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class LlmAgent:
def __init__(self, llm):
self.llm = llm
def generate_paragraph(self, query: str, context: {}, histo: [(str, str)], language='fr') -> str:
"""generates the answer"""
template = (f"You are a conversation bot designed to answer to the query from users delimited by "
f"triple backticks: "
f"\\n ``` {query} ```\\n"
f"Your answer is based on the context delimited by triple backticks: "
f"\\n ``` {context} ```\\n"
f"You are consistent and avoid redundancies with the rest of the initial conversation in French"
f"delimited by triple backticks: "
f"\\n ``` {histo} ```\\n"
f"Your response shall be in {language} and shall be concise"
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)
print("****************")
print(template)
print("----")
print(p)
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, histo_fr: 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(s.split('.')[:-1])
template = (f"Your task consists in translating the answer in French to the query "
f"delimited by triple backticks: ```{query}``` \\n"
f"You are given the answer in english delimited by triple backticks: ```{answer_en}```"
f"\\n You don't add new content to the answer in English but: "
f"\\n 1 You can use some vocabulary from the context in French delimited by triple backticks: "
f"```{context_fr}```"
f"\\n 2 You are consistent and avoid redundancies with the rest of the initial"
f" conversation in French delimited by triple backticks: ```{histo_fr}```"
)
p = self.llm(template)
# p = _cut_unfinished_sentence(p)
return p
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