5 Commits
Author SHA1 Message Date
somew1nd 371aa6df56 fix: complete README and relevant file headers per Apache 2.0 requirements 2026-09-11 19:59:56 -07:00
yaoyao-open-source 1d82d59ec8 Revert "refactor: clean up legacy code, rename hopper to entity_extractor, and add third-party notices"
This reverts commit 54fcef9887.

Please do not submit unrelated docs and codes in the same commit. I am reverting this commit so that the related files can be submitted in better-organized future commits.
2026-09-11 19:32:22 -07:00
somew1nd 54fcef9887 refactor: clean up legacy code, rename hopper to entity_extractor, and add third-party notices
- Add NOTICE file and README license references for mobile-use and finalrun-agent
- Add derivative attribution headers to 17 files derived from mobile-use
- Rename hopper agent to entity_extractor across prompts, tools, and configs
- Remove obsolete adb_tunnel, ApiBaseUrl, and legacy CLI utility scripts
- Replace legacy examples with native Artemis diagnostic and workflow examples
- Update unit and tool tests to validate entity_extractor and SDK builders
2026-09-11 16:19:42 -07:00
somew1nd e984d17635 fix: isolate subprocess stdin and decouple startup to prevent MCP stdio deadlocks
- Set stdin=subprocess.DEVNULL across runtime, client, and utility subprocess calls to avoid hijacking the parent process's stdin.
- Run awake service initialization asynchronously on a daemon thread in MCP server startup.
- Redirect logger header printing to stderr to ensure stdio JSON-RPC purity.
- Add unit and lifecycle tests for MCP stdio protocol handshake and stdin isolation.
2026-08-26 23:26:10 -07:00
somew1nd 206a9ce921 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
2026-08-13 11:46:47 -07:00