feat(anthropic.py): support anthropic 'tool_choice' param

Closes https://github.com/BerriAI/litellm/issues/3752

litellm/llms/anthropic.py

@@ -10,6 +10,7 @@ from .prompt_templates.factory import prompt_factory, custom_prompt
 from litellm.llms.custom_httpx.http_handler import AsyncHTTPHandler
 from .base import BaseLLM
 import httpx  # type: ignore
+from litellm.types.llms.anthropic import AnthropicMessagesToolChoice
 
 
 class AnthropicConstants(Enum):
@@ -102,6 +103,17 @@ class AnthropicConfig:
                 optional_params["max_tokens"] = value
             if param == "tools":
                 optional_params["tools"] = value
+            if param == "tool_choice":
+                _tool_choice: Optional[AnthropicMessagesToolChoice] = None
+                if value == "auto":
+                    _tool_choice = {"type": "auto"}
+                elif value == "required":
+                    _tool_choice = {"type": "any"}
+                elif isinstance(value, dict):
+                    _tool_choice = {"type": "tool", "name": value["function"]["name"]}
+
+                if _tool_choice is not None:
+                    optional_params["tool_choice"] = _tool_choice
             if param == "stream" and value == True:
                 optional_params["stream"] = value
             if param == "stop":

litellm/main.py

@@ -486,7 +486,7 @@ def completion(
     response_format: Optional[dict] = None,
     seed: Optional[int] = None,
     tools: Optional[List] = None,
-    tool_choice: Optional[str] = None,
+    tool_choice: Optional[Union[str, dict]] = None,
     logprobs: Optional[bool] = None,
     top_logprobs: Optional[int] = None,
     deployment_id=None,

litellm/tests/test_completion.py

@@ -278,9 +278,12 @@ def test_completion_claude_3_function_call():
             model="anthropic/claude-3-opus-20240229",
             messages=messages,
             tools=tools,
-            tool_choice={"type": "tool", "name": "get_weather"},
-            extra_headers={"anthropic-beta": "tools-2024-05-16"},
+            tool_choice={
+                "type": "function",
+                "function": {"name": "get_current_weather"},
+            },
         )
+
         # Add any assertions, here to check response args
         print(response)
         assert isinstance(response.choices[0].message.tool_calls[0].function.name, str)

litellm/types/llms/anthropic.py

@@ -5,6 +5,11 @@ from pydantic import BaseModel, validator
 from typing_extensions import Literal, Required, TypedDict
 
 
+class AnthropicMessagesToolChoice(TypedDict, total=False):
+    type: Required[Literal["auto", "any", "tool"]]
+    name: str
+
+
 class AnthopicMessagesAssistantMessageTextContentParam(TypedDict, total=False):
     type: Required[Literal["text"]]