feat!: SentenceWindowRetriever returns List[Document] with docs ordered by split_idx_start (#8590)

* initial import

* adding a few pylint disable

* adding tests

* fixing integration tests

* adding release notes

* fixing types and docstrings

Author: davidsbatista

Diff for: haystack/components/retrievers/in_memory/bm25_retriever.py

@@ -38,7 +38,7 @@ class InMemoryBM25Retriever:
     ```
     """
 
-    def __init__(
+    def __init__(  # pylint: disable=too-many-positional-arguments
         self,
         document_store: InMemoryDocumentStore,
         filters: Optional[Dict[str, Any]] = None,

Diff for: haystack/components/retrievers/in_memory/embedding_retriever.py

@@ -50,7 +50,7 @@ class InMemoryEmbeddingRetriever:
     ```
     """
 
-    def __init__(
+    def __init__(  # pylint: disable=too-many-positional-arguments
         self,
         document_store: InMemoryDocumentStore,
         filters: Optional[Dict[str, Any]] = None,
@@ -143,7 +143,7 @@ def from_dict(cls, data: Dict[str, Any]) -> "InMemoryEmbeddingRetriever":
         return default_from_dict(cls, data)
 
     @component.output_types(documents=List[Document])
-    def run(
+    def run(  # pylint: disable=too-many-positional-arguments
         self,
         query_embedding: List[float],
         filters: Optional[Dict[str, Any]] = None,

Diff for: haystack/components/retrievers/sentence_window_retriever.py

@@ -151,7 +151,7 @@ def from_dict(cls, data: Dict[str, Any]) -> "SentenceWindowRetriever":
         # deserialize the component
         return default_from_dict(cls, data)
 
-    @component.output_types(context_windows=List[str], context_documents=List[List[Document]])
+    @component.output_types(context_windows=List[str], context_documents=List[Document])
     def run(self, retrieved_documents: List[Document], window_size: Optional[int] = None):
         """
         Based on the `source_id` and on the `doc.meta['split_id']` get surrounding documents from the document store.
@@ -166,9 +166,9 @@ def run(self, retrieved_documents: List[Document], window_size: Optional[int] =
             A dictionary with the following keys:
                 - `context_windows`: A list of strings, where each string represents the concatenated text from the
                                      context window of the corresponding document in `retrieved_documents`.
-                - `context_documents`: A list of lists of `Document` objects, where each inner list contains the
-                                     documents that come from the context window for the corresponding document in
-                                     `retrieved_documents`.
+                - `context_documents`: A list `Document` objects, containing the retrieved documents plus the context
+                                      document surrounding them. The documents are sorted by the `split_idx_start`
+                                      meta field.
 
         """
         window_size = window_size or self.window_size
@@ -200,6 +200,7 @@ def run(self, retrieved_documents: List[Document], window_size: Optional[int] =
                 }
             )
             context_text.append(self.merge_documents_text(context_docs))
-            context_documents.append(context_docs)
+            context_docs_sorted = sorted(context_docs, key=lambda doc: doc.meta["split_idx_start"])
+            context_documents.extend(context_docs_sorted)
 
         return {"context_windows": context_text, "context_documents": context_documents}

Diff for: releasenotes/notes/sentence-window-retriever-change-output-7beca98e9951039e.yaml

@@ -0,0 +1,4 @@
+---
+upgrade:
+  - |
+    The SentenceWindowRetriever output key `context_documents` now outputs a List[Document] containing the retrieved documents together with the context windows ordered by `split_idx_start`.

Diff for: test/components/retrievers/test_sentence_window_retriever.py

@@ -141,6 +141,39 @@ def test_constructor_parameter_does_not_change(self):
         retriever.run(retrieved_documents=[Document.from_dict(doc)], window_size=1)
         assert retriever.window_size == 5
 
+    def test_context_documents_returned_are_ordered_by_split_idx_start(self):
+        docs = []
+        accumulated_length = 0
+        for sent in range(10):
+            content = f"Sentence {sent}."
+            docs.append(
+                Document(
+                    content=content,
+                    meta={
+                        "id": f"doc_{sent}",
+                        "split_idx_start": accumulated_length,
+                        "source_id": "source1",
+                        "split_id": sent,
+                    },
+                )
+            )
+            accumulated_length += len(content)
+
+        import random
+
+        random.shuffle(docs)
+
+        doc_store = InMemoryDocumentStore()
+        doc_store.write_documents(docs)
+        retriever = SentenceWindowRetriever(document_store=doc_store, window_size=3)
+
+        # run the retriever with a document whose content = "Sentence 4."
+        result = retriever.run(retrieved_documents=[doc for doc in docs if doc.content == "Sentence 4."])
+
+        # assert that the context documents are in the correct order
+        assert len(result["context_documents"]) == 7
+        assert [doc.meta["split_idx_start"] for doc in result["context_documents"]] == [11, 22, 33, 44, 55, 66, 77]
+
     @pytest.mark.integration
     def test_run_with_pipeline(self):
         splitter = DocumentSplitter(split_length=1, split_overlap=0, split_by="sentence")
@@ -165,13 +198,13 @@ def test_run_with_pipeline(self):
             "This is a text with some words. There is a second sentence. And there is also a third sentence. "
             "It also contains a fourth sentence. And a fifth sentence."
         ]
-        assert len(result["sentence_window_retriever"]["context_documents"][0]) == 5
+        assert len(result["sentence_window_retriever"]["context_documents"]) == 5
 
         result = pipe.run({"bm25_retriever": {"query": "third"}, "sentence_window_retriever": {"window_size": 1}})
         assert result["sentence_window_retriever"]["context_windows"] == [
             " There is a second sentence. And there is also a third sentence. It also contains a fourth sentence."
         ]
-        assert len(result["sentence_window_retriever"]["context_documents"][0]) == 3
+        assert len(result["sentence_window_retriever"]["context_documents"]) == 3
 
     @pytest.mark.integration
     def test_serialization_deserialization_in_pipeline(self):