upgrade: revert back to SentenceWindowRetrieval

docs/pydoc/config/retrievers_api.yml

@@ -6,7 +6,7 @@ loaders:
  "in_memory/bm25_retriever",
  "in_memory/embedding_retriever",
  "filter_retriever",
- "sentence_window_retriever",
+ "sentence_window_retrieval",
  ]
  ignore_when_discovered: ["__init__"]
 processors:

haystack/components/retrievers/__init__.py

@@ -5,6 +5,6 @@
 from haystack.components.retrievers.filter_retriever import FilterRetriever
 from haystack.components.retrievers.in_memory.bm25_retriever import InMemoryBM25Retriever
 from haystack.components.retrievers.in_memory.embedding_retriever import InMemoryEmbeddingRetriever
-from haystack.components.retrievers.sentence_window_retriever import SentenceWindowRetriever
+from haystack.components.retrievers.sentence_window_retrieval import SentenceWindowRetrieval
 
-__all__ = ["FilterRetriever", "InMemoryEmbeddingRetriever", "InMemoryBM25Retriever", "SentenceWindowRetriever"]
+__all__ = ["FilterRetriever", "InMemoryEmbeddingRetriever", "InMemoryBM25Retriever", "SentenceWindowRetrieval"]

haystack/components/retrievers/sentence_window_retriever.py → haystack/components/retrievers/sentence_window_retrieval.py

@@ -10,27 +10,27 @@
 
 
 @component
-class SentenceWindowRetriever:
+class SentenceWindowRetrieval:
  """
  Retrieves documents adjacent to a given document in the Document Store.
 
  During indexing, documents are broken into smaller chunks, or sentences. When you submit a query,
  the Retriever fetches the most relevant sentence. To provide full context,
- SentenceWindowRetriever fetches a number of neighboring sentences before and after each
+ SentenceWindowRetrieval fetches a number of neighboring sentences before and after each
  relevant one. You can set this number with the `window_size` parameter.
  It uses `source_id` and `doc.meta['split_id']` to locate the surrounding documents.
 
  This component works with existing Retrievers, like BM25Retriever or
  EmbeddingRetriever. First, use a Retriever to find documents based on a query and then use
- SentenceWindowRetriever to get the surrounding documents for context.
+ SentenceWindowRetrieval to get the surrounding documents for context.
 
