fix(dspy): store tool argument defaults in JSON form (#10574)

* fix(dspy): store tool argument defaults in JSON form

Tool put each parameter's default into its JSON schema as the raw Python
object. An Enum or date default then broke native function calling with
"Object of type Unit is not JSON serializable" when the schema was sent
to the provider. Convert defaults with pydantic's JSON conversion, and
keep the raw value when it has no JSON form.

* fix(dspy): keep tool defaults that have no JSON form

A non-UTF-8 bytes default made Tool() raise UnicodeDecodeError, and a
Decimal default on a float argument was advertised as a string that the
tool then rejected. Keep the raw value for Decimal and for any default
that fails to convert.

* fix(dspy): store Decimal tool defaults as JSON numbers

A Decimal default stayed a Decimal in the schema, so serializing the tool
for the request still raised TypeError. A float fits both float and
Decimal arguments.

Author: jayhemnani9910

dspy/adapters/types/tool.py

@@ -1,9 +1,11 @@
 import asyncio
 import inspect
+from decimal import Decimal
 from typing import TYPE_CHECKING, Any, Callable, Literal, Protocol, get_origin, get_type_hints
 
 import json_repair
 import pydantic
+import pydantic_core
 from jsonschema import ValidationError, validate
 from pydantic import BaseModel, TypeAdapter, create_model
 
@@ -111,7 +113,7 @@ def _parse_function(self, func: Callable, arg_desc: dict[str, str] | None = None
             else:
                 args[k] = _resolve_json_schema_reference(TypeAdapter(v).json_schema())
             if default_values[k] is not inspect.Parameter.empty:
-                args[k]["default"] = default_values[k]
+                args[k]["default"] = _to_json_default(default_values[k])
             if arg_desc and k in arg_desc:
                 args[k]["description"] = arg_desc[k]
 
@@ -520,6 +522,17 @@ def _normalize_tool_call_dict(data: dict[str, Any]) -> dict[str, Any]:
     }
 
 
+def _to_json_default(value: Any) -> Any:
+    """Convert a parameter default to its JSON form, e.g. an Enum member to its value."""
+    if isinstance(value, Decimal):
+        # A JSON number fits both float and Decimal arguments; pydantic would give a string.
+        return float(value)
+    try:
+        return pydantic_core.to_jsonable_python(value)
+    except Exception:
+        return value
+
+
 def _resolve_json_schema_reference(schema: dict) -> dict:
     """Recursively resolve json model schema, expanding all references."""
 

tests/adapters/test_tool.py

@@ -146,6 +146,42 @@ def test_tool_from_function():
     assert tool.args["y"]["default"] == "hello"
 
 
+def test_tool_defaults_are_json_serializable():
+    import datetime
+    import enum
+    import json
+    from decimal import Decimal
+
+    class Unit(enum.Enum):
+        CELSIUS = "celsius"
+        FAHRENHEIT = "fahrenheit"
+
+    def forecast(
+        city: str,
+        unit: Unit = Unit.CELSIUS,
+        start: datetime.date = datetime.date(2026, 1, 2),
+        price: Decimal = Decimal("1.5"),
+        factor: float = Decimal("0.1"),
+    ) -> str:
+        return city
+
+    tool = Tool(forecast)
+    assert tool.args["unit"]["default"] == "celsius"
+    assert tool.args["start"]["default"] == "2026-01-02"
+    assert tool.args["price"]["default"] == 1.5
+    assert tool.args["factor"]["default"] == 0.1
+    assert tool(city="x", price=tool.args["price"]["default"], factor=tool.args["factor"]["default"]) == "x"
+    json.dumps(tool.format_as_litellm_function_call())
+
+
+def test_tool_defaults_without_json_form_are_kept():
+    def scale(data: bytes = b"\xff") -> str:
+        return "ok"
+
+    tool = Tool(scale)
+    assert tool.args["data"]["default"] == b"\xff"
+
+
 def test_format_as_litellm_function_call_excludes_defaulted_args_from_required():
     # `x` has no default and must be required; `y` has a default and must be optional.
     tool = Tool(dummy_function)