Update app.py

app.py

@@ -2,7 +2,6 @@ import streamlit as st
 import pandas as pd
 import torch  # Ensure PyTorch is imported
 from transformers import AutoTokenizer, AutoModelForCausalLM
-import speech_recognition as sr
 
 # Load the Netflix dataset from CSV
 @st.cache_data
@@ -31,36 +30,15 @@ def search_movie_details(query, data):
     
     return results
 
-# Function to convert voice to text
-def voice_to_text():
-    recognizer = sr.Recognizer()
-    with sr.Microphone() as source:
-        st.write("Speak now...")
-        audio = recognizer.listen(source)
-        try:
-            return recognizer.recognize_google(audio)
-        except sr.UnknownValueError:
-            return "Sorry, I could not understand the audio."
-        except sr.RequestError:
-            return "Sorry, the speech service is down."
-
 # Streamlit App
-st.title("Netflix Movie Details Chatbot 🎬")
+st.title("Netflix Movies 🎬")
 
 # Load dataset and model
 data = load_data()
 tokenizer, model = load_model()
 
-# Input options: Text or Voice
-input_option = st.radio("Choose input method:", ("Text", "Voice"))
-
-user_input = ""
-if input_option == "Text":
-    user_input = st.text_input("Enter the movie name, director, or cast:")
-elif input_option == "Voice":
-    if st.button("Start Recording"):
-        user_input = voice_to_text()
-        st.write(f"You said: {user_input}")
+# User Input (Only Text)
+user_input = st.text_input("Enter the movie name, director, or cast:")
 
 # Generate response
 if user_input:
@@ -80,5 +58,3 @@ if user_input:
             st.write("---")
     else:
         st.write("**I have no data about this movie. Please search another movie.**")
-
-