fe 100644
--- a/haystack/modeling/model/biadaptive_model.py
+++ b/haystack/modeling/model/biadaptive_model.py
@@ -350,7 +350,6 @@ class BiAdaptiveModel(nn.Module):
             pooled_output[0] = pooled_output1
 
         if passage_input_ids is not None and passage_segment_ids is not None and passage_attention_mask is not None:
-
             max_seq_len = passage_input_ids.shape[-1]
             passage_input_ids = passage_input_ids.view(-1, max_seq_len)
             passage_attention_mask = passage_attention_mask.view(-1, max_seq_len)
diff --git a/haystack/modeling/model/multimodal/__init__.py b/haystack/modeling/model/multimodal/__init__.py
index 7974d599a..df11f619e 100644
--- a/haystack/modeling/model/multimodal/__init__.py
+++ b/haystack/modeling/model/multimodal/__init__.py
@@ -152,7 +152,6 @@ def get_model(
 
 
 def _is_sentence_transformers_model(pretrained_model_name_or_path: Union[Path, str], use_auth_token: Union[bool, str]):
-
     # Check if sentence transformers config file is in local path
     if Path(pretrained_model_name_or_path).exists():
         if (Path(pretrained_model_name_or_path) / "config_sentence_transformers.json").exists():
diff --git a/haystack/modeling/model/prediction_head.py b/haystack/modeling/model/prediction_head.py
index 5d19c6694..06db1bdae 100644
--- a/haystack/modeling/model/prediction_head.py
+++ b/haystack/modeling/model/prediction_head.py
@@ -631,7 +631,6 @@ class QuestionAnsweringHead(PredictionHead):
 
         # Iterate over each set of document level prediction
         for pred_d, no_ans_gap, basket in zip(top_preds, no_ans_gaps, baskets):
-
             # Unpack document offsets, clear text and id
             token_offsets = basket.raw["document_offsets"]
             pred_id = basket.id_external if basket.id_external else basket.id_internal
diff --git a/haystack/modeling/model/triadaptive_model.py b/haystack/modeling/model/triadaptive_model.py
index b0b330057..62255e756 100644
--- a/haystack/modeling/model/triadaptive_model.py
+++ b/haystack/modeling/model/triadaptive_model.py
@@ -323,7 +323,6 @@ class TriAdaptiveModel(nn.Module):
 
             # Current batch consists of tables and texts
             elif any(table_mask):
-
                 # Make input two-dimensional
                 max_seq_len = kwargs["passage_input_ids"].shape[-1]
                 passage_input_ids = kwargs["passage_input_ids"].view(-1, max_seq_len)
diff --git a/haystack/modeling/training/base.py b/haystack/modeling/training/base.py
index 15ee17a08..48e66b0b2 100644
--- a/haystack/modeling/training/base.py
+++ b/haystack/modeling/training/base.py
@@ -931,7 +931,6 @@ class DistillationLoss(Module):
         for student_attention, teacher_attention, dim_mapping in zip(
             attentions, teacher_attentions[self.teacher_block_size - 1 :: self.teacher_block_size], self.dim_mappings
         ):
-
             # this wasn't described in the paper, but it was used in the original implementation
             student_attention = torch.where(
                 student_attention <= -1e2, torch.zeros_like(student_attention), student_attention
diff --git a/haystack/modeling/utils.py b/haystack/modeling/utils.py
index 81487dcab..8c849823d 100644
--- a/haystack/modeling/utils.py
+++ b/haystack/modeling/utils.py
@@ -38,7 +38,6 @@ def silence_transformers_logs(from_pretrained_func):
 
     @wraps(from_pretrained_func)
     def quiet_from_pretrained_func(cls, *args, **kwargs):
-
         # Raise the log level of Transformers
         t_logger = logging.getLogger("transformers")
         original_log_level = t_logger.level
@@ -268,6 +267,7 @@ def grouper(iterable, n: int, worker_id: int = 0, total_workers: int = 1):
     :param worker_id: the worker_id for the PyTorch DataLoader
     :param total_workers: total number of workers for the PyTorch DataLoader
     """
+
     # TODO make me comprehensible :)
     def get_iter_start_pos(gen):
         start_pos = worker_id * n
diff --git a/haystack/nodes/_json_schema.py b/haystack/nodes/_json_schema.py
index 853442d7b..20c5d8917 100644
--- a/haystack/nodes/_json_schema.py
+++ b/haystack/nodes/_json_schema.py
@@ -441,7 +441,6 @@ def update_json_schema(destination_path: Path = JSON_SCHEMAS_PATH, main_only: bo
         json.dump(get_json_schema(filename=filename, version="ignore"), json_file, indent=2)
 
     if not main_only and "rc" not in haystack_version:
-
         # Create/update the specific version file too
         filename = f"haystack-pipeline-{haystack_version}.schema.json"
         with open(destination_path / filename, "w") as json_file:
diff --git a/haystack/nodes/answer_generator/base.py b/haystack/nodes/answer_generator/base.py
index 3fa494c2f..e851015cd 100644
--- a/haystack/nodes/answer_generator/base.py
+++ b/haystack/nodes/answer_generator/base.py
@@ -32,7 +32,6 @@ class BaseGenerator(BaseComponent):
         pass
 
