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fix(anthropic): close strict JSON schemas on the Messages to Responses bridge (#51337)
* fix(anthropic): close strict JSON schemas on the Messages to Responses bridge Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * perf(anthropic): copy each strict schema subtree once Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * fix(anthropic): close nullable objects in strict JSON schemas Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> --------- Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
This commit is contained in:
kenneth-berri
GitHub
parent
7c7e02b06f
commit
4cd8f9174d
5 changed files with 167 additions and 68 deletions
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@ -1,4 +1,3 @@
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import copy
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import hashlib
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import json
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from collections.abc import AsyncIterator, Iterator, Mapping, Sequence
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@ -20,6 +19,8 @@ from litellm.llms.anthropic.messages.convertible_blocks import tool_result_text_
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from litellm.llms.anthropic.messages.utils import (
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is_reasoning_auto_summary_enabled,
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json_copy_or_original,
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object_mapping,
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openai_strict_json_schema,
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prompt_cache_key_from_user_id,
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)
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from litellm.responses.utils import auto_reasoning_summary
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@ -1017,66 +1018,23 @@ class LiteLLMAnthropicMessagesAdapter:
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Returns:
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OpenAI-compatible response_format dict, or None if invalid
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"""
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if not isinstance(output_format, dict):
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output_format_object: Final = object_mapping(output_format)
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if output_format_object is None or output_format_object.get("type") != "json_schema":
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return None
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output_type: Final = output_format.get("type")
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if output_type != "json_schema":
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return None
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schema = output_format.get("schema")
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schema: Final = output_format_object.get("schema")
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if not schema:
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return None
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# Deep copy to avoid mutating the original schema
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schema = copy.deepcopy(schema)
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# OpenAI strict mode requires additionalProperties: false on every object
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self._add_additional_properties_false(schema)
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# Convert to OpenAI response_format structure
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return {
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"type": "json_schema",
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"json_schema": {
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"name": "structured_output",
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"schema": schema,
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"schema": openai_strict_json_schema(schema),
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"strict": True,
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},
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}
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@staticmethod
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def _add_additional_properties_false(schema: dict) -> None:
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"""
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Recursively ensure object schemas comply with OpenAI strict mode.
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OpenAI's strict mode requires:
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1. 'additionalProperties': false at every object nesting level
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2. All property keys listed in 'required'
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"""
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if not isinstance(schema, dict):
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return
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if schema.get("type") == "object" and "properties" in schema:
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schema["additionalProperties"] = False
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schema["required"] = list(schema["properties"].keys())
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for prop in schema["properties"].values():
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LiteLLMAnthropicMessagesAdapter._add_additional_properties_false(prop)
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# Handle array items
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if "items" in schema:
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LiteLLMAnthropicMessagesAdapter._add_additional_properties_false(schema["items"])
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# Handle anyOf/oneOf/allOf
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for key in ("anyOf", "oneOf", "allOf"):
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if key in schema:
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for sub_schema in schema[key]:
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LiteLLMAnthropicMessagesAdapter._add_additional_properties_false(sub_schema)
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# Handle $defs / definitions
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for key in ("$defs", "definitions"):
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if key in schema:
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for def_schema in schema[key].values():
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LiteLLMAnthropicMessagesAdapter._add_additional_properties_false(def_schema)
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def _translate_midturn_system_message_to_openai(
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self,
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message: AnthropicMessagesSystemMessageParam,
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@ -35,6 +35,8 @@ from litellm.llms.anthropic.messages.native.utils import (
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from litellm.llms.anthropic.messages.utils import (
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is_reasoning_auto_summary_enabled,
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json_copy_or_original,
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object_mapping,
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openai_strict_json_schema,
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prompt_cache_key_from_user_id,
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)
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from litellm.types.llms.anthropic import (
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@ -588,10 +590,8 @@ class LiteLLMAnthropicToResponsesAPIAdapter:
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)
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@staticmethod
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def _resolve_output_format_strict(strict: bool | None) -> bool:
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if strict is None:
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return True
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return strict
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def _resolve_output_format_strict(strict: object) -> bool:
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return True if strict is None else bool(strict)
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def translate_request(
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self,
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@ -690,19 +690,23 @@ class LiteLLMAnthropicToResponsesAPIAdapter:
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# output_format / output_config.format -> text format
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# output_format: {"type": "json_schema", "schema": {...}}
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# output_config: {"format": {"type": "json_schema", "schema": {...}}}
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output_format: object = anthropic_request.get("output_format")
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output_config = anthropic_request.get("output_config")
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if not isinstance(output_format, dict) and isinstance(output_config, dict):
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output_format = output_config.get("format")
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if isinstance(output_format, dict) and output_format.get("type") == "json_schema":
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output_config_object: Final = object_mapping(anthropic_request.get("output_config"))
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top_level_output_format: Final = object_mapping(anthropic_request.get("output_format"))
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output_format: Final = (
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top_level_output_format
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if top_level_output_format is not None or output_config_object is None
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else object_mapping(output_config_object.get("format"))
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)
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if output_format is not None and output_format.get("type") == "json_schema":
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schema: Final = output_format.get("schema")
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if schema:
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output_strict: Final = self._resolve_output_format_strict(output_format.get("strict"))
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responses_kwargs["text"] = {
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"format": {
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"type": "json_schema",
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"name": "structured_output",
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"schema": schema,
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"strict": self._resolve_output_format_strict(output_format.get("strict")),
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"schema": openai_strict_json_schema(schema) if output_strict else schema,
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"strict": output_strict,
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}
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}
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@ -1,6 +1,7 @@
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import copy
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import json
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import os
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from collections.abc import Mapping
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from collections.abc import Mapping, Sequence
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from types import MappingProxyType
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from typing import TYPE_CHECKING, Final, TypeVar
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@ -37,6 +38,61 @@ def json_copy_or_original(value: _JsonValue) -> _JsonValue:
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return value
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_SUBSCHEMA_LIST_KEYWORDS: Final = ("anyOf", "oneOf", "allOf")
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_SUBSCHEMA_MAP_KEYWORDS: Final = ("$defs", "definitions")
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_JSON_ARRAY: Final = TypeAdapter(list[object])
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def _json_array(value: object) -> Sequence[object] | None:
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try:
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return _JSON_ARRAY.validate_python(value, strict=True)
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except ValidationError:
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return None
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def openai_strict_json_schema(schema: object) -> object:
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"""New copy of a JSON schema where every object with properties forbids extra keys and requires all of them.
