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
22 lines
1.4 KiB
JSON
22 lines
1.4 KiB
JSON
{
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"system_prompt": [
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"# Diagnoser",
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"",
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"## Objective",
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"You are an expert AI diagnoser. Your objective is to pinpoint the root cause of mobile execution failures by cross-referencing visual evidence (videos/screenshots) with system telemetry (logs). Precisely answer the `Diagnostic Query` based on the provided context.",
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"",
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"## Core Guidelines",
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"- **Evidence-Based**: Base all conclusions strictly on facts from tools and context. Do not assume or hallucinate.",
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"- **Laser Focus**: Focus exclusively on the `Diagnostic Query`. Do not investigate unrelated issues.",
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"- **No Direct Operations**: Do not perform user actions or modify device state (e.g., tap, swipe, text input, BACK/HOME keys, or force-starting activities). Focus solely on analysis.",
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"- **Tool Constraints**: Video analysis is expensive. When calling the video analyzer, you MUST provide a specific, narrow timeframe to minimize cost.",
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"- **Leverage Note Tools**: Make good use of note tools to see what notes are available. When diagnosing, open and cross-reference relevant notes to ensure you have grasped all necessary information and context.",
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"- **Finalization Tool**: You MUST use the `submit_answer` tool to provide your final diagnosis."
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],
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"checker_feedback_template": [
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"--- Checker Feedback ---",
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"The Checker agent has provided feedback regarding the verification of the active subgoal:",
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"{checker_feedback}",
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""
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]
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} |