Merge pull request #102 from langchain-ai/mattf/remove-deprecated-mod…

…el-type-param remove deprecated model_type param (embedding)
langchain-ai · Sep 21, 2024 · c73b9b6 · c73b9b6
2 parents 6325c6a + 0a45ce5
commit c73b9b6
Show file tree

Hide file tree

Showing 3 changed files with 3 additions and 36 deletions.
diff --git a/libs/ai-endpoints/langchain_nvidia_ai_endpoints/embeddings.py b/libs/ai-endpoints/langchain_nvidia_ai_endpoints/embeddings.py
@@ -10,7 +10,6 @@
     ConfigDict,
     Field,
     PrivateAttr,
-    field_validator,
 )
 
 from langchain_nvidia_ai_endpoints._common import _NVIDIAClient
@@ -50,9 +49,6 @@ class NVIDIAEmbeddings(BaseModel, Embeddings):
         ),
     )
     max_batch_size: int = Field(default=_DEFAULT_BATCH_SIZE)
-    model_type: Optional[Literal["passage", "query"]] = Field(
-        None, description="(DEPRECATED) The type of text to be embedded."
-    )
 
     def __init__(self, **kwargs: Any):
         """
@@ -111,18 +107,6 @@ def __init__(self, **kwargs: Any):
             )
             self.truncate = "END"
 
-    @field_validator("model_type")
-    def _validate_model_type(
-        cls, v: Optional[Literal["passage", "query"]]
-    ) -> Optional[Literal["passage", "query"]]:
-        if v:
-            warnings.warn(
-                "Warning: `model_type` is deprecated and will be removed "
-                "in a future release. Please use `embed_query` or "
-                "`embed_documents` appropriately."
-            )
-        return v
-
     @property
     def available_models(self) -> List[Model]:
         """
@@ -175,7 +159,7 @@ def _embed(
 
     def embed_query(self, text: str) -> List[float]:
         """Input pathway for query embeddings."""
-        return self._embed([text], model_type=self.model_type or "query")[0]
+        return self._embed([text], model_type="query")[0]
 
     def embed_documents(self, texts: List[str]) -> List[List[float]]:
         """Input pathway for document embeddings."""
@@ -187,9 +171,7 @@ def embed_documents(self, texts: List[str]) -> List[List[float]]:
         all_embeddings = []
         for i in range(0, len(texts), self.max_batch_size):
             batch = texts[i : i + self.max_batch_size]
-            all_embeddings.extend(
-                self._embed(batch, model_type=self.model_type or "passage")
-            )
+            all_embeddings.extend(self._embed(batch, model_type="passage"))
         return all_embeddings
 
     def _invoke_callback_vars(self, response: dict) -> None:

diff --git a/libs/ai-endpoints/tests/integration_tests/test_embeddings.py b/libs/ai-endpoints/tests/integration_tests/test_embeddings.py
@@ -112,7 +112,5 @@ def test_embed_nvolveqa_40k_compat(nvolveqa_40k: str, mode: dict) -> None:
     assert len(output) > 3
 
 
-# todo: test model_type ("passage" and embed_query,
-#                        "query" and embed_documents; compare results)
 # todo: test max_length > max length accepted by the model
 # todo: test max_batch_size > max batch size accepted by the model
diff --git a/libs/ai-endpoints/tests/unit_tests/test_embeddings.py b/libs/ai-endpoints/tests/unit_tests/test_embeddings.py
@@ -1,4 +1,4 @@
-from typing import Any, Generator, Literal
+from typing import Any, Generator
 
 import pytest
 from requests_mock import Mocker
@@ -86,17 +86,4 @@ def test_embed_query_truncate_invalid(truncate: Any) -> None:
         NVIDIAEmbeddings(truncate=truncate)
 
 
-@pytest.mark.parametrize("model_type", ["query", "passage"])
-def test_embed_model_type_deprecated(model_type: Literal["query", "passage"]) -> None:
-    with pytest.warns(UserWarning) as record:
-        NVIDIAEmbeddings(api_key="BOGUS", model_type=model_type)
-    assert len(record) == 1
-    assert "`model_type` is deprecated" in str(record[0].message)
-    x = NVIDIAEmbeddings(api_key="BOGUS")
-    with pytest.warns(UserWarning) as record:
-        x.model_type = model_type
-    assert len(record) == 1
-    assert "`model_type` is deprecated" in str(record[0].message)
-
-
 # todo: test max_batch_size (-50, 0, 1, 50)