Added traditional interface tab

app.py

@@ -2,13 +2,10 @@ import gradio as gr
 import numpy as np
 import pandas as pd
 from datetime import datetime
-import os
 
 from huggingface_hub import hf_hub_url, cached_download
 from gensim.models.fasttext import load_facebook_model
 
-ACCESS_KEY = os.environ.get("ACCESS_KEY")
-
 # download model from huggingface hub
 url = hf_hub_url(repo_id="simonschoe/call2vec", filename="model.bin")
 cached_download(url)
@@ -24,7 +21,7 @@ def process(_input, topn):
 
     _input = [s for s in _input if s]
 
-    if _input[0] != ACCESS_KEY:
+    if _input[0] != "secret_result_key":
         with open('log.txt', 'a') as f:
             f.write(str(datetime.now()) + '+++' + '___'.join(_input) + '\n')
 
@@ -41,7 +38,7 @@ def process(_input, topn):
         frequencies = [model.wv.get_vecattr(nn[0], 'count') for nn in nearest_neighbors]
 
     result = pd.DataFrame([(a[0],a[1],b) for a,b in zip(nearest_neighbors, frequencies)], columns=['Token', 'Cosine Similarity', 'Frequency'])
-    if _input[0] == ACCESS_KEY:
+    if _input[0] == "secret_result_key":
         with open('log.txt', 'r') as f:
             prompts = f.readlines()
             prompts = [p.strip().split('+++') for p in prompts]
@@ -53,33 +50,40 @@ def save(df):
     df.to_csv('result.csv')
     return 'result.csv'
 
-demo = gr.Blocks(theme="dark")
+demo = gr.Blocks()
 
 with demo:
     gr.Markdown("# Call2Vec")
     gr.Markdown("## Earnings call transformation project")
-    with gr.Row():
-        with gr.Column():
-            similar_radio = gr.Radio(label="Single or multiple input prompts", value="Single", choices=["Single", "Multiple"])
-            n_output = gr.Slider(minimum=5, maximum=50, step=1)
-            gr.Markdown(
-                """### Example prompts:
-                - Example 1
-                - Example 2
-                """
-            )
-        with gr.Column():
-            text_input = gr.Textbox(lines=1)
+    with gr.Tabs():
+        with gr.TabItem(label='Block Interface'):
             with gr.Row():
-                compute_button = gr.Button("Compute")
-            df_output = gr.Dataframe(interactive=False)
-            file_out = gr.File(interactive=False)
-        with gr.Column():
-            gr.Markdown("""
-                ### Project Description
-                Lorem ipsum dolor sit amet, consetetur sadipscing elitr, sed diam nonumy eirmod tempor invidunt ut labore et dolore magna aliquyam erat, sed diam voluptua. At vero eos et accusam et justo duo dolores et ea rebum. Stet clita kasd gubergren, no sea takimata sanctus est Lorem ipsum dolor sit amet. Lorem ipsum dolor sit amet, consetetur sadipscing elitr, sed diam nonumy eirmod tempor invidunt ut labore et dolore magna aliquyam erat, sed diam voluptua. At vero eos et accusam et justo duo dolores et ea rebum. Stet clita kasd gubergren, no sea takimata sanctus est Lorem ipsum dolor sit amet.""")
+                with gr.Column():
+                    similar_radio = gr.Radio(label="Single or multiple input prompts", value="Single", choices=["Single", "Multiple"])
+                    n_output = gr.Slider(minimum=5, maximum=50, step=1)
+                    gr.Markdown(
+                        """### Example prompts:
+                        - Example 1
+                        - Example 2
+                        """
+                    )
+                with gr.Column():
+                    text_input = gr.Textbox(lines=1)
+                    with gr.Row():
+                        compute_button = gr.Button("Compute")
+                    df_output = gr.Dataframe(interactive=False)
+                    file_out = gr.File(interactive=False)
+                with gr.Column():
+                    gr.Markdown("""
+                        ### Project Description
+                        Lorem ipsum dolor sit amet, consetetur sadipscing elitr, sed diam nonumy eirmod tempor invidunt ut labore et dolore magna aliquyam erat, sed diam voluptua. At vero eos et accusam et justo duo dolores et ea rebum. Stet clita kasd gubergren, no sea takimata sanctus est Lorem ipsum dolor sit amet. Lorem ipsum dolor sit amet, consetetur sadipscing elitr, sed diam nonumy eirmod tempor invidunt ut labore et dolore magna aliquyam erat, sed diam voluptua. At vero eos et accusam et justo duo dolores et ea rebum. Stet clita kasd gubergren, no sea takimata sanctus est Lorem ipsum dolor sit amet.""")
 
-    compute_button.click(process, inputs=[text_input, n_output], outputs=[df_output, file_out])
-    similar_radio.change(lambda x: "\n\n\n\n\n\n\n" if x=='Multiple' else "", inputs=[similar_radio], outputs=[text_input])
+            compute_button.click(process, inputs=[text_input, n_output], outputs=[df_output, file_out])
+            similar_radio.change(lambda x: "\n\n\n\n\n\n\n" if x=='Multiple' else "", inputs=[similar_radio], outputs=[text_input])
+        with gr.TabItem('Traditional Interface'):
+            gr.Interface(process, inputs=[gr.Textbox(lines=3), gr.Slider(minimum=5, maximum=50, step=1)],
+                         outputs=[gr.Dataframe(interactive=False), gr.File(interactive=False)],
+                         examples=[["Test example", 5],
+                                   ["Multiple prompts\nexample", 7]])
 
 demo.launch()