semsearch.py

import numpy as np
import torch
import pandas as pd
import translate
import gradio as gr

# data = pd.read_csv("./embedding_data.csv")
# embeddings = np.load("./embeddings.npy")

def normalize_vector(v):
    norm = np.linalg.norm(v)
    if norm == 0:
        return v
    return v / norm


def embed_one(model, tokenizer, text, normalize=True):
    tokens = tokenizer(text, return_tensors="pt", truncation=True)
    with torch.no_grad():
        embedding = model.model.encoder(**tokens).last_hidden_state.mean(axis=1)
        embedding = embedding.detach().numpy()[0]

    if normalize:
        return normalize_vector(embedding)
    else:
        return embedding


def knn(query_embedding, embeddings, df, k=5, hebrew=True):
    sims = np.dot(embeddings, query_embedding.T)
    outs = np.argsort(sims, axis=0)[-k:][::-1]
    select = outs.ravel()
    if hebrew:
        return df.iloc[select][["arabic", "hebrew", "validated"]]
    else:
        return df.iloc[select][["arabic", "english", "validated"]]

def run_knn(text, k=5):
    print(text)
    query_embedding = embed_one(translate.model_from_ar,
                                translate.tokenizer_from_ar, text)
    return knn(query_embedding, embeddings, data, k=k, hebrew=True)


def style_dataframe(df):
    styled_df = df.style.set_properties(**{
        'font-family': 'Arial, sans-serif',
        'font-size': '20px',
        'text-align': 'right',
        'direction': 'rtl',
        'align': 'right'
    }).set_table_styles([
    {'selector': 'th', 'props': [('text-align', 'right')]}
])
    return styled_df


def style_dataframe(df):
    return df.style.set_table_styles([
        {'selector': 'thead', 'props': [('text-align', 'right')]},
        {'selector': '.index_name', 'props': [('text-align', 'right')]},
    ]).set_properties(**{
        'text-align': 'right',
    })  # Replace 'column_name' with your actual column name


def update_df(hidden_arabic):
    df = run_knn(hidden_arabic, 100)
    # replace true and false in validated column with checkmark and x emoji
    df["validated"] = df["validated"].apply(lambda x: "✅" if x else "❌")
    # replace name validated with "מאומת"
    df = df.rename(columns={"validated": "מאומת"})
    # replace name arabic with "ערבית"
    df = df.rename(columns={"arabic": "ערבית"})
    # replace name hebrew with "עברית"
    df = df.rename(columns={"hebrew": "עברית"})
    styled_df = style_dataframe(df)
    return gr.DataFrame(value=styled_df, visible=True)