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libs/partners/openai/fix_mypy_errors.py

@@ -1,148 +0,0 @@
-#!/usr/bin/env python3
-"""Script to fix all mypy errors in the OpenAI batch implementation."""
-
-import re
-
-def fix_batch_method_signature():
-    """Fix the batch method signature incompatibility."""
-    file_path = 'langchain_openai/chat_models/base.py'
-    
-    with open(file_path, 'r') as f:
-        content = f.read()
-    
-    # Remove the use_batch_api parameter from the batch method signature
-    old_signature = """    @override
-    def batch(
-        self,
-        inputs: list[LanguageModelInput],
-        config: Optional[Union[RunnableConfig, list[RunnableConfig]]] = None,
-        *,
-        return_exceptions: bool = False,
-        use_batch_api: bool = False,
-        **kwargs: Any,
-    ) -> list[BaseMessage]:"""
-    
-    new_signature = """    @override
-    def batch(
-        self,
-        inputs: list[LanguageModelInput],
-        config: Optional[Union[RunnableConfig, list[RunnableConfig]]] = None,
-        *,
-        return_exceptions: bool = False,
-        **kwargs: Any,
-    ) -> list[BaseMessage]:"""
-    
-    content = content.replace(old_signature, new_signature)
-    
-    # Update the docstring to remove references to use_batch_api parameter
-    old_docstring_part = """        This method provides two processing modes:
-        1. Standard mode (use_batch_api=False): Uses parallel invoke for
-           immediate results
-        2. Batch API mode (use_batch_api=True): Uses OpenAI's Batch API
-           for 50% cost savings
-
-        Args:
-            inputs: List of inputs to process in batch.
-            config: Configuration for the batch processing.
-            return_exceptions: Whether to return exceptions instead of raising them.
-            use_batch_api: Whether to use OpenAI's Batch API for cost savings.
-            **kwargs: Additional keyword arguments."""
-    
-    new_docstring_part = """        This method uses the standard parallel invoke approach for immediate results.
-        For cost savings with asynchronous processing, use batch_create() and 
-        batch_retrieve() methods instead.
-
-        Args:
-            inputs: List of inputs to process in batch.
-            config: Configuration for the batch processing.
-            return_exceptions: Whether to return exceptions instead of raising them.
-            **kwargs: Additional keyword arguments."""
-    
-    content = content.replace(old_docstring_part, new_docstring_part)
-    
-    # Update the method implementation to remove use_batch_api logic
-    old_impl_start = """        # Extract use_batch_api from kwargs if present
-        use_batch_api = kwargs.pop("use_batch_api", False)
-        
-        if use_batch_api:"""
-    
-    # Find and replace the entire conditional block
-    pattern = r'        # Extract use_batch_api from kwargs if present.*?        else:\s*\n            # Use standard batch processing.*?return results'
-    
-    new_impl = """        # Use standard batch processing (parallel invoke)
-        return super().batch(
-            inputs=inputs,
-            config=config,
-            return_exceptions=return_exceptions,
-            **kwargs,
-        )"""
-    
-    content = re.sub(pattern, new_impl, content, flags=re.DOTALL)
-    
-    with open(file_path, 'w') as f:
-        f.write(content)
-    
-    print("Fixed batch method signature incompatibility")
-
-def fix_test_files():
-    """Fix various test file issues."""
-    
-    # Fix unit test file
-    unit_test_path = 'tests/unit_tests/chat_models/test_batch.py'
-    with open(unit_test_path, 'r') as f:
-        content = f.read()
-    
-    # Fix OpenAIBatchClient constructor calls - remove poll_interval and timeout
-    content = re.sub(
-        r'OpenAIBatchClient\(mock_client, poll_interval=\d+\.?\d*, timeout=\d+\.?\d*\)',
-        'OpenAIBatchClient(mock_client)',
-        content
-    )
-    
-    # Fix create_batch calls - change batch_requests to requests
-    content = content.replace('batch_requests=', 'requests=')
-    
-    # Fix attribute access issues
-    content = content.replace('batch_response.status', 'batch_response["status"]')
-    content = content.replace('batch_response.output_file_id', 'batch_response["output_file_id"]')
-    
-    # Remove timeout attribute access
-    content = re.sub(r'client\.timeout = \d+\.?\d*\n', '', content)
-    
-    with open(unit_test_path, 'w') as f:
-        f.write(content)
-    
-    # Fix integration test file
-    integration_test_path = 'tests/integration_tests/chat_models/test_batch_integration.py'
-    with open(integration_test_path, 'r') as f:
-        content = f.read()
-    
-    # Remove max_tokens parameter from ChatOpenAI constructor
-    content = re.sub(r', max_tokens=\d+', '', content)
-    
-    # Fix type annotations for message lists
-    content = content.replace('list[HumanMessage]', 'list[BaseMessage]')
-    
-    # Fix content access for messages
-    content = re.sub(
-        r'(\w+)\.content\.strip\(\)',
-        r'str(\1.content).strip()',
-        content
-    )
-    
-    # Add missing return type annotation
-    content = re.sub(
-        r'def (test_\w+)\(([^)]*)\):',
-        r'def \1(\2) -> None:',
-        content
-    )
-    
-    with open(integration_test_path, 'w') as f:
-        f.write(content)
-    
-    print("Fixed test file issues")
-
-if __name__ == "__main__":
-    fix_batch_method_signature()
-    fix_test_files()
-    print("All mypy errors should now be fixed")