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
86 lines
3.1 KiB
Python
86 lines
3.1 KiB
Python
# Copyright 2026 Google LLC
|
|
#
|
|
# Licensed under the Apache License, Version 2.0 (the "License");
|
|
# you may not use this file except in compliance with the License.
|
|
# You may obtain a copy of the License at
|
|
#
|
|
# http://www.apache.org/licenses/LICENSE-2.0
|
|
#
|
|
# Unless required by applicable law or agreed to in writing, software
|
|
# distributed under the License is distributed on an "AS IS" BASIS,
|
|
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
|
# See the License for the specific language governing permissions and
|
|
# limitations under the License.
|
|
|
|
"""Telemetry Tracer and Span Life Cycle Manager."""
|
|
|
|
from contextlib import asynccontextmanager
|
|
from contextvars import ContextVar
|
|
import json
|
|
from pathlib import Path
|
|
from typing import Any
|
|
from collections.abc import AsyncIterator
|
|
from uuid import uuid4
|
|
|
|
from artemis.telemetry.models import SpanType, TelemetrySpan
|
|
from artemis.utils.logger import get_logger
|
|
|
|
logger = get_logger(__name__)
|
|
|
|
CURRENT_TRACE_ID: ContextVar[str] = ContextVar("CURRENT_TRACE_ID", default="global-session")
|
|
CURRENT_PARENT_SPAN_ID: ContextVar[str | None] = ContextVar("CURRENT_PARENT_SPAN_ID", default=None)
|
|
|
|
|
|
class TelemetryTracer:
|
|
"""Central tracer for recording and persisting telemetry spans."""
|
|
|
|
def __init__(self, trace_id: str | None = None, traces_dir: Path | None = None):
|
|
self.trace_id = trace_id or str(uuid4())
|
|
self.traces_dir = traces_dir or Path("traces") / self.trace_id
|
|
self.spans: list[TelemetrySpan] = []
|
|
self._log_file: Path | None = None
|
|
|
|
def _ensure_log_file(self) -> Path:
|
|
if self._log_file is None:
|
|
self.traces_dir.mkdir(parents=True, exist_ok=True)
|
|
self._log_file = self.traces_dir / "telemetry_spans.jsonl"
|
|
return self._log_file
|
|
|
|
def record_span(self, span: TelemetrySpan) -> None:
|
|
"""Appends and persists completed span."""
|
|
self.spans.append(span)
|
|
try:
|
|
log_file = self._ensure_log_file()
|
|
with open(log_file, "a", encoding="utf-8") as f:
|
|
f.write(json.dumps(span.model_dump(), ensure_ascii=False) + "\n")
|
|
except Exception as e:
|
|
logger.warning(f"Failed to persist telemetry span {span.span_id}: {e}")
|
|
|
|
@asynccontextmanager
|
|
async def start_span(
|
|
self,
|
|
name: str,
|
|
span_type: SpanType = SpanType.CUSTOM,
|
|
payload: dict[str, Any] | None = None,
|
|
) -> AsyncIterator[TelemetrySpan]:
|
|
"""Asynchronous context manager creating and recording a span."""
|
|
parent_id = CURRENT_PARENT_SPAN_ID.get()
|
|
span = TelemetrySpan(
|
|
trace_id=self.trace_id,
|
|
parent_id=parent_id,
|
|
name=name,
|
|
type=span_type,
|
|
payload=payload or {},
|
|
)
|
|
|
|
token = CURRENT_PARENT_SPAN_ID.set(span.span_id)
|
|
try:
|
|
yield span
|
|
span.finish(status="success")
|
|
except Exception as e:
|
|
span.finish(status="failed", error=str(e))
|
|
raise
|
|
finally:
|
|
CURRENT_PARENT_SPAN_ID.reset(token)
|
|
self.record_span(span)
|