Create app.py

app.py

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+
+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()