CI: fix format after newly introduced formatting rules from ruff release (#8696)

Author: mathislucka

haystack/components/audio/whisper_local.py

@@ -72,7 +72,7 @@ def __init__(
         whisper_import.check()
         if model not in get_args(WhisperLocalModel):
             raise ValueError(
-                f"Model name '{model}' not recognized. Choose one among: " f"{', '.join(get_args(WhisperLocalModel))}."
+                f"Model name '{model}' not recognized. Choose one among: {', '.join(get_args(WhisperLocalModel))}."
             )
         self.model = model
         self.whisper_params = whisper_params or {}

haystack/components/converters/openapi_functions.py

@@ -249,8 +249,7 @@ def _parse_openapi_spec(self, content: str) -> Dict[str, Any]:
             open_api_spec_content = yaml.safe_load(content)
         except yaml.YAMLError:
             error_message = (
-                "Failed to parse the OpenAPI specification. "
-                "The content does not appear to be valid JSON or YAML.\n\n"
+                "Failed to parse the OpenAPI specification. The content does not appear to be valid JSON or YAML.\n\n"
             )
             raise RuntimeError(error_message, content)
 

haystack/components/generators/chat/hugging_face_local.py

@@ -148,7 +148,7 @@ def __init__(
 
         if task not in PIPELINE_SUPPORTED_TASKS:
             raise ValueError(
-                f"Task '{task}' is not supported. " f"The supported tasks are: {', '.join(PIPELINE_SUPPORTED_TASKS)}."
+                f"Task '{task}' is not supported. The supported tasks are: {', '.join(PIPELINE_SUPPORTED_TASKS)}."
             )
         huggingface_pipeline_kwargs["task"] = task
 

haystack/components/rankers/lost_in_the_middle.py

@@ -51,7 +51,7 @@ def __init__(self, word_count_threshold: Optional[int] = None, top_k: Optional[i
         """
         if isinstance(word_count_threshold, int) and word_count_threshold <= 0:
             raise ValueError(
-                f"Invalid value for word_count_threshold: {word_count_threshold}. " f"word_count_threshold must be > 0."
+                f"Invalid value for word_count_threshold: {word_count_threshold}. word_count_threshold must be > 0."
             )
         if isinstance(top_k, int) and top_k <= 0:
             raise ValueError(f"top_k must be > 0, but got {top_k}")
@@ -78,7 +78,7 @@ def run(
         """
         if isinstance(word_count_threshold, int) and word_count_threshold <= 0:
             raise ValueError(
-                f"Invalid value for word_count_threshold: {word_count_threshold}. " f"word_count_threshold must be > 0."
+                f"Invalid value for word_count_threshold: {word_count_threshold}. word_count_threshold must be > 0."
             )
         if isinstance(top_k, int) and top_k <= 0:
             raise ValueError(f"top_k must be > 0, but got {top_k}")

haystack/core/component/component.py

@@ -268,9 +268,9 @@ def __call__(cls, *args, **kwargs):
             try:
                 pre_init_hook.in_progress = True
                 named_positional_args = ComponentMeta._positional_to_kwargs(cls, args)
-                assert (
-                    set(named_positional_args.keys()).intersection(kwargs.keys()) == set()
-                ), "positional and keyword arguments overlap"
+                assert set(named_positional_args.keys()).intersection(kwargs.keys()) == set(), (
+                    "positional and keyword arguments overlap"
+                )
                 kwargs.update(named_positional_args)
                 pre_init_hook.callback(cls, kwargs)
                 instance = super().__call__(**kwargs)
@@ -309,8 +309,8 @@ def _component_repr(component: Component) -> str:
     # We're explicitly ignoring the type here because we're sure that the component
     # has the __haystack_input__ and __haystack_output__ attributes at this point
     return (
-        f'{result}\n{getattr(component, "__haystack_input__", "<invalid_input_sockets>")}'
-        f'\n{getattr(component, "__haystack_output__", "<invalid_output_sockets>")}'
+        f"{result}\n{getattr(component, '__haystack_input__', '<invalid_input_sockets>')}"
+        f"\n{getattr(component, '__haystack_output__', '<invalid_output_sockets>')}"
     )
 
