Delete add.py

add.py

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-# Finacial Sentiment Analysis Using Huggingface App
-# Team Name :- Free Thinkers
-# Authors:- Lalit Chaudhary and Khushter Kaifi
-# Update On- 2 Jan 2024
-
-# streamlit is a Python library used for creating web applications with minimal effort.
-# pipeline is a class from the Hugging Face Transformers library that allows you to easily use pre-trained models for various natural language processing (NLP) tasks
-
-import streamlit as st
-from transformers import pipeline
-
-# This line creates a sentiment analysis pipeline using the Hugging Face Transformers library. 
-# The pipeline is pre-configured to perform sentiment analysis on input text.
-# # Load sentiment analysis pipeline
-sentiment_pipeline = pipeline("sentiment-analysis")
-
-# Sets the title of the Streamlit web application
-st.title("Financial Sentiment Analysis Using HuggingFace \n Team Name:- Free Thinkers")
-
-# Displays a text input box where the user can enter a sentence for sentiment analysis.
-st.write("Enter a Sentence to Analyze the Sentiment:")
-user_input = st.text_input("")
-st.write("Press the Enter key")
-
-# Performing Sentiment Analysis:
-# Checks if the user has entered some text. If yes, 
-# it uses the sentiment_pipeline to analyze the sentiment of the input text and stores the result in the result variable.
-
-if user_input:
-    result = sentiment_pipeline(user_input)
-    sentiment = result[0]["label"]
-    confidence = result[0]["score"]
-
-
-# Displaying Results:
-#If there is user input, it displays the sentiment and confidence score. 
-# The sentiment is extracted from the "label" field in the result, and the confidence score is extracted from the "score" field.
-    st.write(f"Sentiment: {sentiment}")
-    st.write(f"Confidence: {confidence:.2%}")