IL-167 add documentation and expose new classes

src/intelligence_layer/use_cases/__init__.py

@@ -37,8 +37,10 @@
 from .qa.long_context_qa import LongContextQaInput as LongContextQaInput
 from .qa.multiple_chunk_qa import MultipleChunkQa as MultipleChunkQa
 from .qa.multiple_chunk_qa import MultipleChunkQaInput as MultipleChunkQaInput
+from .qa.retriever_based_qa import EnrichedSubanswer as EnrichedSubanswer
 from .qa.retriever_based_qa import RetrieverBasedQa as RetrieverBasedQa
 from .qa.retriever_based_qa import RetrieverBasedQaInput as RetrieverBasedQaInput
+from .qa.retriever_based_qa import RetrieverBasedQaOutput as RetrieverBasedQaOutput
 from .qa.single_chunk_qa import SingleChunkQa as SingleChunkQa
 from .qa.single_chunk_qa import SingleChunkQaInput as SingleChunkQaInput
 from .qa.single_chunk_qa import SingleChunkQaOutput as SingleChunkQaOutput

src/intelligence_layer/use_cases/qa/retriever_based_qa.py

@@ -32,6 +32,16 @@ class RetrieverBasedQaInput(BaseModel):
 
 
 class EnrichedSubanswer(Subanswer, Generic[ID]):
+    """Individual answer for a chunk that also contains the origin of the chunk.
+
+    Attributes:
+        answer: The answer generated by the task. Can be a string or None (if no answer was found).
+        chunk: Piece of the original text that answer is based on.
+        highlights: The specific sentences that explain the answer the most.
+            These are generated by the `TextHighlight` Task.
+        id: The id of the document where the chunk came from.
+    """
+
     id: ID