mirror of
https://github.com/1Panel-dev/MaxKB.git
synced 2025-12-28 05:42:51 +00:00
66 lines
2.1 KiB
Python
66 lines
2.1 KiB
Python
# coding=utf-8
|
||
"""
|
||
@project: MaxKB
|
||
@Author：虎
|
||
@file： embedding.py
|
||
@date：2024/10/17 16:48
|
||
@desc:
|
||
"""
|
||
from typing import Dict, List
|
||
from langchain_community.embeddings import QianfanEmbeddingsEndpoint
|
||
import openai
|
||
from models_provider.base_model_provider import MaxKBBaseModel
|
||
|
||
|
||
class QianfanV1Embeddings(MaxKBBaseModel, QianfanEmbeddingsEndpoint):
|
||
@staticmethod
|
||
def new_instance(model_type, model_name, model_credential: Dict[str, object], **model_kwargs):
|
||
return QianfanV1Embeddings(
|
||
model=model_name,
|
||
qianfan_ak=model_credential.get('qianfan_ak'),
|
||
qianfan_sk=model_credential.get('qianfan_sk'),
|
||
)
|
||
|
||
|
||
class QianfanV2EmbeddingModel(MaxKBBaseModel):
|
||
model_name: str
|
||
|
||
@staticmethod
|
||
def is_cache_model():
|
||
return False
|
||
|
||
def __init__(self, api_key, base_url, model_name: str):
|
||
self.client = openai.OpenAI(api_key=api_key, base_url=base_url).embeddings
|
||
self.model_name = model_name
|
||
|
||
@staticmethod
|
||
def new_instance(model_type, model_name, model_credential: Dict[str, object], **model_kwargs):
|
||
return QianfanV2EmbeddingModel(
|
||
api_key=model_credential.get('qianfan_ak'),
|
||
model_name=model_name,
|
||
base_url=model_credential.get('api_base'),
|
||
)
|
||
|
||
def embed_query(self, text: str):
|
||
res = self.embed_documents([text])
|
||
return res[0]
|
||
|
||
def embed_documents(
|
||
self, texts: List[ str],
|
||
) -> List[List[float]]:
|
||
res = self.client.create(input=texts, model=self.model_name, encoding_format="float")
|
||
return [e.embedding for e in res.data]
|
||
|
||
|
||
class QianfanEmbeddings(MaxKBBaseModel):
|
||
|
||
|
||
@staticmethod
|
||
def new_instance(model_type, model_name, model_credential: Dict[str, object], **model_kwargs):
|
||
api_version = model_credential.get('api_version', 'v1')
|
||
|
||
if api_version == "v1":
|
||
return QianfanV1Embeddings.new_instance(model_type, model_name, model_credential, **model_kwargs)
|
||
elif api_version == "v2":
|
||
return QianfanV2EmbeddingModel.new_instance(model_type, model_name, model_credential, **model_kwargs)
|