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from langchain_community.embeddings import OpenAIEmbeddings
from langchain_community.embeddings import HuggingFaceEmbeddings
from modules.config.constants import OPENAI_API_KEY, HUGGINGFACE_TOKEN
class EmbeddingModelLoader:
def __init__(self, config):
self.config = config
def load_embedding_model(self):
if self.config["vectorstore"]["model"] in ["text-embedding-ada-002"]:
embedding_model = OpenAIEmbeddings(
deployment="SL-document_embedder",
model=self.config["vectorestore"]["model"],
show_progress_bar=True,
openai_api_key=OPENAI_API_KEY,
disallowed_special=(),
)
else:
embedding_model = HuggingFaceEmbeddings(
model_name=self.config["vectorstore"]["model"],
model_kwargs={
"device": f"{self.config['device']}",
"token": f"{HUGGINGFACE_TOKEN}",
"trust_remote_code": True,
},
)
return embedding_model
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