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from langchain_community.embeddings import OpenAIEmbeddings
from langchain.embeddings import HuggingFaceEmbeddings
from modules.constants import *
class EmbeddingModelLoader:
def __init__(self, config):
self.config = config
def load_embedding_model(self):
if self.config["embedding_options"]["model"] in ["text-embedding-ada-002"]:
embedding_model = OpenAIEmbeddings(
deployment="SL-document_embedder",
model=self.config["embedding_options"]["model"],
show_progress_bar=True,
openai_api_key=OPENAI_API_KEY,
)
else:
embedding_model = HuggingFaceEmbeddings(
model_name="sentence-transformers/all-MiniLM-L6-v2",
model_kwargs={"device": "cpu"},
)
return embedding_model
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