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final_fix.py

@@ -0,0 +1,112 @@
+#!/usr/bin/env python3
+"""Final comprehensive script to fix all remaining linting issues."""
+
+import re
+
+def fix_base_py_final():
+    """Fix all remaining issues in base.py"""
+    file_path = '/home/daytona/langchain/libs/partners/openai/langchain_openai/chat_models/base.py'
+    
+    with open(file_path, 'r') as f:
+        content = f.read()
+    
+    # Add missing imports - find a good place to add them
+    # Look for existing langchain_core imports and add after them
+    if 'from langchain_core.runnables import RunnablePassthrough' in content:
+        content = content.replace(
+            'from langchain_core.runnables import RunnablePassthrough',
+            'from langchain_core.runnables import RunnablePassthrough\nfrom langchain_core.runnables.config import RunnableConfig\nfrom typing_extensions import override'
+        )
+    
+    # Fix long lines in docstrings
+    content = content.replace(
+        '         2. Batch API mode (use_batch_api=True): Uses OpenAI\'s Batch API for 50% cost savings',
+        '         2. Batch API mode (use_batch_api=True): Uses OpenAI\'s Batch API for\n            50% cost savings'
+    )
+    
+    content = content.replace(
+        '            use_batch_api: If True, use OpenAI\'s Batch API for cost savings with polling.',
+        '            use_batch_api: If True, use OpenAI\'s Batch API for cost savings\n                          with polling.'
+    )
+    
+    content = content.replace(
+        '                          If False (default), use standard parallel processing for immediate results.',
+        '                          If False (default), use standard parallel processing\n                          for immediate results.'
+    )
+    
+    with open(file_path, 'w') as f:
+        f.write(content)
+    print("Fixed base.py final issues")
+
+def fix_batch_py_final():
+    """Fix all remaining issues in batch.py"""
+    file_path = '/home/daytona/langchain/libs/partners/openai/langchain_openai/chat_models/batch.py'
+    
+    with open(file_path, 'r') as f:
+        content = f.read()
+    
+    # Fix remaining List references
+    content = re.sub(r'list\[List\[BaseMessage\]\]', 'list[list[BaseMessage]]', content)
+    
+    # Fix unused variable
+    content = content.replace(
+        'batch = self.client.batches.cancel(batch_id)',
+        '_ = self.client.batches.cancel(batch_id)'
+    )
+    
+    # Fix long lines
+    content = content.replace(
+        '    High-level processor for managing OpenAI Batch API lifecycle with LangChain integration.',
+        '    High-level processor for managing OpenAI Batch API lifecycle with\n    LangChain integration.'
+    )
+    
+    content = content.replace(
+        '                    f"Batch {batch_id} failed with status {batch_info[\'status\']}"',
+        '                    f"Batch {batch_id} failed with status "\n                    f"{batch_info[\'status\']}"'
+    )
+    
+    with open(file_path, 'w') as f:
+        f.write(content)
+    print("Fixed batch.py final issues")
+
+def fix_unit_tests_final():
+    """Fix remaining unit test issues"""
+    file_path = '/home/daytona/langchain/libs/partners/openai/tests/unit_tests/chat_models/test_batch.py'
+    
+    with open(file_path, 'r') as f:
+        content = f.read()
+    
+    # Find the specific problematic test and fix it properly
+    # Look for the pattern where results is undefined
+    lines = content.split('\n')
+    fixed_lines = []
+    i = 0
+    
+    while i < len(lines):
+        line = lines[i]
+        
+        # Look for the problematic pattern
+        if '_ = self.llm.batch(inputs, use_batch_api=True)' in line:
+            # Check if the next few lines reference 'results'
+            next_lines = lines[i+1:i+5] if i+5 < len(lines) else lines[i+1:]
+            if any('assert len(results)' in next_line or 'for i, result in enumerate(results)' in next_line for next_line in next_lines):
+                # Replace the assignment to actually capture results
+                fixed_lines.append(line.replace('_ = self.llm.batch(inputs, use_batch_api=True)', 'results = self.llm.batch(inputs, use_batch_api=True)'))
+            else:
+                fixed_lines.append(line)
+        else:
+            fixed_lines.append(line)
+        i += 1
+    
+    content = '\n'.join(fixed_lines)
+    
+    with open(file_path, 'w') as f:
+        f.write(content)
+    print("Fixed unit tests final issues")
+
+if __name__ == "__main__":
+    print("Running final comprehensive fixes...")
+    fix_base_py_final()
+    fix_batch_py_final()
+    fix_unit_tests_final()
+    print("All final fixes completed!")