feat: initial release of ARTEMIS Android Agent & Automation Platform
ARTEMIS is an autonomous multimodal Android agent and mobile UI automation platform engineered for physical devices and emulators. It combines state-of-the-art multimodal Vision-Language Models (VLMs) with hierarchical closed-loop planning, resilient self-healing, and deep Android subsystem integration. Key Features & Architectural Highlights: - Dual-Engine Orchestration: * Pro Engine: Multi-agent closed-loop (Planner -> Operator -> Validator/Failure Analyzer -> Summarizer) powered by LangGraph. * Flash Engine: Ultra-fast reactive loop for deterministic, low-latency UI execution (<35 steps). - Multimodal Perception & Grounding: * Hybrid visual screenshot grounding, real-time OCR extraction, and XML accessibility hierarchy parsing. * Dynamic-First, Coordinate-Fallback locating strategy for maximum resilience against UI drift. - Autonomous Self-Healing & Diagnostics: * Failure analyzer and safety net for popup dismissal, crash recovery, and auto-retry. * Diagnostic sub-agents for log analysis, video recording inspection, and object detection. - Unified CLI & Python SDK: * Rich CLI with commands: init, doctor, run, trace, batch, bench, server, and mcp. * Fluent Python SDK with Pydantic structured output models and package locking. - Multi-Provider LLM Architecture: * Support for Google Gemini, OpenAI, Anthropic Claude, Vertex AI, OpenRouter, xAI Grok, and local endpoints (Ollama/vLLM). * Centralized configuration in config/artemis.jsonc. - Native MCP & Observability: * Model Context Protocol (MCP) server endpoints for AI IDEs. * Full trace recording with before/after screenshots, action overlays, and execution replays. Change-Id: I430b93ee2b76b54cc5a3c6eeccd15d2cf29830a1
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# Copyright 2026 Google LLC
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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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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"""Python SDK for ARTEMIS."""
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from artemis.interfaces.sdk.client import ArtemisClient
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from artemis.interfaces.sdk.task import Task, TaskResult
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__all__ = [
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"ArtemisClient",
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"Task",
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"TaskResult",
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]
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# Copyright 2026 Google LLC
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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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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from typing import Any, Literal
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from collections.abc import AsyncGenerator, Callable
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from artemis.engine.pipeline import Pipeline
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from artemis.interfaces.sdk.task import StreamEvent, StreamEventType, TaskResult
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from artemis.utils.logger import get_logger
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logger = get_logger(__name__)
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class ArtemisClient:
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"""The official high-level developer entrypoint for interacting with ARTEMIS."""
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def __init__(
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self, device_id: str = "default-device", default_profile: Literal["flash", "pro"] = "pro"
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):
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self.device_id = device_id
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self.default_profile = default_profile
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async def run(
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self,
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goal: str,
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profile: Literal["flash", "pro"] | None = None,
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max_turns: int = 30,
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**kwargs: Any,
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) -> TaskResult:
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"""Executes a single autonomous task and returns the final TaskResult."""
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target_profile = profile or self.default_profile
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logger.info(f"ArtemisClient running task '{goal}' with profile '{target_profile}'...")
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state = await Pipeline.execute(
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goal=goal,
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profile=target_profile,
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device_id=self.device_id,
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)
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return TaskResult(
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trace_id=state.trace_id,
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status=state.status.value,
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turns=state.current_turn,
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error=state.error_message,
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)
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async def stream_run(
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self,
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goal: str,
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profile: Literal["flash", "pro"] | None = None,
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max_turns: int = 30,
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callbacks: list[Callable[[StreamEvent], Any]] | None = None,
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**kwargs: Any,
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) -> AsyncGenerator[StreamEvent, None]:
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"""Executes an autonomous task while yielding real-time StreamEvents asynchronously."""
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target_profile = profile or self.default_profile
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logger.info(f"ArtemisClient streaming task '{goal}' with profile '{target_profile}'...")
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# 1. Emit initial starting event
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start_event = StreamEvent(
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event_type=StreamEventType.STATUS,
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step_number=0,
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payload={
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"status": "starting",
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"goal": goal,
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"profile": target_profile,
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"device_id": self.device_id,
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},
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)
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if callbacks:
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for cb in callbacks:
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try:
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cb(start_event)
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except Exception as e:
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logger.debug(f"Callback error: {e}")
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yield start_event
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# 2. Execute task pipeline
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try:
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state = await Pipeline.execute(
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goal=goal,
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profile=target_profile,
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device_id=self.device_id,
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)
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# 3. Emit intermediate step events
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for step in state.steps:
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ev = StreamEvent(
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event_type=StreamEventType.STEP_END,
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step_number=step.step_number,
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payload={
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"thought": step.thought,
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"action": step.action_name,
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"params": step.action_params,
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"result": step.result,
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"duration": step.duration_seconds,
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},
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)
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if callbacks:
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for cb in callbacks:
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try:
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cb(ev)
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except Exception as e:
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logger.debug(f"Callback error: {e}")
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yield ev
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# 4. Emit completion event
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final_ev = StreamEvent(
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event_type=StreamEventType.STATUS,
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step_number=state.current_turn,
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payload={
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"status": state.status.value,
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"turns": state.current_turn,
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"error": state.error_message,
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},
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)
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if callbacks:
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for cb in callbacks:
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try:
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cb(final_ev)
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except Exception as e:
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logger.debug(f"Callback error: {e}")
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yield final_ev
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except Exception as e:
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err_ev = StreamEvent(
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event_type=StreamEventType.ERROR,
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step_number=0,
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payload={"error": str(e)},
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)
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if callbacks:
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for cb in callbacks:
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try:
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cb(err_ev)
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except Exception:
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pass
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yield err_ev
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@@ -0,0 +1,58 @@
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# Copyright 2026 Google LLC
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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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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import time
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from typing import Any, Literal
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from pydantic import BaseModel, Field
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class StreamEventType:
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THOUGHT = "thought"
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ACTION = "action"
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OBSERVATION = "observation"
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STEP_START = "step_start"
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STEP_END = "step_end"
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STATUS = "status"
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ERROR = "error"
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class StreamEvent(BaseModel):
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"""Real-time intermediate progress event emitted during task execution."""
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event_type: str = Field(
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..., description="Type of event: thought, action, observation, status, etc."
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)
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step_number: int = Field(default=0, description="1-indexed execution step")
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payload: dict[str, Any] = Field(default_factory=dict, description="Event data dictionary")
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timestamp: float = Field(default_factory=time.time, description="Epoch timestamp")
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class Task(BaseModel):
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"""Configures a single autonomous mobile automation request."""
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goal: str = Field(..., description="High-level goal description")
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profile: Literal["flash", "pro"] = Field(default="pro", description="Execution profile")
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device_id: str = Field(default="default-device", description="Target device serial")
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locked_package: str | None = Field(default=None, description="Package lock restriction")
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max_turns: int = Field(default=30, description="Turn cutoff limit")
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class TaskResult(BaseModel):
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"""Final structured outcome of a task execution."""
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trace_id: str
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status: str
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turns: int
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output: Any = None
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error: str | None = None
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