chore: remove mentions of sonnet 3.5

libs/langchain_v1/langchain/agents/middleware/model_fallback.py

@@ -31,7 +31,7 @@ class ModelFallbackMiddleware(AgentMiddleware):
 
         fallback = ModelFallbackMiddleware(
             "openai:gpt-4o-mini",  # Try first on error
-            "anthropic:claude-3-5-sonnet-20241022",  # Then this
+            "anthropic:claude-sonnet-4-5-20250929",  # Then this
         )
 
         agent = create_agent(

libs/langchain_v1/langchain/agents/middleware/tool_emulator.py

@@ -47,9 +47,7 @@ class LLMToolEmulator(AgentMiddleware):
 
         Use a custom model for emulation:
         ```python
-        middleware = LLMToolEmulator(
-            tools=["get_weather"], model="anthropic:claude-3-5-sonnet-latest"
-        )
+        middleware = LLMToolEmulator(tools=["get_weather"], model="anthropic:claude-sonnet-4-5")
         ```
 
         Emulate specific tools by passing tool instances:
@@ -71,7 +69,7 @@ def __init__(
                 If None (default), ALL tools will be emulated.
                 If empty list, no tools will be emulated.
             model: Model to use for emulation.
-                Defaults to "anthropic:claude-3-5-sonnet-latest".
+                Defaults to "anthropic:claude-sonnet-4-5".
                 Can be a model identifier string or BaseChatModel instance.
         """
         super().__init__()
@@ -91,7 +89,7 @@ def __init__(
 
         # Initialize emulator model
         if model is None:
-            self.model = init_chat_model("anthropic:claude-3-5-sonnet-latest", temperature=1)
+            self.model = init_chat_model("anthropic:claude-sonnet-4-5", temperature=1)
         elif isinstance(model, BaseChatModel):
             self.model = model
         else:

libs/langchain_v1/tests/integration_tests/agents/middleware/test_shell_tool_integration.py

@@ -17,7 +17,7 @@ def _get_model(provider: str) -> Any:
     if provider == "anthropic":
         from langchain_anthropic import ChatAnthropic
 
-        return ChatAnthropic(model="claude-3-5-sonnet-20241022")
+        return ChatAnthropic(model="claude-sonnet-4-5-20250929")
     elif provider == "openai":
         from langchain_openai import ChatOpenAI
 

libs/langchain_v1/tests/unit_tests/agents/middleware/test_tool_emulator.py

@@ -369,9 +369,7 @@ def test_custom_model_string(self) -> None:
         """Test passing a model string for emulation."""
         # Just test that initialization works - don't require anthropic package
         try:
-            emulator = LLMToolEmulator(
-                tools=["get_weather"], model="anthropic:claude-3-5-sonnet-latest"
-            )
+            emulator = LLMToolEmulator(tools=["get_weather"], model="anthropic:claude-sonnet-4-5")
             assert emulator.model is not None
             assert "get_weather" in emulator.tools_to_emulate
         except ImportError:

libs/partners/anthropic/langchain_anthropic/chat_models.py

@@ -820,7 +820,7 @@ class Joke(BaseModel):
         image_url = "https://upload.wikimedia.org/wikipedia/commons/thumb/d/dd/Gfp-wisconsin-madison-the-nature-boardwalk.jpg/2560px-Gfp-wisconsin-madison-the-nature-boardwalk.jpg"
         image_data = base64.b64encode(httpx.get(image_url).content).decode("utf-8")
 
-        model = ChatAnthropic(model="claude-3-5-sonnet-latest")
+        model = ChatAnthropic(model="claude-sonnet-4-5")
         message = HumanMessage(
             content=[
                 {
@@ -887,7 +887,7 @@ class Joke(BaseModel):
         url = "https://www.w3.org/WAI/ER/tests/xhtml/testfiles/resources/pdf/dummy.pdf"
         data = b64encode(requests.get(url).content).decode()
 
-        model = ChatAnthropic(model="claude-3-5-sonnet-latest")
+        model = ChatAnthropic(model="claude-sonnet-4-5")
         ai_msg = model.invoke(
             [
                 HumanMessage(
@@ -1948,7 +1948,7 @@ class GetPrice(BaseModel):
                 product: str = Field(..., description="The product to look up.")
 
