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fix(anthropic): strip top-level oneOf/allOf/anyOf from tool input_schema
Extends the existing _normalize_tool_input_schema to also drop top-level union keywords that Anthropic's tool schema validator rejects with HTTP 400. Several upstream and plugin tools ship schemas with a top-level oneOf/ allOf/anyOf (common for Pydantic discriminated unions). The existing strip_nullable_unions pass only handles anyOf-with-null patterns; a non-null top-level union keyword sails through and hits the API. Salvage of #16471 — approach folded into the existing normalize helper rather than introducing a parallel _sanitize_input_schema function, to avoid two schema-munging code paths running against the same input. Co-authored-by: Grey0202 <grey0202@users.noreply.github.com>
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@ -1225,6 +1225,14 @@ def _normalize_tool_input_schema(schema: Any) -> Dict[str, Any]:
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``keep_nullable_hint=False`` because the Anthropic validator does not
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recognize the OpenAPI-style ``nullable: true`` extension and strict
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schema-to-grammar converters may reject unknown keywords.
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Top-level ``oneOf``/``allOf``/``anyOf`` are also stripped here: the
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Anthropic API rejects union keywords at the schema root with a generic
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HTTP 400. Several upstream and plugin tools ship schemas with one of
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these keywords at the top level (commonly for Pydantic discriminated
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unions). If we land here with those keywords still present after
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nullable-union stripping, drop them and fall back to a plain object
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schema so the tool still validates at the Anthropic boundary.
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"""
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if not schema:
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return {"type": "object", "properties": {}}
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@ -1234,6 +1242,12 @@ def _normalize_tool_input_schema(schema: Any) -> Dict[str, Any]:
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normalized = strip_nullable_unions(schema, keep_nullable_hint=False)
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if not isinstance(normalized, dict):
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return {"type": "object", "properties": {}}
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# Strip top-level union keywords that Anthropic's validator rejects.
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banned = {"oneOf", "allOf", "anyOf"}
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if banned & normalized.keys():
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normalized = {k: v for k, v in normalized.items() if k not in banned}
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if "type" not in normalized:
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normalized["type"] = "object"
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if normalized.get("type") == "object" and not isinstance(normalized.get("properties"), dict):
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normalized = {**normalized, "properties": {}}
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return normalized
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