ItemStudy/ItemRelate.py

import os
os.environ["OPENAI_API_KEY"]= "sk-PRJ811XeKzEy20Ug3dA98a34Af8b40B5816dE15503D33599"
os.environ["OPENAI_BASE_URL"]= "http://154.9.28.247:3000/v1/"

from openai import OpenAI
client = OpenAI()

from sklearn.metrics.pairwise import cosine_similarity

def main(scale):

	item=[]
	vec=[]

	for i in scale:
		item.append(i)
		vec.append(client.embeddings.create(
    		input=scale[i], model="text-embedding-3-small" # nomic-embed-text text-embedding-3-small
			).data[0].embedding)

	simi=cosine_similarity(vec)

	que=[]

	for i,v in enumerate(simi):
		for j in range(0,i):
			que.append({"from":item[j], "to":item[i], "similarity":simi[i][j]})

	return 	sorted(que, key = lambda t : t["similarity"], reverse=True)