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c7db908 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 | from langchain_openai import OpenAIEmbeddings
from langchain.evaluation import load_evaluator
from dotenv import load_dotenv
import openai
import os
# Load environment variables. Assumes that project contains .env file with API keys
load_dotenv()
#---- Set OpenAI API key
# Change environment variable name from "OPENAI_API_KEY" to the name given in
# your .env file.
openai.api_key = os.environ['OPENAI_API_KEY']
def main():
# Get embedding for a word.
embedding_function = OpenAIEmbeddings()
vector = embedding_function.embed_query("apple")
print(f"Vector for 'apple': {vector}")
print(f"Vector length: {len(vector)}")
# Compare vector of two words
evaluator = load_evaluator("pairwise_embedding_distance")
words = ("apple", "iphone")
x = evaluator.evaluate_string_pairs(prediction=words[0], prediction_b=words[1])
print(f"Comparing ({words[0]}, {words[1]}): {x}")
if __name__ == "__main__":
main()
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