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
65 lines
2.7 KiB
Python
65 lines
2.7 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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"""Telemetry Data Models and Schema Definitions."""
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from enum import Enum
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import time
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from typing import Any
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from uuid import uuid4
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from pydantic import BaseModel, Field
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class SpanType(str, Enum):
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AGENT = "agent"
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LLM_CALL = "llm_call"
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TOOL_EXECUTION = "tool_execution"
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DEVICE_ACTION = "device_action"
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SCREEN_CAPTURE = "screen_capture"
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CUSTOM = "custom"
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class TokenUsage(BaseModel):
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"""LLM token consumption metrics."""
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prompt_tokens: int = Field(default=0, description="Input prompt tokens")
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completion_tokens: int = Field(default=0, description="Output generated tokens")
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total_tokens: int = Field(default=0, description="Total tokens consumed")
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class TelemetrySpan(BaseModel):
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"""Structured telemetry span representing a single unit of agentic execution."""
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span_id: str = Field(default_factory=lambda: str(uuid4()))
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trace_id: str = Field(..., description="Root trace/session identifier")
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parent_id: str | None = Field(default=None, description="Parent span identifier")
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name: str = Field(..., description="Human-readable span operation name")
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type: SpanType = Field(default=SpanType.CUSTOM, description="Span categorization")
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start_time: float = Field(default_factory=time.time, description="Start timestamp")
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end_time: float | None = Field(default=None, description="Completion timestamp")
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duration_ms: float | None = Field(default=None, description="Elapsed execution time in ms")
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status: str = Field(default="running", description="Status ('running', 'success', 'failed')")
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payload: dict[str, Any] = Field(
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default_factory=dict, description="Custom parameters and payloads"
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)
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error: str | None = Field(default=None, description="Exception message if failed")
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token_usage: TokenUsage | None = Field(default=None, description="Token consumption metrics")
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def finish(self, status: str = "success", error: str | None = None) -> None:
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"""Closes the span and calculates duration."""
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self.end_time = time.time()
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self.duration_ms = (self.end_time - self.start_time) * 1000.0
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self.status = status
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self.error = error
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