[pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

Author: pre-commit-ci[bot]

examples/arena_hard.py

@@ -15,12 +15,12 @@
 import re
 from typing import Any, Dict, List, Optional, Union
 
+from distilabel.steps.tasks.typing import ChatType
+from distilabel.steps.typing import StepOutput
 from typing_extensions import override
 
 from distilabel.steps import GlobalStep, StepInput
 from distilabel.steps.tasks.base import Task
-from distilabel.steps.tasks.typing import ChatType
-from distilabel.steps.typing import StepOutput
 
 
 class ArenaHard(Task):
@@ -331,6 +331,8 @@ def process(self, inputs: StepInput) -> StepOutput:  # type: ignore
 if __name__ == "__main__":
     import json
 
+    from distilabel.steps.typing import StepOutput
+
     from distilabel.models import InferenceEndpointsLLM, OpenAILLM
     from distilabel.pipeline import Pipeline
     from distilabel.steps import (
@@ -341,7 +343,6 @@ def process(self, inputs: StepInput) -> StepOutput:  # type: ignore
         step,
     )
     from distilabel.steps.tasks import TextGeneration
-    from distilabel.steps.typing import StepOutput
 
     @step(inputs=["turns"], outputs=["system_prompt", "instruction"])
     def PrepareForTextGeneration(*inputs: StepInput) -> StepOutput:

examples/deepseek_prover.py

@@ -17,6 +17,7 @@
 from textwrap import dedent
 from typing import Any, Dict, List, Optional, Union
 
+from distilabel.steps.tasks.typing import ChatType
 from jinja2 import Template
 from pydantic import PrivateAttr
 from typing_extensions import override
@@ -25,7 +26,6 @@
 from distilabel.pipeline import Pipeline
 from distilabel.steps import LoadDataFromHub
 from distilabel.steps.tasks.base import Task
-from distilabel.steps.tasks.typing import ChatType
 
 _PARSE_DEEPSEEK_PROVER_AUTOFORMAL_REGEX = r"```lean4(.*?)```"
 

src/distilabel/distiset.py

@@ -509,9 +509,9 @@ def load_from_disk(
         )
         dest_distiset_path = distiset_path
 
-        assert fs.isdir(
-            original_distiset_path
-        ), "`distiset_path` must be a `PathLike` object pointing to a folder or a URI of a remote filesystem."
+        assert fs.isdir(original_distiset_path), (
+            "`distiset_path` must be a `PathLike` object pointing to a folder or a URI of a remote filesystem."
+        )
 
         has_config = False
         has_artifacts = False

src/distilabel/pipeline/batch_manager.py

@@ -231,10 +231,10 @@ def from_step(
             input_batch_size=getattr(step, "input_batch_size", None),
             data={predecessor: [] for predecessor in predecessors},
             convergence_step=convergence_step,
-            next_expected_seq_no={predecessor: (0, 0) for predecessor in predecessors},
+            next_expected_seq_no=dict.fromkeys(predecessors, (0, 0)),
             step_signature=step.signature,
             use_cache=step.use_cache,
-            step_offset={predecessor: (0, 0) for predecessor in predecessors},
+            step_offset=dict.fromkeys(predecessors, (0, 0)),
         )
 
     def _get_seq_no(self) -> int:

src/distilabel/pipeline/write_buffer.py

@@ -65,11 +65,9 @@ def __init__(
             step: [] for step in leaf_steps
         }
         # TODO: make this configurable
-        self._buffers_dump_batch_size: Dict[str, int] = {
-            step: 50 for step in leaf_steps
-        }
+        self._buffers_dump_batch_size: Dict[str, int] = dict.fromkeys(leaf_steps, 50)
         self._buffer_last_schema = {}
-        self._buffers_last_file: Dict[str, int] = {step: 1 for step in leaf_steps}
+        self._buffers_last_file: Dict[str, int] = dict.fromkeys(leaf_steps, 1)
         self._steps_cached = steps_cached or {}
         self._logger = logging.getLogger("distilabel.write_buffer")
 

src/distilabel/steps/base.py

@@ -101,7 +101,7 @@ def _infer_step_name(
         base_name = "_".join(parts[:-1])
         while name in step_names:
             idx = int(name.split("_")[-1])
-            name = f"{base_name}_{idx+1}"
+            name = f"{base_name}_{idx + 1}"
     return name
 
 

src/distilabel/steps/tasks/base.py

@@ -211,7 +211,7 @@ def _output_on_failure(
         a new field `distilabel_meta` with the raw output of the LLM.
         """
         # Create a dictionary with the outputs of the task (every output set to None)
-        outputs = {output: None for output in self.outputs}
+        outputs = dict.fromkeys(self.outputs)
         outputs["model_name"] = self.llm.model_name  # type: ignore
         outputs = self._create_metadata(
             outputs,

src/distilabel/steps/tasks/improving_text_embeddings.py

@@ -66,7 +66,7 @@ def format_output(
             A Python dictionary with the parsed output based on the `keys` property.
         """
         if output is None:
-            return {key: None for key in self.keys}
+            return dict.fromkeys(self.keys)
 
         def escape_backslashes_in_values(s):
             # Regular expression to match the key-value pairs in the dictionary
@@ -100,7 +100,7 @@ def replace_backslashes(match):
             pass
 
         if not isinstance(output, dict):
-            return {key: None for key in self.keys}
+            return dict.fromkeys(self.keys)
 
         return {key: output.get(key, None) for key in self.keys}
 

src/distilabel/steps/tasks/math_shepherd/completer.py

@@ -485,7 +485,7 @@ def _auto_label(
                     self._logger.info("Completer failed due to empty completion")
                     continue
                 if completion[-1] == golden_answers[instruction_i]:
-                    label = f" { self.tags[0]}"
+                    label = f" {self.tags[0]}"
                     # If we found one, it's enough as we are doing Hard Estimation
                     continue
             # In case we had no solutions from the previous step, otherwise we would have

src/distilabel/steps/tasks/text_generation.py

@@ -229,7 +229,7 @@ def unload(self) -> None:
     @property
     def inputs(self) -> "StepColumns":
         """The input for the task is the `instruction` by default, or the `columns` given as input."""
-        columns = {column: True for column in self.columns}
+        columns = dict.fromkeys(self.columns, True)
         columns["system_prompt"] = False
         return columns