chroma func _similarity_search_with_relevance_scores missing "kwargs" parameter

[sudolong]

System Info

LangChain: v0.0.214

Who can help?

No response

Information

• The official example notebooks/scripts
• My own modified scripts

Related Components

• LLMs/Chat Models
• Embedding Models
• Prompts / Prompt Templates / Prompt Selectors
• Output Parsers
• Document Loaders
• Vector Stores / Retrievers
• Memory
• Agents / Agent Executors
• Tools / Toolkits
• Chains
• Callbacks/Tracing
• Async

Reproduction

https://github.com/hwchase17/langchain/blob/v0.0.214/langchain/vectorstores/base.py#L410
https://github.com/hwchase17/langchain/blob/v0.0.214/langchain/vectorstores/chroma.py#L225
https://github.com/hwchase17/langchain/blob/v0.0.214/langchain/vectorstores/chroma.py#L198

The filter option does not work when search_type is similarity_score_threshold

Expected behavior

work:

def _similarity_search_with_relevance_scores(
        self,
        query: str,
        k: int = 4,
        **kwargs: Any,
    ) -> List[Tuple[Document, float]]:
        return self.similarity_search_with_score(query, k, **kwargs)

[sudolong]

@hwchase17 Please take a moment to take a look

[dosubot]

Hi, @sudolong! I'm Dosu, and I'm helping the LangChain team manage their backlog. I wanted to let you know that we are marking this issue as stale.

From what I understand, you opened this issue regarding a missing "kwargs" parameter in the chroma function _similarity_search_with_relevance_scores. You mentioned that the function should work with the "filter" option when the search_type is similarity_score_threshold. There has been recent activity with hwchase17 being requested to take a look at the issue.

Before we proceed, we would like to confirm if this issue is still relevant to the latest version of the LangChain repository. If it is, please let us know by commenting on the issue. Otherwise, feel free to close the issue yourself, or it will be automatically closed in 7 days.

Thank you for your understanding and contribution to the LangChain project!