     def run(self, query: str, documents: List[Document], top_k: Optional[int] = None, labels: Optional[MultiLabel] = None, add_isolated_node_eval: bool = False):  # type: ignore
-
         if documents:
             results = self.predict(query=query, documents=documents, top_k=top_k)
         else:
diff --git a/haystack/nodes/answer_generator/openai.py b/haystack/nodes/answer_generator/openai.py
index f786f8512..1156dc871 100644
--- a/haystack/nodes/answer_generator/openai.py
+++ b/haystack/nodes/answer_generator/openai.py
@@ -63,7 +63,6 @@ class OpenAIAnswerGenerator(BaseGenerator):
         stop_words: Optional[List] = None,
         progress_bar: bool = True,
     ):
-
         """
         :param api_key: Your API key from OpenAI. It is required for this node to work.
         :param model: ID of the engine to use for generating the answer. You can select one of `"text-ada-001"`,
diff --git a/haystack/nodes/answer_generator/transformers.py b/haystack/nodes/answer_generator/transformers.py
index 26e83e53c..fd5dd30d0 100644
--- a/haystack/nodes/answer_generator/transformers.py
+++ b/haystack/nodes/answer_generator/transformers.py
@@ -168,7 +168,6 @@ class RAGenerator(BaseGenerator):
     def _get_contextualized_inputs(
         self, texts: List[str], query: str, titles: Optional[List[str]] = None, return_tensors: str = "pt"
     ):
-
         titles_list = titles if self.embed_title and titles is not None else [""] * len(texts)
         prefix = self.prefix if self.prefix is not None else self.model.config.generator.prefix
 
@@ -190,7 +189,6 @@ class RAGenerator(BaseGenerator):
         )
 
     def _prepare_passage_embeddings(self, docs: List[Document], embeddings: numpy.ndarray) -> torch.Tensor:
-
         # If document missing embedding, then need embedding for all the documents
         is_embedding_required = embeddings is None or any(embedding is None for embedding in embeddings)
 
diff --git a/haystack/nodes/audio/answer_to_speech.py b/haystack/nodes/audio/answer_to_speech.py
index 8b36241f5..79a9a8ec3 100644
--- a/haystack/nodes/audio/answer_to_speech.py
+++ b/haystack/nodes/audio/answer_to_speech.py
@@ -68,7 +68,6 @@ class AnswerToSpeech(BaseComponent):
     def run(self, answers: List[Answer]) -> Tuple[Dict[str, List[Answer]], str]:  # type: ignore
         audio_answers = []
         for answer in tqdm(answers, disable=not self.progress_bar, desc="Converting answers to audio"):
-
             answer_audio = self.converter.text_to_audio_file(
                 text=answer.answer, generated_audio_dir=self.generated_audio_dir, **self.params
             )
diff --git a/haystack/nodes/audio/document_to_speech.py b/haystack/nodes/audio/document_to_speech.py
index 6a1aa884b..9bb492602 100644
--- a/haystack/nodes/audio/document_to_speech.py
+++ b/haystack/nodes/audio/document_to_speech.py
@@ -56,7 +56,6 @@ class DocumentToSpeech(BaseComponent):
     def run(self, documents: List[Document]) -> Tuple[Dict[str, List[Document]], str]:  # type: ignore
         audio_documents = []
         for doc in tqdm(documents):
-
             content_audio = self.converter.text_to_audio_file(
                 text=doc.content, generated_audio_dir=self.generated_audio_dir, **self.params
             )
diff --git a/haystack/nodes/base.py b/haystack/nodes/base.py
index d43d92430..03def748b 100644
--- a/haystack/nodes/base.py
+++ b/haystack/nodes/base.py
@@ -26,7 +26,6 @@ def exportable_to_yaml(init_func):
 
     @wraps(init_func)
     def wrapper_exportable_to_yaml(self, *args, **kwargs):
-
         # Create the configuration dictionary if it doesn't exist yet
         if not self._component_config:
             self._component_config = {"params": {}, "type": type(self).__name__}
@@ -68,7 +67,6 @@ class BaseComponent(ABC):
     # __init_subclass__ is invoked when a subclass of BaseComponent is _imported_
     # (not instantiated). It works approximately as a metaclass.
     def __init_subclass__(cls, **kwargs):
-
         super().__init_subclass__(**kwargs)
 
         # Each component must specify the number of outgoing edges (= different outputs).
diff --git a/haystack/nodes/connector/crawler.py b/haystack/nodes/connector/crawler.py
index 6f055122a..0864b7175 100644
--- a/haystack/nodes/connector/crawler.py
+++ b/haystack/nodes/connector/crawler.py
@@ -468,7 +468,6 @@ class Crawler(BaseComponent):
         already_found_links: Optional[List] = None,
         loading_wait_time: Optional[int] = None,
     ) -> set:
-
         self.driver.get(base_url)
         if loading_wait_time is not None:
             time.sleep(loading_wait_time)
@@ -491,7 +490,6 @@ class Crawler(BaseComponent):
                     not self._is_inpage_navigation(base_url=base_url, sub_link=sub_link)
                 ):
                     if filter_pattern is not None:
-
                         if filter_pattern.search(sub_link):
                             sub_links.add(sub_link)
                     else:
diff --git a/haystack/nodes/extractor/entity.py b/haystack/nodes/extractor/entity.py
index 0b284ff40..c99a345ca 100644
--- a/haystack/nodes/extractor/entity.py
+++ b/haystack/nodes/extractor/entity.py
@@ -502,7 +502,6 @@ def simplify_ner_for_qa(output):
     """
     compact_output = []
     for answer in output["answers"]:
-
         entities = []
         for entity in answer.meta["entities"]:
             if (
diff --git a/haystack/nodes/file_converter/azure.py b/haystack/nodes/file_converter/azure.py
index 281c5bfd1..f4181cecf 100644
--- a/haystack/nodes/file_converter/azure.py
+++ b/haystack/nodes/file_converter/azure.py
@@ -94,7 +94,6 @@ class AzureConverter(BaseConverter):
         pages: Optional[str] = None,
         known_language: Optional[str] = None,
     ) -> List[Document]:
-
         """
         Extract text and tables from a PDF, JPEG, PNG, BMP or TIFF file using Azure's Form Recognizer service.
 
