82 lines
3.0 KiB
Python
82 lines
3.0 KiB
Python
# -*- coding: utf-8 -*-
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"""some utils of angent_builder example"""
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import re
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def load_txt(instruction_file: str) -> str:
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"""
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load .txt file
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Arguments:
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instruction_file: str type, which is the .txt file pth
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Returns:
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instruction: str type, which is the str in the instruction_file
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"""
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with open(instruction_file, "r", encoding="utf-8") as f:
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instruction = f.read()
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return instruction
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# extract scenario和participants
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def extract_scenario_and_participants(content: str) -> dict:
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"""
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extract the scenario and participants from agent builder's response
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Arguments:
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content: the agent builders response
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Returns:
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result: dict
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Examples:
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content: #scenario#: Astronomy club meeting
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#participants#:
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* Club Leader: Act as the club leader who is knowledgeable about\
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astronomy and optics. You are leading a discussion about the \
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capabilities of telescopes versus the human eye. Please provide \
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accurate information and guide the discussion.
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* Curious Member: Act as a curious club member who is interested \
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in astronomy but may not know all the technical details. You are \
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eager to learn and ask questions.
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* Experienced Astronomer: Act as an experienced astronomer who has \
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practical experience using telescopes for stargazing. You can \
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provide real-world examples and insights into the topic.
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Return:
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{'Scenario': 'Astronomy club meeting',
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'Participants':
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{'Club_Leader': 'Act as the club leader who is knowledgeable \
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about astronomy and optics. You are leading a discussion about the \
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capabilities of telescopes versus the human eye. Please provide\
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accurate information and guide the discussion.',
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'Curious_Member': 'Act as a curious club member who is interested \
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in astronomy but may not know all the technical details. You are \
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eager to learn and ask questions.',
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'Experienced_Astronomer': 'Act as an experienced astronomer who has\
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practical experience using telescopes for stargazing. You can\
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provide real-world examples and insights into the topic.'}}
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"""
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result = {}
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# define regular expression
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scenario_pattern = r"#scenario#:\s*(.*)"
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participants_pattern = r"\*\s*([^:\n]+):\s*([^\n]+)"
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# search and extract scenario
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scenario_match = re.search(scenario_pattern, content)
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if scenario_match:
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result["Scenario"] = scenario_match.group(1).strip()
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# search and extract participants
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participants_matches = re.finditer(participants_pattern, content)
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participants_dict = {}
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for match in participants_matches:
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participant_type, characteristic = match.groups()
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participants_dict[
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participant_type.strip().replace(" ", "_")
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] = characteristic.strip()
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result["Participants"] = participants_dict
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return result
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