Merge 0a9d0a1e08 into a6b7f62760

litellm/constants.py

@@ -1540,6 +1540,9 @@ OPENAI_FINISH_REASONS: Final = [
 ]
 HUMANLOOP_PROMPT_CACHE_TTL_SECONDS: Final = int(os.getenv("HUMANLOOP_PROMPT_CACHE_TTL_SECONDS", 60))  # 1 minute
 RESPONSE_FORMAT_TOOL_NAME = "json_tool_call"  # default tool name used when converting response format to tool call
+RESPONSE_FORMAT_UNFORCED_TOOL_DESCRIPTION: Final = (
+    "Always respond by calling this tool. Its input is your final answer; do not reply in plain text."
+)
 
 ########################### Logging Callback Constants ###########################
 AZURE_STORAGE_MSFT_VERSION: Final = "2019-07-07"

litellm/llms/bedrock/chat/converse_transformation.py

@@ -19,6 +19,7 @@ from litellm._logging import verbose_logger
 from litellm.constants import (
     BEDROCK_MIN_THINKING_BUDGET_TOKENS,
     RESPONSE_FORMAT_TOOL_NAME,
+    RESPONSE_FORMAT_UNFORCED_TOOL_DESCRIPTION,
 )
 from litellm.litellm_core_utils.core_helpers import (
     filter_exceptions_from_params,
@@ -1277,16 +1278,20 @@ class AmazonConverseConfig(BaseConfig):
         elif json_schema is not None:
             # Fallback: translate to a synthetic tool call
             # https://docs.anthropic.com/en/docs/build-with-claude/tool-use#json-mode
+            tool_choice_blocked: Final = is_thinking_enabled or AnthropicModelInfo.forced_tool_use_unsupported(model)
             _tool: Final = self._create_json_tool_call_for_response_format(
                 json_schema=json_schema,
-                description=description,
+                description=(
+                    " ".join(filter(None, (RESPONSE_FORMAT_UNFORCED_TOOL_DESCRIPTION, description)))
+                    if tool_choice_blocked
+                    else description
+                ),
             )
             optional_params = self._add_tools_to_optional_params(optional_params=optional_params, tools=[_tool])
 
             if (
                 litellm.utils.supports_tool_choice(model=model, custom_llm_provider=self.custom_llm_provider)
-                and not is_thinking_enabled
-                and not AnthropicModelInfo.forced_tool_use_unsupported(model)
+                and not tool_choice_blocked
             ):
                 optional_params["tool_choice"] = ToolChoiceValuesBlock(
                     tool=SpecificToolChoiceBlock(name=RESPONSE_FORMAT_TOOL_NAME)

litellm/llms/bedrock/chat/invoke_transformations/anthropic_claude3_transformation.py

@@ -3,7 +3,7 @@ from typing import TYPE_CHECKING, Any, Final
 import httpx
 
 from litellm.anthropic_beta_headers_manager import filter_and_transform_beta_headers
-from litellm.constants import RESPONSE_FORMAT_TOOL_NAME
+from litellm.constants import RESPONSE_FORMAT_TOOL_NAME, RESPONSE_FORMAT_UNFORCED_TOOL_DESCRIPTION
 from litellm.litellm_core_utils.prompt_templates.factory import (
     convert_to_anthropic_image_obj,
 )
@@ -135,6 +135,22 @@ class AmazonAnthropicClaudeConfig(AmazonInvokeConfig, AnthropicConfig):
             and AnthropicModelInfo.forced_tool_use_unsupported(original_model)
         ):
             optional_params.pop("tool_choice")
+        if (
+            "response_format" in non_default_params
+            and "tools" in optional_params
+            and (
+                self.is_thinking_enabled(non_default_params)
+                or AnthropicModelInfo.forced_tool_use_unsupported(original_model)
+            )
+        ):
+            # Rebuild the tool instead of writing into it: Anthropic-format tools reach
+            # here as the caller's own dicts, and the repo rules out in-place mutation
+            optional_params["tools"] = [  # rebind-ok: out-param store like siblings
+                {**tool, "description": RESPONSE_FORMAT_UNFORCED_TOOL_DESCRIPTION}
+                if tool.get("name") == RESPONSE_FORMAT_TOOL_NAME
+                else tool
+                for tool in optional_params["tools"]
+            ]
 
         return optional_params
 

tests/unit/llms/bedrock/chat/invoke_transformations/test_bedrock_chat_invoke_transformations_anthropic_claude3_transformation.py

@@ -12,6 +12,7 @@ import pytest
 # Ensure the project root is on the import path so `litellm` can be imported when
 # tests are executed from any working directory.
 import litellm
+from litellm.constants import RESPONSE_FORMAT_UNFORCED_TOOL_DESCRIPTION
 from litellm.llms.bedrock.chat.invoke_transformations.anthropic_claude3_transformation import (
     AmazonAnthropicClaudeConfig,
 )
@@ -709,7 +710,12 @@ def test_bedrock_chat_invoke_drop_params_still_inlines_for_non_native(local_mode
 
 @pytest.mark.parametrize(
     "model",
-    ["us.anthropic.claude-fable-5-1", "anthropic.claude-fable-5-1"],
+    [
+        "us.anthropic.claude-fable-5-1",
+        "anthropic.claude-fable-5-1",
+        "us.anthropic.claude-opus-5-5",
+        "anthropic.claude-opus-5-5",
+    ],
 )
 def test_bedrock_chat_invoke_fable_5_1_response_format_avoids_forced_tool_choice(local_model_cost_map, model):
     """Regression: Bedrock rejects both native ``output_config.format`` and forced
@@ -731,10 +737,49 @@ def test_bedrock_chat_invoke_fable_5_1_response_format_avoids_forced_tool_choice
     )
 
     assert "output_format" not in result
-    assert "tools" in result
+    assert result["tools"][0]["description"] == RESPONSE_FORMAT_UNFORCED_TOOL_DESCRIPTION
     assert "tool_choice" not in result
 
 
+@pytest.mark.parametrize(
+    ("extra_params", "expected_tool_choice", "expected_description"),
+    [
+        ({}, {"name": "json_tool_call", "type": "tool"}, None),
+        ({"reasoning_effort": "low"}, None, RESPONSE_FORMAT_UNFORCED_TOOL_DESCRIPTION),
+        (
+            {
+                "tools": [{"type": "function", "function": {"name": "get_weather", "parameters": {"type": "object"}}}],
+                "tool_choice": "auto",
+            },
+            {"type": "auto"},
+            None,
+        ),
+    ],
+)
+def test_bedrock_chat_invoke_response_format_tool_description_asks_for_the_tool_only_when_it_cannot_be_forced(
+    local_model_cost_map, extra_params, expected_tool_choice, expected_description
+):
+    result = AmazonAnthropicClaudeConfig().map_openai_params(
+        non_default_params={
+            "response_format": {
+                "type": "json_schema",
+                "json_schema": {
+                    "name": "City",
+                    "schema": {"type": "object", "properties": {"name": {"type": "string"}}},
+                },
+            },
+            "max_tokens": 4096,
+            **extra_params,
+        },
+        optional_params={},
+        model="us.anthropic.claude-opus-5",
+        drop_params=False,
+    )
+
+    assert result.get("tool_choice") == expected_tool_choice
+    assert result["tools"][0].get("description") == expected_description
+
+
 @pytest.mark.parametrize("model", ["us.anthropic.claude-sonnet-5", "us.anthropic.claude-fable-5-1"])
 def test_bedrock_chat_invoke_tool_based_response_format_still_upgrades_legacy_thinking(local_model_cost_map, model):
     result = AmazonAnthropicClaudeConfig().map_openai_params(

tests/unit/llms/bedrock/chat/test_converse_transformation.py

@@ -9,6 +9,7 @@ import pytest
 
 import litellm
 from litellm import ModelResponse
+from litellm.constants import RESPONSE_FORMAT_UNFORCED_TOOL_DESCRIPTION
 from litellm.litellm_core_utils.prompt_templates.mid_conversation_system import CONVERTED_SYSTEM_NOTE
 from litellm.llms.bedrock.chat.converse_transformation import AmazonConverseConfig
 from litellm.types.llms.bedrock import ConverseTokenUsageBlock
@@ -7642,7 +7643,12 @@ def test_unforced_tool_choice_unaffected_on_fable_5_1_converse(local_model_cost_
 
 @pytest.mark.parametrize(
     "model",
-    ["anthropic.claude-fable-5-1", "us.anthropic.claude-fable-5-1"],
+    [
+        "anthropic.claude-fable-5-1",
+        "us.anthropic.claude-fable-5-1",
+        "anthropic.claude-opus-5-5",
+        "us.anthropic.claude-opus-5-5",
+    ],
 )
 def test_response_format_avoids_native_and_forced_tool_choice_on_fable_5_1_converse(
     local_model_cost_map, model
@@ -7668,11 +7674,50 @@ def test_response_format_avoids_native_and_forced_tool_choice_on_fable_5_1_conve
     )
 
     assert "outputConfig" not in result
-    assert "tools" in result
+    assert result["tools"][0]["function"]["description"] == RESPONSE_FORMAT_UNFORCED_TOOL_DESCRIPTION
     assert "tool_choice" not in result
     assert result.get("json_mode") is True
 
 
+@pytest.mark.parametrize(
+    ("extra_params", "expected_tool_choice", "expected_description"),
+    [
+        ({}, {"tool": {"name": "json_tool_call"}}, "A city"),
+        ({"reasoning_effort": "low"}, None, f"{RESPONSE_FORMAT_UNFORCED_TOOL_DESCRIPTION} A city"),
+        (
+            {
+                "tools": [{"type": "function", "function": {"name": "get_weather", "parameters": {"type": "object"}}}],
+                "tool_choice": "auto",
+            },
+            {"auto": {}},
+            "A city",
+        ),
+    ],
+)
+def test_response_format_tool_description_asks_for_the_tool_only_when_it_cannot_be_forced(
+    local_model_cost_map, extra_params, expected_tool_choice, expected_description
+):
+    result = AmazonConverseConfig().map_openai_params(
+        non_default_params={
+            "response_format": {
+                "type": "json_schema",
+                "json_schema": {
+                    "name": "City",
+                    "description": "A city",
+                    "schema": {"type": "object", "properties": {"name": {"type": "string"}}},
+                },
+            },
+            **extra_params,
+        },
+        optional_params={},
+        model="us.anthropic.claude-opus-5",
+        drop_params=False,
+    )
+
+    assert result.get("tool_choice") == expected_tool_choice
+    assert result["tools"][0]["function"]["description"] == expected_description
+
+
 def test_forced_tool_choice_forwarded_on_converse_models_that_support_it(
     local_model_cost_map, monkeypatch
 ):