"""Data loading utilities for chunks and JSON files."""

import json
from pathlib import Path
from typing import List, Dict, Any
from langchain.docstore.document import Document


def load_json(filepath: Path | str) -> List[Dict[str, Any]]:
    """
    Load JSON data from file.
    
    Args:
        filepath: Path to JSON file
        
    Returns:
        List of dictionaries containing the JSON data
    """
    filepath = Path(filepath)
    
    if not filepath.exists():
        raise FileNotFoundError(f"JSON file not found: {filepath}")
    
    with open(filepath, 'r', encoding='utf-8') as f:
        data = json.load(f)
    
    return data


def open_file(filepath: Path | str) -> str:
    """
    Open and read a text file.
    
    Args:
        filepath: Path to text file
        
    Returns:
        File contents as string
    """
    filepath = Path(filepath)
    
    if not filepath.exists():
        raise FileNotFoundError(f"File not found: {filepath}")
    
    with open(filepath, 'r', encoding='utf-8') as f:
        content = f.read()
    
    return content


def load_chunks(chunks_file: Path | str = None) -> List[Dict[str, Any]]:
    """
    Load document chunks from JSON file.
    
    Args:
        chunks_file: Path to chunks JSON file. If None, uses default path.
        
    Returns:
        List of chunk dictionaries
    """
    if chunks_file is None:
        chunks_file = Path("reports/docling_chunks.json")
    
    return load_json(chunks_file)


def chunks_to_documents(chunks: List[Dict[str, Any]]) -> List[Document]:
    """
    Convert chunk dictionaries to LangChain Document objects.
    
    Args:
        chunks: List of chunk dictionaries
        
    Returns:
        List of Document objects
    """
    documents = []
    
    for chunk in chunks:
        doc = Document(
            page_content=chunk.get("content", ""),
            metadata=chunk.get("metadata", {})
        )
        documents.append(doc)
    
    return documents


def validate_chunks(chunks: List[Dict[str, Any]]) -> bool:
    """
    Validate that chunks have required fields.
    
    Args:
        chunks: List of chunk dictionaries
        
    Returns:
        True if valid, raises ValueError if invalid
    """
    required_fields = ["content", "metadata"]
    
    for i, chunk in enumerate(chunks):
        for field in required_fields:
            if field not in chunk:
                raise ValueError(f"Chunk {i} missing required field: {field}")
        
        # Validate metadata has required fields
        metadata = chunk["metadata"]
        if not isinstance(metadata, dict):
            raise ValueError(f"Chunk {i} metadata must be a dictionary")
        
        # Check for common metadata fields
        if "filename" not in metadata:
            raise ValueError(f"Chunk {i} metadata missing 'filename' field")
    
    return True