diff --git a/haystack/nodes/file_converter/parsr.py b/haystack/nodes/file_converter/parsr.py
index 736c6de6c..e4036be04 100644
--- a/haystack/nodes/file_converter/parsr.py
+++ b/haystack/nodes/file_converter/parsr.py
@@ -257,7 +257,6 @@ class ParsrConverter(BaseConverter):
         meta: Optional[Dict[str, Any]] = None,
         id_hash_keys: Optional[List[str]] = None,
     ) -> Document:
-
         row_idx_start = 0
         caption = ""
         number_of_columns = max(len(row["content"]) for row in element["content"])
diff --git a/haystack/nodes/image_to_text/base.py b/haystack/nodes/image_to_text/base.py
index b382e0bbf..01b4a6764 100644
--- a/haystack/nodes/image_to_text/base.py
+++ b/haystack/nodes/image_to_text/base.py
@@ -29,7 +29,6 @@ class BaseImageToText(BaseComponent):
         pass
 
     def run(self, file_paths: Optional[List[str]] = None, documents: Optional[List[Document]] = None):  # type: ignore
-
         if file_paths is None and documents is None:
             raise ValueError("You must either specify documents or image file_paths to process.")
 
@@ -49,5 +48,4 @@ class BaseImageToText(BaseComponent):
     def run_batch(  # type: ignore
         self, file_paths: Optional[List[str]] = None, documents: Optional[List[Document]] = None
     ):
-
         return self.run(file_paths=file_paths, documents=documents)
diff --git a/haystack/nodes/other/document_merger.py b/haystack/nodes/other/document_merger.py
index 435568000..72677fd36 100644
--- a/haystack/nodes/other/document_merger.py
+++ b/haystack/nodes/other/document_merger.py
@@ -70,7 +70,6 @@ class DocumentMerger(BaseComponent):
     def _keep_common_keys(self, list_of_dicts: List[Dict[str, Any]]) -> dict:
         merge_dictionary = deepcopy(list_of_dicts[0])
         for key, value in list_of_dicts[0].items():
-
             # if not all other dicts have this key, delete directly
             if not all(key in dict.keys() for dict in list_of_dicts):
                 del merge_dictionary[key]
diff --git a/haystack/nodes/other/join.py b/haystack/nodes/other/join.py
index 7caf0f8f4..f96ef03a2 100644
--- a/haystack/nodes/other/join.py
+++ b/haystack/nodes/other/join.py
@@ -7,7 +7,6 @@ from haystack.nodes.base import BaseComponent
 
 
 class JoinNode(BaseComponent):
-
     outgoing_edges: int = 1
 
     def run(  # type: ignore
diff --git a/haystack/nodes/other/join_docs.py b/haystack/nodes/other/join_docs.py
index 45339271b..27761535c 100644
--- a/haystack/nodes/other/join_docs.py
+++ b/haystack/nodes/other/join_docs.py
@@ -90,7 +90,7 @@ class JoinDocuments(JoinNode):
             top_k_join = len(sorted_docs)
 
         docs = []
-        for (id, score) in sorted_docs[:top_k_join]:
+        for id, score in sorted_docs[:top_k_join]:
             doc = document_map[id]
             doc.score = score
             docs.append(doc)
diff --git a/haystack/nodes/other/shaper.py b/haystack/nodes/other/shaper.py
index bb6933bb6..ca5669b44 100644
--- a/haystack/nodes/other/shaper.py
+++ b/haystack/nodes/other/shaper.py
@@ -397,7 +397,6 @@ class Shaper(BaseComponent):
         meta: Optional[dict] = None,
         invocation_context: Optional[Dict[str, Any]] = None,
     ) -> Tuple[Dict, str]:
-
         return self.run(
             query=query,
             file_paths=file_paths,
diff --git a/haystack/nodes/preprocessor/preprocessor.py b/haystack/nodes/preprocessor/preprocessor.py
index 311603c67..e384f4c3b 100644
--- a/haystack/nodes/preprocessor/preprocessor.py
+++ b/haystack/nodes/preprocessor/preprocessor.py
@@ -141,7 +141,6 @@ class PreProcessor(BasePreProcessor):
         split_respect_sentence_boundary: Optional[bool] = None,
         id_hash_keys: Optional[List[str]] = None,
     ) -> List[Document]:
-
         """
         Perform document cleaning and splitting. Can take a single document or a list of documents as input and returns a list of documents.
         """
@@ -323,7 +322,8 @@ class PreProcessor(BasePreProcessor):
     ) -> List[Document]:
         """Perform document splitting on a single document. This method can split on different units, at different lengths,
         with different strides. It can also respect sentence boundaries. Its exact functionality is defined by
-        the parameters passed into PreProcessor.__init__(). Takes a single document as input and returns a list of documents."""
+        the parameters passed into PreProcessor.__init__(). Takes a single document as input and returns a list of documents.
+        """
         if id_hash_keys is None:
             id_hash_keys = self.id_hash_keys
 
