33 lines
1.2 KiB
Python
33 lines
1.2 KiB
Python
from toolbench.inference.Downstream_tasks.base_env import base_env
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class base_search_method:
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"""For the base tree search method, you need to support the following functions"""
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def __init__(self,llm,io_func: base_env, process_id=0, callbacks = None):
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"""Args:
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llm: The interface of the LLM
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io_func(base_env): Interface to the environment,
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process_id (int, optional): In multiprocessing annotation, this describes the process id. Defaults to 0.
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callbacks (_type_, optional): _description_. Defaults to None.
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"""
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pass
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def to_json(self,answer=False,process=True):
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'''
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return a json object,
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If "answer" = True. must have the following field to make answer annotation
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If "process" = True. You need provide the full information of the tree searching process
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"answer_generation": {
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"valid_data": bool,
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"final_answer": string,
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"finish_type": enum["give_up","give_answer"]
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"train_messages": [ [openAI-message] ],
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}
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'''
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raise NotImplementedError
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def start(self, **args):
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"""This is the entry point of the searching process"""
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raise NotImplementedError
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