somew1nd
12d7902a82
Fix queue cancellation, concurrency limits and worker status updates. Use direct Explorer imports, split the Diagnoser loop into helpers and remove unused tool registration and prompt-builder code. Correct model caching, endpoint selection and retry handling.
125 lines
4.3 KiB
Python
125 lines
4.3 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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"""Universal Image Processor tool for executing image transformations."""
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from typing import Any
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from langchain_core.tools import BaseTool
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from pydantic import BaseModel, Field
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from artemis.context import ArtemisContext
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from artemis.data_engine.trace import trace, trace_langchain_tool
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from artemis.drivers.base import BaseDeviceDriver
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from artemis.graph.state import State
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from artemis.tools.base import ArtemisTool
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from artemis.tools.tool_wrapper import ToolWrapper
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from artemis.tools.types import CyFunctionDetector
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from artemis.utils.logger import get_logger
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logger = get_logger(__name__)
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# pylint: disable=too-few-public-methods
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class AskVisionCoderArgs(BaseModel):
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"""Arguments schema for invoking the Image Processor subagent."""
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model_config = {"ignored_types": (CyFunctionDetector,)}
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instruction: str = Field(
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...,
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description=(
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"Step-by-step instructions on what image processing or"
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" modifications should be performed."
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),
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)
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target_image_id: str = Field(
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...,
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description=(
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"The ID of the image in the Image Pool to start from (e.g. 'img_0', 'img_1')."
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),
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)
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# Alias for naming consistency
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AskImageProcessorArgs = AskVisionCoderArgs
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class AskImageProcessorTool(ArtemisTool):
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"""Universal tool for executing image transformations via ImageProcessor subagent."""
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def __init__(self):
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super().__init__(
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name="ask_image_processor",
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description=(
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"Call this tool to ask the image processor agent to run"
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" complex image transformations or modifications."
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),
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args_schema=AskVisionCoderArgs,
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category="custom",
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)
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# pylint: disable=too-many-arguments,too-many-positional-arguments
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async def execute(
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self,
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driver: BaseDeviceDriver | None = None, # pylint: disable=unused-argument
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ctx: ArtemisContext | None = None,
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instruction: str | None = None,
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target_image_id: str | None = None,
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state: State | None = None,
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**kwargs: Any,
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) -> Any:
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inst = instruction or kwargs.get("Instruction") or ""
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tid = target_image_id or kwargs.get("TargetImageId") or kwargs.get("target_image_id") or ""
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st = state if state is not None else kwargs.get("state")
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return await _run_image_processor_logic(ctx, st, inst, tid)
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# Universal tool instance & aliases
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ask_image_processor = AskImageProcessorTool()
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AskImageProcessor = AskImageProcessorTool
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AskVisionCoderTool = AskImageProcessorTool
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ImageProcessorTool = AskImageProcessorTool
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def get_ask_image_processor_tool(ctx: ArtemisContext) -> BaseTool:
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"""Exports ask_image_processor as a LangChain BaseTool."""
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return trace_langchain_tool(ask_image_processor.to_langchain_tool(ctx), ctx)
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async def _run_image_processor_logic(
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ctx: ArtemisContext | None,
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state: State | None,
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instruction: str,
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target_image_id: str, # pylint: disable=unused-argument
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) -> Any:
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@trace(type="agent", name="image_processor", ctx=ctx)
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async def run_image_processor_agent(inst: str, img_path: str) -> dict:
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from artemis.agents.image_processor.image_processor import ( # pylint: disable=import-outside-toplevel
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ImageProcessor,
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)
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agent = ImageProcessor(ctx)
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return await agent.run(inst, img_path)
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screenshot_path = state.latest_screenshot if state else None
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result = await run_image_processor_agent(instruction, screenshot_path)
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return result
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ask_image_processor_wrapper = ToolWrapper(
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tool_fn_getter=get_ask_image_processor_tool,
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on_success_fn=lambda output: f"Image Processor replied:\n{output}",
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on_failure_fn=lambda error: f"Image Processor failed: {error}",
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)
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