@@ -762,7 +762,6 @@ class PreProcessor(BasePreProcessor):
         return sentences
 
     def _load_sentence_tokenizer(self, language_name: Optional[str]) -> nltk.tokenize.punkt.PunktSentenceTokenizer:
-
         # Try to load a custom model from 'tokenizer_model_path'
         if self.tokenizer_model_folder is not None:
             tokenizer_model_path = Path(self.tokenizer_model_folder).absolute() / f"{self.language}.pickle"
diff --git a/haystack/nodes/prompt/prompt_node.py b/haystack/nodes/prompt/prompt_node.py
index 0bc2eb2e4..0073717e1 100644
--- a/haystack/nodes/prompt/prompt_node.py
+++ b/haystack/nodes/prompt/prompt_node.py
@@ -31,7 +31,6 @@ logger = logging.getLogger(__name__)
 
 
 class BasePromptTemplate(BaseComponent):
-
     outgoing_edges = 1
 
     def run(
diff --git a/haystack/nodes/reader/farm.py b/haystack/nodes/reader/farm.py
index 10a2d3c20..1bdc507fd 100644
--- a/haystack/nodes/reader/farm.py
+++ b/haystack/nodes/reader/farm.py
@@ -70,7 +70,6 @@ class FARMReader(BaseReader):
         use_auth_token: Optional[Union[str, bool]] = None,
         max_query_length: int = 64,
     ):
-
         """
         :param model_name_or_path: Directory of a saved model or the name of a public model e.g. 'bert-base-cased',
         'deepset/bert-base-cased-squad2', 'deepset/bert-base-cased-squad2', 'distilbert-base-uncased-distilled-squad'.
diff --git a/haystack/nodes/retriever/_embedding_encoder.py b/haystack/nodes/retriever/_embedding_encoder.py
index 564d9f834..a54048b58 100644
--- a/haystack/nodes/retriever/_embedding_encoder.py
+++ b/haystack/nodes/retriever/_embedding_encoder.py
@@ -43,7 +43,6 @@ logger = logging.getLogger(__name__)
 
 class _DefaultEmbeddingEncoder(_BaseEmbeddingEncoder):
     def __init__(self, retriever: "EmbeddingRetriever"):
-
         self.embedding_model = Inferencer.load(
             retriever.embedding_model,
             revision=retriever.model_version,
@@ -244,7 +243,6 @@ class _SentenceTransformersEmbeddingEncoder(_BaseEmbeddingEncoder):
 
 class _RetribertEmbeddingEncoder(_BaseEmbeddingEncoder):
     def __init__(self, retriever: "EmbeddingRetriever"):
-
         self.progress_bar = retriever.progress_bar
         self.batch_size = retriever.batch_size
         self.max_length = retriever.max_seq_len
@@ -310,7 +308,6 @@ class _RetribertEmbeddingEncoder(_BaseEmbeddingEncoder):
         return np.concatenate(embeddings)
 
     def _create_dataloader(self, text_to_encode: List[dict]) -> NamedDataLoader:
-
         dataset, tensor_names = self.dataset_from_dicts(text_to_encode)
         dataloader = NamedDataLoader(
             dataset=dataset, sampler=SequentialSampler(dataset), batch_size=self.batch_size, tensor_names=tensor_names
diff --git a/haystack/nodes/retriever/multimodal/embedder.py b/haystack/nodes/retriever/multimodal/embedder.py
index 9267192bd..e9ba4a90d 100644
--- a/haystack/nodes/retriever/multimodal/embedder.py
+++ b/haystack/nodes/retriever/multimodal/embedder.py
@@ -150,7 +150,6 @@ class MultiModalEmbedder:
             # Get output for each model
             outputs_by_type: Dict[str, torch.Tensor] = {}  # replace str with ContentTypes starting Python3.8
             for data_type, data in data_by_type.items():
-
                 model = self.models.get(data_type)
                 if not model:
                     raise ModelingError(
diff --git a/haystack/nodes/summarizer/base.py b/haystack/nodes/summarizer/base.py
index 917f1723e..804f53caa 100644
--- a/haystack/nodes/summarizer/base.py
+++ b/haystack/nodes/summarizer/base.py
@@ -30,7 +30,6 @@ class BaseSummarizer(BaseComponent):
         pass
 
     def run(self, documents: List[Document]):  # type: ignore
-
         results: Dict = {"documents": []}
 
         if documents:
@@ -41,7 +40,6 @@ class BaseSummarizer(BaseComponent):
     def run_batch(  # type: ignore
         self, documents: Union[List[Document], List[List[Document]]], batch_size: Optional[int] = None
     ):
-
         results = self.predict_batch(documents=documents, batch_size=batch_size)
 
         return {"documents": results}, "output_1"
diff --git a/haystack/pipelines/base.py b/haystack/pipelines/base.py
index 5c9dbd60c..d5a04c413 100644
--- a/haystack/pipelines/base.py
+++ b/haystack/pipelines/base.py
@@ -1513,7 +1513,6 @@ class Pipeline:
 
         partial_dfs = []
         for i, (query, query_labels) in enumerate(zip(queries, query_labels_per_query)):
-
             if query_labels is None or query_labels.labels is None:
                 logger.warning("There is no label for query '%s'. Query will be omitted.", query)
                 continue
@@ -2205,7 +2204,6 @@ class Pipeline:
         """
         if params:
             if not all(node_id in self.graph.nodes for node_id in params.keys()):
-
                 # Might be a non-targeted param. Verify that too
                 not_a_node = set(params.keys()) - set(self.graph.nodes)
                 # "debug" will be picked up by _dispatch_run, see its code
diff --git a/haystack/pipelines/config.py b/haystack/pipelines/config.py
index 9e1b5570c..9aed6d3b6 100644
--- a/haystack/pipelines/config.py
+++ b/haystack/pipelines/config.py
@@ -283,11 +283,9 @@ def validate_schema(pipeline_config: Dict, strict_version_check: bool = False, e
             break
 
         except ValidationError as validation:
-
             # If the validation comes from an unknown node, try to find it and retry:
             if list(validation.relative_schema_path) == ["properties", "components", "items", "anyOf"]:
                 if validation.instance["type"] not in loaded_custom_nodes:
-
                     logger.info(
                         "Missing definition for node of type %s. Looking into local classes...",
                         validation.instance["type"],
@@ -431,7 +429,6 @@ def _add_node_to_pipeline_graph(
 