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OpenAI strict structured outputs rejects any schema that leaves an object open or a property optional.
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"""
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source: Final = object_mapping(schema)
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if source is None:
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return copy.deepcopy(schema)
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properties: Final = object_mapping(source.get("properties"))
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closing: Final[Mapping[str, object]] = (
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{"required": list(properties), "additionalProperties": False}
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if properties is not None and _is_object_type(source.get("type"))
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else {}
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)
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return {**{key: _strict_subschema(key, value) for key, value in source.items()}, **closing}
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def _is_object_type(schema_type: object) -> bool:
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"""Whether a ``type`` keyword names an object, alone or in a union such as ``["object", "null"]``."""
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types: Final = _json_array(schema_type)
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return schema_type == "object" if types is None else "object" in types
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def _strict_subschema(key: str, value: object) -> object:
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if key == "items":
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return openai_strict_json_schema(value)
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if key == "properties" or key in _SUBSCHEMA_MAP_KEYWORDS:
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named: Final = object_mapping(value)
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return (
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copy.deepcopy(value)
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if named is None
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else {name: openai_strict_json_schema(subschema) for name, subschema in named.items()}
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)
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if key in _SUBSCHEMA_LIST_KEYWORDS:
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variants: Final = _json_array(value)
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return (
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copy.deepcopy(value) if variants is None else [openai_strict_json_schema(variant) for variant in variants]
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)
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return copy.deepcopy(value)
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class _ClaudeCodeUserId(LiteLLMBaseModel):
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"""The JSON Claude Code packs into ``metadata.user_id``; only ``session_id`` is per conversation."""
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@ -136,7 +192,7 @@ def proxy_sub_call_logging_kwargs(parent_kwargs: Mapping[str, object]) -> ProxyS
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if disable_header is None
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else {**parent_params, "proxy_server_request": {"headers": {X_LITELLM_DISABLE_CALLBACKS: disable_header}}}
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)
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trusted_vars: Final = _object_mapping(parent_kwargs.get(TRUSTED_CALLBACK_VARS_FIELD))
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trusted_vars: Final = object_mapping(parent_kwargs.get(TRUSTED_CALLBACK_VARS_FIELD))
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if trusted_vars is None:
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return dynamic_params
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return {**dynamic_params, "litellm_trusted_callback_vars": trusted_vars}
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@ -154,13 +210,13 @@ def proxy_sub_call_trace_id(parent_kwargs: Mapping[str, object]) -> str | None:
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def _disable_callbacks_header(parent_kwargs: Mapping[str, object]) -> str | None:
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parent_request: Final = _object_mapping(parent_kwargs.get("proxy_server_request"))
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headers: Final = _object_mapping(parent_request.get("headers")) if parent_request is not None else None
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parent_request: Final = object_mapping(parent_kwargs.get("proxy_server_request"))
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headers: Final = object_mapping(parent_request.get("headers")) if parent_request is not None else None
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header: Final = headers.get(X_LITELLM_DISABLE_CALLBACKS) if headers is not None else None
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return header if isinstance(header, str) else None
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def _object_mapping(value: object) -> Mapping[str, object] | None:
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def object_mapping(value: object) -> Mapping[str, object] | None:
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try:
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return _OBJECT_MAPPING.validate_python(value)
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except ValidationError:
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@ -3,6 +3,7 @@ Tests for LiteLLMAnthropicToResponsesAPIAdapter
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(litellm/llms/anthropic/messages/responses_adapters/transformation.py)
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"""
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import copy
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import json
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import os
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from collections.abc import Mapping
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@ -217,8 +218,8 @@ class TestOutputConfigStructuredOutput:
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assert kwargs["text"]["format"]["schema"] == self._SCHEMA
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assert kwargs["text"]["format"]["strict"] is False
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def test_optional_property_stays_out_of_required_list(self):
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"""A property absent from required must stay absent from required in the translated schema."""
