Update app.py

app.py

@@ -1,46 +1,9 @@
 import streamlit as st
 
 from transformers import pipeline
-from googletrans import Translator
-from gtts import gTTS
-from playsound import playsound
 
-# Define language models and initialize pipelines
-bart_model_name = "facebook/bart-large"
-bart_pipeline = pipeline("text-generation", model=bart_model_name)
-
-# Define translator
-translator = Translator()
-
-# Function to generate text and translate to desired language
-def generate_and_translate_text(prompt, target_lang):
-    # Generate text
-    generated_text = bart_pipeline(prompt)[0]["generated_text"]
-
-    # Translate text
-    if target_lang != "en":
-        translated_text = translator.translate(generated_text, dest=target_lang).text
-        return translated_text
-    else:
-        return generated_text
-
-# Function to convert text to speech
-def text_to_speech(text):
-    # Create audio file
-    audio_file = gTTS(text)
-    audio_file.save("story.mp3")
-
-    # Play audio file
-    playsound("story.mp3")
-
-# User input
-prompt = input("Enter your story prompt: ")
-target_lang = input("Choose target language (default: English): ")
-
-# Generate and translate story text
-story_text = generate_and_translate_text(prompt, target_lang)
-
-print(f"Story: {story_text}")
-
-# Convert story text to speech
-text_to_speech(story_text)
+pipe = pipeline('sentiment-analysis')
+text = st.text_area('enter some text!')
+if text :
+    out=pipe(text)
+    st.json(out)