diff --git a/requirements.txt b/requirements.txt
index 502d7d1a0d19..151bd8f69a39 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -1,3 +1,9 @@
 altair
 pandas
 streamlit
+transformers
+torch
+GoogleBard
+langchain
+ProGPT
+edge-tts
\ No newline at end of file
diff --git a/streamlit_app.py b/streamlit_app.py
index 7a0ed1272052..de0ac2066739 100644
--- a/streamlit_app.py
+++ b/streamlit_app.py
@@ -1,40 +1,13 @@
-import altair as alt
-import numpy as np
-import pandas as pd
 import streamlit as st
+from transformers import pipeline
 
-"""
-# Welcome to Streamlit!
+# Load the text-to-speech pipeline
+tts_pipeline = pipeline("text-to-speech")
 
-Edit `/streamlit_app.py` to customize this app to your heart's desire :heart:.
-If you have any questions, checkout our [documentation](https://docs.streamlit.io) and [community
-forums](https://discuss.streamlit.io).
+# Text input field
+text_input = st.text_input("Enter text to be spoken:")
 
-In the meantime, below is an example of what you can do with just a few lines of code:
-"""
-
-num_points = st.slider("Number of points in spiral", 1, 10000, 1100)
-num_turns = st.slider("Number of turns in spiral", 1, 300, 31)
-
-indices = np.linspace(0, 1, num_points)
-theta = 2 * np.pi * num_turns * indices
-radius = indices
-
-x = radius * np.cos(theta)
-y = radius * np.sin(theta)
-
-df = pd.DataFrame({
-    "x": x,
-    "y": y,
-    "idx": indices,
-    "rand": np.random.randn(num_points),
-})
-
-st.altair_chart(alt.Chart(df, height=700, width=700)
-    .mark_point(filled=True)
-    .encode(
-        x=alt.X("x", axis=None),
-        y=alt.Y("y", axis=None),
-        color=alt.Color("idx", legend=None, scale=alt.Scale()),
-        size=alt.Size("rand", legend=None, scale=alt.Scale(range=[1, 150])),
-    ))
+# Generate audio and play it
+if text_input:
+    audio = tts_pipeline(text_input)
+    st.audio(audio)