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fix(anthropic): keep union and $ref tool schemas from being emptied
A tool whose parameters are a Pydantic Union[A, B] reached Anthropic taking no arguments at all. Pydantic puts anyOf over $defs at the root with no type or properties, so the sanitizer stamped type: "object" over it, invented an empty properties, and then dropped anyOf with its allowlist. The $defs glossary still went on the wire, paid for and referenced by nothing. Nothing raised: Anthropic accepts a tool with no arguments, so the model simply stopped calling it. Root oneOf, allOf and a bare $ref failed the same way. Resolve a root-level local $ref, then merge root combinators, before the allowlist runs. The merging reuses flatten_top_level_schema_combinators, which OpenAI, Azure and OpenAI Responses already put tool schemas through, so this adopts an existing tradeoff rather than inventing one: branches merge, and required narrows to what every branch demands. Schemas that already worked are untouched, including a combinator nested inside a property, which Anthropic accepts. An external, missing or non-object root $ref is left exactly as before rather than gaining a new failure mode. Fixes #43157
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ajitsharmas2007
parent
491d454826
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1ce03b290d
2 changed files with 154 additions and 1 deletions
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@ -1140,10 +1140,17 @@ def sanitize_input_schema_for_anthropic(input_schema: dict) -> "AnthropicInputSc
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(``AnthropicConfig._map_tool_helper``) and Anthropic Messages MCP paths run
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a schema through here so an external MCP schema cannot succeed on one route
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and 400 on the other.
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A root that is a local ``$ref`` or a top-level combinator is resolved into an
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object first. Without that, ``type: "object"`` and an empty ``properties``
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are stamped over a schema whose fields live one level down, and the
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allowlist then drops the combinator: a ``TypeAdapter(Union[A, B])`` tool
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reaches Anthropic taking no arguments at all. An unresolvable root (external
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or missing ``$ref``, a branch that cannot merge) is left alone.
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"""
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from litellm.types.llms.anthropic import AnthropicInputSchema
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normalized = dict(input_schema) if input_schema else {}
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normalized = dict(flatten_top_level_schema_combinators(_inline_root_schema_ref(input_schema or {})))
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if normalized.get("type") != "object":
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normalized["type"] = "object"
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if "properties" not in normalized:
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@ -1204,6 +1211,25 @@ def _resolve_local_schema_ref(root: Mapping[str, object], ref: str) -> Mapping[s
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return target if isinstance(target, dict) else None
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def _inline_root_schema_ref(schema: Mapping[str, object]) -> Mapping[str, object]:
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"""Replace a root-level local ``$ref`` with the schema it points at.
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The glossaries are carried over so refs inside the target still resolve, and
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the target wins on any key it shares with the root. A root without a ``$ref``,
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or one pointing outside the document or at a missing name, is returned as is.
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"""
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ref: Final = schema.get("$ref")
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if not isinstance(ref, str):
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return schema
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target: Final = _resolve_local_schema_ref(schema, ref)
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if target is None:
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return schema
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glossaries: Final = MappingProxyType(
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{container: schema[container] for _, container in _LOCAL_SCHEMA_REF_PREFIXES if container in schema}
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)
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return MappingProxyType({**glossaries, **target})
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def _mergeable_branch(
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root: Mapping[str, object],
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branch: object,
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@ -1990,3 +1990,130 @@ class TestMergeConsecutiveSystemMessages:
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)
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assert merged == [{"role": "system"}, {"role": "user", "content": "Hi"}]
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class TestSanitizeInputSchemaForAnthropic:
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"""Anthropic rejects a tool schema whose root is a union or a ``$ref``, so the
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sanitizer coerces one into an object. Stamping ``type: "object"`` and an empty
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``properties`` over a root whose fields live one level down, then dropping the
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combinator with the allowlist, sent a ``TypeAdapter(Union[A, B])`` tool to
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Anthropic taking no arguments at all (#43157)."""
