import streamlit as st
from utils.levels import complete_level, render_page, initialize_level
from utils.login import initialize_login, get_login
import requests
import os


def check_sentence_similarity(source_sentence, sentence):
    response = requests.post(
        "https://api-inference.huggingface.co/models/sentence-transformers/all-MiniLM-L6-v2",
        headers={"Authorization": "Bearer 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"},
        json={
            "inputs": {"source_sentence": source_sentence, "sentences": [sentence]},
        },
    )
    return response.json()[0]


def get_audio_transcription(filename):
    with open(filename, "rb") as f:
        data = f.read()
    response = requests.post(
        "https://api-inference.huggingface.co/models/openai/whisper-medium",
        headers={"Authorization": "Bearer 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"},
        data=data,
    )
    return response.json()


LEVEL = 4

initialize_login()
initialize_level()


def step_page():
    st.header("Tryit Out")

    uploaded_file = st.file_uploader("Upload a file", type=["wav", "mp3", "flac"])
    if uploaded_file:
        audio_file = os.path.join(".sessions", get_login()["username"], "audio.flac")
        with open(audio_file, "wb") as f:
            f.write(uploaded_file.getbuffer())
    else:
        audio_file = "assets/sample1.flac"

    st.audio(audio_file, format="audio/flac")

    transcript = st.text_input("What did you hear?")
    if st.button("Check") and transcript:
        with st.spinner("Checking..."):
            output = get_audio_transcription(audio_file)
        similarity = check_sentence_similarity(output["text"], transcript)
        if similarity > 0.75:
            st.success(
                f"Correct! You are {similarity * 100}% similar to the original sentence."
            )
        else:
            st.error("You are not similar enough to the original sentence.")
            st.info(f"Original sentence: {output['text']}")


render_page(step_page, LEVEL)