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IInstance.py
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76 lines (60 loc) · 2.81 KB
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# =============================================================================
# MIT License
# Copyright (c) 2026 Aparavi Software AG
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights
# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
# copies of the Software, and to permit persons to whom the Software is
# furnished to do so, subject to the following conditions:
#
# The above copyright notice and this permission notice shall be included in
# all copies or substantial portions of the Software.
#
# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
# SOFTWARE.
# =============================================================================
"""
Chart (Chart.js) tool node instance.
Binds the pipeline LLM to the ``ChartjsDriver`` and delegates tool
invocation.
"""
from __future__ import annotations
from typing import Any
from rocketlib import IInstanceBase
from rocketlib.types import IInvokeLLM
from .IGlobal import IGlobal
def _make_llm_invoker(instance: Any) -> Any:
"""Create an LLM-invoking callable bound to the pipeline instance.
Returns a callable that accepts a ``Question`` and returns the LLM
response text.
"""
llm_nodes = instance.getControllerNodeIds('llm')
if not llm_nodes:
return None
llm_node_id = llm_nodes[0]
def invoke_llm(question: Any) -> str:
result = instance.invoke('llm', IInvokeLLM(op='ask', question=question), nodeId=llm_node_id)
if hasattr(result, 'getText') and callable(result.getText):
return (result.getText() or '').strip()
return str(result).strip()
return invoke_llm
class IInstance(IInstanceBase):
IGlobal: IGlobal
def invoke(self, param: Any) -> Any: # noqa: ANN401
driver = getattr(self.IGlobal, 'driver', None)
if driver is None:
raise RuntimeError('chart_chartjs: driver not initialized')
# Bind the LLM invoker before each invocation
if driver._llm_invoke is None:
llm_invoker = _make_llm_invoker(self.instance)
if llm_invoker is None:
raise RuntimeError('Chart generator requires an LLM node connected to the pipeline.')
driver.set_llm_invoker(llm_invoker)
return driver.handle_invoke(param)