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class LlmAgent: |
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def __init__(self, llm): |
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self.llm = llm |
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def generate_paragraph(self, query: str, context: {}, histo: [(str, str)], language='fr') -> str: |
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"""generates the answer""" |
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template = (f"You are a conversation bot designed to answer to the query from users delimited by " |
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f"triple backticks: " |
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f"\\n ``` {query} ```\\n" |
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f"Your answer is based on the context delimited by triple backticks: " |
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f"\\n ``` {context} ```\\n" |
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f"You are consistent and avoid redundancies with the rest of the initial conversation in French" |
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f"delimited by triple backticks: " |
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f"\\n ``` {histo} ```\\n" |
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f"Your response shall be in {language} and shall be concise" |
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f"In case the provided context is not relevant to answer to the question, just return that you " |
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f"don't know the answer ") |
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p = self.llm(template) |
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print("****************") |
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print(template) |
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print("----") |
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print(p) |
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return p |
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def translate(self, text: str, language="en") -> str: |
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"""translates""" |
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languages = "`French to English" if language == "en" else "English to French" |
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template = (f" Your task consists in translating {languages}\\n" |
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f" the following text delimited by by triple backticks: ```{text}```\n" |
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) |
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p = self.llm(template) |
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return p |
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def generate_answer(self, query: str, answer_en: str, histo_fr: str, context_fr: str) -> str: |
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"""provides the final answer in French based on the initial query and the answer in english""" |
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def _cut_unfinished_sentence(s: str): |
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return '.'.join(s.split('.')[:-1]) |
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template = (f"Your task consists in translating the answer in French to the query " |
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f"delimited by triple backticks: ```{query}``` \\n" |
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f"You are given the answer in english delimited by triple backticks: ```{answer_en}```" |
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f"\\n You don't add new content to the answer in English but: " |
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f"\\n 1 You can use some vocabulary from the context in French delimited by triple backticks: " |
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f"```{context_fr}```" |
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f"\\n 2 You are consistent and avoid redundancies with the rest of the initial" |
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f" conversation in French delimited by triple backticks: ```{histo_fr}```" |
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) |
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p = self.llm(template) |
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return p |
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