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276 | class FLAREInstructQueryEngine(BaseQueryEngine):
"""FLARE Instruct query engine.
This is the version of FLARE that uses retrieval-encouraging instructions.
NOTE: this is a beta feature. Interfaces might change, and it might not
always give correct answers.
Args:
query_engine (BaseQueryEngine): query engine to use
llm (Optional[LLM]): LLM model. Defaults to None.
instruct_prompt (Optional[PromptTemplate]): instruct prompt. Defaults to None.
lookahead_answer_inserter (Optional[BaseLookaheadAnswerInserter]):
lookahead answer inserter. Defaults to None.
done_output_parser (Optional[IsDoneOutputParser]): done output parser.
Defaults to None.
query_task_output_parser (Optional[QueryTaskOutputParser]):
query task output parser. Defaults to None.
max_iterations (int): max iterations. Defaults to 10.
max_lookahead_query_tasks (int): max lookahead query tasks. Defaults to 1.
callback_manager (Optional[CallbackManager]): callback manager.
Defaults to None.
verbose (bool): give verbose outputs. Defaults to False.
"""
def __init__(
self,
query_engine: BaseQueryEngine,
llm: Optional[LLM] = None,
instruct_prompt: Optional[BasePromptTemplate] = None,
lookahead_answer_inserter: Optional[BaseLookaheadAnswerInserter] = None,
done_output_parser: Optional[IsDoneOutputParser] = None,
query_task_output_parser: Optional[QueryTaskOutputParser] = None,
max_iterations: int = 10,
max_lookahead_query_tasks: int = 1,
callback_manager: Optional[CallbackManager] = None,
verbose: bool = False,
) -> None:
"""Init params."""
super().__init__(callback_manager=callback_manager)
self._query_engine = query_engine
self._llm = llm or Settings.llm
self._instruct_prompt = instruct_prompt or DEFAULT_INSTRUCT_PROMPT
self._lookahead_answer_inserter = lookahead_answer_inserter or (
LLMLookaheadAnswerInserter(llm=self._llm)
)
self._done_output_parser = done_output_parser or IsDoneOutputParser()
self._query_task_output_parser = (
query_task_output_parser or QueryTaskOutputParser()
)
self._max_iterations = max_iterations
self._max_lookahead_query_tasks = max_lookahead_query_tasks
self._verbose = verbose
def _get_prompts(self) -> Dict[str, Any]:
"""Get prompts."""
return {
"instruct_prompt": self._instruct_prompt,
}
def _update_prompts(self, prompts: PromptDictType) -> None:
"""Update prompts."""
if "instruct_prompt" in prompts:
self._instruct_prompt = prompts["instruct_prompt"]
def _get_prompt_modules(self) -> PromptMixinType:
"""Get prompt sub-modules."""
return {
"query_engine": self._query_engine,
"lookahead_answer_inserter": self._lookahead_answer_inserter,
}
def _get_relevant_lookahead_response(self, updated_lookahead_resp: str) -> str:
"""Get relevant lookahead response."""
# if there's remaining query tasks, then truncate the response
# until the start position of the first tag
# there may be remaining query tasks because the _max_lookahead_query_tasks
# is less than the total number of generated [Search(query)] tags
remaining_query_tasks = self._query_task_output_parser.parse(
updated_lookahead_resp
)
if len(remaining_query_tasks) == 0:
relevant_lookahead_resp = updated_lookahead_resp
else:
first_task = remaining_query_tasks[0]
relevant_lookahead_resp = updated_lookahead_resp[: first_task.start_idx]
return relevant_lookahead_resp
def _query(self, query_bundle: QueryBundle) -> RESPONSE_TYPE:
"""Query and get response."""
print_text(f"Query: {query_bundle.query_str}\n", color="green")
cur_response = ""
source_nodes = []
for iter in range(self._max_iterations):
if self._verbose:
print_text(f"Current response: {cur_response}\n", color="blue")
# generate "lookahead response" that contains "[Search(query)]" tags
# e.g.
# The colors on the flag of Ghana have the following meanings. Red is
# for [Search(Ghana flag meaning)],...
lookahead_resp = self._llm.predict(
self._instruct_prompt,
query_str=query_bundle.query_str,
existing_answer=cur_response,
)
lookahead_resp = lookahead_resp.strip()
if self._verbose:
print_text(f"Lookahead response: {lookahead_resp}\n", color="pink")
is_done, fmt_lookahead = self._done_output_parser.parse(lookahead_resp)
if is_done:
cur_response = cur_response.strip() + " " + fmt_lookahead.strip()
break
# parse lookahead response into query tasks
query_tasks = self._query_task_output_parser.parse(lookahead_resp)
# get answers for each query task
query_tasks = query_tasks[: self._max_lookahead_query_tasks]
query_answers = []
for _, query_task in enumerate(query_tasks):
answer_obj = self._query_engine.query(query_task.query_str)
if not isinstance(answer_obj, Response):
raise ValueError(
f"Expected Response object, got {type(answer_obj)} instead."
)
query_answer = str(answer_obj)
query_answers.append(query_answer)
source_nodes.extend(answer_obj.source_nodes)
# fill in the lookahead response template with the query answers
# from the query engine
updated_lookahead_resp = self._lookahead_answer_inserter.insert(
lookahead_resp, query_tasks, query_answers, prev_response=cur_response
)
# get "relevant" lookahead response by truncating the updated
# lookahead response until the start position of the first tag
# also remove the prefix from the lookahead response, so that
# we can concatenate it with the existing response
relevant_lookahead_resp_wo_prefix = self._get_relevant_lookahead_response(
updated_lookahead_resp
)
if self._verbose:
print_text(
"Updated lookahead response: "
+ f"{relevant_lookahead_resp_wo_prefix}\n",
color="pink",
)
# append the relevant lookahead response to the final response
cur_response = (
cur_response.strip() + " " + relevant_lookahead_resp_wo_prefix.strip()
)
# NOTE: at the moment, does not support streaming
return Response(response=cur_response, source_nodes=source_nodes)
async def _aquery(self, query_bundle: QueryBundle) -> RESPONSE_TYPE:
return self._query(query_bundle)
def retrieve(self, query_bundle: QueryBundle) -> List[NodeWithScore]:
# if the query engine is a retriever, then use the retrieve method
if isinstance(self._query_engine, RetrieverQueryEngine):
return self._query_engine.retrieve(query_bundle)
else:
raise NotImplementedError(
"This query engine does not support retrieve, use query directly"
)
async def aretrieve(self, query_bundle: QueryBundle) -> List[NodeWithScore]:
# if the query engine is a retriever, then use the retrieve method
if isinstance(self._query_engine, RetrieverQueryEngine):
return await self._query_engine.aretrieve(query_bundle)
else:
raise NotImplementedError(
"This query engine does not support retrieve, use query directly"
)
|
