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
139 lines
4.8 KiB
Python
139 lines
4.8 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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from datetime import datetime, timedelta
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import time
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from artemis.context import ArtemisContext
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from artemis.controllers.platform_specific_commands_controller import get_adb_device
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from artemis.utils.logger import get_logger
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logger = get_logger(__name__)
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def parse_log_time(time_str: str) -> datetime:
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"""Parses a log timestamp string into a datetime object."""
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now = datetime.now()
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current_year = now.year
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def _try_parse(year: int) -> datetime | None:
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for fmt in ("%Y-%m-%d %H:%M:%S.%f", "%Y-%m-%d %H:%M:%S"):
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try:
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return datetime.strptime(f"{year}-{time_str}", fmt)
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except ValueError:
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pass
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return None
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dt = _try_parse(current_year)
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if dt is None:
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raise ValueError(f"Unsupported time format: {time_str}")
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# If parsed time is in the future (allowing 1 hour grace for clock drift),
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# we assume it belongs to the previous year.
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if dt > now + timedelta(hours=1):
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prev_dt = _try_parse(current_year - 1)
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if prev_dt is not None:
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dt = prev_dt
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return dt
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def resolve_time(
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time_input: str | float | None, session_start: float | None
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) -> tuple[str | None, datetime | None]:
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"""Resolves relative or absolute time input into formatted string and datetime."""
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if time_input is None:
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return None, None
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if isinstance(time_input, (int, float)) or (
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isinstance(time_input, str) and time_input.replace(".", "", 1).isdigit()
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):
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# It's relative seconds
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if session_start is None:
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raise ValueError("Cannot resolve relative time without session start time.")
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rel_sec = float(time_input)
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abs_ts = session_start + rel_sec
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t_struct = time.localtime(abs_ts)
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t_str = time.strftime("%m-%d %H:%M:%S", t_struct)
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ms = int((abs_ts - int(abs_ts)) * 1000)
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formatted_str = f"{t_str}.{ms:03d}"
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dt = datetime.fromtimestamp(abs_ts)
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return formatted_str, dt
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# Assume it's absolute time string "MM-DD HH:MM:SS.ms"
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try:
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dt = parse_log_time(str(time_input))
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except ValueError as e:
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raise ValueError(f"Unsupported time format: {time_input}") from e
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return str(time_input), dt
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# pylint: disable=too-many-locals
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def fetch_and_filter_logs(
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ctx: ArtemisContext,
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lines: int = 1000,
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since_time: str | None = None,
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until_time: str | None = None,
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) -> str:
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"""Fetches logs from ADB device and filters them by time if needed."""
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device = get_adb_device(ctx)
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session_start = ctx.data_engine.session_start_time if ctx.data_engine else None
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since_str, since_dt = resolve_time(since_time, session_start)
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_, until_dt = resolve_time(until_time, session_start)
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if since_str:
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try:
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logger.info(f"Attempting to fetch logs since {since_str}...")
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logs = device.shell(f'logcat -v threadtime -t "{since_str}"')
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except Exception as e: # pylint: disable=broad-exception-caught
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logger.warning(
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f"Failed to fetch logs since time directly: {e}. Falling back"
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" to reading lines and filtering."
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)
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logs = device.shell(f"logcat -v threadtime -t {lines}")
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else:
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logger.info(f"Reading last {lines} lines of logs...")
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logs = device.shell(f"logcat -v threadtime -t {lines}")
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if since_dt or until_dt:
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filtered_lines = []
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for line in logs.splitlines():
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if len(line) >= 18:
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log_time_str = line[:18]
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try:
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log_dt = parse_log_time(log_time_str)
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if since_dt and log_dt < since_dt:
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continue
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if until_dt and log_dt > until_dt:
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continue
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filtered_lines.append(line)
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except ValueError:
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pass
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# Cap to the requested line limit so timestamp fetches don't overflow context
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if 0 < lines < len(filtered_lines):
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filtered_lines = filtered_lines[-lines:]
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logs = "\n".join(filtered_lines)
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else:
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# Ensure fallback capping even when no datetime parsing occurred
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log_lines = logs.splitlines()
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if 0 < lines < len(log_lines):
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logs = "\n".join(log_lines[-lines:])
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return logs
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