     try:
         for input_node in node["inputs"]:
-
             # Separate node and edge name, if specified
             input_node_name, input_edge_name = input_node, None
             if "." in input_node:
diff --git a/haystack/pipelines/standard_pipelines.py b/haystack/pipelines/standard_pipelines.py
index b82dd03e1..f3556d40d 100644
--- a/haystack/pipelines/standard_pipelines.py
+++ b/haystack/pipelines/standard_pipelines.py
@@ -122,7 +122,6 @@ class BaseStandardPipeline(ABC):
         context_matching_boost_split_overlaps: bool = True,
         context_matching_threshold: float = 65.0,
     ) -> EvaluationResult:
-
         """
         Evaluates the pipeline by running the pipeline once per query in debug mode
         and putting together all data that is needed for evaluation, e.g. calculating metrics.
@@ -181,7 +180,6 @@ class BaseStandardPipeline(ABC):
         context_matching_boost_split_overlaps: bool = True,
         context_matching_threshold: float = 65.0,
     ) -> EvaluationResult:
-
         """
          Evaluates the pipeline by running the pipeline once per query in the debug mode
          and putting together all data that is needed for evaluation, for example, calculating metrics.
diff --git a/haystack/utils/augment_squad.py b/haystack/utils/augment_squad.py
index 17bd85079..2d265d1a1 100644
--- a/haystack/utils/augment_squad.py
+++ b/haystack/utils/augment_squad.py
@@ -126,7 +126,6 @@ def get_replacements(
     batch_size: int = 16,
     device: torch.device = torch.device("cpu:0"),
 ) -> List[List[str]]:
-
     """Returns a list of possible replacements for each word in the text."""
     input_ids, words, word_subword_mapping = tokenize_and_extract_words(text, tokenizer)
 
diff --git a/haystack/utils/export_utils.py b/haystack/utils/export_utils.py
index fea4ea0fd..0ca4e5859 100644
--- a/haystack/utils/export_utils.py
+++ b/haystack/utils/export_utils.py
@@ -123,7 +123,6 @@ def print_questions(results: dict):
         for query, answers in zip(results["queries"], results["answers"]):
             print(f" - Q: {query}")
             for answer in answers:
-
                 # Verify that the pairs contains Answers under the `answer` key
                 if not isinstance(answer, Answer):
                     raise ValueError(
diff --git a/haystack/utils/import_utils.py b/haystack/utils/import_utils.py
index 97e28cbc0..a021e41f5 100644
--- a/haystack/utils/import_utils.py
+++ b/haystack/utils/import_utils.py
@@ -44,7 +44,6 @@ def _missing_dependency_stub_factory(classname: str, dep_group: str, import_erro
 
     class MissingDependency:
         def __init__(self, *args, **kwargs):
-
             _optional_component_not_installed(classname, dep_group, import_error)
 
         def __getattr__(self, *a, **k):
diff --git a/haystack/utils/squad_to_dpr.py b/haystack/utils/squad_to_dpr.py
index 0215df7f1..f90568574 100644
--- a/haystack/utils/squad_to_dpr.py
+++ b/haystack/utils/squad_to_dpr.py
@@ -132,7 +132,6 @@ def add_is_impossible(squad_data: dict, json_file_path: Path):
     squad_articles = list(squad_data["data"])  # create new list with this list although lists are inmutable :/
     for article in squad_articles:
         for paragraph in article["paragraphs"]:
-
             for question in paragraph["qas"]:
                 question["is_impossible"] = False
 
diff --git a/pyproject.toml b/pyproject.toml
index 8c7ceffdd..0dbc04b81 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -201,9 +201,8 @@ dev = [
   "python-multipart",
   "psutil",
   # Linting
-  "pylint==2.15.10",
-  # Code formatting
-  "black[jupyter]==22.6.0",
+  "pylint",
+  "farm-haystack[formatting]",
   # Documentation
   "pydoc-markdown",
   "mkdocs",
@@ -211,6 +210,13 @@ dev = [
   "watchdog",
   "requests-cache",
 ]
+
+formatting = [
+  # Version specified following Black stability policy:
+  # https://black.readthedocs.io/en/stable/the_black_code_style/index.html#stability-policy
+  "black[jupyter]~=23.0",
+]
+
 all = [
   "farm-haystack[docstores,audio,crawler,preprocessing,ocr,ray,dev,onnx,beir]",
 ]
diff --git a/rest_api/test/test_rest_api.py b/rest_api/test/test_rest_api.py
index 330ffcd53..3a9680965 100644
--- a/rest_api/test/test_rest_api.py
+++ b/rest_api/test/test_rest_api.py
@@ -36,7 +36,6 @@ def test_single_worker_warning_for_indexing_pipelines(caplog):
 
 
 def test_check_error_for_pipeline_not_found():
-
     yaml_pipeline_path = Path(__file__).parent.resolve() / "samples" / "test.in-memory-haystack-pipeline.yml"
     p, _ = _load_pipeline(yaml_pipeline_path, "ThisPipelineDoesntExist")
     assert p is None
@@ -50,7 +49,6 @@ def test_overwrite_params_with_env_variables_when_no_params_in_pipeline_yaml(mon
 
 
 def test_bad_yaml_pipeline_configuration_error():
-
     yaml_pipeline_path = Path(__file__).parent.resolve() / "samples" / "test.bogus_pipeline.yml"
     with pytest.raises(PipelineSchemaError) as excinfo:
         _load_pipeline(yaml_pipeline_path, None)
diff --git a/test/benchmarks/model_distillation.py b/test/benchmarks/model_distillation.py
index b870b42f8..b59daca81 100644
--- a/test/benchmarks/model_distillation.py
+++ b/test/benchmarks/model_distillation.py
@@ -20,6 +20,7 @@ download_links = {
     },
 }
 
