MaxKB/apps/models_provider/impl/tencent_model_provider/model/embedding.py
2025-04-17 18:01:33 +08:00

42 lines
1.5 KiB
Python

from typing import Dict, List
from langchain_core.embeddings import Embeddings
from tencentcloud.common import credential
from tencentcloud.hunyuan.v20230901.hunyuan_client import HunyuanClient
from tencentcloud.hunyuan.v20230901.models import GetEmbeddingRequest
from models_provider.base_model_provider import MaxKBBaseModel
class TencentEmbeddingModel(MaxKBBaseModel, Embeddings):
def embed_documents(self, texts: List[str]) -> List[List[float]]:
return [self.embed_query(text) for text in texts]
def embed_query(self, text: str) -> List[float]:
request = GetEmbeddingRequest()
request.Input = text
res = self.client.GetEmbedding(request)
return res.Data[0].Embedding
def __init__(self, secret_id: str, secret_key: str, model_name: str):
self.secret_id = secret_id
self.secret_key = secret_key
self.model_name = model_name
cred = credential.Credential(
secret_id, secret_key
)
self.client = HunyuanClient(cred, "")
@staticmethod
def new_instance(model_type: str, model_name: str, model_credential: Dict[str, str], **model_kwargs):
return TencentEmbeddingModel(
secret_id=model_credential.get('SecretId'),
secret_key=model_credential.get('SecretKey'),
model_name=model_name,
)
def _generate_auth_token(self):
# Example method to generate an authentication token for the model API
return f"{self.secret_id}:{self.secret_key}"