 

haystack/core/pipeline/draw.py

@@ -124,7 +124,7 @@ def _to_mermaid_text(graph: networkx.MultiDiGraph) -> str:
     }
 
     states = {
-        comp: f"{comp}[\"<b>{comp}</b><br><small><i>{type(data['instance']).__name__}{optional_inputs[comp]}</i></small>\"]:::component"  # noqa
+        comp: f'{comp}["<b>{comp}</b><br><small><i>{type(data["instance"]).__name__}{optional_inputs[comp]}</i></small>"]:::component'  # noqa
         for comp, data in graph.nodes(data=True)
         if comp not in ["input", "output"]
     }
@@ -139,11 +139,11 @@ def _to_mermaid_text(graph: networkx.MultiDiGraph) -> str:
             connections_list.append(conn_string)
 
     input_connections = [
-        f"i{{&ast;}}--\"{conn_data['label']}<br><small><i>{conn_data['conn_type']}</i></small>\"--> {states[to_comp]}"
+        f'i{{&ast;}}--"{conn_data["label"]}<br><small><i>{conn_data["conn_type"]}</i></small>"--> {states[to_comp]}'
         for _, to_comp, conn_data in graph.out_edges("input", data=True)
     ]
     output_connections = [
-        f"{states[from_comp]}--\"{conn_data['label']}<br><small><i>{conn_data['conn_type']}</i></small>\"--> o{{&ast;}}"
+        f'{states[from_comp]}--"{conn_data["label"]}<br><small><i>{conn_data["conn_type"]}</i></small>"--> o{{&ast;}}'
         for from_comp, _, conn_data in graph.in_edges("output", data=True)
     ]
     connections = "\n".join(connections_list + input_connections + output_connections)

haystack/document_stores/in_memory/document_store.py

@@ -396,8 +396,7 @@ def filter_documents(self, filters: Optional[Dict[str, Any]] = None) -> List[Doc
         if filters:
             if "operator" not in filters and "conditions" not in filters:
                 raise ValueError(
-                    "Invalid filter syntax. See https://docs.haystack.deepset.ai/docs/metadata-filtering "
-                    "for details."
+                    "Invalid filter syntax. See https://docs.haystack.deepset.ai/docs/metadata-filtering for details."
                 )
             return [doc for doc in self.storage.values() if document_matches_filter(filters=filters, document=doc)]
         return list(self.storage.values())
@@ -506,8 +505,7 @@ def bm25_retrieval(
         if filters:
             if "operator" not in filters:
                 raise ValueError(
-                    "Invalid filter syntax. See https://docs.haystack.deepset.ai/docs/metadata-filtering "
-                    "for details."
+                    "Invalid filter syntax. See https://docs.haystack.deepset.ai/docs/metadata-filtering for details."
                 )
             filters = {"operator": "AND", "conditions": [content_type_filter, filters]}
         else:
@@ -574,8 +572,7 @@ def embedding_retrieval(
             return []
         elif len(documents_with_embeddings) < len(all_documents):
             logger.info(
-                "Skipping some Documents that don't have an embedding. "
-                "To generate embeddings, use a DocumentEmbedder."
+                "Skipping some Documents that don't have an embedding. To generate embeddings, use a DocumentEmbedder."
             )
 
         scores = self._compute_query_embedding_similarity_scores(

haystack/marshal/yaml.py

@@ -31,8 +31,7 @@ def marshal(self, dict_: Dict[str, Any]) -> str:
             return yaml.dump(dict_, Dumper=YamlDumper)
         except yaml.representer.RepresenterError as e:
             raise TypeError(
-                "Error dumping pipeline to YAML - Ensure that all pipeline "
-                "components only serialize basic Python types"
+                "Error dumping pipeline to YAML - Ensure that all pipeline components only serialize basic Python types"
             ) from e
 
