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Fixes issue #5072 - adds additional support to Weaviate #5085

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merged 4 commits into from
May 23, 2023
Merged

Fixes issue #5072 - adds additional support to Weaviate #5085

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f9bf64f
Fixes issue #5072 - adds additional support to Weaviate
jettro May 22, 2023
25b6fd4
Fixes issue #5072 - adds additional support to Weaviate
jettro May 22, 2023
80c0d4e
Fixes issue #5072 - improve integration test
jettro May 22, 2023
7b28804
fix
dev2049 May 23, 2023
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4 changes: 4 additions & 0 deletions langchain/vectorstores/weaviate.py
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Original file line number Diff line number Diff line change
Expand Up @@ -201,6 +201,8 @@ def similarity_search_by_text(
query_obj = self._client.query.get(self._index_name, self._query_attrs)
if kwargs.get("where_filter"):
query_obj = query_obj.with_where(kwargs.get("where_filter"))
if kwargs.get("additional"):
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does this apply to other search methods as well? (like similarity_search_by_vector)

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Yes, we can use the same mechanism in the function similarity_search_by_vector. They have different values that you can use in the additional field. But that is specified in the Weaviate documentation. Not sure if we should replicate that here as well.

I would not use it in the functions similarity_search_with_score and max_marginal_relevance_search_by_vector. They allready use the mechanism with the additional field. They already return a score.

Do you want me to add it to the similarity_search_by_vector method as well?

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that'd be great!

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Done

query_obj = query_obj.with_additional(kwargs.get("additional"))
result = query_obj.with_near_text(content).with_limit(k).do()
if "errors" in result:
raise ValueError(f"Error during query: {result['errors']}")
Expand All @@ -218,6 +220,8 @@ def similarity_search_by_vector(
query_obj = self._client.query.get(self._index_name, self._query_attrs)
if kwargs.get("where_filter"):
query_obj = query_obj.with_where(kwargs.get("where_filter"))
if kwargs.get("additional"):
query_obj = query_obj.with_additional(kwargs.get("additional"))
result = query_obj.with_near_vector(vector).with_limit(k).do()
if "errors" in result:
raise ValueError(f"Error during query: {result['errors']}")
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17 changes: 17 additions & 0 deletions tests/integration_tests/vectorstores/test_weaviate.py
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Expand Up @@ -81,6 +81,23 @@ def test_similarity_search_with_metadata_and_filter(
)
assert output == [Document(page_content="foo", metadata={"page": 0})]

@pytest.mark.vcr(ignore_localhost=True)
def test_similarity_search_with_metadata_and_additional(
self, weaviate_url: str, embedding_openai: OpenAIEmbeddings
) -> None:
"""Test end to end construction and search with metadata and additional."""
texts = ["foo", "bar", "baz"]
metadatas = [{"page": i} for i in range(len(texts))]
docsearch = Weaviate.from_texts(
texts, embedding_openai, metadatas=metadatas, weaviate_url=weaviate_url
)
output = docsearch.similarity_search(
"foo",
k=2,
additional=["certainty"],
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is certainty supposed to be in the output? maybe im misunderstanding what with_additional does

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@jettro jettro May 22, 2023 •
edited
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You are absolutely right. I am trying to run the integration tests myself. But I cannot make it work. Now that you mention it, I think the output check should be like this:

assert output == [Document(page_content="foo", metadata={"page": 0, "_additional": {"certainty": 0}})]

I do not know how to get the value for certainty in the test. Of course I can make the change and commit, but I cannot test it myself at the moment.

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as in you can't make the integration test pass or you can't make it run at all? to run you can do

pytest tests/integration_tests/vectorstores/test_weaviate.py

you'll want to spin up local weaviate container, instructions for that at top of integration test file

cd tests/integration_tests/vectorstores/docker-compose
docker compose -f weaviate.yml up

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Thanks, learning about poetry at the same time. I managed to get the integration tests running with your tips. Now it keeps telling me he is missing the OpenAI key:

E ValueError: Error during query: [{'locations': [{'column': 6, 'line': 1}], 'message': 'explorer: get class: vectorize params: vectorize params: vectorize params: vectorize keywords: remote client vectorize: OpenAI API Key: no api key found neither in request header: X-OpenAI-Api-Key nor in environment variable under OPENAI_APIKEY', 'path': ['Get', 'LangChain_47555ec10c224f01abb7b82f7458c0b6']}]

Trying to figure out what to do here. I added the .env file in the integration_tests folder

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the integration test requires OpenAI model. if you have an openai api key just set that in the terminal you're running this in with

export OPENAI_API_KEY="<api_key>"

if you don't have openai key i can just run the test

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Sorry, I really tried everything I could, but I cannot fix it. If you can try the test, then I will try to fix it later for my environment.

)
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
Expand Down