# 使用豆包来向量化文本

import requests

VOLC_EMBEDDINGS_API_URL = "https://ark.cn-beijing.volces.com/api/v3/embeddings"
VOLC_API_KEY = "79b39c58-56db-4d8a-a8f8-84b95fca08db"


def get_doubao_embedding(doc):
    headers = {
        "Content-Type": "application/json",
        "Authorization": f"Bearer {VOLC_API_KEY}",
    }
    params = {"model": "doubao-embedding-text-240715", "input": doc}
    response = requests.post(VOLC_EMBEDDINGS_API_URL, json=params, headers=headers)
    if response.status_code == 200:
        data = response.json()
        embedding = data["data"][0]["embedding"]
        return embedding
    else:
        raise Exception(f"Embedding API error:{response.text}")


embedding = get_doubao_embedding("这是一段文档")
print(embedding)