 
  ### Usage example
 
  ```python
  from haystack import Document, Pipeline
  from haystack.components.retrievers.in_memory import InMemoryBM25Retriever
- from haystack.components.retrievers import SentenceWindowRetriever
+ from haystack.components.retrievers import SentenceWindowRetrieval
  from haystack.components.preprocessors import DocumentSplitter
  from haystack.document_stores.in_memory import InMemoryDocumentStore
 
@@ -47,7 +47,7 @@ class SentenceWindowRetriever:
 
  rag = Pipeline()
  rag.add_component("bm25_retriever", InMemoryBM25Retriever(doc_store, top_k=1))
- rag.add_component("sentence_window_retriever", SentenceWindowRetriever(document_store=doc_store, window_size=2))
+ rag.add_component("sentence_window_retriever", SentenceWindowRetrieval(document_store=doc_store, window_size=2))
  rag.connect("bm25_retriever", "sentence_window_retriever")
 
  rag.run({'bm25_retriever': {"query":"third"}})
@@ -60,7 +60,7 @@ class SentenceWindowRetriever:
 
  def __init__(self, document_store: DocumentStore, window_size: int = 3):
  """
- Creates a new SentenceWindowRetriever component.
+ Creates a new SentenceWindowRetrieval component.
 
  :param document_store: The Document Store to retrieve the surrounding documents from.
  :param window_size: The number of documents to retrieve before and after the relevant one.
@@ -110,7 +110,7 @@ def to_dict(self) -> Dict[str, Any]:
  return default_to_dict(self, document_store=docstore, window_size=self.window_size)
 
  @classmethod
- def from_dict(cls, data: Dict[str, Any]) -> "SentenceWindowRetriever":
+ def from_dict(cls, data: Dict[str, Any]) -> "SentenceWindowRetrieval":
  """
  Deserializes the component from a dictionary.
 

releasenotes/notes/revert-sentence-window-retrieval-8f5721772b28377e.yaml

@@ -0,0 +1,4 @@
+---
+upgrade:
+ - |
+ `SentenceWindowRetriever` component has been reverted back to `SenetenceWindowRetrieval`.

test/components/retrievers/test_sentence_window_retriever.py → test/components/retrievers/test_sentence_window_retrieval.py

@@ -2,23 +2,23 @@
 
 from haystack import Document, DeserializationError, Pipeline
 from haystack.components.retrievers import InMemoryBM25Retriever
-from haystack.components.retrievers.sentence_window_retriever import SentenceWindowRetriever
+from haystack.components.retrievers.sentence_window_retrieval import SentenceWindowRetrieval
 from haystack.document_stores.in_memory import InMemoryDocumentStore
 from haystack.components.preprocessors import DocumentSplitter
 
 
-class TestSentenceWindowRetriever:
+class TestSentenceWindowRetrieval:
  def test_init_default(self):
- retriever = SentenceWindowRetriever(InMemoryDocumentStore())
- assert retriever.window_size == 3
+ retrieval = SentenceWindowRetrieval(InMemoryDocumentStore())
+ assert retrieval.window_size == 3
 
  def test_init_with_parameters(self):
- retriever = SentenceWindowRetriever(InMemoryDocumentStore(), window_size=5)
- assert retriever.window_size == 5
+ retrieval = SentenceWindowRetrieval(InMemoryDocumentStore(), window_size=5)
+ assert retrieval.window_size == 5
 
  def test_init_with_invalid_window_size_parameter(self):
  with pytest.raises(ValueError):
- SentenceWindowRetriever(InMemoryDocumentStore(), window_size=-2)
+ SentenceWindowRetrieval(InMemoryDocumentStore(), window_size=-2)
 
  def test_merge_documents(self):
  docs = [
@@ -50,15 +50,15 @@ def test_merge_documents(self):
  "_split_overlap": [{"doc_id": "doc_1", "range": (23, 52)}],
  },
  ]
- merged_text = SentenceWindowRetriever.merge_documents_text([Document.from_dict(doc) for doc in docs])
+ merged_text = SentenceWindowRetrieval.merge_documents_text([Document.from_dict(doc) for doc in docs])
  expected = "This is a text with some words. There is a second sentence. And there is also a third sentence"
  assert merged_text == expected
 
  def test_to_dict(self):
- window_retriever = SentenceWindowRetriever(InMemoryDocumentStore())
- data = window_retriever.to_dict()
+ window_retrieval = SentenceWindowRetrieval(InMemoryDocumentStore())
+ data = window_retrieval.to_dict()
 
- assert data["type"] == "haystack.components.retrievers.sentence_window_retriever.SentenceWindowRetriever"
+ assert data["type"] == "haystack.components.retrievers.sentence_window_retrieval.SentenceWindowRetrieval"
  assert data["init_parameters"]["window_size"] == 3
  assert (
  data["init_parameters"]["document_store"]["type"]
@@ -67,7 +67,7 @@ def test_to_dict(self):
 
  def test_from_dict(self):
  data = {
- "type": "haystack.components.retrievers.sentence_window_retriever.SentenceWindowRetriever",
+ "type": "haystack.components.retrievers.sentence_window_retrieval.SentenceWindowRetrieval",
  "init_parameters": {
  "document_store": {
  "type": "haystack.document_stores.in_memory.document_store.InMemoryDocumentStore",
@@ -76,36 +76,36 @@ def test_from_dict(self):
  "window_size": 5,
  },
  }
- component = SentenceWindowRetriever.from_dict(data)
+ component = SentenceWindowRetrieval.from_dict(data)
  assert isinstance(component.document_store, InMemoryDocumentStore)
  assert component.window_size == 5
 
  def test_from_dict_without_docstore(self):
- data = {"type": "SentenceWindowRetriever", "init_parameters": {}}
+ data = {"type": "SentenceWindowRetrieval", "init_parameters": {}}
  with pytest.raises(DeserializationError, match="Missing 'document_store' in serialization data"):
- SentenceWindowRetriever.from_dict(data)
+ SentenceWindowRetrieval.from_dict(data)
 
  def test_from_dict_without_docstore_type(self):
- data = {"type": "SentenceWindowRetriever", "init_parameters": {"document_store": {"init_parameters": {}}}}
+ data = {"type": "SentenceWindowRetrieval", "init_parameters": {"document_store": {"init_parameters": {}}}}
  with pytest.raises(DeserializationError, match="Missing 'type' in document store's serialization data"):
- SentenceWindowRetriever.from_dict(data)
+ SentenceWindowRetrieval.from_dict(data)
 
  def test_from_dict_non_existing_docstore(self):
  data = {
- "type": "SentenceWindowRetriever",
+ "type": "SentenceWindowRetrieval",
  "init_parameters": {"document_store": {"type": "Nonexisting.Docstore", "init_parameters": {}}},
  }
  with pytest.raises(DeserializationError):
- SentenceWindowRetriever.from_dict(data)
+ SentenceWindowRetrieval.from_dict(data)
 
  def test_document_without_split_id(self):
  docs = [
  Document(content="This is a text with some words. There is a ", meta={"id": "doc_0"}),
  Document(content="some words. There is a second sentence. And there is ", meta={"id": "doc_1"}),
  ]
  with pytest.raises(ValueError):
- retriever = SentenceWindowRetriever(document_store=InMemoryDocumentStore(), window_size=3)
- retriever.run(retrieved_documents=docs)
+ retrieval = SentenceWindowRetrieval(document_store=InMemoryDocumentStore(), window_size=3)
+ retrieval.run(retrieved_documents=docs)
 
  def test_document_without_source_id(self):
  docs = [
@@ -115,8 +115,8 @@ def test_document_without_source_id(self):
  ),
  ]
  with pytest.raises(ValueError):
- retriever = SentenceWindowRetriever(document_store=InMemoryDocumentStore(), window_size=3)
- retriever.run(retrieved_documents=docs)
+ retrieval = SentenceWindowRetrieval(document_store=InMemoryDocumentStore(), window_size=3)
+ retrieval.run(retrieved_documents=docs)
 
  @pytest.mark.integration
  def test_run_with_pipeline(self):
@@ -132,12 +132,12 @@ def test_run_with_pipeline(self):
 
  rag = Pipeline()
  rag.add_component("bm25_retriever", InMemoryBM25Retriever(doc_store, top_k=1))
- rag.add_component("sentence_window_retriever", SentenceWindowRetriever(document_store=doc_store, window_size=2))
- rag.connect("bm25_retriever", "sentence_window_retriever")
+ rag.add_component("sentence_window_retrieval", SentenceWindowRetrieval(document_store=doc_store, window_size=2))
+ rag.connect("bm25_retriever", "sentence_window_retrieval")
  result = rag.run({"bm25_retriever": {"query": "third"}})
 
  expected = {
- "sentence_window_retriever": {
+ "sentence_window_retrieval": {
  "context_windows": [
  "some words. There is a second sentence. And there is also a third sentence. It also "
  "contains a fourth sentence. And a fifth sentence. And a sixth sentence. And a "