"""
Step 2: Create overlapping chunks from messages.
"""

import pandas as pd
from typing import List
from pipeline.models.base import PipelineStep
from pipeline.common_defs import Chunk, Message

class ChunkCreator(PipelineStep):
    """Create overlapping chunks from messages"""
    
    def __init__(self, chunk_size: int = 20, overlap: int = 5, 
                 output_dir: str = './pipeline_output'):
        super().__init__(output_dir)
        self.chunk_size = chunk_size
        self.overlap = overlap
    
    def execute(self, df: pd.DataFrame) -> List[Chunk]:
        """
        Create overlapping chunks from DataFrame.
        
        Args:
            df: DataFrame with message data
            
        Returns:
            List of Chunk objects
        """
        self.logger.info(f"Creating chunks (size={self.chunk_size}, overlap={self.overlap})...")
        
        chunks = []
        total = len(df)
        step = self.chunk_size - self.overlap
        
        for i in range(0, total, step):
            chunk_df = df.iloc[i:i+self.chunk_size]
            if len(chunk_df) == 0:
                break
            
            # Create messages list
            messages = []
            for _, row in chunk_df.iterrows():
                msg = Message(
                    line_number=int(row['line_number']),
                    timestamp=str(row.get('timestamp', '')),
                    sender=str(row.get('sender', '')),
                    message=str(row.get('message', '')),
                    message_normalized=str(row.get('message_normalized', ''))
                )
                messages.append(msg)
            
            # Create chunk
            chunk = Chunk(
                chunk_id=len(chunks),
                start_line=int(chunk_df['line_number'].iloc[0]),
                end_line=int(chunk_df['line_number'].iloc[-1]),
                messages=messages,
                combined_text=' '.join(chunk_df['message_normalized'].fillna('')),
                timestamp_start=str(chunk_df['timestamp'].iloc[0]),
                timestamp_end=str(chunk_df['timestamp'].iloc[-1])
            )
            chunks.append(chunk)
        
        self.logger.info(f"Created {len(chunks):,} chunks")
        
        # Save chunks
        self._save_chunks(chunks)
        
        return chunks
    
    def _save_chunks(self, chunks: List[Chunk]):
        """Save chunks to JSON"""
        chunks_data = []
        for chunk in chunks:
            chunk_dict = {
                'chunk_id': chunk.chunk_id,
                'start_line': chunk.start_line,
                'end_line': chunk.end_line,
                'combined_text': chunk.combined_text,
                'timestamp_start': chunk.timestamp_start,
                'timestamp_end': chunk.timestamp_end,
                'num_messages': len(chunk.messages)
            }
            chunks_data.append(chunk_dict)
        
        self.save_results(chunks_data, 'chunks.json')

if __name__ == "__main__":
    # Example usage
    import pandas as pd
    df = pd.read_csv('pipeline_output/preprocessed_messages.csv')
    
    creator = ChunkCreator(chunk_size=20, overlap=5)
    chunks = creator.execute(df)
    print(f"Created {len(chunks)} chunks")