     def unmarshal(self, data_: Union[str, bytes, bytearray]) -> Dict[str, Any]:

haystack/utils/filters.py

@@ -112,8 +112,7 @@ def _less_than_equal(document_value: Any, filter_value: Any) -> bool:
 def _in(document_value: Any, filter_value: Any) -> bool:
     if not isinstance(filter_value, list):
         msg = (
-            f"Filter value must be a `list` when using operator 'in' or 'not in', "
-            f"received type '{type(filter_value)}'"
+            f"Filter value must be a `list` when using operator 'in' or 'not in', received type '{type(filter_value)}'"
         )
         raise FilterError(msg)
     return any(_equal(e, document_value) for e in filter_value)

haystack/utils/hf.py

@@ -205,7 +205,7 @@ def resolve_hf_pipeline_kwargs(
         task = model_info(huggingface_pipeline_kwargs["model"], token=huggingface_pipeline_kwargs["token"]).pipeline_tag
 
     if task not in supported_tasks:
-        raise ValueError(f"Task '{task}' is not supported. " f"The supported tasks are: {', '.join(supported_tasks)}.")
+        raise ValueError(f"Task '{task}' is not supported. The supported tasks are: {', '.join(supported_tasks)}.")
     huggingface_pipeline_kwargs["task"] = task
     return huggingface_pipeline_kwargs
 

test/components/audio/test_whisper_local.py

@@ -190,14 +190,14 @@ def test_whisper_local_transcriber(self, test_files_path):
         docs = output["documents"]
         assert len(docs) == 3
 
-        assert all(
-            word in docs[0].content.strip().lower() for word in {"content", "the", "document"}
-        ), f"Expected words not found in: {docs[0].content.strip().lower()}"
+        assert all(word in docs[0].content.strip().lower() for word in {"content", "the", "document"}), (
+            f"Expected words not found in: {docs[0].content.strip().lower()}"
+        )
         assert test_files_path / "audio" / "this is the content of the document.wav" == docs[0].meta["audio_file"]
 
-        assert all(
-            word in docs[1].content.strip().lower() for word in {"context", "answer"}
-        ), f"Expected words not found in: {docs[1].content.strip().lower()}"
+        assert all(word in docs[1].content.strip().lower() for word in {"context", "answer"}), (
+            f"Expected words not found in: {docs[1].content.strip().lower()}"
+        )
         path = test_files_path / "audio" / "the context for this answer is here.wav"
         assert path.absolute() == docs[1].meta["audio_file"]
 

test/components/converters/test_docx_file_to_document.py

@@ -175,9 +175,9 @@ def test_run_with_table(self, test_files_path):
         table_index = next(i for i, part in enumerate(content_parts) if "| This | Is     | Just a |" in part)
         # check that natural order of the document is preserved
         assert any("Donald Trump" in part for part in content_parts[:table_index]), "Text before table not found"
-        assert any(
-            "Now we are in Page 2" in part for part in content_parts[table_index + 1 :]
-        ), "Text after table not found"
+        assert any("Now we are in Page 2" in part for part in content_parts[table_index + 1 :]), (
+            "Text after table not found"
+        )
 
     def test_run_with_store_full_path_false(self, test_files_path):
         """

test/components/embedders/test_openai_document_embedder.py

@@ -251,8 +251,8 @@ def test_run(self):
             assert len(doc.embedding) == 1536
             assert all(isinstance(x, float) for x in doc.embedding)
 
