feat!: Rename model_name_or_path to model in ExtractiveReader (#…

…6736)

* rename model parameter and internam model attribute in ExtractiveReader

* fix tests for ExtractiveReader

* fix e2e

* reno

* another fix

* review feedback

* Update releasenotes/notes/rename-model-param-reader-b8cbb0d638e3b8c2.yaml

e2e/pipelines/test_eval_extractive_qa_pipeline.py

@@ -13,7 +13,7 @@ def test_extractive_qa_pipeline(tmp_path):
     # Create the pipeline
     qa_pipeline = Pipeline()
     qa_pipeline.add_component(instance=InMemoryBM25Retriever(document_store=InMemoryDocumentStore()), name="retriever")
-    qa_pipeline.add_component(instance=ExtractiveReader(model_name_or_path="deepset/tinyroberta-squad2"), name="reader")
+    qa_pipeline.add_component(instance=ExtractiveReader(model="deepset/tinyroberta-squad2"), name="reader")
     qa_pipeline.connect("retriever", "reader")
 
     # Populate the document store

e2e/pipelines/test_extractive_qa_pipeline.py

@@ -10,7 +10,7 @@ def test_extractive_qa_pipeline(tmp_path):
     # Create the pipeline
     qa_pipeline = Pipeline()
     qa_pipeline.add_component(instance=InMemoryBM25Retriever(document_store=InMemoryDocumentStore()), name="retriever")
-    qa_pipeline.add_component(instance=ExtractiveReader(model_name_or_path="deepset/tinyroberta-squad2"), name="reader")
+    qa_pipeline.add_component(instance=ExtractiveReader(model="deepset/tinyroberta-squad2"), name="reader")
     qa_pipeline.connect("retriever", "reader")
 
     # Draw the pipeline

haystack/components/readers/extractive.py

@@ -38,7 +38,7 @@ class ExtractiveReader:
 
     def __init__(
         self,
-        model_name_or_path: Union[Path, str] = "deepset/roberta-base-squad2-distilled",
+        model: Union[Path, str] = "deepset/roberta-base-squad2-distilled",
         device: Optional[str] = None,
         token: Union[bool, str, None] = None,
         top_k: int = 20,
@@ -54,7 +54,7 @@ def __init__(
     ) -> None:
         """
         Creates an ExtractiveReader
-        :param model_name_or_path: A Hugging Face transformers question answering model.
+        :param model: A Hugging Face transformers question answering model.
             Can either be a path to a folder containing the model files or an identifier for the Hugging Face hub.
             Default: `'deepset/roberta-base-squad2-distilled'`
         :param device: Pytorch device string. Uses GPU by default, if available.
@@ -83,11 +83,11 @@ def __init__(
             both of these answers could be kept if this variable is set to 0.24 or lower.
             If None is provided then all answers are kept.
         :param model_kwargs: Additional keyword arguments passed to `AutoModelForQuestionAnswering.from_pretrained`
-            when loading the model specified in `model_name_or_path`. For details on what kwargs you can pass,
+            when loading the model specified in `model`. For details on what kwargs you can pass,
             see the model's documentation.
         """
         torch_and_transformers_import.check()
-        self.model_name_or_path = str(model_name_or_path)
+        self.model_name_or_path = str(model)
         self.model = None
         self.device = device
         self.token = token
@@ -114,7 +114,7 @@ def to_dict(self) -> Dict[str, Any]:
         """
         serialization_dict = default_to_dict(
             self,
-            model_name_or_path=self.model_name_or_path,
+            model=self.model_name_or_path,
             device=self.device,
             token=self.token if not isinstance(self.token, str) else None,
             max_seq_length=self.max_seq_length,

releasenotes/notes/rename-model-param-reader-b8cbb0d638e3b8c2.yaml

@@ -0,0 +1,3 @@
+---
+upgrade:
+    - Rename parameter `model_name_or_path` to `model` in `ExtractiveReader`.

test/components/readers/test_extractive.py

@@ -72,7 +72,7 @@ def forward(self, input_ids, attention_mask, *args, **kwargs):
 
     with patch("haystack.components.readers.extractive.AutoModelForQuestionAnswering.from_pretrained") as model:
         model.return_value = MockModel()
-        reader = ExtractiveReader(model_name_or_path="mock-model", device="cpu:0")
+        reader = ExtractiveReader(model="mock-model", device="cpu:0")
         reader.warm_up()
         return reader
 
@@ -94,7 +94,7 @@ def test_to_dict():
     assert data == {
         "type": "haystack.components.readers.extractive.ExtractiveReader",
         "init_parameters": {
-            "model_name_or_path": "my-model",
+            "model": "my-model",
             "device": None,
             "token": None,  # don't serialize valid tokens
             "top_k": 20,
@@ -117,7 +117,7 @@ def test_to_dict_empty_model_kwargs():
     assert data == {
         "type": "haystack.components.readers.extractive.ExtractiveReader",
         "init_parameters": {
-            "model_name_or_path": "my-model",
+            "model": "my-model",
             "device": None,
             "token": None,  # don't serialize valid tokens
             "top_k": 20,
@@ -137,7 +137,7 @@ def test_from_dict():
     data = {
         "type": "haystack.components.readers.extractive.ExtractiveReader",
         "init_parameters": {
-            "model_name_or_path": "my-model",
+            "model": "my-model",
             "device": None,
             "token": None,
             "top_k": 20,