import gradio as gr
from sentence_transformers import SentenceTransformer
import pandas as pd

model = SentenceTransformer('all-MiniLM-L6-v2')

sentences = [
        "This is the first sentence.",
        "Here is another sentence for embedding.",
        "Sentence Transformers are powerful for semantic search."
]


embeddings = model.encode(sentences)

df = pd.DataFrame({'sentence': sentences, 'embedding': list(embeddings)})

df.to_csv('sentence_embeddings.csv', index=False)
def greet(name):
  return "Hello " + name + "!!"

demo = gr.Interface(fn=greet, inputs="text", outputs="text")
demo.launch()