Update app.py

app.py

@@ -1,12 +1,68 @@
+# -*- coding: utf-8 -*-
+"""Copy of [Student]_Module_2_Session_3.ipynb
+
+Automatically generated by Colab.
+
+Original file is located at
+    https://colab.research.google.com/drive/1pmME28f5Z7SNxUoX5va3W-90XP5zPnQu
+
+Installations
+"""
+
+!pip install gradio --quiet
+!pip install transformers --quiet
+
+"""#Let's build a demo for a sentiment analysis task !
+
+Import the necessary modules :
+"""
+
+from transformers import pipeline
 import gradio as gr
 
-description = "Story generation with GPT-2"
-title = "Generate your own story"
-examples = [["Adventurer is approached by a mysterious stranger in the tavern for a new quest."]]
+"""Import the pipeline :"""
+
+sentiment = pipeline("sentiment-analysis")
+
+"""Test the pipeline on these reviews (you can also test on your own reviews) :"""
+
+#"I really enjoyed my stay !"
+#"Worst rental I ever got"
+
+sentiment("I really enjoyed my stay !")
+
+"""What is the format of the output ? How can you get only the sentiment or the confidence score ?"""
+
+print(sentiment("I really enjoyed my stay !")[0]['label'])
+print(sentiment("I really enjoyed my stay !")[0]['score'])
+print(sentiment("Worst rental I ever got")[0]['label'])
+print(sentiment("Worst rental I ever got")[0]['score'])
+
+"""Create a function that takes a text in input, and returns a sentiment, and a confidence score as 2 different variables"""
+
+def get_sentiment(text):
+  return sentiment(text)[0]['label'], sentiment(text)[0]['score']
+
+"""Build an interface for the app using Gradio."""
+The customer wants this result :
+
+interface = gr.Interface(fn=get_sentiment,
+                         inputs=gr.Textbox(lines=1, label="Enter the review:"),
+                         outputs=[gr.Text(label='Sentiment:'),
+                                  gr.Text(label='Score:')])
+
+interface.launch()
+
+ar_sentiment = pipeline("sentiment-analysis", model='CAMeL-Lab/bert-base-arabic-camelbert-da-sentiment')
+
+ar_sentiment('انا احب ذلك')
+
+def get_ar_sentiment(text):
+  return ar_sentiment(text)[0]['label'], ar_sentiment(text)[0]['score']
 
-interface = gr.Interface.load("huggingface/pranavpsv/gpt2-genre-story-generator",
-            description=description,
-            examples=examples
-)
+interface = gr.Interface(fn=get_ar_sentiment,
+                         inputs=gr.Textbox(lines=1, label="Enter the review:"),
+                         outputs=[gr.Text(label='Sentiment:'),
+                                  gr.Text(label='Score:')])
 
 interface.launch()