app.py

from sentence_transformers import SentenceTransformer, SimilarityFunction

import streamlit as st

model_name = "nomic-ai/nomic-embed-text-v2-moe"
with st.form("embedding"):
    sentence1 = st.text_inupt(label="Sentence 1:",value="Hello!")
    sentence2 = st.text_inupt(label="Sentence 2:",value="¡Hola!")
    sim_fun = st.selectbox('Similarity Function', ['COSINE', 'DOT_PRODUCT', 'EUCLIDEAN', 'MANHATTAN'])
    calculate = st.form_submit_button('Calculate')

if calculate:
    model = SentenceTransformer(model_name, trust_remote_code=True)
    sentences = [sentence1, sentence2]
    embeddings = model.encode(sentences, prompt_name="passage")

    similarity_fn_enum = getattr(SimilarityFunction, sim_fun)
    model.similarity_fn_name = similarity_fn_enum

    similarities = model.similarity(embeddings[0], embeddings[1])
    st.write(f"similarity: {similarities}")