Add requirements.txt

app.py

@@ -2,12 +2,6 @@ import gradio as gr
 from sentence_transformers import SentenceTransformer
 from sklearn.metrics.pairwise import cosine_similarity
 import time
-import os
-# I needed my Hugging Face token to be set in the environment variables
-# to allow me to use the Hugging Face API to retrieve some of the models.
-# I have removed the token from the code for security reasons. Plus I don't
-# need it now that the models are downloaded.
-os.environ['HF_TOKEN'] = 'hf_XLm......'
 
 sentences = [
     # "Yes, Route 359 is located entirely within the town of Skaneateles, ",
@@ -53,48 +47,6 @@ def run_model(model_name, passage_1, passage_2):
     return '\n'.join(messages)
 
 
-# def update_text(index):
-#     """Updates the text box based on the radio button selection."""
-#     text = sentences[index]
-#     return text
-
-
-# with gr.Blocks() as interface:
-#     gr.Markdown("# Sentence Transformer Embeddings")
-#     # description = "This is a demo of the Sentence Transformers library."
-#     model_name = gr.Dropdown(
-#         choices=['sentence-transformers/all-MiniLM-L6-v2',
-#                  'sentence-transformers/all-mpnet-base-v2',
-#                  'sentence-transformers/msmarco-distilroberta-base-v2',],
-#         value='sentence-transformers/all-MiniLM-L6-v2',
-#         label="Choose Model",
-#         type="value")
-#     radio = gr.Radio(
-#         choices=[sentence[:72] + ' ...' for sentence in sentences],
-#         label="Pick a passage (optional)",
-#         type="index")
-
-#     # Create a text box to display the selection
-#     passage_1 = gr.Textbox(
-#         label="Passage 1",
-#         placeholder="Pick passage from above or enter your own.",)
-
-#     # Connect the radio button change event to the update_text function
-#     radio.change(update_text, inputs=radio, outputs=passage_1)
-
-#     passage_2 = gr.Textbox(
-#         label="Passage 2",
-#         placeholder="Enter a passage to compare to passage 1.",
-#         type="text")
-
-#     button = gr.Button(value="Submit")
-
-#     # Connect the button click event to the submit_button_clicked function, passing radio choice
-#     button.click(run_model, inputs=[
-#         model_name, passage_1, passage_2], outputs=gr.Textbox(label="Results"))
-
-#     interface.launch()
-
 app = gr.Interface(
     fn=run_model,
     inputs=[

requirements.txt

@@ -0,0 +1,3 @@
+gradio==4.27.0
+scikit_learn==1.3.0
+sentence_transformers==2.5.1