feat(mistralai): remove tenacity retries for embeddings (#33491)

libs/partners/mistralai/langchain_mistralai/embeddings.py

@@ -1,7 +1,7 @@
 import asyncio
 import logging
 import warnings
-from collections.abc import Iterable
+from collections.abc import Callable, Iterable
 
 import httpx
 from httpx import Response
@@ -57,6 +57,7 @@ class MistralAIEmbeddings(BaseModel, Embeddings):
         api_key:
             The API key for the MistralAI API. If not provided, it will be read from the
             environment variable `MISTRAL_API_KEY`.
+        max_concurrent_requests: int
         max_retries:
             The number of times to retry a request if it fails.
         timeout:
@@ -133,9 +134,9 @@ class MistralAIEmbeddings(BaseModel, Embeddings):
         default_factory=secret_from_env("MISTRAL_API_KEY", default=""),
     )
     endpoint: str = "https://api.mistral.ai/v1/"
-    max_retries: int = 5
+    max_retries: int | None = 5
     timeout: int = 120
-    wait_time: int = 30
+    wait_time: int | None = 30
     max_concurrent_requests: int = 64
     tokenizer: Tokenizer = Field(default=None)
 
@@ -212,6 +213,18 @@ class MistralAIEmbeddings(BaseModel, Embeddings):
         if batch:
             yield batch
 
+    def _retry(self, func: Callable) -> Callable:
+        if self.max_retries is None or self.wait_time is None:
+            return func
+
+        return retry(
+            retry=retry_if_exception_type(
+                (httpx.TimeoutException, httpx.HTTPStatusError)
+            ),
+            wait=wait_fixed(self.wait_time),
+            stop=stop_after_attempt(self.max_retries),
+        )(func)
+
     def embed_documents(self, texts: list[str]) -> list[list[float]]:
         """Embed a list of document texts.
 
@@ -225,13 +238,7 @@ class MistralAIEmbeddings(BaseModel, Embeddings):
         try:
             batch_responses = []
 
-            @retry(
+            @self._retry
-                retry=retry_if_exception_type(
-                    (httpx.TimeoutException, httpx.HTTPStatusError)
-                ),
-                wait=wait_fixed(self.wait_time),
-                stop=stop_after_attempt(self.max_retries),
-            )
             def _embed_batch(batch: list[str]) -> Response:
                 response = self.client.post(
                     url="/embeddings",
@@ -266,13 +273,7 @@ class MistralAIEmbeddings(BaseModel, Embeddings):
         """
         try:
 
-            @retry(
+            @self._retry
-                retry=retry_if_exception_type(
-                    (httpx.TimeoutException, httpx.HTTPStatusError)
-                ),
-                wait=wait_fixed(self.wait_time),
-                stop=stop_after_attempt(self.max_retries),
-            )
             async def _aembed_batch(batch: list[str]) -> Response:
                 response = await self.async_client.post(
                     url="/embeddings",

libs/partners/mistralai/tests/integration_tests/test_embeddings.py

@@ -35,7 +35,7 @@ async def test_mistralai_embedding_documents_async() -> None:
     assert len(output[0]) == 1024
 
 
-async def test_mistralai_embedding_documents_http_error_async() -> None:
+async def test_mistralai_embedding_documents_tenacity_error_async() -> None:
     """Test MistralAI embeddings for documents."""
     documents = ["foo bar", "test document"]
     embedding = MistralAIEmbeddings(max_retries=0)
@@ -50,6 +50,21 @@ async def test_mistralai_embedding_documents_http_error_async() -> None:
         await embedding.aembed_documents(documents)
 
 
+async def test_mistralai_embedding_documents_http_error_async() -> None:
+    """Test MistralAI embeddings for documents."""
+    documents = ["foo bar", "test document"]
+    embedding = MistralAIEmbeddings(max_retries=None)
+    mock_response = httpx.Response(
+        status_code=400,
+        request=httpx.Request("POST", url=embedding.async_client.base_url),
+    )
+    with (
+        patch.object(embedding.async_client, "post", return_value=mock_response),
+        pytest.raises(httpx.HTTPStatusError),
+    ):
+        await embedding.aembed_documents(documents)
+
+
 async def test_mistralai_embedding_query_async() -> None:
     """Test MistralAI embeddings for query."""
     document = "foo bar"