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def test_optional_property_stays_out_of_required_list_when_not_strict(self):
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"""Without strict, a property absent from required stays absent from required in the translated schema."""
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schema = {
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"type": "object",
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"properties": {
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@ -228,7 +229,7 @@ class TestOutputConfigStructuredOutput:
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"required": ["name"],
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"additionalProperties": False,
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}
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req = _make_request(output_format={"type": "json_schema", "schema": schema})
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req = _make_request(output_format={"type": "json_schema", "schema": schema, "strict": False})
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kwargs = _ADAPTER.translate_request(req)
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fmt_schema = kwargs["text"]["format"]["schema"]
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assert fmt_schema["required"] == ["name"]
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@ -247,6 +248,79 @@ class TestOutputConfigStructuredOutput:
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assert output_format == snapshot
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assert req["output_format"] == snapshot
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@pytest.mark.parametrize("format_field", ("output_format", "output_config"))
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@pytest.mark.parametrize("strict_options", ({}, {"strict": True}))
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def test_strict_schema_closes_every_object_like_messages_to_chat_adapter(
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self,
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format_field: Literal["output_format", "output_config"],
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strict_options: Mapping[str, bool],
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) -> None:
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"""Regression for #51200: strict output schemas must be closed at every nesting level."""
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def open_object(properties: Mapping[str, object], required: list[str]) -> dict[str, object]:
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return {"type": "object", "properties": properties, "required": required, "additionalProperties": True}
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def closed_object(properties: Mapping[str, object]) -> dict[str, object]:
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return {
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"type": "object",
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"properties": properties,
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"required": list(properties),
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"additionalProperties": False,
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}
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schema: Final = {
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**open_object(
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{
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"entry": open_object({"value": {"type": "string"}, "note": {"type": "string"}}, ["value"]),
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"rows": {"type": "array", "items": open_object({"id": {"type": "integer"}}, [])},
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"choice": {"anyOf": [open_object({"a": {"type": "string"}}, []), {"type": "null"}]},
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"ref": {"$ref": "#/$defs/Item"},
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"maybe": {**open_object({"flag": {"type": "boolean"}}, []), "type": ["object", "null"]},
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},
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["entry"],
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),
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"$defs": {"Item": open_object({"label": {"type": "string"}}, [])},
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}
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output_format: Final = {"type": "json_schema", "schema": schema, **strict_options}
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snapshot: Final = copy.deepcopy(output_format)
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request: Final = _make_request(
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**{format_field: output_format if format_field == "output_format" else {"format": output_format}}
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)
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expected_schema: Final = {
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**closed_object(
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{
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"entry": closed_object({"value": {"type": "string"}, "note": {"type": "string"}}),
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"rows": {"type": "array", "items": closed_object({"id": {"type": "integer"}})},
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"choice": {"anyOf": [closed_object({"a": {"type": "string"}}), {"type": "null"}]},
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"ref": {"$ref": "#/$defs/Item"},
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"maybe": {**closed_object({"flag": {"type": "boolean"}}), "type": ["object", "null"]},
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}
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),
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"$defs": {"Item": closed_object({"label": {"type": "string"}})},
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}
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translated: Final = _ADAPTER.translate_request(request)
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chat, _ = LiteLLMAnthropicMessagesAdapter().translate_anthropic_to_openai(request)
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assert translated["text"] == {
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"format": {"type": "json_schema", "name": "structured_output", "schema": expected_schema, "strict": True}
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}
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assert chat.get("response_format") == {
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"type": "json_schema",
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"json_schema": {"name": "structured_output", "schema": expected_schema, "strict": True},
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}
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assert output_format == snapshot
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def test_non_strict_schema_is_forwarded_unchanged(self) -> None:
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schema: Final = {
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"type": "object",
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"properties": {"entry": {"type": "object", "properties": {"value": {"type": "string"}}}},
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"additionalProperties": True,
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}
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request: Final = _make_request(output_format={"type": "json_schema", "schema": schema, "strict": False})
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assert _ADAPTER.translate_request(request)["text"]["format"]["schema"] == schema
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# ---------------------------------------------------------------------------
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# translate_messages_to_responses_input
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@ -301,7 +301,14 @@ async def test_anthropic_format_counts_the_structured_output_schema(monkeypatch:
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assert sent == {
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"model": "gpt-4o",
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"input": [{"type": "message", "role": "user", "content": [{"type": "input_text", "text": "Answer in JSON."}]}],
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"text": {"format": {"type": "json_schema", "name": "structured_output", "schema": schema, "strict": True}},
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"text": {
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"format": {
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"type": "json_schema",
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"name": "structured_output",
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"schema": {**schema, "required": ["answer"], "additionalProperties": False},
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"strict": True,
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}
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},
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}
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