"""
utils.py
"""

# Standard imports
import os
from typing import List

# Third party imports
import numpy as np
from openai import OpenAI

client = OpenAI(api_key=os.environ.get("OPENAI_API_KEY"))

# Maximum tokens for text-embedding-3-large
MAX_TOKENS = 8191  # We don't have access to the tokenizer for text-embedding-3-large, and just assume 1 character = 1 token here


def get_embeddings(
    texts: List[str], model: str = "text-embedding-3-large"
) -> List[List[float]]:
    """
    Generate embeddings for a list of texts using OpenAI API synchronously.

    Args:
        texts: List of strings to embed.
        model: OpenAI embedding model to use (default: text-embedding-3-large).

    Returns:
        A list of embeddings (each embedding is a list of floats).

    Raises:
        Exception: If the OpenAI API call fails.
    """

    # Truncate texts to max token limit
    truncated_texts = [text[:MAX_TOKENS] for text in texts]

    # Make the API call
    response = client.embeddings.create(input=truncated_texts, model=model)

    # Extract embeddings from response
    embeddings = np.array([data.embedding for data in response.data])
    return embeddings