litellm/proxy/openai_files_endpoints/common_utils.py

import base64
import re
from typing import List, Literal, Union

from litellm.types.utils import SpecialEnums


def _is_base64_encoded_unified_file_id(b64_uid: str) -> Union[str, Literal[False]]:
    # Add padding back if needed
    padded = b64_uid + "=" * (-len(b64_uid) % 4)
    # Decode from base64
    try:
        decoded = base64.urlsafe_b64decode(padded).decode()
        if decoded.startswith(SpecialEnums.LITELM_MANAGED_FILE_ID_PREFIX.value):
            return decoded
        else:
            return False
    except Exception:
        return False


def convert_b64_uid_to_unified_uid(b64_uid: str) -> str:
    is_base64_unified_file_id = _is_base64_encoded_unified_file_id(b64_uid)
    if is_base64_unified_file_id:
        return is_base64_unified_file_id
    else:
        return b64_uid


def get_models_from_unified_file_id(unified_file_id: str) -> List[str]:
    """
    Extract model names from unified file ID.

    Example:
    unified_file_id = "litellm_proxy:application/octet-stream;unified_id,c4843482-b176-4901-8292-7523fd0f2c6e;target_model_names,gpt-4o-mini,gemini-2.0-flash"
    returns: ["gpt-4o-mini", "gemini-2.0-flash"]
    """
    try:
        match = re.search(r"target_model_names,([^;]+)", unified_file_id)
        if match:
            # Split on comma and strip whitespace from each model name
            return [model.strip() for model in match.group(1).split(",")]
        return []
    except Exception:
        return []