langchain/retrievers/llama_index.py/LlamaIndexGraphRetriever/get_relevant_documents
class LlamaIndexGraphRetriever:    def get_relevant_documents(self, query: str) -> List[Document]:
        """Get documents relevant for a query."""
        try:
            from llama_index.composability.graph import (
                QUERY_CONFIG_TYPE,
                ComposableGraph,
            )
            from llama_index.response.schema import Response
        except ImportError:
            raise ImportError(
                "You need to install `pip install llama-index` to use this retriever."
            )
        graph = cast(ComposableGraph, self.graph)

        # for now, inject response_mode="no_text" into query configs
        for query_config in self.query_configs:
            query_config["response_mode"] = "no_text"
        query_configs = cast(List[QUERY_CONFIG_TYPE], self.query_configs)
        response = graph.query(query, query_configs=query_configs)
        response = cast(Response, response)

        # parse source nodes
        docs = []
        for source_node in response.source_nodes:
            metadata = source_node.extra_info or {}
            docs.append(
                Document(page_content=source_node.source_text, metadata=metadata)
            )
        return docs