removed formatting tools from make format to avoid formatting redunda…

…ncy, we should have one source-of-truth for formatting, which is the pre-commit

.pre-commit-config.yaml

@@ -23,19 +23,16 @@ repos:
       - id: ruff
         args: ['--fix', '--config=pyproject.toml']
         exclude: ^docs/|.*\.(json|yaml|md|txt)$
-      - id: ruff-format
-        args: ['--config=pyproject.toml']
-        exclude: ^docs/|.*\.(json|yaml|md|txt)$
 
   # stage files after ruff
   - repo: local
     hooks:
-      - id: git-add
-        name: git-add
-        entry: git add
+      - id: run-make-format
+        name: Run Make Format
+        entry: make format
         language: system
         stages: [commit]
-        pass_filenames: true
+        pass_filenames: false
 
   # - repo: https://github.com/pycqa/flake8
   #   rev: 4.0.1

Makefile

@@ -24,7 +24,6 @@ setup:
 format:
 	$(PYTHON) black $(SRC_DIR) --config pyproject.toml
 	$(PYTHON) ruff check --fix $(SRC_DIR)
-	$(PYTHON) ruff format $(SRC_DIR)
 # remove git ls-files | xargs pre-commit run black --files, causes a circular dependency
 
 # Run lint checks using Ruff

adalflow/adalflow/components/retriever/bm25_retriever.py

@@ -232,7 +232,9 @@ def _initialize(self, corpus: List[List[str]]):
 
     def _calc_idf(self):
         idf_sum = 0
-        negative_idf = []  # idf can be negative if word is too common: more than half of the documents
+        negative_idf = (
+            []
+        )  # idf can be negative if word is too common: more than half of the documents
         self.idf: Dict[str, float] = {}
         for token, freq in self.nd.items():
             idf = math.log(self.total_documents - freq + 0.5) - math.log(freq + 0.5)

adalflow/adalflow/core/component.py

@@ -138,7 +138,9 @@ def call(self, query: str) -> str:
     training: bool
     teacher_mode: bool = False
     tracing: bool = False
-    name: str = "Component"  # name will help with GradComponent output naming as "{name}_output"
+    name: str = (
+        "Component"  # name will help with GradComponent output naming as "{name}_output"
+    )
     _component_type = "base"
 
     # def _generate_unique_name(self):

adalflow/adalflow/optim/_llm_optimizer.py

@@ -114,9 +114,9 @@ def __init__(
         # Ensure the temperature is at least 1
         model_kwargs["temperature"] = max(1, model_kwargs.get("temperature", 1))
 
-        self.instruction_history: List[
-            Instruction
-        ] = []  # trace the history of the instructions
+        self.instruction_history: List[Instruction] = (
+            []
+        )  # trace the history of the instructions
         self.starter_instruction: Optional[str] = None
         if self.instruction_parameter.data is not None:
             self.starter_instruction = self.instruction_parameter.data

adalflow/adalflow/optim/few_shot/bootstrap_optimizer.py

@@ -139,7 +139,8 @@ def sample(
                         )
                     # if demo.id in demos and demos[demo.id].score is not None:
                     w = (
-                        w - student_demo_score
+                        w
+                        - student_demo_score
                         # w - demos[demo.id].score
                     )  # assign higher weights to failed demos but successful in augmented
                     if w < 0:

adalflow/adalflow/optim/parameter.py

@@ -170,9 +170,9 @@ def __init__(
         self._score: float = score  # end to end evaluation score
 
         self._student_traces: Dict[str, DataClass] = {}  # id
-        self._demos: List[
-            DataClass
-        ] = []  # used for the optimizer to save the proposed demos
+        self._demos: List[DataClass] = (
+            []
+        )  # used for the optimizer to save the proposed demos
         self._previous_demos: List[DataClass] = []
         self.eval_input = eval_input
 

adalflow/adalflow/optim/trainer/trainer.py

@@ -1517,7 +1517,8 @@ def _downsample_move_batch(
         error_indices = [i for i, score in enumerate(acc_score_list) if score <= 0.5]
 
         if (
-            len(error_indices) + len(correct_indices) <= max_moving_batch_size
+            len(error_indices) + len(correct_indices)
+            <= max_moving_batch_size
             # and len(correct_indices) <= max_moving_batch_size
         ):
             return all_samples, all_losses, all_y_preds, acc_score_list

adalflow/adalflow/tracing/generator_state_logger.py

@@ -59,9 +59,9 @@ def __init__(
         self.filename = filename or "generator_state_trace.json"
         self.filepath = os.path.join(self.filepath, self.filename)
 
-        self._trace_map: Dict[
-            str, List[GeneratorStatesRecord]
-        ] = {}  # generator_name: [prompt_states]
+        self._trace_map: Dict[str, List[GeneratorStatesRecord]] = (
+            {}
+        )  # generator_name: [prompt_states]
         # load previous records if the file exists
         if os.path.exists(self.filepath):
             self.load(self.filepath)

pyproject.toml

@@ -79,9 +79,3 @@ lint.extend-ignore = [
     "UP007", # Wants | over Union, which breaks 3.8
 ]
 exclude = ["docs/*"]
-
-[tool.ruff.format]
-quote-style = "double"
-indent-style = "space"
-skip-magic-trailing-comma = false
-line-ending = 'auto'