FunctionTool schema missing required fields for Pydantic BaseModel parameters #4777
Description
Describe the Bug:
When a FunctionTool accepts a Pydantic BaseModel parameter, the generated function declaration schema does not populate the nested model schema’s required field. As a result, the LLM may treat required model fields as optional and omit them when invoking the tool.
When this happens, model_validate(...) fails internally, but the exception is silently caught. The tool is still invoked with the original raw dict instead of the expected model instance. This defers the failure to the tool implementation, where it may later surface as a downstream runtime error.
Steps to Reproduce:
Create a script with following repro and run it
from pydantic import BaseModel
from google.adk.tools.function_tool import FunctionTool
class SearchRequest(BaseModel):
query: str # required
max_results: int # required
filter: str = "" # optional (has default)
def search(request: SearchRequest) -> list:
"""Search for documents."""
return []
tool = FunctionTool(search)
decl = tool._get_declaration()
inner_schema = decl.parameters.properties["request"]
print("properties:", list(inner_schema.properties.keys()))
print("required: ", inner_schema.required)Expected Behavior:
The generated schema for a BaseModel parameter should include a required field listing all model fields that have no default value. This allows the LLM to correctly identify which fields are mandatory and always include them when invoking the tool.
Observed Behavior:
Running the above script produces the following output:
properties: ['query', 'max_results', 'filter']
required: None
Environment Details:
- ADK Library Version (pip show google-adk): 1.26.0
- Desktop OS : Windows
- Python Version (python -V) : 3.10
How often has this issue occurred?:
- Always (100%)