feat (v2): Update so model_max_length updates max_seq_length for …

…Sentence Transformers (#8334)

* Update so model_max_length does what is expected

* Add release notes

* Some fixes

* Another test

haystack/components/embedders/sentence_transformers_document_embedder.py

@@ -187,6 +187,8 @@ def warm_up(self):
                 model_kwargs=self.model_kwargs,
                 tokenizer_kwargs=self.tokenizer_kwargs,
             )
+            if self.tokenizer_kwargs and self.tokenizer_kwargs.get("model_max_length"):
+                self.embedding_backend.model.max_seq_length = self.tokenizer_kwargs["model_max_length"]
 
     @component.output_types(documents=List[Document])
     def run(self, documents: List[Document]):

haystack/components/embedders/sentence_transformers_text_embedder.py

@@ -173,6 +173,8 @@ def warm_up(self):
                 model_kwargs=self.model_kwargs,
                 tokenizer_kwargs=self.tokenizer_kwargs,
             )
+            if self.tokenizer_kwargs and self.tokenizer_kwargs.get("model_max_length"):
+                self.embedding_backend.model.max_seq_length = self.tokenizer_kwargs["model_max_length"]
 
     @component.output_types(embedding=List[float])
     def run(self, text: str):

releasenotes/notes/update-max-seq-lenght-st-1dc3d7a9c9a3bdcd.yaml

@@ -0,0 +1,4 @@
+---
+features:
+  - |
+    Updates SentenceTransformersDocumentEmbedder and SentenceTransformersTextEmbedder so model_max_length passed through tokenizer_kwargs also updates the max_seq_length of the underly SentenceTransformer model.

test/components/embedders/test_sentence_transformers_document_embedder.py

@@ -226,18 +226,22 @@ def test_from_dict_none_device(self):
     )
     def test_warmup(self, mocked_factory):
         embedder = SentenceTransformersDocumentEmbedder(
-            model="model", token=None, device=ComponentDevice.from_str("cpu")
+            model="model",
+            token=None,
+            device=ComponentDevice.from_str("cpu"),
+            tokenizer_kwargs={"model_max_length": 512},
         )
         mocked_factory.get_embedding_backend.assert_not_called()
         embedder.warm_up()
+        embedder.embedding_backend.model.max_seq_length = 512
         mocked_factory.get_embedding_backend.assert_called_once_with(
             model="model",
             device="cpu",
             auth_token=None,
             trust_remote_code=False,
             truncate_dim=None,
             model_kwargs=None,
-            tokenizer_kwargs=None,
+            tokenizer_kwargs={"model_max_length": 512},
         )
 
     @patch(

test/components/embedders/test_sentence_transformers_text_embedder.py

@@ -201,17 +201,23 @@ def test_from_dict_none_device(self):
         "haystack.components.embedders.sentence_transformers_text_embedder._SentenceTransformersEmbeddingBackendFactory"
     )
     def test_warmup(self, mocked_factory):
-        embedder = SentenceTransformersTextEmbedder(model="model", token=None, device=ComponentDevice.from_str("cpu"))
+        embedder = SentenceTransformersTextEmbedder(
+            model="model",
+            token=None,
+            device=ComponentDevice.from_str("cpu"),
+            tokenizer_kwargs={"model_max_length": 512},
+        )
         mocked_factory.get_embedding_backend.assert_not_called()
         embedder.warm_up()
+        embedder.embedding_backend.model.max_seq_length = 512
         mocked_factory.get_embedding_backend.assert_called_once_with(
             model="model",
             device="cpu",
             auth_token=None,
             trust_remote_code=False,
             truncate_dim=None,
             model_kwargs=None,
-            tokenizer_kwargs=None,
+            tokenizer_kwargs={"model_max_length": 512},
         )
 
     @patch(