 
-            model = ChatAnthropic(model="claude-3-5-sonnet-latest", temperature=0)
+            model = ChatAnthropic(model="claude-sonnet-4-5", temperature=0)
             model_with_tools = model.bind_tools([GetWeather, GetPrice])
             model_with_tools.invoke(
                 "What is the weather like in San Francisco",
@@ -1958,7 +1958,7 @@ class GetPrice(BaseModel):
             #         {'text': '<thinking>\nBased on the user\'s question, the relevant function to call is GetWeather, which requires the "location" parameter.\n\nThe user has directly specified the location as "San Francisco". Since San Francisco is a well known city, I can reasonably infer they mean San Francisco, CA without needing the state specified.\n\nAll the required parameters are provided, so I can proceed with the API call.\n</thinking>', 'type': 'text'},
             #         {'text': None, 'type': 'tool_use', 'id': 'toolu_01SCgExKzQ7eqSkMHfygvYuu', 'name': 'GetWeather', 'input': {'location': 'San Francisco, CA'}}
             #     ],
-            #     response_metadata={'id': 'msg_01GM3zQtoFv8jGQMW7abLnhi', 'model': 'claude-3-5-sonnet-latest', 'stop_reason': 'tool_use', 'stop_sequence': None, 'usage': {'input_tokens': 487, 'output_tokens': 145}},
+            #     response_metadata={'id': 'msg_01GM3zQtoFv8jGQMW7abLnhi', 'model': 'claude-sonnet-4-5', 'stop_reason': 'tool_use', 'stop_sequence': None, 'usage': {'input_tokens': 487, 'output_tokens': 145}},
             #     id='run-87b1331e-9251-4a68-acef-f0a018b639cc-0'
             # )
             ```
@@ -1982,7 +1982,7 @@ class GetPrice(BaseModel):
                 product: str = Field(..., description="The product to look up.")
 
 
-            model = ChatAnthropic(model="claude-3-5-sonnet-latest", temperature=0)
+            model = ChatAnthropic(model="claude-sonnet-4-5", temperature=0)
             model_with_tools = model.bind_tools([GetWeather, GetPrice], tool_choice="any")
             model_with_tools.invoke(
                 "what is the weather like in San Francisco",
@@ -2008,7 +2008,7 @@ class GetPrice(BaseModel):
             product: str = Field(..., description="The product to look up.")
 
 
-        model = ChatAnthropic(model="claude-3-5-sonnet-latest", temperature=0)
+        model = ChatAnthropic(model="claude-sonnet-4-5", temperature=0)
         model_with_tools = model.bind_tools([GetWeather, GetPrice], tool_choice="GetWeather")
         model_with_tools.invoke("What is the weather like in San Francisco")
         ```
@@ -2043,7 +2043,7 @@ class GetPrice(BaseModel):
         # We need to pass in extra headers to enable use of the beta cache
         # control API.
         model = ChatAnthropic(
-            model="claude-3-5-sonnet-latest",
+            model="claude-sonnet-4-5",
             temperature=0,
         )
         model_with_tools = model.bind_tools([GetWeather, cached_price_tool])
@@ -2068,7 +2068,7 @@ class GetPrice(BaseModel):
             ],
             response_metadata={
                 "id": "msg_01Xg7Wr5inFWgBxE5jH9rpRo",
-                "model": "claude-3-5-sonnet-latest",
+                "model": "claude-sonnet-4-5",
                 "stop_reason": "tool_use",
                 "stop_sequence": None,
                 "usage": {
@@ -2113,7 +2113,7 @@ class GetPrice(BaseModel):
             ],
             response_metadata={
                 "id": "msg_016RfWHrRvW6DAGCdwB6Ac64",
-                "model": "claude-3-5-sonnet-latest",
+                "model": "claude-sonnet-4-5",
                 "stop_reason": "tool_use",
                 "stop_sequence": None,
                 "usage": {
@@ -2240,7 +2240,7 @@ class AnswerWithJustification(BaseModel):
             justification: str
 
 
-        model = ChatAnthropic(model="claude-3-5-sonnet-latest", temperature=0)
+        model = ChatAnthropic(model="claude-sonnet-4-5", temperature=0)
         structured_model = model.with_structured_output(AnswerWithJustification)
 
         structured_model.invoke("What weighs more a pound of bricks or a pound of feathers")
@@ -2265,7 +2265,7 @@ class AnswerWithJustification(BaseModel):
             justification: str
 
 
-        model = ChatAnthropic(model="claude-3-5-sonnet-latest", temperature=0)
+        model = ChatAnthropic(model="claude-sonnet-4-5", temperature=0)
         structured_model = model.with_structured_output(AnswerWithJustification, include_raw=True)
 
         structured_model.invoke("What weighs more a pound of bricks or a pound of feathers")
@@ -2293,7 +2293,7 @@ class AnswerWithJustification(BaseModel):
                 "required": ["answer", "justification"],
             },
         }
-        model = ChatAnthropic(model="claude-3-5-sonnet-latest", temperature=0)
+        model = ChatAnthropic(model="claude-sonnet-4-5", temperature=0)
         structured_model = model.with_structured_output(schema)
 
         structured_model.invoke("What weighs more a pound of bricks or a pound of feathers")
@@ -2365,7 +2365,7 @@ def get_num_tokens_from_messages(
         from langchain_anthropic import ChatAnthropic
         from langchain_core.messages import HumanMessage, SystemMessage
 
-        model = ChatAnthropic(model="claude-3-5-sonnet-20241022")
+        model = ChatAnthropic(model="claude-sonnet-4-5-20250929")
 
         messages = [
             SystemMessage(content="You are a scientist"),
@@ -2385,7 +2385,7 @@ def get_num_tokens_from_messages(
         from langchain_core.messages import HumanMessage
         from langchain_core.tools import tool
 
-        model = ChatAnthropic(model="claude-3-5-sonnet-20241022")
+        model = ChatAnthropic(model="claude-sonnet-4-5-20250929")
 
         @tool(parse_docstring=True)
         def get_weather(location: str) -> str:

libs/partners/anthropic/langchain_anthropic/llms.py

@@ -25,7 +25,7 @@
 class _AnthropicCommon(BaseLanguageModel):
     client: Any = None  #: :meta private:
     async_client: Any = None  #: :meta private:
-    model: str = Field(default="claude-3-5-sonnet-latest", alias="model_name")
+    model: str = Field(default="claude-sonnet-4-5", alias="model_name")
     """Model name to use."""
 
     max_tokens: int = Field(default=1024, alias="max_tokens_to_sample")

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

@@ -588,7 +588,7 @@ class GenerateUsername(BaseModel):
 
 
 def test_disable_parallel_tool_calling() -> None:
-    llm = ChatAnthropic(model="claude-3-5-sonnet-20241022")  # type: ignore[call-arg]
+    llm = ChatAnthropic(model="claude-sonnet-4-5-20250929")  # type: ignore[call-arg]
     llm_with_tools = llm.bind_tools([GenerateUsername], parallel_tool_calls=False)
     result = llm_with_tools.invoke(
         "Use the GenerateUsername tool to generate user names for:\n\n"
@@ -665,7 +665,7 @@ def test_with_structured_output() -> None:
 
 
 def test_get_num_tokens_from_messages() -> None:
-    llm = ChatAnthropic(model="claude-3-5-sonnet-20241022")  # type: ignore[call-arg]
+    llm = ChatAnthropic(model="claude-sonnet-4-5-20250929")  # type: ignore[call-arg]
 
     # Test simple case
     messages = [

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

@@ -55,17 +55,17 @@ def test_streaming_attribute_should_stream(async_api: bool) -> None:  # noqa: FB
 
 def test_anthropic_client_caching() -> None:
     """Test that the OpenAI client is cached."""
-    llm1 = ChatAnthropic(model="claude-3-5-sonnet-latest")
-    llm2 = ChatAnthropic(model="claude-3-5-sonnet-latest")
+    llm1 = ChatAnthropic(model="claude-sonnet-4-5")
+    llm2 = ChatAnthropic(model="claude-sonnet-4-5")
     assert llm1._client._client is llm2._client._client
 
-    llm3 = ChatAnthropic(model="claude-3-5-sonnet-latest", base_url="foo")
+    llm3 = ChatAnthropic(model="claude-sonnet-4-5", base_url="foo")
     assert llm1._client._client is not llm3._client._client
 
