Update app.py

app.py

@@ -10,16 +10,6 @@ fine_tuned_tokenizer = GPT2Tokenizer.from_pretrained(model_dir)
 # Create a text-generation pipeline
 generator = pipeline('text-generation', model=fine_tuned_model, tokenizer=fine_tuned_tokenizer)
 
-# Function to dynamically truncate output while keeping it meaningful
-def truncate_tweet(tweet, max_length=280):
-    # Ensure the tweet is concise, ending on a complete sentence
-    if len(tweet) > max_length:
-        tweet = tweet[:max_length]
-        last_period = tweet.rfind(".")
-        if last_period != -1:
-            tweet = tweet[:last_period + 1]
-    return tweet.strip()
-
 # Function to intelligently add relevant hashtags and emojis
 def add_relevant_tags(tweet, input_question):
     # Pre-defined mappings of topics to hashtags and emojis
@@ -54,20 +44,23 @@ def generate_tweet(input_question):
     # Format the input without "Question:" and "Answer:"
     prompt = input_question.strip()
     
-    # Generate the output with a higher max_length for longer responses
+    # Generate the output with a max length of around 200 to 280 characters
     output = generator(prompt, max_length=300, num_return_sequences=1, temperature=0.7, top_p=0.9)
     
-    # Extract the generated text and clean it
+    # Extract the generated text
     tweet = output[0]['generated_text']
     
-    # Remove "Question:" and "Answer:" from the generated text
-    tweet = re.sub(r"(Question:|Answer:|A:|)", "", tweet).strip()
-
-    # Remove any part of the tweet that starts with the input question
-    tweet = tweet.replace(input_question, "").strip()
+    # Ensure the tweet is between 200 and 280 characters
+    tweet_length = len(tweet)
+    if tweet_length > 280:
+        tweet = tweet[:280]
+        last_period = tweet.rfind(".")
+        if last_period != -1:
+            tweet = tweet[:last_period + 1]
+    elif tweet_length < 200:
+        tweet = tweet.ljust(200)
 
-    # Truncate and add relevant hashtags and emojis
-    tweet = truncate_tweet(tweet)
+    # Add relevant hashtags and emojis
     tweet = add_relevant_tags(tweet, input_question) 
 
     return tweet