Open brycecf opened 5 months ago
Hey there, @brycecf! Nice to see you diving into another interesting challenge. How's everything going?
Yes, it is possible to use a QueryEngineTool
with a QueryPipeline
built with the low-level DAG API for implementing multi-document queries. However, it requires that the QueryPipeline
or its equivalent functionality be encapsulated within a class that implements the BaseQueryEngine
interface. The constructor of QueryEngineTool
specifically requires an instance of BaseQueryEngine
or a subclass thereof. This means that as long as your QueryPipeline
or the mechanism you use for multi-document queries can be adapted to follow the BaseQueryEngine
interface, you can use it with QueryEngineTool
.
The BaseQueryEngine
interface is expected to provide at least a query
method (and possibly an aquery
method for asynchronous operations, as suggested by the presence of an acall
method in QueryEngineTool
). Therefore, to integrate a QueryPipeline
with QueryEngineTool
, you would need to create a wrapper class around your QueryPipeline
that implements the BaseQueryEngine
interface. This wrapper would translate calls to the query
(and aquery
, if applicable) methods into operations on your QueryPipeline
.
Here's a simplified example of how such a wrapper might look:
from llama_index.core.base.base_query_engine import BaseQueryEngine
class QueryPipelineWrapper(BaseQueryEngine):
def __init__(self, query_pipeline):
self.query_pipeline = query_pipeline
def query(self, query_str):
# Implement the logic to use the query_pipeline for querying
# This is a placeholder for the actual implementation
response = self.query_pipeline.execute(query_str)
return response
# Optionally implement aquery if asynchronous operations are supported
This wrapper class (QueryPipelineWrapper
) takes an instance of your QueryPipeline
and makes it compatible with the QueryEngineTool
by adhering to the BaseQueryEngine
interface. You can then instantiate a QueryEngineTool
with an instance of this wrapper:
query_pipeline = YourQueryPipelineImplementation(...)
query_pipeline_wrapper = QueryPipelineWrapper(query_pipeline)
query_engine_tool = QueryEngineTool(query_engine=query_pipeline_wrapper, metadata=your_metadata)
This approach allows you to use the QueryEngineTool
with a QueryPipeline
built with the low-level DAG API for implementing multi-document queries, by ensuring compatibility through the BaseQueryEngine
interface.
You can find more details about the QueryEngineTool
and BaseQueryEngine
in the LlamaIndex codebase at the following links:
Please let me know if you need further clarification or have any other questions.
I think you can wrap it in a custom query engine (Also linking in my beta docs, because that's what I had open) https://docs.llamaindex.ai/en/logan-docs_3.0/examples/query_engine/custom_query_engine/
The API is quite new though, it could probably use a better way to do this. The main issue is a query engine has one input (the query), while the query pipeline can have arbitrary inputs
Hi @brycecf , I am facing same issue. I have built query pipeline, Now I can't use that in other library where It supports only query engine. Hopw to create custom query engine, if I have built query pipeline already
Question Validation
Question
I am using a QueryPipeline built with the low-level DAG API. I want to use QueryEngineTools to implement multi-document queries, but the constructor seems to require a query engine, which is not used in the QueryPipeline. Is there still a way to use a QueryEngineTool with a QueryPipeine? If not, is there an alternative?