Delete pipeline.py

pipeline.py

@@ -1,24 +0,0 @@
-from transformers import pipeline
-from utils import clean_text, generate_wordcloud
-
-# Load Hugging Face models
-sentiment_model = pipeline("sentiment-analysis", model="distilbert-base-uncased-finetuned-sst-2-english")
-summarizer = pipeline("summarization", model="sshleifer/distilbart-cnn-12-6")
-
-def process_comment(text):
-    # Clean text
-    cleaned = clean_text(text)
-
-    # Sentiment
-    sentiment = sentiment_model(cleaned)[0]
-
-    # Summary
-    try:
-        summary = summarizer(cleaned, max_length=60, min_length=10, do_sample=False)[0]["summary_text"]
-    except:
-        summary = "Summary not available (text too short)."
-
-    # Word cloud
-    wc_img = generate_wordcloud(cleaned)
-
-    return sentiment, summary, wc_img