47 lines
1.5 KiB
Python
47 lines
1.5 KiB
Python
# coding=utf-8
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"""
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@project: MaxKB
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@Author：虎
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@file： embedding.py
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@date：2024/7/12 17:44
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@desc:
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"""
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from typing import Dict
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import requests
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from langchain_community.embeddings import OpenAIEmbeddings
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from common.utils.logger import maxkb_logger
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from models_provider.base_model_provider import MaxKBBaseModel
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class SiliconCloudEmbeddingModel(MaxKBBaseModel, OpenAIEmbeddings):
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@staticmethod
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def new_instance(model_type, model_name, model_credential: Dict[str, object], **model_kwargs):
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return SiliconCloudEmbeddingModel(
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openai_api_key=model_credential.get('api_key'),
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model=model_name,
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openai_api_base=model_credential.get('api_base'),
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)
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def embed_query(self, text: str) -> list:
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payload = {
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"model": self.model,
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"input": text
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}
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headers = {
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"Authorization": f"Bearer {self.openai_api_key}",
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"Content-Type": "application/json"
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}
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response = requests.post(self.openai_api_base + '/embeddings', json=payload, headers=headers)
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data = response.json()
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# print(data)
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if data['data'] is None or 'code' in data:
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raise ValueError(f"Embedding API returned no data: {data}")
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# 假设返回结构中有 'data[0].embedding'
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return data["data"][0]["embedding"]
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def embed_documents(self, texts: list) -> list:
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return [self.embed_query(text) for text in texts]
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