+
 # loading json config file
 def load_config(path: str) -> dict:
     with open(path, "r") as f:
diff --git a/test/benchmarks/retriever.py b/test/benchmarks/retriever.py
index e4698c3e5..b72208b80 100644
--- a/test/benchmarks/retriever.py
+++ b/test/benchmarks/retriever.py
@@ -53,7 +53,6 @@ def benchmark_indexing(
     save_markdown,
     **kwargs,
 ):
-
     retriever_results = []
     for n_docs in n_docs_options:
         for retriever_name, doc_store_name in retriever_doc_stores:
diff --git a/test/benchmarks/retriever_simplified.py b/test/benchmarks/retriever_simplified.py
index 4ddc2a5a8..d3ae4ab50 100644
--- a/test/benchmarks/retriever_simplified.py
+++ b/test/benchmarks/retriever_simplified.py
@@ -14,7 +14,6 @@ from utils import get_document_store
 
 
 def benchmark_querying(index_type, n_docs=100_000, similarity="dot_product"):
-
     doc_index = "document"
     label_index = "label"
 
diff --git a/test/conftest.py b/test/conftest.py
index 699daf76b..da9b1e184 100644
--- a/test/conftest.py
+++ b/test/conftest.py
@@ -730,7 +730,6 @@ def retriever_with_docs(request, document_store_with_docs):
 
 
 def get_retriever(retriever_type, document_store):
-
     if retriever_type == "dpr":
         retriever = DensePassageRetriever(
             document_store=document_store,
diff --git a/test/document_stores/test_deepsetcloud.py b/test/document_stores/test_deepsetcloud.py
index d0d33a8c6..41d1b0a8e 100644
--- a/test/document_stores/test_deepsetcloud.py
+++ b/test/document_stores/test_deepsetcloud.py
@@ -64,7 +64,6 @@ def dc_api_mock(request):
 @pytest.mark.integration
 @pytest.mark.usefixtures("dc_api_mock")
 class TestDeepsetCloudDocumentStore:
-
     # Fixtures
 
     @pytest.fixture
@@ -191,7 +190,6 @@ class TestDeepsetCloudDocumentStore:
             assert doc.meta["file_id"] == first_doc.meta["file_id"]
 
     def test_query(self, ds):
-
         with open(SAMPLES_PATH / "dc" / "query_winterfell.response", "r") as f:
             query_winterfell_response = f.read()
             query_winterfell_docs = json.loads(query_winterfell_response)
diff --git a/test/document_stores/test_elasticsearch.py b/test/document_stores/test_elasticsearch.py
index 5b9ee1577..5791026b1 100644
--- a/test/document_stores/test_elasticsearch.py
+++ b/test/document_stores/test_elasticsearch.py
@@ -223,7 +223,6 @@ class TestElasticsearchDocumentStore(DocumentStoreBaseTestAbstract, SearchEngine
 
     @pytest.mark.integration
     def test_existing_alias_missing_fields(self, ds):
-
         client = ds.client
         client.indices.delete(index="haystack_existing_alias_1", ignore=[404])
         client.indices.delete(index="haystack_existing_alias_2", ignore=[404])
diff --git a/test/document_stores/test_opensearch.py b/test/document_stores/test_opensearch.py
index f043536be..b89f8a9d0 100644
--- a/test/document_stores/test_opensearch.py
+++ b/test/document_stores/test_opensearch.py
@@ -24,7 +24,6 @@ from .test_search_engine import SearchEngineDocumentStoreTestAbstract
 
 
 class TestOpenSearchDocumentStore(DocumentStoreBaseTestAbstract, SearchEngineDocumentStoreTestAbstract):
-
     # Constants
     query_emb = np.random.random_sample(size=(2, 2))
     index_name = __name__
diff --git a/test/document_stores/test_pinecone.py b/test/document_stores/test_pinecone.py
index 37fd78ef2..626f41a72 100644
--- a/test/document_stores/test_pinecone.py
+++ b/test/document_stores/test_pinecone.py
@@ -21,7 +21,6 @@ META_FIELDS = ["meta_field", "name", "date", "numeric_field", "odd_document"]
 
 
 class TestPineconeDocumentStore(DocumentStoreBaseTestAbstract):
-
     # Fixtures
 
     @pytest.fixture
diff --git a/test/mocks/pinecone.py b/test/mocks/pinecone.py
index b9561ce2a..2c247dbf4 100644
--- a/test/mocks/pinecone.py
+++ b/test/mocks/pinecone.py
@@ -11,6 +11,7 @@ logger = logging.getLogger(__name__)
 # Mock Pinecone instance
 CONFIG: dict = {"api_key": None, "environment": None, "indexes": {}}
 
