refactor: clean up legacy code, rename hopper to entity_extractor, and add third-party notices
- Add NOTICE file and README license references for mobile-use and finalrun-agent - Add derivative attribution headers to 17 files derived from mobile-use - Rename hopper agent to entity_extractor across prompts, tools, and configs - Remove obsolete adb_tunnel, ApiBaseUrl, and legacy CLI utility scripts - Replace legacy examples with native Artemis diagnostic and workflow examples - Update unit and tool tests to validate entity_extractor and SDK builders
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@@ -11,123 +11,71 @@
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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#
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# Portions of this file are derived from mobile-use (https://github.com/minitap-ai/mobile-use)
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# Copyright 2025-2026 Minitap, Inc. Licensed under the Apache License 2.0.
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"""Builder for TaskRequest objects using a fluent interface."""
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"""Fluent specification builders for ARTEMIS automation task requests.
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Provides type-safe configuration chaining for task objectives, execution bounds,
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device sandboxing constraints, and structured schema validations.
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"""
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from __future__ import annotations
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from pathlib import Path
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from typing import Generic, TypeVar, cast
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from typing import Generic, Self, TypeVar, cast
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try:
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from typing import Self
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except ImportError:
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from typing import Self
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from pydantic import BaseModel
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from artemis.constants import RECURSION_LIMIT
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from artemis.sdk.types.agent import AgentProfile
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from artemis.sdk.types.task import TaskRequest, TaskRequestCommon
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from pydantic import BaseModel
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TIn = TypeVar("TIn", bound=BaseModel | None)
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TOut = TypeVar("TOut", bound=BaseModel)
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class _CyFunctionDetectorMeta(type):
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def __instancecheck__(self, instance):
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name = type(instance).__name__
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return (
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name
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in (
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"cyfunction",
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"cython_function_or_method",
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"builtin_function_or_method",
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)
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or "cyfunction" in name.lower()
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)
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class TaskRequestCommonBuilder:
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"""Configurator for common execution bounds and sandbox constraints."""
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class CyFunctionDetector(metaclass=_CyFunctionDetectorMeta):
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pass
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class TaskRequestCommonBuilder(BaseModel):
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"""Builder class providing a fluent interface for creating TaskRequestCommon objects."""
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model_config = {"ignored_types": (CyFunctionDetector,)}
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def __init__(self):
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self._max_steps = RECURSION_LIMIT
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self._record_trace = True
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self._trace_path = Path("traces")
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def __init__(self) -> None:
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self._max_steps: int = RECURSION_LIMIT
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self._record_trace: bool = True
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self._trace_path: Path = Path("traces")
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self._llm_output_path: Path | None = None
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self._locked_app_package: str | None = None
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self._app_path: Path | None = None
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def with_max_steps(self, max_steps: int) -> Self:
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"""Set the maximum number of steps the task can take.
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Args:
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max_steps: Maximum number of steps
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"""
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"""Constrain the maximum interaction turns allowed."""
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self._max_steps = max_steps
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return self
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def with_trace_recording(self, enabled: bool = True, path: str | None = None) -> Self:
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"""Configure trace recording for the task.
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Traces record screenshots and actions during execution.
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Args:
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enabled: Whether to enable trace recording
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path: Directory path where traces should be saved
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"""
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def with_trace_recording(self, enabled: bool = True, path: str | Path | None = None) -> Self:
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"""Toggle telemetry snapshot capture and set output storage directory."""
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self._record_trace = enabled
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if enabled and path:
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self._trace_path = Path(path)
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return self
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def with_llm_output_saving(self, path: str) -> Self:
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"""Configure LLM output saving for the task.
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Args:
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path: Path where to save the LLM output message
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"""
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def with_llm_output_saving(self, path: str | Path) -> Self:
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"""Designate destination path for persisting raw reasoning payloads."""
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self._llm_output_path = Path(path)
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return self
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def with_locked_app_package(self, package_name: str) -> Self:
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"""Set the app package to lock execution to.
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This ensures the specified app is launched and in the foreground before
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the agentic loop starts.
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Args:
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package_name: Package name (Android, e.g., 'com.whatsapp')
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"""
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self._locked_app_package = package_name
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"""Bind test execution strictly to the target Android package namespace."""
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self._locked_app_package = package_name.strip()
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return self
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def with_app_path(self, app_path: str | Path) -> Self:
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"""Set the path to an app to install before running the task.
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For Android: Path to an APK file.
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The app will be installed automatically before the task starts.
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Args:
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app_path: Path to the app file to install
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"""
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self._app_path = Path(app_path) if isinstance(app_path, str) else app_path
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"""Provide path to local APK for automatic installation prior to run."""
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self._app_path = Path(app_path)
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return self
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def build(self) -> TaskRequestCommon:
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"""Build the TaskRequestCommon object.
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Returns:
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A configured TaskRequestCommon object
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Raises:
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ValueError: If required fields are missing
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"""
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"""Materialize configured constraints into a TaskRequestCommon contract."""
