release[anthropic]: 0.3.15 (#31479)

Co-authored-by: Eugene Yurtsev <[email protected]>

Author: baskaryan

libs/partners/anthropic/pyproject.toml

@@ -12,7 +12,7 @@ dependencies = [
     "pydantic<3.0.0,>=2.7.4",
 ]
 name = "langchain-anthropic"
-version = "0.3.14"
+version = "0.3.15"
 description = "An integration package connecting AnthropicMessages and LangChain"
 readme = "README.md"
 

libs/partners/anthropic/tests/integration_tests/test_chat_models.py

@@ -3,7 +3,7 @@
 import json
 import os
 from base64 import b64encode
-from typing import Optional
+from typing import Optional, cast
 
 import httpx
 import pytest
@@ -42,7 +42,10 @@ def test_stream() -> None:
     chunks_with_model_name = 0
     for token in llm.stream("I'm Pickle Rick"):
         assert isinstance(token.content, str)
-        full = token if full is None else full + token
+        if full is None:
+            full = cast(BaseMessageChunk, token)
+        else:
+            full = full + token
         assert isinstance(token, AIMessageChunk)
         if token.usage_metadata is not None:
             if token.usage_metadata.get("input_tokens"):
@@ -81,7 +84,10 @@ async def test_astream() -> None:
     chunks_with_output_token_counts = 0
     async for token in llm.astream("I'm Pickle Rick"):
         assert isinstance(token.content, str)
-        full = token if full is None else full + token
+        if full is None:
+            full = cast(BaseMessageChunk, token)
+        else:
+            full = full + token
         assert isinstance(token, AIMessageChunk)
         if token.usage_metadata is not None:
             if token.usage_metadata.get("input_tokens"):
@@ -697,7 +703,10 @@ def test_citations() -> None:
     # Test streaming
     full: Optional[BaseMessageChunk] = None
     for chunk in llm.stream(messages):
-        full = chunk if full is None else full + chunk
+        if full is None:
+            full = cast(BaseMessageChunk, chunk)
+        else:
+            full = full + chunk
     assert isinstance(full, AIMessageChunk)
     assert isinstance(full.content, list)
     assert any("citations" in block for block in full.content)
@@ -722,7 +731,10 @@ def test_thinking() -> None:
     # Test streaming
     full: Optional[BaseMessageChunk] = None
     for chunk in llm.stream("Hello"):
-        full = chunk if full is None else full + chunk
+        if full is None:
+            full = cast(BaseMessageChunk, chunk)
+        else:
+            full = full + chunk
     assert isinstance(full, AIMessageChunk)
     assert isinstance(full.content, list)
     assert any("thinking" in block for block in full.content)
@@ -756,7 +768,10 @@ def test_redacted_thinking() -> None:
     # Test streaming
     full: Optional[BaseMessageChunk] = None
     for chunk in llm.stream(query):
-        full = chunk if full is None else full + chunk
+        if full is None:
+            full = cast(BaseMessageChunk, chunk)
+        else:
+            full = full + chunk
     assert isinstance(full, AIMessageChunk)
     assert isinstance(full.content, list)
     stream_has_reasoning = False

libs/partners/anthropic/tests/integration_tests/test_standard.py

@@ -4,7 +4,7 @@
 from typing import Literal, cast
 
 from langchain_core.language_models import BaseChatModel
-from langchain_core.messages import AIMessage
+from langchain_core.messages import AIMessage, BaseMessageChunk
 from langchain_tests.integration_tests import ChatModelIntegrationTests
 
 from langchain_anthropic import ChatAnthropic
@@ -146,7 +146,10 @@ def _invoke(llm: ChatAnthropic, input_: list, stream: bool) -> AIMessage:
     if stream:
         full = None
         for chunk in llm.stream(input_):
-            full = full + chunk if full else chunk  # type: ignore[operator]
+            if full is None:
+                full = cast(BaseMessageChunk, chunk)
+            else:
+                full = full + chunk
         return cast(AIMessage, full)
     else:
         return cast(AIMessage, llm.invoke(input_))