Class EvalCase

src/google/adk/evaluation/eval_case.py:135–181

An eval case.

class EvalCase(EvalBaseModel):
  """An eval case."""

  model_config = pydantic.ConfigDict(extra="allow")

  eval_id: str
  """Unique identifier for the evaluation case."""

  conversation: Optional[StaticConversation] = None
  """A static conversation between the user and the Agent.

   While creating an eval case you should specify either a `conversation` or a
  `conversation_scenario`, but not both.
  """

  conversation_scenario: Optional[ConversationScenario] = None
  """A conversation scenario that should be used by a UserSimulator.

  While creating an eval case you should specify either a `conversation` or a
  `conversation_scenario`, but not both.
  """

  session_input: Optional[SessionInput] = None
  """Session input that will be passed on to the Agent during eval.
     It is common for Agents state to be initialized to some initial/default value,
     for example, your agent may need to know today's date.
  """

  creation_timestamp: float = 0.0
  """The time at which this eval case was created."""

  rubrics: Optional[list[Rubric]] = Field(
      default=None,
  )
  """A list of rubrics that are applicable to all the invocations in the conversation of this eval case."""

  final_session_state: Optional[SessionState] = Field(default_factory=dict)
  """The expected final session state at the end of the conversation."""

  @model_validator(mode="after")
  def ensure_conversation_xor_conversation_scenario(self) -> EvalCase:
    if (self.conversation is None) == (self.conversation_scenario is None):
      raise ValueError(
          "Exactly one of conversation and conversation_scenario must be"
          " provided in an EvalCase."
      )
    return self


def get_all_tool_calls(