Knowledge Graph Query Engine#

Knowledge Graph Query Engine.

class llama_index.core.query_engine.knowledge_graph_query_engine.KnowledgeGraphQueryEngine(llm: Optional[LLM] = None, storage_context: Optional[StorageContext] = None, graph_query_synthesis_prompt: Optional[BasePromptTemplate] = None, graph_response_answer_prompt: Optional[BasePromptTemplate] = None, refresh_schema: bool = False, verbose: bool = False, response_synthesizer: Optional[BaseSynthesizer] = None, service_context: Optional[ServiceContext] = None, **kwargs: Any)#

Knowledge graph query engine.

Query engine to call a knowledge graph.

  • service_context (Optional[ServiceContext]) – A service context to use.

  • storage_context (Optional[StorageContext]) – A storage context to use.

  • refresh_schema (bool) – Whether to refresh the schema.

  • verbose (bool) – Whether to print intermediate results.

  • response_synthesizer (Optional[BaseSynthesizer]) – A BaseSynthesizer object.

  • **kwargs – Additional keyword arguments.

async agenerate_query(query_str: str) str#

Generate a Graph Store Query from a query bundle.

as_query_component(partial: Optional[Dict[str, Any]] = None, **kwargs: Any) QueryComponent#

Get query component.

generate_query(query_str: str) str#

Generate a Graph Store Query from a query bundle.

get_prompts() Dict[str, BasePromptTemplate]#

Get a prompt.

update_prompts(prompts_dict: Dict[str, BasePromptTemplate]) None#

Update prompts.

Other prompts will remain in place.