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Merge pull request #1 from Devparihar5/test_v1

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fix: Refactor FaissStore to enhance error handling, improve type hint…
This commit is contained in:
Devendra Parihar
2024-10-01 19:43:26 +05:30
committed by GitHub
parent 3b4a95ef33 aa7f59f88c
commit c57ff3ae51
1 changed files with 18 additions and 25 deletions
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43
application/vectorstore/faiss.py
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@@ -3,30 +3,27 @@ from application.vectorstore.base import BaseVectorStore
from application.core.settings import settings
import os
def get_vectorstore(path):
def get_vectorstore(path: str) -> str:
if path:
vectorstore = "indexes/"+path
vectorstore = os.path.join("application", vectorstore)
vectorstore = os.path.join("application", "indexes", path)
else:
vectorstore = os.path.join("application")
return vectorstore
class FaissStore(BaseVectorStore):
def __init__(self, source_id, embeddings_key, docs_init=None):
def __init__(self, source_id: str, embeddings_key: str, docs_init=None):
super().__init__()
self.path = get_vectorstore(source_id)
embeddings = self._get_embeddings(settings.EMBEDDINGS_NAME, embeddings_key)
if docs_init:
self.docsearch = FAISS.from_documents(
docs_init, embeddings
)
else:
self.docsearch = FAISS.load_local(
self.path, embeddings,
allow_dangerous_deserialization=True
)
try:
if docs_init:
self.docsearch = FAISS.from_documents(docs_init, embeddings)
else:
self.docsearch = FAISS.load_local(self.path, embeddings, allow_dangerous_deserialization=True)
except Exception as e:
raise
self.assert_embedding_dimensions(embeddings)
def search(self, *args, **kwargs):
@@ -42,16 +39,12 @@ class FaissStore(BaseVectorStore):
return self.docsearch.delete(*args, **kwargs)
def assert_embedding_dimensions(self, embeddings):
"""
Check that the word embedding dimension of the docsearch index matches
the dimension of the word embeddings used
"""
"""Check that the word embedding dimension of the docsearch index matches the dimension of the word embeddings used."""
if settings.EMBEDDINGS_NAME == "huggingface_sentence-transformers/all-mpnet-base-v2":
try:
word_embedding_dimension = embeddings.dimension
except AttributeError as e:
raise AttributeError("'dimension' attribute not found in embeddings instance. Make sure the embeddings object is properly initialized.") from e
word_embedding_dimension = getattr(embeddings, 'dimension', None)
if word_embedding_dimension is None:
raise AttributeError("'dimension' attribute not found in embeddings instance.")
docsearch_index_dimension = self.docsearch.index.d
if word_embedding_dimension != docsearch_index_dimension:
raise ValueError(f"Embedding dimension mismatch: embeddings.dimension ({word_embedding_dimension}) " +
f"!= docsearch index dimension ({docsearch_index_dimension})")
raise ValueError(f"Embedding dimension mismatch: embeddings.dimension ({word_embedding_dimension}) != docsearch index dimension ({docsearch_index_dimension})")