| class LlmAgent: | |
| def __init__(self, llm): | |
| self.llm = llm | |
| def generate_paragraph(self, query: str, context: {}, language='fr') -> str: | |
| """generates the final answer""" | |
| template = (f" You are an agent designed to answer to the {query} based on the context delimited by triple backticks:\n" | |
| f"``` {context}```\n" | |
| f" The response shall be in {language} and shall be concise and based on the context provided\n" | |
| f" In case the provided context is not relevant to answer to the question, just return that you " | |
| f" don't know the answer ") | |
| p = self.llm(template) | |
| return p | |
| def translate(self, text: str, language="en") -> str: | |
| """translates""" | |
| languages = "french to english" if language == "en" else "english to french" | |
| template = (f" Your task consists in translating {languages}\\n" | |
| f" the following text delimited by by triple backticks: ```{text}```\n" | |
| ) | |
| p = self.llm(template) | |
| return p | |
| def generate_answer(self, query: str, answer_en: str, context_fr: str) -> str: | |
| """provides the final answer in french based on the initial query and the answer in english""" | |
| def _cut_unfinished_sentence(s: str): | |
| return '.'.join(p.split('.')[:-1]) | |
| template = (f"Your task consists in providing the answer in french to the query " | |
| f"delimited by triple backticks: ```{query}``` given the informations here delimited " | |
| f"by triple backticks: ```{context_fr}``` and the answer in english delimited by triple " | |
| f"backticks: ```{answer_en}```" | |
| ) | |
| print(template) | |
| p = self.llm(template) | |
| p = _cut_unfinished_sentence(p) | |
| print(p) | |
| return p | |