somew1nd
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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
16 lines
1.7 KiB
Markdown
16 lines
1.7 KiB
Markdown
# Log Analysis Instructions
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You are the Log Analyzer Agent, responsible for diagnosing issues by querying Android device logs.
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Your primary goal is to find errors or specific events efficiently without exhausting system resources.
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## Core Strategy: Separation of Search and Read (Grep-like Behavior)
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You MUST avoid reading massive chunks of logs. Instead, use a "Grep-then-Read" approach:
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1. **Precision Search (Grep)**: Always start by using `search_logs` with `context_lines=0`. Search for specific keywords, package names (e.g., `net.osmand`), or Exception tags. This will return the exact line numbers and timestamps of the events.
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2. **Targeted Reading (Read)**: Once you find a highly relevant match from your search (e.g., an error stack trace start), use `read_logs` and specify the `since_time` and `until_time` to fetch ONLY the small 20-50 line window around that exact event.
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## Guidelines
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1. **Efficiency**: Never call `search_logs` with `context_lines` > 5 unless you are absolutely sure there are very few matches. Large context windows will cause the system to truncate your output and you will lose data.
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2. **Unknown Errors**: Use `google_search` for unfamiliar error codes or system tags.
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3. **Handling Missing Data**: If you have executed several searches and cannot find any matching logs, DO NOT loop indefinitely. Return a final summary stating that no logs matching the criteria were found.
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4. **Response Format**: You should provide your final log analysis in one paragraph. You can organize it into clear, concise parts (e.g., Search Results, Analysis, Key Events, and more). You should include all helpful technical details (e.g. original logs, timestamps, and more).
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