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276 | class SubQuestionQueryEngine(BaseQueryEngine):
"""Sub question query engine.
A query engine that breaks down a complex query (e.g. compare and contrast) into
many sub questions and their target query engine for execution.
After executing all sub questions, all responses are gathered and sent to
response synthesizer to produce the final response.
Args:
question_gen (BaseQuestionGenerator): A module for generating sub questions
given a complex question and tools.
response_synthesizer (BaseSynthesizer): A response synthesizer for
generating the final response
query_engine_tools (Sequence[QueryEngineTool]): Tools to answer the
sub questions.
verbose (bool): whether to print intermediate questions and answers.
Defaults to True
use_async (bool): whether to execute the sub questions with asyncio.
Defaults to True
"""
def __init__(
self,
question_gen: BaseQuestionGenerator,
response_synthesizer: BaseSynthesizer,
query_engine_tools: Sequence[QueryEngineTool],
callback_manager: Optional[CallbackManager] = None,
verbose: bool = True,
use_async: bool = False,
) -> None:
self._question_gen = question_gen
self._response_synthesizer = response_synthesizer
self._metadatas = [x.metadata for x in query_engine_tools]
self._query_engines = {
tool.metadata.name: tool.query_engine for tool in query_engine_tools
}
self._verbose = verbose
self._use_async = use_async
super().__init__(callback_manager)
def _get_prompt_modules(self) -> PromptMixinType:
"""Get prompt sub-modules."""
return {
"question_gen": self._question_gen,
"response_synthesizer": self._response_synthesizer,
}
@classmethod
def from_defaults(
cls,
query_engine_tools: Sequence[QueryEngineTool],
llm: Optional[LLM] = None,
question_gen: Optional[BaseQuestionGenerator] = None,
response_synthesizer: Optional[BaseSynthesizer] = None,
verbose: bool = True,
use_async: bool = True,
) -> "SubQuestionQueryEngine":
callback_manager = Settings.callback_manager
if len(query_engine_tools) > 0:
callback_manager = query_engine_tools[0].query_engine.callback_manager
llm = llm or Settings.llm
if question_gen is None:
try:
from llama_index.question_gen.openai import (
OpenAIQuestionGenerator,
) # pants: no-infer-dep
# try to use OpenAI function calling based question generator.
# if incompatible, use general LLM question generator
question_gen = OpenAIQuestionGenerator.from_defaults(llm=llm)
except ImportError as e:
raise ImportError(
"`llama-index-question-gen-openai` package cannot be found. "
"Please install it by using `pip install `llama-index-question-gen-openai`"
)
except ValueError:
question_gen = LLMQuestionGenerator.from_defaults(llm=llm)
synth = response_synthesizer or get_response_synthesizer(
llm=llm,
callback_manager=callback_manager,
use_async=use_async,
)
return cls(
question_gen,
synth,
query_engine_tools,
callback_manager=callback_manager,
verbose=verbose,
use_async=use_async,
)
def _query(self, query_bundle: QueryBundle) -> RESPONSE_TYPE:
with self.callback_manager.event(
CBEventType.QUERY, payload={EventPayload.QUERY_STR: query_bundle.query_str}
) as query_event:
sub_questions = self._question_gen.generate(self._metadatas, query_bundle)
colors = get_color_mapping([str(i) for i in range(len(sub_questions))])
if self._verbose:
print_text(f"Generated {len(sub_questions)} sub questions.\n")
if self._use_async:
tasks = [
self._aquery_subq(sub_q, color=colors[str(ind)])
for ind, sub_q in enumerate(sub_questions)
]
qa_pairs_all = run_async_tasks(tasks)
qa_pairs_all = cast(List[Optional[SubQuestionAnswerPair]], qa_pairs_all)
else:
