title_optimizer.py

import streamlit as st
from ludwig.api import LudwigModel
import pandas as pd

st.cache(show_spinner=False)
def load_model():
  #Update with the path to the Ludwig trained model
  model = LudwigModel.load("results/experiment_run_1/model/")
  return model

model = load_model()

st.header("Automated Title Tag Optimization Using Deep Learning\nby @hamletbatista")
st.text("This demo uses a Google T5 model trained for Title Tag Optimization")

add_text_sidebar = st.sidebar.title("Menu")
add_text_sidebar = st.sidebar.text("🐍🔥 DISCLAIMER\n You DON'T need to learn Python\n to be a great SEO.")

filename = st.text_input(label="Provide CSV filename with titles and keywords to optimize")

import pandas as pd

if len(filename) > 0 and filename.find(".csv") > 0:
  test_df = pd.read_csv(filename)#("test.csv")

  predictions = model.predict(test_df)

  test_df = test_df.rename(columns={"Simplified_Title": "Original_Title"})
  
  #st.text('Original Titles and Keywords:')
  #st.write(test_df)
  #st.table(test_df)

  st.text('Optimized Titles:')
  pred_df = predictions[0]

  #Clean up titles

  pred_df["Title"] = pred_df["Title_predictions"].apply(lambda x: " ".join(x))

  final_df = test_df.join(pred_df)[["Original_Title", "Keyword", "Title"]].rename(columns={"Title": "Optimized_Title"})

  #st.write(final_df)
  st.table(final_df)