Update app.py

app.py

@@ -8,38 +8,47 @@ import seaborn as sns
 from matplotlib.backends.backend_agg import FigureCanvasAgg
 from io import BytesIO
 
-import twitter
+import configparser
+import tweepy
 
-api = twitter.Api(consumer_key='IXpQTCB9vo9IGfOVAPBePE2Wi',
-                    consumer_secret='qD1m4zaAiM6h2T7swBuWboORTXY4cA9eNcgDHlfFAuqKfNTiT3',
-                    access_token_key='1529787212417605634-Io7LlY8AEdZEzOgiAYMb3hZyu9gsLL',
-                    access_token_secret='QGo3eOn7xgPWHusmuP2JDZxkTMPJ51wtgO9wV3PY1b8wm')
+config = configparser.ConfigParser()
+config.read('./config.ini')
+
+api_key = config['twitter']['api_key']
+api_key_secret = config['twitter']['api_key_secret']
+access_token = config['twitter']['access_token']
+access_token_secret = config['twitter']['access_token_secret']
+
+# Authenticate with Twitter
+auth = tweepy.OAuthHandler(api_key, api_key_secret)
+auth.set_access_token(access_token, access_token_secret)
+api = tweepy.API(auth)
+
+tweets = []
 
 
 def drawTweet(tweet,i):
-    # Set the dimensions of the image
+    
     width, height = 1000, 200
     
-    # Create a blank image with a white background
+    
     image = Image.new('RGBA', (width, height), 'white')
 
-    # Get a drawing context
+    
     draw = ImageDraw.Draw(image)
 
-    # Set the font for the tweet text
+    
     font = ImageFont.truetype('arial.ttf',  size=36, encoding='utf-16')
 
     user = tweet.user
 
 
     user_tag = user.screen_name
-    text = tweet.text
+    tweet_text = tweet.full_text
 
 
-    tweet_text = text
-
     words = tweet_text.split()
-    # Insert a newline character after every 10 words
+    
     formatted_string = ''
     for i, word in enumerate(words):
         formatted_string += word+' '
@@ -68,13 +77,12 @@ def drawTweet(tweet,i):
 
 
 def collect_tweets(topic):
-
-    # Search for tweets matching the query
-    tweets = api.GetSearch(term=f"{topic} -filter:retweets", lang='en', result_type="recent", count=100)
-    
-    # Filter out retweets
     
-    tweets.sort(key=lambda tweet: tweet.favorite_count + tweet.retweet_count, reverse=True)
+
+    limit=20
+    tweets = tweepy.Cursor(api.search_tweets,q=f"{topic} -filter:retweets", lang="en", tweet_mode='extended', result_type = 'recent').items(limit)
+
+    tweets = [tweet for tweet in tweets]
 
     images = []
     i = 1
@@ -87,11 +95,12 @@ def collect_tweets(topic):
     return images,sentiment_plot
 
 def sentiment_analysis(tweets,topic):
-            
+        
+        
         tweet_procs = []
         for tweet in tweets:
                 tweet_words = []
-                for word in tweet.text.split(' '):
+                for word in tweet.full_text.split(' '):
                         if word.startswith('@') and len(word) > 1:
                             word = '@user'
                         elif word.startswith('https'):
@@ -104,6 +113,8 @@ def sentiment_analysis(tweets,topic):
         API_URL = "https://api-inference.huggingface.co/models/cardiffnlp/twitter-roberta-base-sentiment"
         headers = {"Authorization": "Bearer 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"}
 
+        print(len(tweet_procs))
+
         def query(payload):
             response = requests.post(API_URL, headers=headers, json=payload)
             return response.json()
@@ -152,10 +163,9 @@ def sentiment_analysis(tweets,topic):
 
 
 
-# Create the Gradio app
+
 app = gr.Interface(fn=collect_tweets, inputs=gr.Textbox(label="Enter a topic for tweets"),  outputs=[gr.Gallery(label="Generated images", show_label=False, elem_id="gallery").style(grid=[2], height="50"), gr.Image(label="Sentiment Analysis Result")])
 
-# Run the app
 app.launch()