def retrieve_and_rank()

in experiments/legacy/backend/category.py [0:0]

• 10 lines of code
• 4 McCabe index (conditional complexity)

def retrieve_and_rank(    
    desc: str, 
    image: Optional[str] = None, 
    base64: bool = False,
    num_neighbors: int = config.NUM_NEIGHBORS,
    filters: list[str] = []) -> list[list[str]]:
    """Wrapper function to sequence retrieve and rank functions.
    
    Args:
        desc: user provided description of product
        image: can be local file path, GCS URI or base64 encoded image
        base64: True indicates image is base64. False (default) will be 
          interpreted as image path (either local or GCS)
        num_neigbhors: number of nearest neighbors to return for EACH embedding
        filters: category prefix to restrict results to

    Returns:
      The candidates ranked by the LLM from most to least relevant. If there are
      duplicate candidates the list is deduped prior to returning
    """
    candidates = retrieve(desc, image, base64, num_neighbors, filters)
    if filters and not candidates:
      return [['ERROR: No existing products match that category']]
    return rank(desc, [candidate['category'] for candidate in candidates])