%pip install openai python-dotenv

import os
from openai import OpenAI
from dotenv import load_dotenv
import numpy as np
load_dotenv()

API_KEY = os.getenv("OPENAI_API_KEY","")
assert API_KEY, "ERROR: OpenAI Key is missing"

client = OpenAI(
    api_key=API_KEY
    )

# Dependencies for embeddings_utils
%pip install matplotlib plotly scikit-learn pandas

def cosine_similarity(a, b):
    return np.dot(a, b) / (np.linalg.norm(a) * np.linalg.norm(b))

text = 'the quick brown fox jumped over the lazy dog'
model = 'text-embedding-ada-002'

client.embeddings.create(input = [text], model=model).data[0].embedding

# compare several words
automobile_embedding    = client.embeddings.create(input = 'automobile', model=model).data[0].embedding
vehicle_embedding       = client.embeddings.create(input = 'vehicle', model=model).data[0].embedding
dinosaur_embedding      = client.embeddings.create(input = 'dinosaur', model=model).data[0].embedding
stick_embedding         = client.embeddings.create(input = 'stick', model=model).data[0].embedding

# comparing cosine similarity, automobiles vs automobiles should be 1.0, i.e exactly the same, while automobiles vs dinosaurs should be between 0 and 1, i.e. not the same
print(cosine_similarity(automobile_embedding, automobile_embedding))
print(cosine_similarity(automobile_embedding, vehicle_embedding))
print(cosine_similarity(automobile_embedding, dinosaur_embedding))
print(cosine_similarity(automobile_embedding, stick_embedding))