#!/usr/bin/env python3
"""Comprehensive script to fix all linting issues in the OpenAI batch API implementation."""

import re

def fix_base_py_comprehensive():
    """Fix all 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 the existing imports section and add what's needed
    # Look for the langchain_core imports section
    if 'from langchain_core.language_models.chat_models import BaseChatModel' in content:
        # Add the missing imports after the existing langchain_core imports
        import_pattern = r'(from langchain_core\.runnables import RunnablePassthrough\n)'
        replacement = r'\1from langchain_core.runnables.config import RunnableConfig\nfrom typing_extensions import override\n'
        content = re.sub(import_pattern, replacement, content)
    
    # Fix type annotations to use modern syntax
    content = re.sub(r'List\[LanguageModelInput\]', 'list[LanguageModelInput]', content)
    content = re.sub(r'List\[RunnableConfig\]', 'list[RunnableConfig]', content)
    content = re.sub(r'List\[BaseMessage\]', 'list[BaseMessage]', content)
    
    # Fix long lines in docstrings by breaking them
    content = content.replace(
        '        1. Standard mode (use_batch_api=False): Uses parallel invoke for immediate results',
        '        1. Standard mode (use_batch_api=False): Uses parallel invoke for\n           immediate results'
    )
    content = content.replace(
        '        2. Batch API mode (use_batch_api=True): Uses OpenAI Batch API for 50% cost savings',
        '        2. Batch API mode (use_batch_api=True): Uses OpenAI Batch API for\n           50% cost savings'
    )
    
    with open(file_path, 'w') as f:
        f.write(content)
    print("Fixed base.py comprehensively")

def fix_batch_py_types():
    """Fix type annotations 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()
    
    # Replace all Dict and List with lowercase versions
    content = re.sub(r'Dict\[([^\]]+)\]', r'dict[\1]', content)
    content = re.sub(r'List\[([^\]]+)\]', r'list[\1]', content)
    
    # Remove Dict and List from imports if they exist
    content = re.sub(r'from typing import ([^)]*?)Dict,?\s*([^)]*?)\n', r'from typing import \1\2\n', content)
    content = re.sub(r'from typing import ([^)]*?)List,?\s*([^)]*?)\n', r'from typing import \1\2\n', content)
    content = re.sub(r'from typing import ([^)]*?),\s*Dict([^)]*?)\n', r'from typing import \1\2\n', content)
    content = re.sub(r'from typing import ([^)]*?),\s*List([^)]*?)\n', r'from typing import \1\2\n', content)
    
    with open(file_path, 'w') as f:
        f.write(content)
    print("Fixed batch.py type annotations")

def fix_integration_tests_comprehensive():
    """Fix all issues in integration tests"""
    file_path = '/home/daytona/langchain/libs/partners/openai/tests/integration_tests/chat_models/test_batch_integration.py'
    
    with open(file_path, 'r') as f:
        content = f.read()
    
    # Fix long lines by breaking them properly
    content = content.replace(
        'content="What is the capital of France? Answer with just the city name."',
        'content=(\n                        "What is the capital of France? "\n                        "Answer with just the city name."\n                    )'
    )
    
    content = content.replace(
        'content="What is the smallest planet? Answer with just the planet name."',
        'content=(\n                        "What is the smallest planet? "\n                        "Answer with just the planet name."\n                    )'
    )
    
    # Fix unused variables
    content = re.sub(r'processing_time = end_time - start_time', '_ = end_time - start_time', content)
    
    with open(file_path, 'w') as f:
        f.write(content)
    print("Fixed integration tests comprehensively")

def fix_unit_tests_comprehensive():
    """Fix all issues in unit tests"""
    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 and fix the specific test methods that have undefined results
    # This is a more targeted fix for the test that checks conversion
    pattern1 = r'(\s+)_ = self\.llm\.batch\(inputs, use_batch_api=True\)\s*\n(\s+)# Verify conversion happened\s*\n(\s+)assert len\(results\) == num_requests'
    replacement1 = r'\1results = self.llm.batch(inputs, use_batch_api=True)\n\2# Verify conversion happened\n\3assert len(results) == num_requests'
    content = re.sub(pattern1, replacement1, content)
    
    # Fix the other test with undefined results
    pattern2 = r'(\s+)_ = self\.llm\.batch\(inputs, use_batch_api=True\)\s*\n(\s+)assert len\(results\) == 2'
    replacement2 = r'\1results = self.llm.batch(inputs, use_batch_api=True)\n\2assert len(results) == 2'
    content = re.sub(pattern2, replacement2, content)
    
    with open(file_path, 'w') as f:
        f.write(content)
    print("Fixed unit tests comprehensively")

if __name__ == "__main__":
    print("Running comprehensive fixes...")
    fix_base_py_comprehensive()
    fix_batch_py_types()
    fix_integration_tests_comprehensive()
    fix_unit_tests_comprehensive()
    print("All comprehensive fixes completed!")