def get_input_files(
        self,
        metadata_filter: Optional[str] = None,
        filepath_globpattern: Optional[str] = None,
    ) -> list:
        """
        Fetch information on documents in the vector store.

        Args:
            metadata_filter: optional string representing the metadata filtering query
                in the JMESPath format. The search will happen only for documents
                satisfying this filtering.
            filepath_globpattern: optional glob pattern specifying which documents
                will be searched for this query.

        """
        url = self.url + "/v1/inputs"
        response = requests.post(
            url,
            json={
                "metadata_filter": metadata_filter,
                "filepath_globpattern": filepath_globpattern,
            },
            headers={"Content-Type": "application/json"},
        )
        return response.json()

        Fetch information on documents in the vector store.

        Args:
            metadata_filter: optional string representing the metadata filtering query
                in the JMESPath format. The search will happen only for documents
                satisfying this filtering.
            filepath_globpattern: optional glob pattern specifying which documents
                will be searched for this query.

        
llama-index-integrations/retrievers/llama-index-retrievers-pathway/llama_index/retrievers/pathway/base.py