import numpy as np
import gradio as gr
import os
import pandas as pd
from datasets import load_dataset
from sklearn.metrics.pairwise import cosine_similarity

import plotly.express as px
Secret_token = os.getenv('token')

dataset = load_dataset("FDSRashid/embed_matn")
df = dataset["train"].to_pandas()
taraf_max = np.max(df['taraf_ID'].unique())

def plot_similarity_score(taraf_num):
    embed_taraf = df[df['taraf_ID']== taraf_num]['embed'].to_list()
    cos_score = cosine_similarity(embed_taraf)
    fig = px.imshow(cos_score)
    fig.write_html("test1.html")
    return 'test1.html'

with gr.Blocks() as demo: 
  taraf_number = gr.Slider(1,taraf_max , value=10000, label="Taraf", info="Choose the Taraf to Input", step = 1)
  btn = gr.Button('Submit')
  btn.click(fn = plot_similarity_score, inputs = [taraf_number], outputs = [gr.HTML()])
  demo.launch()