-        assert (
-            "text" in result["meta"]["model"] and "ada" in result["meta"]["model"]
-        ), "The model name does not contain 'text' and 'ada'"
+        assert "text" in result["meta"]["model"] and "ada" in result["meta"]["model"], (
+            "The model name does not contain 'text' and 'ada'"
+        )
 
         assert result["meta"]["usage"] == {"prompt_tokens": 15, "total_tokens": 15}, "Usage information does not match"

test/components/embedders/test_openai_text_embedder.py

@@ -130,8 +130,8 @@ def test_run(self):
         assert len(result["embedding"]) == 1536
         assert all(isinstance(x, float) for x in result["embedding"])
 
-        assert (
-            "text" in result["meta"]["model"] and "ada" in result["meta"]["model"]
-        ), "The model name does not contain 'text' and 'ada'"
+        assert "text" in result["meta"]["model"] and "ada" in result["meta"]["model"], (
+            "The model name does not contain 'text' and 'ada'"
+        )
 
         assert result["meta"]["usage"] == {"prompt_tokens": 6, "total_tokens": 6}, "Usage information does not match"

test/components/joiners/test_document_joiner.py

@@ -302,6 +302,6 @@ def test_test_score_norm_with_rrf(self):
                 for i in range(len(join_results["documents"]) - 1)
             )
 
-            assert (
-                is_sorted
-            ), "Documents are not sorted in descending order by score, there is an issue with rff ranking"
+            assert is_sorted, (
+                "Documents are not sorted in descending order by score, there is an issue with rff ranking"
+            )

test/components/preprocessors/test_document_cleaner.py

@@ -71,7 +71,7 @@ def test_remove_whitespaces(self):
         )
         assert len(result["documents"]) == 1
         assert result["documents"][0].content == (
-            "This is a text with some words. " "" "There is a second sentence. " "" "And there is a third sentence.\f"
+            "This is a text with some words. There is a second sentence. And there is a third sentence.\f"
         )
 
     def test_remove_substrings(self):
@@ -210,11 +210,7 @@ def test_ascii_only(self):
     def test_other_document_fields_are_not_lost(self):
         cleaner = DocumentCleaner(keep_id=True)
         document = Document(
-            content="This is a text with some words. \n"
-            ""
-            "There is a second sentence. \n"
-            ""
-            "And there is a third sentence.\n",
+            content="This is a text with some words. \nThere is a second sentence. \nAnd there is a third sentence.\n",
             dataframe=DataFrame({"col1": [1], "col2": [2]}),
             blob=ByteStream.from_string("some_data"),
             meta={"data": 1},

test/components/routers/test_conditional_router.py

@@ -436,9 +436,9 @@ def test_router_with_optional_parameters(self):
 
         # Test pipeline without path parameter
         result = pipe.run(data={"router": {"question": "What?"}})
-        assert result["router"] == {
-            "fallback": "What?"
-        }, "Default route should work in pipeline when 'path' is not provided"
+        assert result["router"] == {"fallback": "What?"}, (
+            "Default route should work in pipeline when 'path' is not provided"
+        )
 
         # Test pipeline with path parameter
         result = pipe.run(data={"router": {"question": "What?", "path": "followup_short"}})

test/core/pipeline/features/test_run.py

@@ -823,7 +823,7 @@ def pipeline_that_has_a_component_with_only_default_inputs():
                         "answers": [
                             GeneratedAnswer(
                                 data="Paris",
-                                query="What " "is " "the " "capital " "of " "France?",
+                                query="What is the capital of France?",
                                 documents=[
                                     Document(
                                         id="413dccdf51a54cca75b7ed2eddac04e6e58560bd2f0caf4106a3efc023fe3651",
@@ -916,7 +916,7 @@ def fake_generator_run(self, generation_kwargs: Optional[Dict[str, Any]] = None,
         pipe,
         [
             PipelineRunData(
-                inputs={"prompt_builder": {"query": "What is the capital of " "Italy?"}},
+                inputs={"prompt_builder": {"query": "What is the capital of Italy?"}},
                 expected_outputs={"router": {"correct_replies": ["Rome"]}},
                 expected_run_order=["prompt_builder", "generator", "router", "prompt_builder", "generator", "router"],
             )