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A: Final = {
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"type": "object",
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"properties": {"kind": {"type": "string"}, "a": {"type": "string"}},
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"required": ["kind", "a"],
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}
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B: Final = {
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"type": "object",
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"properties": {"kind": {"type": "string"}, "b": {"type": "integer"}},
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"required": ["kind", "b"],
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}
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def _union_root(self, combinator):
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return {"$defs": {"A": self.A, "B": self.B}, combinator: [{"$ref": "#/$defs/A"}, {"$ref": "#/$defs/B"}]}
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@pytest.mark.parametrize("combinator", ["anyOf", "oneOf"])
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def test_union_root_keeps_every_branch_field(self, combinator):
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from litellm.litellm_core_utils.prompt_templates.common_utils import (
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sanitize_input_schema_for_anthropic,
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)
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result = sanitize_input_schema_for_anthropic(self._union_root(combinator))
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assert sorted(result["properties"]) == [
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"a",
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"b",
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"kind",
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], f"a {combinator} root must keep its branches' fields, got {dict(result)}"
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def test_ref_root_resolves_to_the_schema_it_points_at(self):
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from litellm.litellm_core_utils.prompt_templates.common_utils import (
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sanitize_input_schema_for_anthropic,
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)
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result = sanitize_input_schema_for_anthropic({"$defs": {"A": self.A}, "$ref": "#/$defs/A"})
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assert sorted(result["properties"]) == ["a", "kind"], f"a $ref root must inline its target, got {dict(result)}"
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assert sorted(result["required"]) == ["a", "kind"], (
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f"the target's required list must survive, got {dict(result)}"
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)
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def test_union_required_narrows_to_the_fields_every_branch_demands(self):
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"""Merging branches is lossy by design: only what all of them require stays
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required, which is the tradeoff OpenAI and Azure already accept via the
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shared flattening helper."""
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from litellm.litellm_core_utils.prompt_templates.common_utils import (
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sanitize_input_schema_for_anthropic,
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)
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result = sanitize_input_schema_for_anthropic(self._union_root("anyOf"))
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assert sorted(result.get("required", [])) == ["kind"], (
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f"only the field both branches require stays required, got {dict(result)}"
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)
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@pytest.mark.parametrize(
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"name, schema, expected_properties",
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[
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("plain object", {"type": "object", "properties": {"x": {"type": "string"}}}, ["x"]),
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("no-arg tool", {"type": "object", "properties": {}}, []),
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("empty schema", {}, []),
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("external $ref root", {"$ref": "https://example.com/schema.json"}, []),
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("missing $ref target", {"$defs": {}, "$ref": "#/$defs/Nope"}, []),
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],
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)
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def test_shapes_the_sanitizer_already_handled_are_untouched(self, name, schema, expected_properties):
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from litellm.litellm_core_utils.prompt_templates.common_utils import (
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sanitize_input_schema_for_anthropic,
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)
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result = sanitize_input_schema_for_anthropic(schema)
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assert sorted(result["properties"]) == expected_properties, f"{name} should be unchanged, got {dict(result)}"
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assert result["type"] == "object", f"{name} must still be coerced to an object, got {dict(result)}"
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def test_a_combinator_nested_inside_a_property_is_left_alone(self):
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"""Anthropic accepts nested combinators; only the root shape is a problem."""
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from litellm.litellm_core_utils.prompt_templates.common_utils import (
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sanitize_input_schema_for_anthropic,
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)
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nested = {"anyOf": [{"type": "string"}, {"type": "integer"}]}
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result = sanitize_input_schema_for_anthropic({"type": "object", "properties": {"x": nested}})
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assert result["properties"]["x"] == nested, f"a nested union must survive verbatim, got {dict(result)}"
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def test_a_pydantic_union_tool_reaches_anthropic_with_its_arguments(self):
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"""The reporter's path: Pydantic emits a root ``anyOf`` over ``$defs``."""
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from typing import Literal
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from pydantic import BaseModel, TypeAdapter
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from litellm.llms.anthropic.chat.transformation import AnthropicConfig
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class Alpha(BaseModel):
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kind: Literal["a"]
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a: str
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class Beta(BaseModel):
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kind: Literal["b"]
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b: int
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tool = {
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"type": "function",
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"function": {
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"name": "record",
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"description": "record an event",
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"parameters": TypeAdapter(Alpha | Beta).json_schema(),
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},
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}
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mapped, _ = AnthropicConfig()._map_tools([tool])
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assert sorted(mapped[0]["input_schema"]["properties"]) == [
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"a",
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"b",
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"kind",
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], f"the tool must reach Anthropic with arguments, got {mapped[0]['input_schema']}"
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