import logging
import os

import gradio as gr
import pandas as pd

import cfg
from cfg import buster

logger = logging.getLogger(__name__)
logging.basicConfig(level=logging.INFO)

USERNAME = os.getenv("BUSTER_USERNAME")
PASSWORD = os.getenv("BUSTER_PASSWORD")


def check_auth(username: str, password: str) -> bool:
    valid_user = username == USERNAME
    valid_password = password == PASSWORD
    is_auth = valid_user and valid_password
    logger.info(f"Log-in attempted by {username=}. {is_auth=}")
    return is_auth


def format_sources(matched_documents: pd.DataFrame) -> str:
    if len(matched_documents) == 0:
        return ""

    documents_answer_template: str = "📝 Here are the sources I used to answer your question:\n\n{documents}\n\n{footnote}"
    document_template: str = "[🔗 {document.title}]({document.url}), relevance: {document.similarity_to_answer:2.1f} %"

    matched_documents.similarity_to_answer = (
        matched_documents.similarity_to_answer * 100
    )
    documents = "\n".join(
        [
            document_template.format(document=document)
            for _, document in matched_documents.iterrows()
        ]
    )
    footnote: str = "I'm a bot 🤖 and not always perfect."

    return documents_answer_template.format(documents=documents, footnote=footnote)


def add_sources(history, completion):
    if completion.answer_relevant:
        formatted_sources = format_sources(completion.matched_documents)
        history.append([None, formatted_sources])

    return history


def user(user_input, history):
    """Adds user's question immediately to the chat."""
    return "", history + [[user_input, None]]


def chat(history):
    user_input = history[-1][0]

    completion = buster.process_input(user_input)

    history[-1][1] = ""

    for token in completion.answer_generator:
        history[-1][1] += token

        yield history, completion


block = gr.Blocks(css="#chatbot .overflow-y-auto{height:500px}")

with block:
    with gr.Row():
        gr.Markdown(
            "<h3><center>Buster 🤖: A Question-Answering Bot for your documentation</center></h3>"
        )

    chatbot = gr.Chatbot()

    with gr.Row():
        question = gr.Textbox(
            label="What's your question?",
            placeholder="Ask a question to AI stackoverflow here...",
            lines=1,
        )
        submit = gr.Button(value="Send", variant="secondary")

    examples = gr.Examples(
        examples=[
            "What's a genetic algorithm?",
            "What's PCA? What is it used for?",
            "How do I deal with noisy data?",
        ],
        inputs=question,
    )

    gr.Markdown(
        "This application uses GPT to search the docs for relevant info and answer questions."
    )

    response = gr.State()

    submit.click(user, [question, chatbot], [question, chatbot], queue=False).then(
        chat, inputs=[chatbot], outputs=[chatbot, response]
    ).then(add_sources, inputs=[chatbot, response], outputs=[chatbot])
    question.submit(user, [question, chatbot], [question, chatbot], queue=False).then(
        chat, inputs=[chatbot], outputs=[chatbot, response]
    ).then(add_sources, inputs=[chatbot, response], outputs=[chatbot])


block.queue(concurrency_count=16)
block.launch(debug=True, share=False, auth=check_auth)