Files
Artemis-Eapil/artemis/interfaces/sdk/client.py
T
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

148 lines
5.0 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.
from typing import Any, Literal
from collections.abc import AsyncGenerator, Callable
from artemis.engine.pipeline import Pipeline
from artemis.interfaces.sdk.task import StreamEvent, StreamEventType, TaskResult
from artemis.utils.logger import get_logger
logger = get_logger(__name__)
class ArtemisClient:
"""The official high-level developer entrypoint for interacting with ARTEMIS."""
def __init__(
self, device_id: str = "default-device", default_profile: Literal["flash", "pro"] = "pro"
):
self.device_id = device_id
self.default_profile = default_profile
async def run(
self,
goal: str,
profile: Literal["flash", "pro"] | None = None,
max_turns: int = 30,
**kwargs: Any,
) -> TaskResult:
"""Executes a single autonomous task and returns the final TaskResult."""
target_profile = profile or self.default_profile
logger.info(f"ArtemisClient running task '{goal}' with profile '{target_profile}'...")
state = await Pipeline.execute(
goal=goal,
profile=target_profile,
device_id=self.device_id,
)
return TaskResult(
trace_id=state.trace_id,
status=state.status.value,
turns=state.current_turn,
error=state.error_message,
)
async def stream_run(
self,
goal: str,
profile: Literal["flash", "pro"] | None = None,
max_turns: int = 30,
callbacks: list[Callable[[StreamEvent], Any]] | None = None,
**kwargs: Any,
) -> AsyncGenerator[StreamEvent, None]:
"""Executes an autonomous task while yielding real-time StreamEvents asynchronously."""
target_profile = profile or self.default_profile
logger.info(f"ArtemisClient streaming task '{goal}' with profile '{target_profile}'...")
# 1. Emit initial starting event
start_event = StreamEvent(
event_type=StreamEventType.STATUS,
step_number=0,
payload={
"status": "starting",
"goal": goal,
"profile": target_profile,
"device_id": self.device_id,
},
)
if callbacks:
for cb in callbacks:
try:
cb(start_event)
except Exception as e:
logger.debug(f"Callback error: {e}")
yield start_event
# 2. Execute task pipeline
try:
state = await Pipeline.execute(
goal=goal,
profile=target_profile,
device_id=self.device_id,
)
# 3. Emit intermediate step events
for step in state.steps:
ev = StreamEvent(
event_type=StreamEventType.STEP_END,
step_number=step.step_number,
payload={
"thought": step.thought,
"action": step.action_name,
"params": step.action_params,
"result": step.result,
"duration": step.duration_seconds,
},
)
if callbacks:
for cb in callbacks:
try:
cb(ev)
except Exception as e:
logger.debug(f"Callback error: {e}")
yield ev
# 4. Emit completion event
final_ev = StreamEvent(
event_type=StreamEventType.STATUS,
step_number=state.current_turn,
payload={
"status": state.status.value,
"turns": state.current_turn,
"error": state.error_message,
},
)
if callbacks:
for cb in callbacks:
try:
cb(final_ev)
except Exception as e:
logger.debug(f"Callback error: {e}")
yield final_ev
except Exception as e:
err_ev = StreamEvent(
event_type=StreamEventType.ERROR,
step_number=0,
payload={"error": str(e)},
)
if callbacks:
for cb in callbacks:
try:
cb(err_ev)
except Exception:
pass
yield err_ev