+
 # Mock Pinecone Index instance
 class IndexObject:
     def __init__(
diff --git a/test/modeling/_test_feature_extraction_end2end.py b/test/modeling/_test_feature_extraction_end2end.py
index 83651621f..ed4f02f7c 100644
--- a/test/modeling/_test_feature_extraction_end2end.py
+++ b/test/modeling/_test_feature_extraction_end2end.py
@@ -63,7 +63,7 @@ def convert_offset_from_word_reference_to_text_reference(offsets, words, word_sp
     Not a fixture, just a utility.
     """
     token_offsets = []
-    for ((start, end), word_index) in zip(offsets, words):
+    for (start, end), word_index in zip(offsets, words):
         word_start = word_spans[word_index][0]
         token_offsets.append((start + word_start, end + word_start))
     return token_offsets
diff --git a/test/modeling/test_feature_extraction.py b/test/modeling/test_feature_extraction.py
index 705411352..0e1a1b7e5 100644
--- a/test/modeling/test_feature_extraction.py
+++ b/test/modeling/test_feature_extraction.py
@@ -67,7 +67,6 @@ FEATURE_EXTRACTORS_TO_TEST = ["bert-base-cased"]
 @pytest.mark.integration
 @pytest.mark.parametrize("model_name", FEATURE_EXTRACTORS_TO_TEST)
 def test_load_modify_save_load(tmp_path, model_name: str):
-
     # Load base tokenizer
     feature_extractor = FeatureExtractor(pretrained_model_name_or_path=model_name, do_lower_case=False)
 
diff --git a/test/nodes/test_document_classifier.py b/test/nodes/test_document_classifier.py
index be98e3f00..d0356568a 100644
--- a/test/nodes/test_document_classifier.py
+++ b/test/nodes/test_document_classifier.py
@@ -24,7 +24,6 @@ def test_document_classifier(document_classifier):
 
 @pytest.mark.integration
 def test_document_classifier_details(document_classifier):
-
     docs = [Document(content="""That's good. I like it."""), Document(content="""That's bad. I don't like it.""")]
     results = document_classifier.predict(documents=docs)
     for doc in results:
@@ -78,7 +77,6 @@ def test_zero_shot_document_classifier(zero_shot_document_classifier):
 
 @pytest.mark.integration
 def test_zero_shot_document_classifier_details(zero_shot_document_classifier):
-
     docs = [Document(content="""That's good. I like it."""), Document(content="""That's bad. I don't like it.""")]
     results = zero_shot_document_classifier.predict(documents=docs)
     for doc in results:
diff --git a/test/nodes/test_extractor.py b/test/nodes/test_extractor.py
index 812eb1b05..4c1511772 100644
--- a/test/nodes/test_extractor.py
+++ b/test/nodes/test_extractor.py
@@ -12,7 +12,6 @@ from ..conftest import SAMPLES_PATH
 
 @pytest.mark.parametrize("document_store_with_docs", ["elasticsearch"], indirect=True)
 def test_extractor(document_store_with_docs):
-
     es_retriever = BM25Retriever(document_store=document_store_with_docs)
     ner = EntityExtractor(model_name_or_path="elastic/distilbert-base-cased-finetuned-conll03-english")
     reader = FARMReader(model_name_or_path="deepset/tinyroberta-squad2", num_processes=0)
@@ -32,7 +31,6 @@ def test_extractor(document_store_with_docs):
 
 @pytest.mark.parametrize("document_store_with_docs", ["elasticsearch"], indirect=True)
 def test_extractor_batch_single_query(document_store_with_docs):
-
     es_retriever = BM25Retriever(document_store=document_store_with_docs)
     ner = EntityExtractor(model_name_or_path="elastic/distilbert-base-cased-finetuned-conll03-english")
     reader = FARMReader(model_name_or_path="deepset/tinyroberta-squad2", num_processes=0)
@@ -52,7 +50,6 @@ def test_extractor_batch_single_query(document_store_with_docs):
 
 @pytest.mark.parametrize("document_store_with_docs", ["elasticsearch"], indirect=True)
 def test_extractor_batch_multiple_queries(document_store_with_docs):
-
     es_retriever = BM25Retriever(document_store=document_store_with_docs)
     ner = EntityExtractor(model_name_or_path="elastic/distilbert-base-cased-finetuned-conll03-english")
     reader = FARMReader(model_name_or_path="deepset/tinyroberta-squad2", num_processes=0)
@@ -76,7 +73,6 @@ def test_extractor_batch_multiple_queries(document_store_with_docs):
 
 @pytest.mark.parametrize("document_store_with_docs", ["elasticsearch"], indirect=True)
 def test_extractor_output_simplifier(document_store_with_docs):
-
     es_retriever = BM25Retriever(document_store=document_store_with_docs)
     ner = EntityExtractor(model_name_or_path="elastic/distilbert-base-cased-finetuned-conll03-english")
     reader = FARMReader(model_name_or_path="deepset/tinyroberta-squad2", num_processes=0)
diff --git a/test/nodes/test_extractor_translation.py b/test/nodes/test_extractor_translation.py
index b1ad8a56e..818c7854c 100644
--- a/test/nodes/test_extractor_translation.py
+++ b/test/nodes/test_extractor_translation.py
@@ -4,6 +4,7 @@ from haystack.pipelines import TranslationWrapperPipeline, ExtractiveQAPipeline
 from haystack.nodes import DensePassageRetriever, EmbeddingRetriever
 from .test_summarizer import SPLIT_DOCS
 
+
 # Keeping few (retriever,document_store,reader) combination to reduce test time
 @pytest.mark.integration
 @pytest.mark.elasticsearch
diff --git a/test/nodes/test_shaper.py b/test/nodes/test_shaper.py
index 4c3cf01a7..9f8b0320c 100644
--- a/test/nodes/test_shaper.py
+++ b/test/nodes/test_shaper.py
@@ -813,7 +813,6 @@ def test_chain_shapers_yaml_2(tmp_path):
 
 
 def test_with_prompt_node(tmp_path):
-
     with open(tmp_path / "tmp_config.yml", "w") as tmp_file:
         tmp_file.write(
             f"""
@@ -863,7 +862,6 @@ def test_with_prompt_node(tmp_path):
 
