fix: Allow injection of ExpandChunks-task into `MultipleChunkRetrie…

…verQa`

src/intelligence_layer/use_cases/qa/multiple_chunk_retriever_qa.py

@@ -15,6 +15,7 @@
 from intelligence_layer.use_cases.search.expand_chunks import (
     ExpandChunks,
     ExpandChunksInput,
+    ExpandChunksOutput,
 )
 from intelligence_layer.use_cases.search.search import Search, SearchInput
 
@@ -49,6 +50,8 @@ class MultipleChunkRetrieverQa(
     In contrast to the regular `RetrieverBasedQa`, this tasks injects multiple chunks into one
     `SingleChunkQa` task run.
 
+    We recommend using this task instead of `RetrieverBasedQa`.
+
     Note:
         `model` provided should be a control-type model.
 
@@ -62,17 +65,17 @@ class MultipleChunkRetrieverQa(
     def __init__(
         self,
         retriever: BaseRetriever[ID],
-        model: ControlModel | None = None,
         insert_chunk_number: int = 5,
-        insert_chunk_size: int = 256,
+        model: ControlModel | None = None,
+        expand_chunks: Task[ExpandChunksInput[ID], ExpandChunksOutput] | None = None,
         single_chunk_qa: Task[SingleChunkQaInput, SingleChunkQaOutput] | None = None,
     ):
         super().__init__()
-        self._model = model or LuminousControlModel("luminous-supreme-control")
         self._search = Search(retriever)
-        self._expand_chunks = ExpandChunks(retriever, self._model, insert_chunk_size)
-        self._single_chunk_qa = single_chunk_qa or SingleChunkQa(self._model)
         self._insert_chunk_number = insert_chunk_number
+        self._model = model or LuminousControlModel("luminous-supreme-control")
+        self._expand_chunks = expand_chunks or ExpandChunks(retriever, self._model)
+        self._single_chunk_qa = single_chunk_qa or SingleChunkQa(self._model)
 
     @staticmethod
     def _combine_input_texts(chunks: Sequence[str]) -> tuple[TextChunk, Sequence[int]]:

src/intelligence_layer/use_cases/qa/retriever_based_qa.py

@@ -1,3 +1,4 @@
+import warnings
 from typing import Generic, Optional, Sequence
 
 from pydantic import BaseModel
@@ -97,6 +98,11 @@ def __init__(
     def do_run(
         self, input: RetrieverBasedQaInput, task_span: TaskSpan
     ) -> RetrieverBasedQaOutput[ID]:
+        warnings.warn(
+            "`RetrieverBasedQa` is deprecated and will be removed in future versions.",
+            DeprecationWarning,
+        )
+
         search_output = self._search.run(
             SearchInput(query=input.question), task_span
         ).results

tests/use_cases/qa/test_multiple_chunk_retriever_qa.py

@@ -1,16 +1,27 @@
 from pytest import fixture
 
 from intelligence_layer.connectors import QdrantInMemoryRetriever
-from intelligence_layer.core import NoOpTracer
+from intelligence_layer.core import LuminousControlModel, NoOpTracer
 from intelligence_layer.core.tracer.in_memory_tracer import InMemoryTracer
-from intelligence_layer.use_cases import MultipleChunkRetrieverQa, RetrieverBasedQaInput
+from intelligence_layer.use_cases import (
+    ExpandChunks,
+    MultipleChunkRetrieverQa,
+    RetrieverBasedQaInput,
+)
 
 
 @fixture
 def multiple_chunk_retriever_qa(
+    luminous_control_model: LuminousControlModel,
     asymmetric_in_memory_retriever: QdrantInMemoryRetriever,
 ) -> MultipleChunkRetrieverQa[int]:
-    return MultipleChunkRetrieverQa(retriever=asymmetric_in_memory_retriever)
+    return MultipleChunkRetrieverQa(
+        retriever=asymmetric_in_memory_retriever,
+        model=luminous_control_model,
+        expand_chunks=ExpandChunks(
+            asymmetric_in_memory_retriever, luminous_control_model, 256
+        ),
+    )
 
 
 def test_multiple_chunk_retriever_qa_using_in_memory_retriever(