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# Copyright (C) #
# 2025-June Sen Li (Sen.Li.Sprout@gmail.com) #
# Permission given to modify the code only for Non-Profit Research #
# as long as you keep this declaration at the top #
#########################################################################
import os
import gradio as gr
import huggingface_hub
import sentence_transformers
# ----------------------------------------------------------------------------------------------------------------------
def func_ClearInputs(): return "", "", ""
def func_sBERT_SimilarityResult(str_Text_1, str_Text_2):
if not str_Text_1.strip() or not str_Text_2.strip():
return "Both text inputs must be non-empty."
# 01. Load SBERT model (you can choose other pre-trained models too)
inferenceClient = huggingface_hub.InferenceClient(provider="hf-inference")
# 02. Get sentence embeddings
str_ModelID_sBERT = "sentence-transformers/all-MiniLM-L6-v2"
arrEmbedding_Text_1 = inferenceClient.feature_extraction(text=str_Text_1, model=str_ModelID_sBERT)
arrEmbedding_Text_2 = inferenceClient.feature_extraction(text=str_Text_2, model=str_ModelID_sBERT)
# 03. Compute cosine similarity
tensor_Similarity = sentence_transformers.util.pytorch_cos_sim(arrEmbedding_Text_1, arrEmbedding_Text_2)
f_Similarity = tensor_Similarity.item()
return f"sBERT Similarity Score: {f_Similarity:.4f}"
# ----------------------------------------------------------------------------------------------------------------------
# Launch the interface and MCP server
if __name__ == "__main__":
print(f"os.getcwd() = {os.getcwd()}")
os.system(f"echo ls -al {os.getcwd()} && ls -al {os.getcwd()}")
os.system(f"echo ls -al /: && ls -al /")
os.system(f"echo ls -al /home/: && ls -al /home/")
# 03. Gradio UI elements
with gr.Blocks() as grBlocks_SentenceSimilarity__MCP_Server:
gr.Markdown("# Sentence-BERT (sBERT) for Text Similarity using HF Inference Server")
gr.Markdown("### This MCP-Server works for MCP-Client https://huggingface.co/spaces/AllIllusion/MCP-Client_SyntheticText_Similarity")
gr.Markdown("This application calculates sBERT Similarity Score between two Texts")
with gr.Row():
grTextBox_Input_1 = gr.Textbox(label="Text Panel 1", lines=20)
grTextBox_Input_2 = gr.Textbox(label="Text Panel 2", lines=20)
with gr.Row():
with gr.Column(scale=1):
grButton_Clear = gr.Button("Clear")
grButton_Submit = gr.Button("Submit")
with gr.Column(scale=3):
grTextbox_Output = gr.Textbox(label="Similarity Result", interactive=False)
# Set button functionality
grButton_Submit.click(fn=func_sBERT_SimilarityResult, inputs=[grTextBox_Input_1, grTextBox_Input_2], outputs=grTextbox_Output)
grButton_Clear.click(fn=func_ClearInputs, inputs=[], outputs=[grTextBox_Input_1, grTextBox_Input_2, grTextbox_Output])
# 04. Launch Gradio MCP server
grBlocks_SentenceSimilarity__MCP_Server.launch(mcp_server=True, share=True) |