DocsGPT/application/vectorstore/faiss.py
2023-10-06 16:05:10 +01:00

27 lines
958 B
Python

from application.vectorstore.base import BaseVectorStore
from langchain.vectorstores import FAISS
from application.core.settings import settings
class FaissStore(BaseVectorStore):
def __init__(self, path, embeddings_key, docs_init=None):
super().__init__()
self.path = path
if docs_init:
self.docsearch = FAISS.from_documents(
docs_init, self._get_embeddings(settings.EMBEDDINGS_NAME, embeddings_key)
)
else:
self.docsearch = FAISS.load_local(
self.path, self._get_embeddings(settings.EMBEDDINGS_NAME, settings.EMBEDDINGS_KEY)
)
def search(self, *args, **kwargs):
return self.docsearch.similarity_search(*args, **kwargs)
def add_texts(self, *args, **kwargs):
return self.docsearch.add_texts(*args, **kwargs)
def save_local(self, *args, **kwargs):
return self.docsearch.save_local(*args, **kwargs)