somew1nd
206a9ce921
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
119 lines
4.4 KiB
Python
119 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 Context Compressor for Artemis Flash profile.
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Replaces pruned historical screenshots with high-density visual step summaries
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when ready, while seamlessly falling back to standard pruned action text if
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the background summary is still in flight.
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"""
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from typing import Any
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from langchain_core.messages import BaseMessage
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from artemis.agents.flash.summarizer import VisualStepSummarizer
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from artemis.utils.logger import get_logger
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logger = get_logger(__name__)
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def compress_flash_messages(
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messages: list[BaseMessage],
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summarizer: VisualStepSummarizer | None = None,
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prune_history_xml: bool = True,
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) -> None:
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"""Compresses multi-turn conversation messages in-place.
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Rules:
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1. Keeps the latest screenshot and live UI hierarchy completely intact.
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2. For earlier steps, if a VisualStepSummarizer has completed the step's summary,
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replaces the intermediate image block with the objective summary text.
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3. If the background summary is not ready yet, gracefully falls back to the existing
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behavior (omitting the image block and retaining the original action text).
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4. If prune_history_xml is True, removes heavy outdated UI Element lists from past turns.
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"""
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if not messages:
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return
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# 1. Identify the last message containing an active screenshot
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last_img_msg_idx = -1
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for idx in range(len(messages) - 1, -1, -1):
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msg = messages[idx]
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msg_content = getattr(msg, "content", None)
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if isinstance(msg_content, list):
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has_image = any(
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isinstance(block, dict) and block.get("type") in ("image_url", "image")
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for block in msg_content
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)
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if has_image:
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last_img_msg_idx = idx
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break
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# 2. Iterate through historical messages and apply compression/fallback
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tool_step_counter = 0
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for idx in range(len(messages)):
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msg = messages[idx]
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msg_content = getattr(msg, "content", None)
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if not isinstance(msg_content, list):
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continue
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# Keep the latest live screen intact
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if idx == last_img_msg_idx:
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continue
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# Count tool steps strictly corresponding to FlashRunner action turns
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is_tool_msg = getattr(msg, "tool_call_id", None) is not None
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if is_tool_msg:
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tool_step_counter += 1
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current_step_num = tool_step_counter
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else:
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current_step_num = None
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new_blocks: list[dict[str, Any]] = []
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summary_injected = False
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for b in msg_content:
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if not isinstance(b, dict):
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continue
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b_type = b.get("type", "")
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b_text = b.get("text", "")
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# Filter heavy outdated XML hierarchy from past steps to save tokens
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if prune_history_xml and b_type == "text" and "--- UI Element List ---" in b_text:
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continue
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if b_type in ("image_url", "image"):
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# Check if this is a tool execution step and background summarizer has a ready summary
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if (
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current_step_num
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and summarizer
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and summarizer.has_summary(current_step_num)
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and not summary_injected
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):
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summary_text = summarizer.get_summary(current_step_num)
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if summary_text:
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new_blocks.append({"type": "text", "text": summary_text})
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summary_injected = True
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# If summarizer is not ready or initial screen, gracefully omit the image block
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continue
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new_blocks.append(b)
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# Defensive fallback: never leave ToolMessage or HumanMessage content empty
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if not new_blocks:
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new_blocks = [{"type": "text", "text": "Action completed." if is_tool_msg else ""}]
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msg.content = new_blocks
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