hugegraph-llm/src/hugegraph_llm/flows/get_graph_index_info.py

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import json

from PyCGraph import GPipeline

from hugegraph_llm.config import huge_settings, index_settings
from hugegraph_llm.flows.common import BaseFlow
from hugegraph_llm.models.embeddings.init_embedding import Embeddings
from hugegraph_llm.state.ai_state import WkFlowInput, WkFlowState
from hugegraph_llm.nodes.hugegraph_node.fetch_graph_data import FetchGraphDataNode


# pylint: disable=arguments-differ,keyword-arg-before-vararg
class GetGraphIndexInfoFlow(BaseFlow):
    def __init__(self):
        pass

    def prepare(self, prepared_input: WkFlowInput, **kwargs):
        return

    def build_flow(self, **kwargs):
        pipeline = GPipeline()
        prepared_input = WkFlowInput()
        self.prepare(prepared_input, **kwargs)
        pipeline.createGParam(prepared_input, "wkflow_input")
        pipeline.createGParam(WkFlowState(), "wkflow_state")
        fetch_node = FetchGraphDataNode()
        pipeline.registerGElement(fetch_node, set(), "fetch_node")
        return pipeline

    def post_deal(self, pipeline=None):
        # Lazy import to avoid circular dependency
        from hugegraph_llm.utils.vector_index_utils import get_vector_index_class  # pylint: disable=import-outside-toplevel

        graph_summary_info = pipeline.getGParamWithNoEmpty("wkflow_state").to_json()

        try:
            vector_index_class = get_vector_index_class(index_settings.cur_vector_index)
            embedding = Embeddings().get_embedding()
            vector_index = vector_index_class.from_name(
                embedding.get_embedding_dim(), huge_settings.graph_name, "graph_vids"
            )
            graph_summary_info["vid_index"] = vector_index.get_vector_index_info()
        except Exception:  # pylint: disable=broad-except
            # If vector index doesn't exist or fails to load, just return graph summary
            pass

        return json.dumps(graph_summary_info, ensure_ascii=False, indent=2)