Upstage 임베딩
Upstage 임베딩
Colab에서 이 노트북을 여는 경우라면 LlamaIndex 🦙 설치가 필요할 거예요.
%pip install llama-index-embeddings-upstage==0.2.1
!pip install llama-index
import os
os.environ["UPSTAGE_API_KEY"] = "YOUR_API_KEY"
from llama_index.embeddings.upstage import UpstageEmbedding
from llama_index.core import Settings
embed_model = UpstageEmbedding()
Settings.embed_model = embed_model
Upstage 임베딩 사용하기
주의: openai 클라이언트를 업데이트해야 할 수도 있어요: pip install -U openai
# get API key and create embeddings
from llama_index.embeddings.upstage import UpstageEmbedding
embed_model = UpstageEmbedding()
embeddings = embed_model.get_text_embedding(
"Upstage new Embeddings models is great."
)
print(embeddings[:5])
[0.02535058930516243, 0.007272760849446058, 0.015372460708022118, -0.007840132340788841, 0.0017625312320888042]
print(len(embeddings))
4096
embeddings = embed_model.get_query_embedding(
"What are some great Embeddings model?"
)
print(embeddings[:5])
[0.03518765792250633, 0.01018011849373579, 0.013282101601362228, -0.008568626828491688, -0.005505830980837345]
print(len(embeddings))
4096
# embed documents
embeddings = embed_model.get_text_embedding_batch(
[
"Upstage new Embeddings models is awesome.",
"Upstage LLM is also awesome.",
]
)
print(len(embeddings))
2
print(embeddings[0][:5])
[0.028246860951185226, 0.008945596404373646, 0.01719627156853676, -0.005711239762604237, 0.0016300849383696914]
출처: 문서