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.
200 lines
7.9 KiB
Python
200 lines
7.9 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 Tool Protocol for ARTEMIS.
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Enables tools to be authored once using standard Pydantic schemas and async handlers,
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then automatically exported to LangChain Tools (Pro Graph), Google GenAI FunctionDeclarations
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(FlashRunner), and MCP Tools (FastMCP) with zero code duplication.
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"""
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import asyncio
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from collections.abc import Callable
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import concurrent.futures
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import inspect
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from typing import Annotated, Any, Literal
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from google.genai import types as genai_types
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from langchain_core.tools import BaseTool, StructuredTool
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from langgraph.prebuilt import InjectedState
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from pydantic import BaseModel
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from artemis.drivers.base import BaseDeviceDriver
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from artemis.drivers.factory import get_driver
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from artemis.utils.logger import get_logger
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logger = get_logger(__name__)
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ToolCategory = Literal["action", "perception", "system", "memory", "custom"]
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class ArtemisTool:
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"""Unified tool wrapper encapsulating schema, execution logic, and multi-protocol export."""
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# pylint: disable=too-many-arguments,too-many-positional-arguments
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def __init__(
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self,
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name: str,
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description: str,
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args_schema: type[BaseModel],
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handler: Callable[..., Any] | None = None,
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category: ToolCategory = "action",
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):
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self.name = name
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self.description = description
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self.args_schema = args_schema
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self.handler = handler
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self.category = category
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def is_available(self, ctx: Any = None) -> bool:
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"""Determines if this tool is currently available and should be exposed to agents."""
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return True
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async def execute(self, driver: BaseDeviceDriver, ctx: Any, **kwargs: Any) -> Any:
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"""Executes the tool handler with injected driver and context."""
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# Inspect handler signature to only pass supported arguments
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if self.handler is not None:
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sig = inspect.signature(self.handler)
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call_kwargs = {}
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for param_name in sig.parameters:
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if param_name == "driver":
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call_kwargs["driver"] = driver
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elif param_name in ("ctx", "context"):
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call_kwargs[param_name] = ctx
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elif param_name in kwargs:
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call_kwargs[param_name] = kwargs[param_name]
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if inspect.iscoroutinefunction(self.handler):
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return await self.handler(**call_kwargs)
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return self.handler(**call_kwargs)
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raise NotImplementedError("Subclasses must implement execute() or provide a handler.")
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async def __call__(self, *args: Any, **kwargs: Any) -> Any:
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"""Allows ArtemisTool instances to be invoked directly as callables."""
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driver = kwargs.pop("driver", None)
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ctx = kwargs.pop("ctx", None) or kwargs.pop("context", None)
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return await self.execute(driver=driver, ctx=ctx, *args, **kwargs)
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def to_langchain_tool(self, ctx: Any, name: str | None = None) -> BaseTool:
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"""Exports this tool to a LangChain StructuredTool."""
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def _get_context_driver() -> BaseDeviceDriver | None:
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if (
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ctx is not None
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and hasattr(ctx, "device")
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and ctx.device
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and getattr(ctx.device, "device_id", None)
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):
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try:
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return get_driver(ctx)
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except Exception as e: # pylint: disable=broad-exception-caught
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logger.debug(f"Failed to get driver: {e}")
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return None
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return getattr(ctx, "_active_driver", None) if ctx is not None else None
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def _func(state: Annotated[Any, InjectedState] = None, **kwargs):
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driver = _get_context_driver()
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if state is not None:
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kwargs["state"] = state
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try:
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loop = asyncio.get_running_loop()
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except RuntimeError:
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loop = None
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if loop and loop.is_running():
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with concurrent.futures.ThreadPoolExecutor(max_workers=1) as pool:
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return pool.submit(
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asyncio.run, self.execute(driver=driver, ctx=ctx, **kwargs)
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).result()
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return asyncio.run(self.execute(driver=driver, ctx=ctx, **kwargs))
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async def _coroutine(state: Annotated[Any, InjectedState] = None, **kwargs):
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driver = _get_context_driver()
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if state is not None:
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kwargs["state"] = state
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return await self.execute(driver=driver, ctx=ctx, **kwargs)
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return StructuredTool.from_function(
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func=_func,
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coroutine=_coroutine,
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name=name or self.name,
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description=self.description,
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args_schema=self.args_schema,
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)
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def to_genai_declaration(self) -> genai_types.FunctionDeclaration:
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"""Exports this tool to a Google GenAI FunctionDeclaration schema."""
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properties = {}
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required = []
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if self.args_schema:
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schema = self.args_schema.model_json_schema()
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props = schema.get("properties", {})
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required = schema.get("required", [])
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for prop_name, prop_data in props.items():
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p_type_str = prop_data.get("type")
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items_data = prop_data.get("items")
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if not p_type_str and "anyOf" in prop_data:
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for sub_schema in prop_data["anyOf"]:
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sub_type = sub_schema.get("type")
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if sub_type and sub_type != "null":
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p_type_str = sub_type
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if "items" in sub_schema and not items_data:
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items_data = sub_schema["items"]
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break
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if not p_type_str:
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p_type_str = "string"
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p_desc = prop_data.get("description", "")
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genai_type = genai_types.Type.STRING
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if p_type_str == "integer":
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genai_type = genai_types.Type.INTEGER
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elif p_type_str == "number":
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genai_type = genai_types.Type.NUMBER
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elif p_type_str == "boolean":
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genai_type = genai_types.Type.BOOLEAN
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elif p_type_str == "array":
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genai_type = genai_types.Type.ARRAY
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elif p_type_str == "object":
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genai_type = genai_types.Type.OBJECT
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# Handle array items if present
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items_schema = None
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if genai_type == genai_types.Type.ARRAY:
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item_type_str = (items_data or {}).get("type", "string")
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item_genai_type = (
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genai_types.Type.INTEGER
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if item_type_str == "integer"
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else genai_types.Type.STRING
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)
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items_schema = genai_types.Schema(type=item_genai_type)
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properties[prop_name] = genai_types.Schema(
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type=genai_type,
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description=p_desc,
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items=items_schema,
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)
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return genai_types.FunctionDeclaration(
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name=self.name,
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description=self.description,
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parameters=genai_types.Schema(
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type=genai_types.Type.OBJECT,
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properties=properties,
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required=required,
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),
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)
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