qa_pairs_all = [
self._query_subq(sub_q, color=colors[str(ind)])
for ind, sub_q in enumerate(sub_questions)
]
# filter out sub questions that failed
qa_pairs: List[SubQuestionAnswerPair] = list(filter(None, qa_pairs_all))
nodes = [self._construct_node(pair) for pair in qa_pairs]
source_nodes = [node for qa_pair in qa_pairs for node in qa_pair.sources]
response = self._response_synthesizer.synthesize(
query=query_bundle,
nodes=nodes,
additional_source_nodes=source_nodes,
)
query_event.on_end(payload={EventPayload.RESPONSE: response})
return response
async def _aquery(self, query_bundle: QueryBundle) -> RESPONSE_TYPE:
with self.callback_manager.event(
CBEventType.QUERY, payload={EventPayload.QUERY_STR: query_bundle.query_str}
) as query_event:
sub_questions = await self._question_gen.agenerate(
self._metadatas, query_bundle
)
colors = get_color_mapping([str(i) for i in range(len(sub_questions))])
if self._verbose:
print_text(f"Generated {len(sub_questions)} sub questions.\n")
tasks = [
self._aquery_subq(sub_q, color=colors[str(ind)])
for ind, sub_q in enumerate(sub_questions)
]
qa_pairs_all = await asyncio.gather(*tasks)
qa_pairs_all = cast(List[Optional[SubQuestionAnswerPair]], qa_pairs_all)
# filter out sub questions that failed
qa_pairs: List[SubQuestionAnswerPair] = list(filter(None, qa_pairs_all))
nodes = [self._construct_node(pair) for pair in qa_pairs]
source_nodes = [node for qa_pair in qa_pairs for node in qa_pair.sources]
response = await self._response_synthesizer.asynthesize(
query=query_bundle,
nodes=nodes,
additional_source_nodes=source_nodes,
)
query_event.on_end(payload={EventPayload.RESPONSE: response})
return response
def _construct_node(self, qa_pair: SubQuestionAnswerPair) -> NodeWithScore:
node_text = (
f"Sub question: {qa_pair.sub_q.sub_question}\nResponse: {qa_pair.answer}"
)
return NodeWithScore(node=TextNode(text=node_text))
async def _aquery_subq(
self, sub_q: SubQuestion, color: Optional[str] = None
) -> Optional[SubQuestionAnswerPair]:
try:
with self.callback_manager.event(
CBEventType.SUB_QUESTION,
payload={EventPayload.SUB_QUESTION: SubQuestionAnswerPair(sub_q=sub_q)},
) as event:
question = sub_q.sub_question
query_engine = self._query_engines[sub_q.tool_name]
if self._verbose:
print_text(f"[{sub_q.tool_name}] Q: {question}\n", color=color)
response = await query_engine.aquery(question)
response_text = str(response)
if self._verbose:
print_text(f"[{sub_q.tool_name}] A: {response_text}\n", color=color)
qa_pair = SubQuestionAnswerPair(
sub_q=sub_q, answer=response_text, sources=response.source_nodes
)
event.on_end(payload={EventPayload.SUB_QUESTION: qa_pair})
return qa_pair
except ValueError:
logger.warning(f"[{sub_q.tool_name}] Failed to run {question}")
return None
def _query_subq(
self, sub_q: SubQuestion, color: Optional[str] = None
) -> Optional[SubQuestionAnswerPair]:
try:
with self.callback_manager.event(
CBEventType.SUB_QUESTION,
payload={EventPayload.SUB_QUESTION: SubQuestionAnswerPair(sub_q=sub_q)},
) as event:
question = sub_q.sub_question
query_engine = self._query_engines[sub_q.tool_name]
if self._verbose:
print_text(f"[{sub_q.tool_name}] Q: {question}\n", color=color)
response = query_engine.query(question)
response_text = str(response)
if self._verbose:
print_text(f"[{sub_q.tool_name}] A: {response_text}\n", color=color)
qa_pair = SubQuestionAnswerPair(
sub_q=sub_q, answer=response_text, sources=response.source_nodes
)
event.on_end(payload={EventPayload.SUB_QUESTION: qa_pair})
return qa_pair
except ValueError:
logger.warning(f"[{sub_q.tool_name}] Failed to run {question}")
return None
|
