Accept uuids kwargs for weaviate (#4800)

# Accept uuids kwargs for weaviate

Fixes #4791

tests/integration_tests/retrievers/test_weaviate_hybrid_search.py

@@ -1,6 +1,7 @@
 """Test Weaviate functionality."""
 import logging
 import os
+import uuid
 from typing import Generator, Union
 from uuid import uuid4
 
@@ -85,3 +86,28 @@ class TestWeaviateHybridSearchRetriever:
         assert output == [
             Document(page_content="foo", metadata={"page": 0}),
         ]
+
+    @pytest.mark.vcr(ignore_localhost=True)
+    def test_get_relevant_documents_with_uuids(self, weaviate_url: str) -> None:
+        """Test end to end construction and MRR search."""
+        texts = ["foo", "bar", "baz"]
+        metadatas = [{"page": i} for i in range(len(texts))]
+        # Weaviate replaces the object if the UUID already exists
+        uuids = [uuid.uuid5(uuid.NAMESPACE_DNS, "same-name") for text in texts]
+
+        client = Client(weaviate_url)
+
+        retriever = WeaviateHybridSearchRetriever(
+            client=client,
+            index_name=f"LangChain_{uuid4().hex}",
+            text_key="text",
+            attributes=["page"],
+        )
+        for i, text in enumerate(texts):
+            # hoge
+            retriever.add_documents(
+                [Document(page_content=text, metadata=metadatas[i])], uuids=[uuids[i]]
+            )
+
+        output = retriever.get_relevant_documents("foo")
+        assert len(output) == 1

tests/integration_tests/vectorstores/test_weaviate.py

@@ -1,6 +1,7 @@
 """Test Weaviate functionality."""
 import logging
 import os
+import uuid
 from typing import Generator, Union
 
 import pytest
@@ -80,6 +81,26 @@ class TestWeaviate:
         )
         assert output == [Document(page_content="foo", metadata={"page": 0})]
 
+    @pytest.mark.vcr(ignore_localhost=True)
+    def test_similarity_search_with_uuids(
+        self, weaviate_url: str, embedding_openai: OpenAIEmbeddings
+    ) -> None:
+        """Test end to end construction and search with uuids."""
+        texts = ["foo", "bar", "baz"]
+        # Weaviate replaces the object if the UUID already exists
+        uuids = [uuid.uuid5(uuid.NAMESPACE_DNS, "same-name") for text in texts]
+
+        metadatas = [{"page": i} for i in range(len(texts))]
+        docsearch = Weaviate.from_texts(
+            texts,
+            embedding_openai,
+            metadatas=metadatas,
+            weaviate_url=weaviate_url,
+            uuids=uuids,
+        )
+        output = docsearch.similarity_search("foo", k=2)
+        assert len(output) == 1
+
     @pytest.mark.vcr(ignore_localhost=True)
     def test_max_marginal_relevance_search(
         self, weaviate_url: str, embedding_openai: OpenAIEmbeddings
@@ -181,3 +202,23 @@ class TestWeaviate:
             Document(page_content="foo"),
             Document(page_content="foo"),
         ]
+
+    def test_add_texts_with_given_uuids(self, weaviate_url: str) -> None:
+        texts = ["foo", "bar", "baz"]
+        embedding = FakeEmbeddings()
+        uuids = [uuid.uuid5(uuid.NAMESPACE_DNS, text) for text in texts]
+
+        docsearch = Weaviate.from_texts(
+            texts,
+            embedding=embedding,
+            weaviate_url=weaviate_url,
+            uuids=uuids,
+        )
+
+        # Weaviate replaces the object if the UUID already exists
+        docsearch.add_texts(["foo"], uuids=[uuids[0]])
+        output = docsearch.similarity_search_by_vector(
+            embedding.embed_query("foo"), k=2
+        )
+        assert output[0] == Document(page_content="foo")
+        assert output[1] != Document(page_content="foo")