release: 0.2.0-alpha.94

.release-please-manifest.json

@@ -1,3 +1,3 @@
 {
-  ".": "0.2.0-alpha.93"
+  ".": "0.2.0-alpha.94"
 }

CHANGELOG.md

@@ -5,6 +5,14 @@ All notable changes to this project will be documented in this file.
 The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/)
 and this project adheres to [Semantic Versioning](http://semver.org/spec/v2.0.0.html).
 
+## 0.2.0-alpha.94 (2025-09-11)
+
+Full Changelog: [v0.2.0-alpha.93...v0.2.0-alpha.94](https://github.com/openlayer-ai/openlayer-python/compare/v0.2.0-alpha.93...v0.2.0-alpha.94)
+
+### Bug Fixes
+
+* custom args with run_batch_from_df ([4a45a89](https://github.com/openlayer-ai/openlayer-python/commit/4a45a899811b1c778b8cecabd82b5f97c46346ab))
+
 ## 0.2.0-alpha.93 (2025-09-10)
 
 Full Changelog: [v0.2.0-alpha.92...v0.2.0-alpha.93](https://github.com/openlayer-ai/openlayer-python/compare/v0.2.0-alpha.92...v0.2.0-alpha.93)

pyproject.toml

@@ -1,6 +1,6 @@
 [project]
 name = "openlayer"
-version = "0.2.0-alpha.93"
+version = "0.2.0-alpha.94"
 description = "The official Python library for the openlayer API"
 dynamic = ["readme"]
 license = "Apache-2.0"

src/openlayer/_version.py

@@ -1,4 +1,4 @@
 # File generated from our OpenAPI spec by Stainless. See CONTRIBUTING.md for details.
 
 __title__ = "openlayer"
-__version__ = "0.2.0-alpha.93"  # x-release-please-version
+__version__ = "0.2.0-alpha.94"  # x-release-please-version

src/openlayer/lib/core/base_model.py

@@ -91,12 +91,10 @@ def batch(self, dataset_path: str, output_dir: str) -> None:
             raise ValueError(f"Unsupported dataset format: {dataset_path}")
 
         # Call the model's run_batch method, passing in the DataFrame
-        output_df, config = self.run_batch_from_df(df, custom_args=self.custom_args)
+        output_df, config = self.run_batch_from_df(df)
         self.write_output_to_directory(output_df, config, output_dir, fmt)
 
-    def run_batch_from_df(
-        self, df: pd.DataFrame, custom_args: dict = None
-    ) -> Tuple[pd.DataFrame, dict]:
+    def run_batch_from_df(self, df: pd.DataFrame) -> Tuple[pd.DataFrame, dict]:
         """Function that runs the model and returns the result."""
         # Ensure the 'output' column exists
         if "output" not in df.columns:
@@ -105,10 +103,6 @@ def run_batch_from_df(
         # Get the signature of the 'run' method
         run_signature = inspect.signature(self.run)
 
-        # If the model has a custom_args attribute, update it
-        if hasattr(self, "custom_args") and custom_args is not None:
-            self.custom_args.update(custom_args)
-
         for index, row in df.iterrows():
             # Filter row_dict to only include keys that are valid parameters
             # for the 'run' method

src/openlayer/lib/integrations/bedrock_tracer.py

@@ -25,9 +25,7 @@
 logger = logging.getLogger(__name__)
 
 
-def trace_bedrock(
-    client: "boto3.client",
-) -> "boto3.client":
+def trace_bedrock(client: "boto3.client") -> "boto3.client":
     """Patch the Bedrock client to trace model invocations.
 
     The following information is collected for each model invocation: