import gradio as gr
import random
import pandas as pd
import requests

# URL of the file you want to download
url = "https://raw.githubusercontent.com/Bestroi150/NLP_LAT_COLL/main/corpus_sermo_vulgaris_token.csv"

# Specify the local file name to save the downloaded content
local_filename = "corpus_sermo_vulgaris_token.csv"

# Send an HTTP GET request to the URL
response = requests.get(url)

# Check if the request was successful (status code 200)
if response.status_code == 200:
    # Open the local file for writing and save the content from the response
    with open(local_filename, 'wb') as f:
        f.write(response.content)
    print(f"File '{local_filename}' has been downloaded and saved.")
else:
    print(f"Failed to download the file. Status code: {response.status_code}")

data = pd.read_csv('corpus_sermo_vulgaris_token.csv')

analytics_data = pd.DataFrame(columns=["Entry", "Clicks"])  # Declare as a global variable

def get_random_entry():
    random_row = data.sample()
    pos = random_row['pos'].values[0]

    if pos == "n":
        entry_str = f"<b>POS:</b> Noun, <b>Lemma:</b> {random_row['lemma'].values[0]}, <b>Gender:</b> {random_row['gender'].values[0]}, <b>Case:</b> {random_row['case'].values[0]}, <b>Number:</b> {random_row['number'].values[0]}"
    elif pos == "adp":        
        entry_str = f"<b>POS:</b> Preposition, <b>Lemma:</b> {random_row['lemma'].values[0]}"
    elif pos == "adi":
        entry_str = f"<b>POS:</b> Adjective, <b>Lemma:</b> {random_row['lemma'].values[0]}, <b>Gender:</b> {random_row['gender'].values[0]}, <b>Case:</b> {random_row['case'].values[0]}, <b>Number:</b> {random_row['number'].values[0]}"
    elif pos == "adv":
        entry_str = f"<b>POS:</b> Adverb, <b>Lemma:</b> {random_row['lemma'].values[0]}"
    elif pos == "pron":
        entry_str = f"<b>POS:</b> Pronoun, <b>Lemma:</b> {random_row['lemma'].values[0]}"
    elif pos == "v":
        entry_str = f"<b>POS:</b> Verb, <b>Lemma:</b> {random_row['lemma'].values[0]}, <b>Aspect:</b> {random_row['aspect'].values[0]}, <b>Tense:</b> {random_row['tense'].values[0]}, <b>VerbForm:</b> {random_row['verbForm'].values[0]}, <b>Voice:</b> {random_row['voice'].values[0]}, <b>Mood:</b> {random_row['mood'].values[0]}"
    else:
        entry_str = f"POS: {pos}, Lemma: {random_row['lemma'].values[0]},"
        if pd.notna(random_row['aspect'].values[0]):
            entry_str += f" Aspect: {random_row['aspect'].values[0]},"
        if pd.notna(random_row['tense'].values[0]):
            entry_str += f" Tense: {random_row['tense'].values[0]},"
        if pd.notna(random_row['verbForm'].values[0]):
            entry_str += f" VerbForm: {random_row['verbForm'].values[0]},"
        if pd.notna(random_row['voice'].values[0]):
            entry_str += f" Voice: {random_row['voice'].values[0]},"
        if pd.notna(random_row['mood'].values[0]):
            entry_str += f" Mood: {random_row['mood'].values[0]},"
        if pd.notna(random_row['number'].values[0]):
            entry_str += f" Number: {random_row['number'].values[0]},"
        if pd.notna(random_row['person'].values[0]):
            entry_str += f" Person: {random_row['person'].values[0]},"
        if pd.notna(random_row['case'].values[0]):
            entry_str += f" Case: {random_row['case'].values[0]},"
        if pd.notna(random_row['gender'].values[0]):
            entry_str += f" Gender: {random_row['gender'].values[0]}"

    # Remove the trailing comma
    entry_str = entry_str.rstrip(',')
    

    return entry_str


iface = gr.Interface(
    fn=get_random_entry,
    inputs=None,
    outputs="html",  # Use HTML as the output type
    live=True,
    theme=gr.themes.Base(primary_hue="teal").set(
    button_primary_background_fill="*primary_400",
    button_primary_background_fill_hover="*primary_300",
))


iface.launch(
    share=True
)