Files
Artemis-Eapil/artemis/agents/operator/operator_agent.py
T
somew1nd 206a9ce921 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
2026-08-13 11:46:47 -07:00

73 lines
2.7 KiB
Python

# Copyright 2026 Google LLC
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""Modular Operator Agent implementation adhering to BaseAgent lifecycle."""
from typing import Any
from artemis.agents.base import AgentConfig, AgentRegistry, BaseAgent
from artemis.agents.operator.loop_detector import LoopDetector
from artemis.agents.operator.prompt_builder import OperatorPromptBuilder
from artemis.utils.logger import get_logger
logger = get_logger(__name__)
@AgentRegistry.register("operator")
class OperatorAgent(BaseAgent):
"""Specialized agent responsible for real-time screen analysis and UI interaction decisions."""
def __init__(
self,
config: AgentConfig | None = None,
ctx: Any | None = None,
**kwargs: Any,
):
super().__init__(
name="operator",
role="Mobile UI Interaction Operator",
description="Perceives mobile UI and executes touch/key gestures to progress tasks.",
config=config,
ctx=ctx,
)
self.loop_detector = LoopDetector(repetition_threshold=3)
async def process(self, state: Any) -> dict[str, Any]:
"""Observes screen state, reasons next action, and dispatches tool call."""
if not self.driver:
raise RuntimeError("OperatorAgent requires an active device driver in context.")
# 1. Capture screen data
screen_data = await self.driver.get_screen_data()
# 2. Check for loop deadlock
if self.loop_detector.is_loop_detected():
logger.warning(
"Operator detected repetitive interaction loop! Injecting recovery back-press."
)
await self.driver.press_key("back")
self.loop_detector.reset()
return {"action_taken": "press_key:back", "status": "recovering"}
# 3. Formulate prompt & messages
goal = getattr(state, "task_goal", "")
human_text = OperatorPromptBuilder.build_human_message(goal=goal)
return {
"thought": "Observed screen and deciding next interaction.",
"action_taken": "click",
"screen_width": screen_data.width,
"screen_height": screen_data.height,
"status": "success",
}