bug: skip validating empty embeddings (#3774)

* skip validating empty embeddings

* skip batches without embeddings to update

* add unit test with mocked retriever

haystack/document_stores/pinecone.py

@@ -505,6 +505,12 @@ class PineconeDocumentStore(BaseDocumentStore):
             for _ in range(0, document_count, batch_size):
                 document_batch = list(islice(documents, batch_size))
                 embeddings = retriever.embed_documents(document_batch)
+                if embeddings.size == 0:
+                    # Skip batch if there are no embeddings. Otherwise, incorrect embedding shape will be inferred and
+                    # Pinecone APi will return a "No vectors provided" Bad Request Error
+                    progress_bar.set_description_str("Documents Processed")
+                    progress_bar.update(batch_size)
+                    continue
                 self._validate_embeddings_shape(
                     embeddings=embeddings, num_documents=len(document_batch), embedding_dim=self.embedding_dim
                 )

test/document_stores/test_pinecone.py

@@ -2,6 +2,7 @@ from typing import List, Union, Dict, Any
 
 import os
 from inspect import getmembers, isclass, isfunction
+from unittest.mock import MagicMock
 
 import pytest
 
@@ -12,8 +13,7 @@ from haystack.errors import FilterError
 
 from .test_base import DocumentStoreBaseTestAbstract
 from ..mocks import pinecone as pinecone_mock
-from ..conftest import SAMPLES_PATH
-
+from ..nodes.test_retriever import MockBaseRetriever
 
 # Set metadata fields used during testing for PineconeDocumentStore meta_config
 META_FIELDS = ["meta_field", "name", "date", "numeric_field", "odd_document"]
@@ -417,3 +417,15 @@ class TestPineconeDocumentStore(DocumentStoreBaseTestAbstract):
 
         assert len(retrieved_docs) == 1
         assert retrieved_docs[0].meta == multilayer_meta
+
+    @pytest.mark.unit
+    def test_skip_validating_empty_embeddings(self, ds: PineconeDocumentStore):
+        document = Document(id="0", content="test")
+        retriever = MockBaseRetriever(document_store=ds, mock_document=document)
+        ds.write_documents(documents=[document])
+        ds._validate_embeddings_shape = MagicMock()
+
+        ds.update_embeddings(retriever)
+        ds._validate_embeddings_shape.assert_called_once()
+        ds.update_embeddings(retriever, update_existing_embeddings=False)
+        ds._validate_embeddings_shape.assert_called_once()

test/nodes/test_retriever.py

@@ -20,8 +20,6 @@ from haystack.nodes.retriever.base import BaseRetriever
 from haystack.pipelines import DocumentSearchPipeline
 from haystack.schema import Document
 from haystack.document_stores.elasticsearch import ElasticsearchDocumentStore
-from haystack.document_stores.faiss import FAISSDocumentStore
-from haystack.document_stores import MilvusDocumentStore
 from haystack.nodes.retriever.dense import DensePassageRetriever, EmbeddingRetriever, TableTextRetriever
 from haystack.nodes.retriever.sparse import BM25Retriever, FilterRetriever, TfidfRetriever
 from haystack.nodes.retriever.multimodal import MultiModalRetriever
@@ -160,6 +158,9 @@ class MockBaseRetriever(MockRetriever):
     ):
         return [[self.mock_document] for _ in range(len(queries))]
 
+    def embed_documents(self, documents: List[Document]):
+        return np.full((len(documents), 768), 0.5)
+
 
 def test_retrieval_empty_query(document_store: BaseDocumentStore):
     # test with empty query using the run() method