fix(tools): accept dict output_schema in SetModelResponseTool (#5469)

[MukundaKatta]

Summary

Fixes #5469. When output_schema is a raw dict (e.g. {"type": "object", "properties": {...}}), SetModelResponseTool.__init__ previously fell through to the generic else branch and used the dict instance as the parameter annotation. Downstream, _function_parameter_parse_util._is_builtin_primitive_or_compound does annotation in _py_builtin_type_to_schema_type.keys(), which calls __hash__ on the annotation and raises TypeError: unhashable type: 'dict'.

This change adds an explicit elif isinstance(output_schema, dict) branch that uses the dict type (hashable) as the annotation, so the existing builtin lookup maps it to Type.OBJECT cleanly. run_async already handles this case via the existing args.get('response') pass-through.

Reproduction (before fix)

from google.adk.agents import Agent

agent = Agent(
    name="test",
    model="gemini-2.5-flash",
    instruction="You are a helpful agent.",
    output_schema={"type": "object", "properties": {"result": {"type": "string"}}},
)
# -> TypeError: unhashable type: 'dict'

Testing plan

• Added regression unit tests in tests/unittests/tools/test_set_model_response_tool.py:
  • test_tool_initialization_raw_dict_schema — __init__ with a raw dict does not crash and stores the schema.
  • test_function_signature_generation_raw_dict_schema — generated signature has a single response: dict parameter (annotation is the dict type, not the dict instance).
  • test_get_declaration_raw_dict_schema — _get_declaration() returns a valid declaration without raising TypeError.
  • test_run_async_raw_dict_schema — run_async returns the response unchanged.
• Run: pytest tests/unittests/tools/test_set_model_response_tool.py -q
• Existing tests for BaseModel, list[BaseModel], list[str], dict[str, int] schemas remain unchanged and still pass.

Notes

• Schema fidelity (propagating dict-schema constraints into the function declaration) is intentionally out of scope; this PR only fixes the crash, matching the issue's reported scope and the existing handling for list[str] / dict[str, int].

[rohityan]

Hi @MukundaKatta , Thank you for your contribution! We appreciate you taking the time to submit this pull request. Your PR has been received by the team and is currently under review. We will provide feedback as soon as we have an update to share.

[rohityan]

Hi @Jacksunwei , can you please review this.