 
 def test_with_multiple_prompt_nodes(tmp_path):
-
     with open(tmp_path / "tmp_config.yml", "w") as tmp_file:
         tmp_file.write(
             f"""
diff --git a/test/pipelines/test_eval.py b/test/pipelines/test_eval.py
index 92e76a808..bbb83656a 100644
--- a/test/pipelines/test_eval.py
+++ b/test/pipelines/test_eval.py
@@ -1297,7 +1297,6 @@ def test_extractive_qa_eval_isolated(reader, retriever_with_docs):
 @pytest.mark.parametrize("document_store_with_docs", ["memory"], indirect=True)
 @pytest.mark.parametrize("reader", ["farm"], indirect=True)
 def test_extractive_qa_eval_wrong_examples(reader, retriever_with_docs):
-
     labels = [
         MultiLabel(
             labels=[
@@ -1345,7 +1344,6 @@ def test_extractive_qa_eval_wrong_examples(reader, retriever_with_docs):
 @pytest.mark.parametrize("document_store_with_docs", ["memory"], indirect=True)
 @pytest.mark.parametrize("reader", ["farm"], indirect=True)
 def test_extractive_qa_print_eval_report(reader, retriever_with_docs):
-
     labels = [
         MultiLabel(
             labels=[
@@ -1483,7 +1481,6 @@ def test_faq_calculate_metrics(retriever_with_docs):
 @pytest.mark.parametrize("document_store_with_docs", ["memory"], indirect=True)
 @pytest.mark.parametrize("reader", ["farm"], indirect=True)
 def test_extractive_qa_eval_translation(reader, retriever_with_docs):
-
     # FIXME it makes no sense to have DE->EN input and DE->EN output, right?
     #  Yet switching direction breaks the test. TO BE FIXED.
     input_translator = TransformersTranslator(model_name_or_path="Helsinki-NLP/opus-mt-de-en")
diff --git a/test/pipelines/test_eval_batch.py b/test/pipelines/test_eval_batch.py
index fcdf4f6ba..bcb00e61c 100644
--- a/test/pipelines/test_eval_batch.py
+++ b/test/pipelines/test_eval_batch.py
@@ -637,7 +637,6 @@ def test_extractive_qa_eval_isolated(reader, retriever_with_docs):
 @pytest.mark.parametrize("document_store_with_docs", ["memory"], indirect=True)
 @pytest.mark.parametrize("reader", ["farm"], indirect=True)
 def test_extractive_qa_eval_wrong_examples(reader, retriever_with_docs):
-
     labels = [
         MultiLabel(
             labels=[
@@ -685,7 +684,6 @@ def test_extractive_qa_eval_wrong_examples(reader, retriever_with_docs):
 @pytest.mark.parametrize("document_store_with_docs", ["memory"], indirect=True)
 @pytest.mark.parametrize("reader", ["farm"], indirect=True)
 def test_extractive_qa_print_eval_report(reader, retriever_with_docs):
-
     labels = [
         MultiLabel(
             labels=[
diff --git a/test/pipelines/test_pipeline.py b/test/pipelines/test_pipeline.py
index b9b4c4888..833777574 100644
--- a/test/pipelines/test_pipeline.py
+++ b/test/pipelines/test_pipeline.py
@@ -677,7 +677,6 @@ def test_generate_code_can_handle_weak_cyclic_pipelines():
 
 
 def test_pipeline_classify_type(tmp_path):
-
     pipe = GenerativeQAPipeline(generator=MockSeq2SegGenerator(), retriever=MockRetriever())
     assert pipe.get_type().startswith("GenerativeQAPipeline")
 
diff --git a/test/pipelines/test_pipeline_debug_and_validation.py b/test/pipelines/test_pipeline_debug_and_validation.py
index 1fd92c3f4..134584e56 100644
--- a/test/pipelines/test_pipeline_debug_and_validation.py
+++ b/test/pipelines/test_pipeline_debug_and_validation.py
@@ -55,7 +55,6 @@ def test_node_names_validation(document_store_with_docs, tmp_path):
 @pytest.mark.elasticsearch
 @pytest.mark.parametrize("document_store_with_docs", ["elasticsearch"], indirect=True)
 def test_debug_attributes_global(document_store_with_docs, tmp_path):
-
     es_retriever = BM25Retriever(document_store=document_store_with_docs)
     reader = FARMReader(model_name_or_path="deepset/minilm-uncased-squad2", num_processes=0)
 
@@ -85,7 +84,6 @@ def test_debug_attributes_global(document_store_with_docs, tmp_path):
 @pytest.mark.elasticsearch
 @pytest.mark.parametrize("document_store_with_docs", ["elasticsearch"], indirect=True)
 def test_debug_attributes_per_node(document_store_with_docs, tmp_path):
-
     es_retriever = BM25Retriever(document_store=document_store_with_docs)
     reader = FARMReader(model_name_or_path="deepset/minilm-uncased-squad2", num_processes=0)
 
@@ -111,7 +109,6 @@ def test_debug_attributes_per_node(document_store_with_docs, tmp_path):
 @pytest.mark.elasticsearch
 @pytest.mark.parametrize("document_store_with_docs", ["elasticsearch"], indirect=True)
 def test_debug_attributes_for_join_nodes(document_store_with_docs, tmp_path):
-
     es_retriever_1 = BM25Retriever(document_store=document_store_with_docs)
     es_retriever_2 = BM25Retriever(document_store=document_store_with_docs)
 
@@ -145,7 +142,6 @@ def test_debug_attributes_for_join_nodes(document_store_with_docs, tmp_path):
 @pytest.mark.elasticsearch
 @pytest.mark.parametrize("document_store_with_docs", ["elasticsearch"], indirect=True)
 def test_global_debug_attributes_override_node_ones(document_store_with_docs, tmp_path):
-
     es_retriever = BM25Retriever(document_store=document_store_with_docs)
     reader = FARMReader(model_name_or_path="deepset/minilm-uncased-squad2", num_processes=0)