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90 lines
2.6 KiB
Python
90 lines
2.6 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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#
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import random
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from abc import ABC
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from functools import partial
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from typing import Tuple, Union
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import pandas as pd
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from agent.component.base import ComponentBase, ComponentParamBase
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class AnswerParam(ComponentParamBase):
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"""
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Define the Answer component parameters.
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"""
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def __init__(self):
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super().__init__()
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self.post_answers = []
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def check(self):
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return True
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class Answer(ComponentBase, ABC):
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component_name = "Answer"
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def _run(self, history, **kwargs):
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if kwargs.get("stream"):
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return partial(self.stream_output)
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ans = self.get_input()
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if self._param.post_answers:
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ans = pd.concat([ans, pd.DataFrame([{"content": random.choice(self._param.post_answers)}])], ignore_index=False)
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return ans
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def stream_output(self):
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res = None
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if hasattr(self, "exception") and self.exception:
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res = {"content": str(self.exception)}
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self.exception = None
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yield res
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self.set_output(res)
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return
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stream = self.get_stream_input()
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if isinstance(stream, pd.DataFrame):
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res = stream
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answer = ""
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for ii, row in stream.iterrows():
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answer += row.to_dict()["content"]
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yield {"content": answer}
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else:
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for st in stream():
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res = st
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yield st
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if self._param.post_answers:
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res["content"] += random.choice(self._param.post_answers)
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yield res
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self.set_output(res)
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def set_exception(self, e):
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self.exception = e
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def output(self, allow_partial=True) -> Tuple[str, Union[pd.DataFrame, partial]]:
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if allow_partial:
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return super.output()
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for r, c in self._canvas.history[::-1]:
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if r == "user":
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return self._param.output_var_name, pd.DataFrame([{"content": c}])
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self._param.output_var_name, pd.DataFrame([])
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