fix(anthropic): support output_config (#35036)

libs/partners/anthropic/langchain_anthropic/chat_models.py

@@ -1167,22 +1167,22 @@ class ChatAnthropic(BaseChatModel):
                 and "schema" in response_format.get("json_schema", {})
             ):
                 response_format = cast(dict, response_format["json_schema"]["schema"])
-            # Convert OpenAI-style response_format to Anthropic's output_format
-            payload["output_format"] = _convert_to_anthropic_output_format(
+            # Convert OpenAI-style response_format to Anthropic's output_config.format
+            output_config = payload.setdefault("output_config", {})
+            output_config["format"] = _convert_to_anthropic_output_config_format(
                 response_format
             )
 
+        # Handle deprecated output_format parameter for backward compatibility
         if "output_format" in payload:
-            # Native structured output requires the structured outputs beta
-            if payload["betas"]:
-                if "structured-outputs-2025-11-13" not in payload["betas"]:
-                    # Merge with existing betas
-                    payload["betas"] = [
-                        *payload["betas"],
-                        "structured-outputs-2025-11-13",
-                    ]
-            else:
-                payload["betas"] = ["structured-outputs-2025-11-13"]
+            warnings.warn(
+                "The 'output_format' parameter is deprecated and will be removed in a "
+                "future version. Use 'output_config={\"format\": ...}' instead.",
+                DeprecationWarning,
+                stacklevel=2,
+            )
+            output_config = payload.setdefault("output_config", {})
+            output_config["format"] = payload.pop("output_format")
 
         if self.reuse_last_container:
             # Check for most recent AIMessage with container set in response_metadata
@@ -1197,24 +1197,9 @@ class ChatAnthropic(BaseChatModel):
                     payload["container"] = container_id
                     break
 
-        # Check if any tools have strict mode enabled
+        # Note: Beta headers are no longer required for structured outputs
+        # (output_config.format or strict tool use) as they are now generally available
         if "tools" in payload and isinstance(payload["tools"], list):
-            has_strict_tool = any(
-                isinstance(tool, dict) and tool.get("strict") is True
-                for tool in payload["tools"]
-            )
-            if has_strict_tool:
-                # Strict tool use requires the structured outputs beta
-                if payload["betas"]:
-                    if "structured-outputs-2025-11-13" not in payload["betas"]:
-                        # Merge with existing betas
-                        payload["betas"] = [
-                            *payload["betas"],
-                            "structured-outputs-2025-11-13",
-                        ]
-                else:
-                    payload["betas"] = ["structured-outputs-2025-11-13"]
-
             # Auto-append required betas for specific tool types and input_examples
             has_input_examples = False
             for tool in payload["tools"]:
@@ -1684,7 +1669,9 @@ class ChatAnthropic(BaseChatModel):
                 )
         elif method == "json_schema":
             llm = self.bind(
-                output_format=_convert_to_anthropic_output_format(schema),
+                output_config={
+                    "format": _convert_to_anthropic_output_config_format(schema)
+                },
                 ls_structured_output_format={
                     "kwargs": {"method": "json_schema"},
                     "schema": convert_to_openai_tool(schema),
@@ -1911,10 +1898,16 @@ def _lc_tool_calls_to_anthropic_tool_use_blocks(
     ]
 
 
-def _convert_to_anthropic_output_format(schema: dict | type) -> dict[str, Any]:
-    """Convert JSON schema, Pydantic model, or `TypedDict` into Claude `output_format`.
+def _convert_to_anthropic_output_config_format(schema: dict | type) -> dict[str, Any]:
+    """Convert JSON schema, Pydantic model, or `TypedDict` into `output_config.format`.
 
     See Claude docs on [structured outputs](https://platform.claude.com/docs/en/build-with-claude/structured-outputs).
+
+    Args:
+        schema: A JSON schema dict, Pydantic model class, or TypedDict.
+
+    Returns:
+        A dict with `type` and `schema` keys suitable for `output_config.format`.
     """
     from anthropic import transform_schema
 

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

@@ -727,7 +727,6 @@ class PersonDict(TypedDict):
 def test_response_format(schema: dict | type) -> None:
     model = ChatAnthropic(
         model="claude-sonnet-4-5",  # type: ignore[call-arg]
-        betas=["structured-outputs-2025-11-13"],
     )
     query = "Chester (a.k.a. Chet) is 100 years old."
 
@@ -779,7 +778,6 @@ def test_response_format_in_agent() -> None:
 def test_strict_tool_use() -> None:
     model = ChatAnthropic(
         model="claude-sonnet-4-5",  # type: ignore[call-arg]
-        betas=["structured-outputs-2025-11-13"],
     )
 
     def get_weather(location: str, unit: Literal["C", "F"]) -> str:

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

@@ -1663,7 +1663,6 @@ def test_streaming_cache_token_reporting() -> None:
 def test_strict_tool_use() -> None:
     model = ChatAnthropic(
         model=MODEL_NAME,  # type: ignore[call-arg]
-        betas=["structured-outputs-2025-11-13"],
     )
 
     def get_weather(location: str, unit: Literal["C", "F"]) -> str:
@@ -1676,8 +1675,8 @@ def test_strict_tool_use() -> None:
     assert tool_definition["strict"] is True
 
 
-def test_beta_merging_with_response_format() -> None:
-    """Test that structured-outputs beta is merged with existing betas."""
+def test_response_format_with_output_config() -> None:
+    """Test that response_format is converted to output_config.format."""
 