-    llm4 = ChatAnthropic(model="claude-3-5-sonnet-latest", timeout=None)
+    llm4 = ChatAnthropic(model="claude-sonnet-4-5", timeout=None)
     assert llm1._client._client is llm4._client._client
 
-    llm5 = ChatAnthropic(model="claude-3-5-sonnet-latest", timeout=3)
+    llm5 = ChatAnthropic(model="claude-sonnet-4-5", timeout=3)
     assert llm1._client._client is not llm5._client._client
 
 
@@ -74,9 +74,7 @@ def test_anthropic_proxy_support() -> None:
     proxy_url = "http://proxy.example.com:8080"
 
     # Test sync client with proxy
-    llm_sync = ChatAnthropic(
-        model="claude-3-5-sonnet-latest", anthropic_proxy=proxy_url
-    )
+    llm_sync = ChatAnthropic(model="claude-sonnet-4-5", anthropic_proxy=proxy_url)
     sync_client = llm_sync._client
     assert sync_client is not None
 
@@ -85,10 +83,8 @@ def test_anthropic_proxy_support() -> None:
     assert async_client is not None
 
     # Test that clients with different proxy settings are not cached together
-    llm_no_proxy = ChatAnthropic(model="claude-3-5-sonnet-latest")
-    llm_with_proxy = ChatAnthropic(
-        model="claude-3-5-sonnet-latest", anthropic_proxy=proxy_url
-    )
+    llm_no_proxy = ChatAnthropic(model="claude-sonnet-4-5")
+    llm_with_proxy = ChatAnthropic(model="claude-sonnet-4-5", anthropic_proxy=proxy_url)
 
     # Different proxy settings should result in different cached clients
     assert llm_no_proxy._client._client is not llm_with_proxy._client._client
@@ -100,7 +96,7 @@ def test_anthropic_proxy_from_environment() -> None:
 
     # Test with environment variable set
     with patch.dict(os.environ, {"ANTHROPIC_PROXY": proxy_url}):
-        llm = ChatAnthropic(model="claude-3-5-sonnet-latest")
+        llm = ChatAnthropic(model="claude-sonnet-4-5")
         assert llm.anthropic_proxy == proxy_url
 
         # Should be able to create clients successfully
@@ -112,9 +108,7 @@ def test_anthropic_proxy_from_environment() -> None:
     # Test that explicit parameter overrides environment variable
     with patch.dict(os.environ, {"ANTHROPIC_PROXY": "http://env-proxy.com"}):
         explicit_proxy = "http://explicit-proxy.com"
-        llm = ChatAnthropic(
-            model="claude-3-5-sonnet-latest", anthropic_proxy=explicit_proxy
-        )
+        llm = ChatAnthropic(model="claude-sonnet-4-5", anthropic_proxy=explicit_proxy)
         assert llm.anthropic_proxy == explicit_proxy
 
 
@@ -132,10 +126,6 @@ def test_set_default_max_tokens() -> None:
     llm = ChatAnthropic(model="claude-3-7-sonnet-latest", anthropic_api_key="test")
     assert llm.max_tokens == 64000
 
-    # Test claude-3-5-sonnet models
-    llm = ChatAnthropic(model="claude-3-5-sonnet-latest", anthropic_api_key="test")
-    assert llm.max_tokens == 8192
-
     # Test claude-3-5-haiku models
     llm = ChatAnthropic(model="claude-3-5-haiku-latest", anthropic_api_key="test")
     assert llm.max_tokens == 8192
@@ -146,13 +136,13 @@ def test_set_default_max_tokens() -> None:
 
     # Test that existing max_tokens values are preserved
     llm = ChatAnthropic(
-        model="claude-3-5-sonnet-latest", max_tokens=2048, anthropic_api_key="test"
+        model="claude-sonnet-4-5", max_tokens=2048, anthropic_api_key="test"
     )
     assert llm.max_tokens == 2048
 
     # Test that explicitly set max_tokens values are preserved
     llm = ChatAnthropic(
-        model="claude-3-5-sonnet-latest", max_tokens=4096, anthropic_api_key="test"
+        model="claude-sonnet-4-5", max_tokens=4096, anthropic_api_key="test"
     )
     assert llm.max_tokens == 4096