 somew1nd
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9a5aaf99b7
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feat: introduce MCP server, cross-platform runtime, and Showcase UI reorganization
- Showcase UI Reorganization:
* Move web UI dashboard from root directory into apps/showcase_ui/ for cleaner project structure
* Add 'artemis ui' CLI command (artemis/interfaces/cli/commands/ui.py) and launcher scripts for the interactive showcase console
- Standalone MCP Server & Notifiers (mcp_server/):
* Implement dedicated MCP server package with mobile automation tools (device_state, inspect_trace, task_manager, task_runner)
* Add multi-channel notifiers (AgentAPI, Desktop notifications, Webhooks, File output, and Composite routing)
* Introduce background task runner and trace store for autonomous mobile execution monitoring
- Cross-Platform Runtime & Toolchain Support:
* Add artemis/platform/ with OS-specific implementations for Linux, macOS (Darwin), and Windows
* Add artemis/runtime/supervisor.py for resilient process and agent runtime supervision
* Add artemis/toolchain/ with dependency resolution and SDK descriptors
* Add cross-platform launcher scripts (start.sh, start.bat) and installer scripts (scripts/install_deps.*)
- Core Enhancements & Diagnostics:
* Enhance coordinate normalization, OCR API fallback, and perception pipeline
* Add credential validation (credentials_validator.py) and system diagnostics
* Update bilingual documentation (README.md, README_CN.md) and architecture diagrams
- Test Suite Expansion:
* Add integration tests for cloud gateway, remote ADB, and Artemis login
* Add unit tests covering core diagnostics, platform detection, toolchain, credentials validator, optional OCR, and MCP tools
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2026-08-18 13:59:27 -07:00 |
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somew1nd
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206a9ce921
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feat: initial release of ARTEMIS Android Agent & Automation Platform
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
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2026-08-13 11:46:47 -07:00 |
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