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-
- 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}"
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