prompt.py

"""
Prompt configuration.
"""
from datetime import datetime
from langchain.prompts.prompt import PromptTemplate
from langchain.prompts import ChatPromptTemplate

from langchain_core.prompts import ChatPromptTemplate

interprate_question_sharepoint_template = """
    whatever is asked, just answer only {{}}"""

PROMPT_INTERPRATE_INTENTION_SHAREPOINT = ChatPromptTemplate.from_template(
    interprate_question_sharepoint_template
)

interprate_question_template = (
    """You are an assistant that have to identify the object of a question.
    A user asks a question about meeting decisions. 
    If the question is about a particular meeting, identified by a meeting number, answer only 'meeting <meeting number>'.
    Otherwise answer only 'other'.
    
    Example:
    Q: What decision was taken at meeting 123th?
    R: meeting 123
    Q: Give me an example of a decision that applied a penalty to a country?
    R: autre
    
    """
    "La question est la suivante: {query}."
)

PROMPT_INTERPRATE_INTENTION = ChatPromptTemplate.from_template(
    interprate_question_template
)

current_date = datetime.now().strftime('%d/%m/%Y')
company_name = "UNEP" # to change

answering_template = (
    f"You are an AI Assistant by Ekimetrics for {company_name}. "
    f"Your task is to help {company_name} employees. "
    "You will be given a question and extracted parts of documents."
    "Provide a clear and structured answer based on the context provided. "
    "When relevant, use bullet points and lists to structure your answers. "
    "Whenever you use information from a document, reference it at the end of the sentence (ex: [doc 2]). "
    "You don't have to use all documents, only if it makes sense in the conversation. "
    "If no relevant information to answer the question is present in the documents, "
    "just say you don't have enough information to answer.\n\n"
    "{context}\n\n"
    "Question: {question}"
    )
ANSWER_PROMPT = ChatPromptTemplate.from_template(answering_template)