"""
 /*************************************************************************
 * 
 * CONFIDENTIAL
 * __________________
 * 
 *  Copyright (2023-2024) AI Labs, IronOne Technologies, LLC
 *  All Rights Reserved
 *
 *  Author  : Theekshana Samaradiwakara
 *  Description :Python Backend API to chat with private data  
 *  CreatedDate : 14/11/2023
 *  LastModifiedDate : 18/03/2024
 *************************************************************************/
 """

def qa_chain_output_parser(result):
    # return {
    #     "question": result["question"], 
    #     "answer": result["answer"],
    #     "source_documents": result["source_documents"]
    # }
    metadata = [i.metadata for i in result.get("source_documents", [])]
    source_documents = result.get("source_documents", [])

    format_data = make_format(metadata, source_documents)
    
    return {
        "user_input": result["question"], 
        "bot_response": result["answer"],
        "format_data": format_data
    }

def general_qa_chain_output_parser(result):
    return {
        "user_input": result["question"], 
        "bot_response": result["text"],
        "format_data": []
    }


def out_of_domain_chain_parser(query):
    return {
        "user_input": query, 
        "bot_response":"sorry this question is out of my domain.",
        "format_data":[]
    }



def make_format(metadata, source_documents):
    """
    This function is used to format the metadata and source documents into an array.
    The output from this function is used when displaying the results on the website.

    """

    formatted_metadata = []
    for index, doc in enumerate(source_documents, 1):
        page_content = doc.page_content
        source = metadata[index - 1]["source"].split("\\")[-1]
        formatted_metadata.append({"pageContent": page_content, "source": source})

    return formatted_metadata