rxh1 commited on
Commit
65625b5
1 Parent(s): 35efa50

Create app.py

Browse files
Files changed (1) hide show
  1. app.py +31 -0
app.py ADDED
@@ -0,0 +1,31 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ from transformers import pipeline
2
+ import streamlit as st
3
+
4
+ classifier = pipeline("text-classification", model="rxh1/Finetune_2")
5
+ text2text = pipeline("text2text-generation", model="facebook/blenderbot_small-90M")
6
+ # Streamlit application title
7
+ st.title("Text Sentiment Classification and Response Generation")
8
+ st.write("Create auto reply for three sentiment: positive, neutral, negative")
9
+
10
+ # Text input for user to enter the text to classify
11
+ text = st.text_area("Enter the text to reply", "")
12
+
13
+ # Perform text classification when the user clicks the "Classify" button
14
+ if st.button("Reply"):
15
+ # Perform text classification on the input text
16
+ result = classifier(text)[0]
17
+
18
+ # Display the classification result
19
+ prediction = result['label']
20
+ st.write("Text:", text)
21
+ st.write("Sentiment:", prediction)
22
+
23
+ # Generate a response based on the classification result
24
+ if prediction == "negative":
25
+ answer = text2text(f"You are the owner of Starbucks and I am the customer and my feeling sentiment is bad.")[0]["generated_text"]
26
+ elif prediction == "neutral":
27
+ answer = text2text(f"You are the owner of Starbucks and I am the customer and my feeling sentiment is peaceful.")[0]["generated_text"]
28
+ else:
29
+ answer = text2text(f"You are the owner of Starbucks and I am the customer and my feeling sentiment is good.")[0]["generated_text"]
30
+
31
+ st.write("Response:", answer)