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
121 lines
4.4 KiB
Python
121 lines
4.4 KiB
Python
# 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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"""Universal diagnostic agent tool for deep system logs and video inspection."""
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from typing import Any
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from langchain_core.tools import BaseTool
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from pydantic import BaseModel, Field
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from artemis.agents.diagnoser.diagnoser import Diagnoser
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from artemis.context import ArtemisContext
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from artemis.data_engine.trace import trace_langchain_tool
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from artemis.drivers.base import BaseDeviceDriver
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from artemis.graph.state import State
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from artemis.tools.base import ArtemisTool, ToolRegistry
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from artemis.tools.tool_wrapper import ToolWrapper
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from artemis.tools.types import CyFunctionDetector
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from artemis.utils.logger import get_logger
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logger = get_logger(__name__)
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# pylint: disable=too-few-public-methods
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class AskDiagnoserArgs(BaseModel):
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"""Arguments schema for invoking the diagnostic subagent."""
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model_config = {"ignored_types": (CyFunctionDetector,)}
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query: str = Field(
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...,
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description=(
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"The diagnostic query or what you want to investigate. Please"
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" provide a specific, narrow time range if applicable."
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),
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)
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async def _run_diagnoser_logic(
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ctx: ArtemisContext | None,
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state: State | None,
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query: str,
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) -> str:
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logger.info(f"ask_diagnoser tool called with query: {query}")
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if ctx is None:
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return "Error: ArtemisContext is required for Diagnoser."
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agent = Diagnoser(ctx)
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try:
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result = await agent.run(query, state)
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return f"Diagnoser replied:\n{result}"
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except Exception as e: # pylint: disable=broad-exception-caught
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logger.error(f"Failed to run diagnoser: {e}")
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return f"Diagnoser failed: {e}"
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class AskDiagnoserTool(ArtemisTool):
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"""Universal tool for invoking the Diagnoser subagent to inspect logs and videos."""
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def __init__(self):
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super().__init__(
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name="ask_diagnoser",
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description=(
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"[DIAGNOSTIC] Analyzes system logs (ADB) and video recordings to "
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"pinpoint the root cause of any step failure, screen freeze, or "
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"unexpected UI drift, and directly executes adb commands. Call this "
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"tool proactively whenever an action fails, status stagnates, or you "
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"are unsure why progress is blocked, to diagnose the issue before "
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"committing to physical actions. Note: When querying video files, "
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"specify a narrow timeframe (e.g., '[10s, 20s]') for faster analysis."
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),
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args_schema=AskDiagnoserArgs,
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category="custom",
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)
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# pylint: disable=too-many-arguments,too-many-positional-arguments
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async def execute(
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self,
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driver: BaseDeviceDriver | None = None, # pylint: disable=unused-argument
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ctx: ArtemisContext | None = None,
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query: str | None = None,
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state: State | None = None,
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**kwargs: Any,
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) -> str:
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q = query or kwargs.get("Query") or ""
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st = state if state is not None else kwargs.get("state")
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return await _run_diagnoser_logic(ctx, st, q)
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# Universal tool instance & aliases
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ask_diagnoser = AskDiagnoserTool()
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AskDiagnoser = AskDiagnoserTool
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DiagnosticTool = AskDiagnoserTool
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ToolRegistry.register(ask_diagnoser)
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def get_ask_diagnostic_agent_tool(ctx: ArtemisContext) -> BaseTool:
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"""Exports ask_diagnoser as a LangChain BaseTool."""
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return trace_langchain_tool(ask_diagnoser.to_langchain_tool(ctx), ctx)
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def get_ask_diagnoser_tool(ctx: ArtemisContext) -> BaseTool:
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"""Exports ask_diagnoser as a LangChain BaseTool (standard naming alias)."""
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return trace_langchain_tool(ask_diagnoser.to_langchain_tool(ctx), ctx)
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ask_diagnoser_wrapper = ToolWrapper(
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tool_fn_getter=get_ask_diagnostic_agent_tool,
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on_success_fn=lambda output: f"Diagnoser replied:\n{output}",
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on_failure_fn=lambda error: f"Diagnoser failed: {error}",
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)
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