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							- #
 - #  Copyright 2024 The InfiniFlow Authors. All Rights Reserved.
 - #
 - #  Licensed under the Apache License, Version 2.0 (the "License");
 - #  you may not use this file except in compliance with the License.
 - #  You may obtain a copy of the License at
 - #
 - #      http://www.apache.org/licenses/LICENSE-2.0
 - #
 - #  Unless required by applicable law or agreed to in writing, software
 - #  distributed under the License is distributed on an "AS IS" BASIS,
 - #  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 - #  See the License for the specific language governing permissions and
 - #  limitations under the License.
 - #
 - import random
 - from abc import ABC
 - from functools import partial
 - from typing import Tuple, Union
 - 
 - import pandas as pd
 - 
 - from agent.component.base import ComponentBase, ComponentParamBase
 - 
 - 
 - class AnswerParam(ComponentParamBase):
 - 
 -     """
 -     Define the Answer component parameters.
 -     """
 -     def __init__(self):
 -         super().__init__()
 -         self.post_answers = []
 - 
 -     def check(self):
 -         return True
 - 
 - 
 - class Answer(ComponentBase, ABC):
 -     component_name = "Answer"
 - 
 -     def _run(self, history, **kwargs):
 -         if kwargs.get("stream"):
 -             return partial(self.stream_output)
 - 
 -         ans = self.get_input()
 -         if self._param.post_answers:
 -             ans = pd.concat([ans, pd.DataFrame([{"content": random.choice(self._param.post_answers)}])], ignore_index=False)
 -         return ans
 - 
 -     def stream_output(self):
 -         res = None
 -         if hasattr(self, "exception") and self.exception:
 -             res = {"content": str(self.exception)}
 -             self.exception = None
 -             yield res
 -             self.set_output(res)
 -             return
 - 
 -         stream = self.get_stream_input()
 -         if isinstance(stream, pd.DataFrame):
 -             res = stream
 -             answer = ""
 -             for ii, row in stream.iterrows():
 -                 answer += row.to_dict()["content"]
 -                 yield {"content": answer}
 -         elif stream is not None:
 -             for st in stream():
 -                 res = st
 -                 yield st
 -         if self._param.post_answers and res:
 -             res["content"] += random.choice(self._param.post_answers)
 -             yield res
 - 
 -         if res is None:
 -             res = {"content": ""}
 - 
 -         self.set_output(res)
 - 
 -     def set_exception(self, e):
 -         self.exception = e
 - 
 -     def output(self, allow_partial=True) -> Tuple[str, Union[pd.DataFrame, partial]]:
 -         if allow_partial:
 -             return super.output()
 - 
 -         for r, c in self._canvas.history[::-1]:
 -             if r == "user":
 -                 return self._param.output_var_name, pd.DataFrame([{"content": c}])
 - 
 -         self._param.output_var_name, pd.DataFrame([])
 
 
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