     class Person(BaseModel):
         """Person data."""
@@ -1685,114 +1684,47 @@ def test_beta_merging_with_response_format() -> None:
         name: str
         age: int
 
-    # Auto-inject structured-outputs beta with no others specified
+    # Test that response_format converts to output_config.format
     model = ChatAnthropic(model=MODEL_NAME)
     payload = model._get_request_payload(
         "Test query",
         response_format=Person.model_json_schema(),
     )
-    assert payload["betas"] == ["structured-outputs-2025-11-13"]
+    assert "output_config" in payload
+    assert "format" in payload["output_config"]
+    assert payload["output_config"]["format"]["type"] == "json_schema"
+    assert "schema" in payload["output_config"]["format"]
 
-    # Merge structured-outputs beta if other betas are present
-    model = ChatAnthropic(
-        model=MODEL_NAME,
-        betas=["mcp-client-2025-04-04"],
-    )
-    payload = model._get_request_payload(
-        "Test query",
-        response_format=Person.model_json_schema(),
-    )
-    assert payload["betas"] == [
-        "mcp-client-2025-04-04",
-        "structured-outputs-2025-11-13",
-    ]
-
-    # Structured-outputs beta already present - don't duplicate
-    model = ChatAnthropic(
-        model=MODEL_NAME,
-        betas=[
-            "mcp-client-2025-04-04",
-            "structured-outputs-2025-11-13",
-        ],
-    )
-    payload = model._get_request_payload(
-        "Test query",
-        response_format=Person.model_json_schema(),
-    )
-    assert payload["betas"] == [
-        "mcp-client-2025-04-04",
-        "structured-outputs-2025-11-13",
-    ]
-
-    # No response_format - betas should not be modified
-    model = ChatAnthropic(
-        model=MODEL_NAME,
-        betas=["mcp-client-2025-04-04"],
-    )
+    # No response_format - output_config should not have format
+    model = ChatAnthropic(model=MODEL_NAME)
     payload = model._get_request_payload("Test query")
-    assert payload["betas"] == ["mcp-client-2025-04-04"]
+    if "output_config" in payload:
+        assert "format" not in payload["output_config"]
 
 
-def test_beta_merging_with_strict_tool_use() -> None:
-    """Test beta merging for strict tools."""
+def test_strict_tool_use_payload() -> None:
+    """Test that strict tool use property is correctly passed through to payload."""
 
     def get_weather(location: str) -> str:
         """Get the weather at a location."""
         return "Sunny"
 
-    # Auto-inject structured-outputs beta with no others specified
+    # Test that strict=True is correctly passed to payload
     model = ChatAnthropic(model=MODEL_NAME)  # type: ignore[call-arg]
     model_with_tools = model.bind_tools([get_weather], strict=True)
     payload = model_with_tools._get_request_payload(  # type: ignore[attr-defined]
         "What's the weather?",
         **model_with_tools.kwargs,  # type: ignore[attr-defined]
     )
-    assert payload["betas"] == ["structured-outputs-2025-11-13"]
+    assert payload["tools"][0]["strict"] is True
 
-    # Merge structured-outputs beta if other betas are present
-    model = ChatAnthropic(
-        model=MODEL_NAME,  # type: ignore[call-arg]
-        betas=["mcp-client-2025-04-04"],
-    )
-    model_with_tools = model.bind_tools([get_weather], strict=True)
-    payload = model_with_tools._get_request_payload(  # type: ignore[attr-defined]
+    # Test that strict=False is correctly passed to payload
+    model_without_strict = model.bind_tools([get_weather], strict=False)
+    payload = model_without_strict._get_request_payload(  # type: ignore[attr-defined]
         "What's the weather?",
-        **model_with_tools.kwargs,  # type: ignore[attr-defined]
+        **model_without_strict.kwargs,  # type: ignore[attr-defined]
     )
-    assert payload["betas"] == [
-        "mcp-client-2025-04-04",
-        "structured-outputs-2025-11-13",
-    ]
-
-    # Structured-outputs beta already present - don't duplicate
-    model = ChatAnthropic(
-        model=MODEL_NAME,  # type: ignore[call-arg]
-        betas=[
-            "mcp-client-2025-04-04",
-            "structured-outputs-2025-11-13",
-        ],
-    )
-    model_with_tools = model.bind_tools([get_weather], strict=True)
-    payload = model_with_tools._get_request_payload(  # type: ignore[attr-defined]
-        "What's the weather?",
-        **model_with_tools.kwargs,  # type: ignore[attr-defined]
-    )
-    assert payload["betas"] == [
-        "mcp-client-2025-04-04",
-        "structured-outputs-2025-11-13",
-    ]
-
-    # No strict tools - betas should not be modified
-    model = ChatAnthropic(
-        model=MODEL_NAME,  # type: ignore[call-arg]
-        betas=["mcp-client-2025-04-04"],
-    )
-    model_with_tools = model.bind_tools([get_weather], strict=False)
-    payload = model_with_tools._get_request_payload(  # type: ignore[attr-defined]
-        "What's the weather?",
-        **model_with_tools.kwargs,  # type: ignore[attr-defined]
-    )
-    assert payload["betas"] == ["mcp-client-2025-04-04"]
+    assert payload["tools"][0].get("strict") is False
 
 
 def test_auto_append_betas_for_tool_types() -> None: