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test(anthropic): expect the json tool description through a shared constant

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mateo-berri 2026-10-12 10:42:09 -07:00
parent b5fa712789
commit 9b5ae73da9
4 changed files with 15 additions and 2 deletions
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3
litellm/constants.py
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@ -1586,6 +1586,9 @@ 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_TOOL_DESCRIPTION: Final = (
"Return the final answer as this structured object, filling every required field."
)
########################### Logging Callback Constants ###########################
AZURE_STORAGE_MSFT_VERSION: Final = "2019-07-07"

3
litellm/llms/anthropic/chat/transformation.py
View file

@ -20,6 +20,7 @@ from litellm.constants import (
DEFAULT_REASONING_EFFORT_MEDIUM_THINKING_BUDGET,
DEFAULT_REASONING_EFFORT_MINIMAL_THINKING_BUDGET,
DEFAULT_REASONING_EFFORT_XHIGH_THINKING_BUDGET,
RESPONSE_FORMAT_TOOL_DESCRIPTION,
RESPONSE_FORMAT_TOOL_NAME,
)
from litellm.litellm_core_utils.core_helpers import map_finish_reason
@ -1754,7 +1755,7 @@ class AnthropicConfig(AnthropicModelInfo, BaseConfig):
_tool: Final = AnthropicMessagesTool(
name=RESPONSE_FORMAT_TOOL_NAME,
description="Return the final answer as this structured object, filling every required field.",
description=RESPONSE_FORMAT_TOOL_DESCRIPTION,
input_schema=_input_schema,
)
return _tool

2
tests/unit/llms/databricks/chat/test_databricks_chat_transformation.py
View file

@ -16,6 +16,7 @@ from litellm.constants import (
DEFAULT_REASONING_EFFORT_HIGH_THINKING_BUDGET,
DEFAULT_REASONING_EFFORT_LOW_THINKING_BUDGET,
DEFAULT_REASONING_EFFORT_MEDIUM_THINKING_BUDGET,
RESPONSE_FORMAT_TOOL_DESCRIPTION,
)
from litellm.llms.custom_httpx.http_handler import AsyncHTTPHandler, HTTPHandler
from litellm.llms.databricks.chat.transformation import (
@ -2143,6 +2144,7 @@ def test_databricks_claude_json_schema_preserves_refs_in_tool_parameters() -> No
"function": {
"name": "json_tool_call",
"parameters": JSON_SCHEMA_RESPONSE_FORMAT["json_schema"]["schema"],
"description": RESPONSE_FORMAT_TOOL_DESCRIPTION,
},
}
]

9
tests/unit/llms/vertex_ai/test_vertex.py
View file

@ -22,6 +22,7 @@ import pytest
import litellm
from litellm import Router, get_optional_params
from litellm.constants import RESPONSE_FORMAT_TOOL_DESCRIPTION
from litellm.llms.vertex_ai.gemini.transformation import _process_gemini_media
from litellm.types.llms.vertex_ai import BlobType
@ -2692,7 +2693,13 @@ def test_gemini_pro_json_schema_args_sent_httpx(
request_body: Final = json.loads(route.calls[0].request.content)
if "claude" in model:
assert request_body["tool_choice"] == {"type": "tool", "name": "json_tool_call"}
assert request_body["tools"] == [{"name": "json_tool_call", "input_schema": _RECIPES_SCHEMA}]
assert request_body["tools"] == [
{
"name": "json_tool_call",
"description": RESPONSE_FORMAT_TOOL_DESCRIPTION,
"input_schema": _RECIPES_SCHEMA,
}
]
else:
assert request_body["generationConfig"]["response_mime_type"] == "application/json"
assert request_body["generationConfig"]["response_json_schema"] == _RECIPES_SCHEMA