Throw error when vector and query are None (#142)

These are okay:

```python
weaviate_vector_store._perform_search(query="hello", vector=None, k=5)

    weaviate_vector_store._perform_search(query=None, vector=[1, 2, 3], k=5)
```

These are not okay:

```python
weaviate_vector_store._perform_search(query=None, k=5)
weaviate_vector_store._perform_search(query=None, vector=None, k=5)

```

Signed-off-by: hsm207 <[email protected]>

---------

Signed-off-by: hsm207 <[email protected]>

langchain_weaviate/vectorstores.py

@@ -230,20 +230,25 @@ def _perform_search(
         if self._embedding is None:
             raise ValueError("_embedding cannot be None for similarity_search")
 
-        if "return_metadata" in kwargs and "score" not in kwargs["return_metadata"]:
-            kwargs["return_metadata"].append("score")
-        else:
+        if "return_metadata" not in kwargs:
             kwargs["return_metadata"] = ["score"]
+        elif "score" not in kwargs["return_metadata"]:
+            kwargs["return_metadata"].append("score")
 
         if (
             "return_properties" in kwargs
             and self._text_key not in kwargs["return_properties"]
         ):
             kwargs["return_properties"].append(self._text_key)
 
-        # workaround to handle test_max_marginal_relevance_search
         vector = kwargs.pop("vector", None)
-        if vector is None and query is not None:
+        if vector is None and query is None:
+            # raise an error because weaviate will do a fetch object query
+            # if both query and vector are None
+            raise ValueError("Either query or vector must be provided.")
+
+        # workaround to handle test_max_marginal_relevance_search
+        if vector is None:
             vector = self._embedding.embed_query(query)
 
         return_uuids = kwargs.pop("return_uuids", False)

tests/integration_tests/test_vectorstores.py

@@ -802,3 +802,25 @@ def run_similarity_test(search_method):
     run_similarity_test("similarity_search")
 
     run_similarity_test("similarity_search_with_score")
+
+
+def test_invalid_search_param(weaviate_client, embedding_openai):
+    index_name = f"TestIndex_{uuid.uuid4().hex}"
+    text_key = "page"
+    weaviate_vector_store = WeaviateVectorStore(
+        weaviate_client, index_name, text_key, embedding_openai
+    )
+
+    with pytest.raises(ValueError) as excinfo:
+        weaviate_vector_store._perform_search(query=None, k=5)
+
+    assert str(excinfo.value) == "Either query or vector must be provided."
+
+    with pytest.raises(ValueError) as excinfo:
+        weaviate_vector_store._perform_search(query=None, vector=None, k=5)
+
+    assert str(excinfo.value) == "Either query or vector must be provided."
+
+    weaviate_vector_store._perform_search(query="hello", vector=None, k=5)
+
+    weaviate_vector_store._perform_search(query=None, vector=[1, 2, 3], k=5)