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return TaskRequestCommon(
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max_steps=self._max_steps,
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record_trace=self._record_trace,
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@@ -139,110 +87,66 @@ class TaskRequestCommonBuilder(BaseModel):
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class TaskRequestBuilder(TaskRequestCommonBuilder, Generic[TIn]):
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"""Builder class providing a fluent interface for creating TaskRequest objects.
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"""Fluent configurator constructing immutable TaskRequest specifications."""
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This builder allows for step-by-step construction of a TaskRequest with
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clear methods that make the configuration process intuitive and type-safe.
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Examples:
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>>> builder = TaskRequestBuilder[None](goal="Open Gmail and check unread
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emails")
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>>> task_request = (
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... builder
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... .with_max_steps(30)
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... .using_profile("LowReasoning")
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... .with_output_description("A list of email subjects and senders")
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... .build()
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... )
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"""
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model_config = {"ignored_types": (CyFunctionDetector,)}
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def __init__(self, goal: str):
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"""Initialize an empty TaskRequestBuilder."""
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def __init__(self, goal: str) -> None:
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super().__init__()
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self._goal = goal
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self._goal: str = goal
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self._profile: str | AgentProfile | None = None
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self._name: str | None = None
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self._output_description = None
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self._output_description: str | None = None
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self._output_format: type[TIn] | None = None
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@classmethod
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def from_common(cls, goal: str, common: TaskRequestCommon):
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res = cls(goal=goal)
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res._max_steps = common.max_steps
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res._record_trace = common.record_trace
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res._trace_path = common.trace_path
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res._llm_output_path = common.llm_output_path
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res._locked_app_package = common.locked_app_package
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res._app_path = common.app_path
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return res
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def from_common(cls, goal: str, common: TaskRequestCommon) -> TaskRequestBuilder[None]:
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"""Derive a new task builder initialized with existing environment constraints."""
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builder = TaskRequestBuilder[None](goal=goal)
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builder._max_steps = common.max_steps
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builder._record_trace = common.record_trace
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builder._trace_path = common.trace_path
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builder._llm_output_path = common.llm_output_path
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builder._locked_app_package = common.locked_app_package
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builder._app_path = common.app_path
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return builder
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def using_profile(self, profile: str | AgentProfile) -> "TaskRequestBuilder[TIn]":
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"""Set the agent profile for executing the task.
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Args:
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profile: The agent profile to use
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"""
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def using_profile(self, profile: str | AgentProfile) -> Self:
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"""Select execution profile (e.g., 'flash', 'pro', or custom AgentProfile)."""
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self._profile = profile
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return self
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def with_name(self, name: str) -> "TaskRequestBuilder[TIn]":
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"""Set the name of the task - useful when recording traces.
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Otherwise, a random name will be generated.
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Args:
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name: Name of the task
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"""
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self._name = name
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def with_name(self, name: str) -> Self:
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"""Assign human-readable identifier to this test task."""
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self._name = name.strip()
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return self
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def without_llm_output_saving(self) -> Self:
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"""Disable LLM output saving for the task."""
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"""Omit persisting standalone model reasoning outputs."""
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self._llm_output_path = None
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return self
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def with_output_description(self, description: str) -> "TaskRequestBuilder[TIn]":
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"""Set the description of the expected output format.
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This is especially useful for data extraction tasks.
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Args:
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description: Description of the expected output format
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"""
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def with_output_description(self, description: str) -> Self:
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"""Supply natural language extraction instructions for unformatted deliverables."""
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self._output_description = description
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return self
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def with_output_format(self, output_format: type[TOut]) -> "TaskRequestBuilder[TOut]":
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"""Set the pydantic model for the expected output format.
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Args:
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output_format: Pydantic model instance defining the output format
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"""
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self._output_format = output_format # type: ignore
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def with_output_format(self, output_format: type[TOut]) -> TaskRequestBuilder[TOut]:
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"""Bind output schema to a structured Pydantic model class."""
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self._output_format = cast(type[TIn], output_format)
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return cast(TaskRequestBuilder[TOut], self)
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def build(self) -> TaskRequest[TIn]:
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"""Build the TaskRequest object.
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"""Validate criteria and construct final TaskRequest instance."""
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if not self._goal or not self._goal.strip():
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raise ValueError("Task goal must be a non-empty natural language objective.")
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Returns:
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A configured TaskRequest object
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if self._output_format is not None and self._output_description is not None:
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raise ValueError("Cannot specify both output_format and output_description simultaneously.")
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Raises:
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ValueError: If required fields are missing
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"""
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if not self._goal:
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raise ValueError("Task goal is required")
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profile_name = self._profile.name if isinstance(self._profile, AgentProfile) else self._profile
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if self._output_format and self._output_description:
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raise ValueError("Output format and description are mutually exclusive")
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task_request = TaskRequest(
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goal=self._goal,
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profile=self._profile.name
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if isinstance(self._profile, AgentProfile)
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else self._profile,
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return TaskRequest(
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goal=self._goal.strip(),
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profile=profile_name,
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task_name=self._name,
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output_description=self._output_description,
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output_format=self._output_format,
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@@ -253,4 +157,3 @@ class TaskRequestBuilder(TaskRequestCommonBuilder, Generic[TIn]):
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locked_app_package=self._locked_app_package,
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app_path=self._app_path,
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)
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return task_request
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