from typing import Any, Dict, List


def compact_raw_context(
    raw_context: Dict[str, Any], max_elements: int = 25, max_string_len: int = 2000
) -> Dict[str, Any]:
    """
    Compact raw context to keep the LLM prompt size bounded.
    Slices large lists and truncates long strings.
    """
    compacted = {}

    for key, value in raw_context.items():
        if isinstance(value, list):
            count = len(value)
            if count > max_elements * 2:
                # Keep first N and last N
                trimmed = value[:max_elements] + value[-max_elements:]
                compacted[f"{key}_trimmed"] = trimmed
                compacted[f"{key}_count"] = count

                # Basic stats for numeric lists
                numeric_values = [v for v in value if isinstance(v, (int, float))]
                if numeric_values:
                    compacted[f"{key}_min"] = min(numeric_values)
                    compacted[f"{key}_max"] = max(numeric_values)
            else:
                compacted[key] = value
        elif isinstance(value, str):
            if len(value) > max_string_len:
                compacted[key] = value[:max_string_len] + "... [truncated]"
            else:
                compacted[key] = value
        elif isinstance(value, dict):
            compacted[key] = compact_raw_context(value, max_elements, max_string_len)
        else:
            compacted[key] = value

    return compacted