mirror of
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93 lines
3.6 KiB
Python
93 lines
3.6 KiB
Python
#
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# Copyright 2024 The InfiniFlow Authors. All Rights Reserved.
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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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import os
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from typing import Any
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from agent.component.base import ComponentBase, ComponentParamBase
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from common.connection_utils import timeout
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class VariableAggregatorParam(ComponentParamBase):
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"""
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Parameters for VariableAggregator
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- groups: list of dicts {"group_name": str, "variables": [variable selectors]}
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"""
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def __init__(self):
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super().__init__()
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# each group expects: {"group_name": str, "variables": List[str]}
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self.groups = []
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def check(self):
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self.check_empty(self.groups, "[VariableAggregator] groups")
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for g in self.groups:
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if not g.get("group_name"):
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raise ValueError("[VariableAggregator] group_name can not be empty!")
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if not g.get("variables"):
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raise ValueError(f"[VariableAggregator] variables of group `{g.get('group_name')}` can not be empty")
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if not isinstance(g.get("variables"), list):
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raise TypeError(f"[VariableAggregator] variables of group `{g.get('group_name')}` should be a list of strings")
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def get_input_form(self) -> dict[str, dict]:
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return {
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"variables": {
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"name": "Variables",
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"type": "list",
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}
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}
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class VariableAggregator(ComponentBase):
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component_name = "VariableAggregator"
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def param_refs(self) -> list[str]:
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return [selector.get("value") if isinstance(selector, dict) else selector for group in self._param.groups for selector in group.get("variables", [])]
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@timeout(int(os.environ.get("COMPONENT_EXEC_TIMEOUT", "3")))
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def _invoke(self, **kwargs):
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# Group mode: for each group, pick the first available variable
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for group in self._param.groups:
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gname = group.get("group_name")
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# record candidate selectors within this group
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self.set_input_value(f"{gname}.variables", list(group.get("variables", [])))
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for selector in group.get("variables", []):
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# Selectors may be {"value": ref} dicts (UI form) or plain
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# reference strings (SDK/API-built canvases); param_refs
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# already accepts both, so resolve them the same way here.
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ref = selector.get("value") if isinstance(selector, dict) else selector
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if not isinstance(ref, str):
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continue
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ref = ref.strip("{}").strip()
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if not ref:
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continue
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val = self._canvas.get_variable_value(ref)
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if val:
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self.set_output(gname, val)
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break
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@staticmethod
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def _to_object(value: Any) -> Any:
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# Try to convert value to serializable object if it has to_object()
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try:
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return value.to_object() # type: ignore[attr-defined]
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except (AttributeError, TypeError):
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return value
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def thoughts(self) -> str:
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return "Aggregating variables from canvas and grouping as configured."
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