Update app.py

app.py

@@ -1,73 +1,33 @@
-# from flask import Flask, request, render_template
-# from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
-# import torch
-#
-# # Initialize Flask app
-# app = Flask(__name__)
-#
-# # Load the fine-tuned model and tokenizer
-# model_dir = "./finetune_model"
-# tokenizer = AutoTokenizer.from_pretrained(model_dir)
-# model = AutoModelForSeq2SeqLM.from_pretrained(model_dir)
-# model.eval()  # Set model to evaluation mode
-#
-# # Generate headline from article
-# def generate_headline(article, max_length=128, num_beams=5):
-#     # Tokenize the input article
-#     inputs = tokenizer(article, max_length=256, truncation=True, return_tensors="pt", padding="max_length")
-#
-#     # Move inputs to the same device as the model
-#     input_ids = inputs['input_ids'].to(model.device)
-#     attention_mask = inputs['attention_mask'].to(model.device)
-#
-#     # Generate headline
-#     outputs = model.generate(input_ids, attention_mask=attention_mask, max_length=max_length, num_beams=num_beams, early_stopping=True)
-#     headline = tokenizer.decode(outputs[0], skip_special_tokens=True)
-#
-#     return headline
-#
-# # Home route to render the form and handle POST requests
-# @app.route('/', methods=['GET', 'POST'])
-# def home():
-#     headline = None
-#     if request.method == 'POST':
-#         article = request.form.get('article')
-#         if article:
-#             headline = generate_headline(article)
-#     return render_template('index.html', headline=headline)
-#
-# # Run the app
-# if __name__ == '__main__':
-#     app.run(host='0.0.0.0', port=5000, debug=True)
-
-
-from flask import Flask, render_template, request, jsonify
-from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
-
-app = Flask(__name__)
-
-# Load the fine-tuned model and tokenizer
-model_dir = "./finetune_model"  # Replace with your model's directory
-tokenizer = AutoTokenizer.from_pretrained(model_dir)
-model = AutoModelForSeq2SeqLM.from_pretrained(model_dir)
-
-def generate_headline(article):
-    """
-    Generate a headline from the given article using the fine-tuned model.
-    """
-    inputs = tokenizer.encode(article, return_tensors="pt", max_length=512, truncation=True)
-    outputs = model.generate(inputs, max_length=128, num_beams=5, early_stopping=True)
-    headline = tokenizer.decode(outputs[0], skip_special_tokens=True)
-    return headline
-
-@app.route("/", methods=["GET", "POST"])
-def home():
-    headline = None
-    if request.method == "POST":
-        article = request.form.get("article")
-        if article:
-            headline = generate_headline(article)
-    return render_template("index.html", headline=headline)
-
-if __name__ == "__main__":
-    app.run(debug=False)
+from flask import Flask, render_template, request, jsonify
+from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
+import os
+
+app = Flask(__name__)
+
+# Load the fine-tuned model and tokenizer
+model_dir = "./finetune_model"  # Replace with your model's directory
+tokenizer = AutoTokenizer.from_pretrained(model_dir)
+model = AutoModelForSeq2SeqLM.from_pretrained(model_dir)
+
+def generate_headline(article):
+    """
+    Generate a headline from the given article using the fine-tuned model.
+    """
+    inputs = tokenizer.encode(article, return_tensors="pt", max_length=512, truncation=True)
+    outputs = model.generate(inputs, max_length=128, num_beams=5, early_stopping=True)
+    headline = tokenizer.decode(outputs[0], skip_special_tokens=True)
+    return headline
+
+@app.route("/", methods=["GET", "POST"])
+def home():
+    headline = None
+    if request.method == "POST":
+        article = request.form.get("article")
+        if article:
+            headline = generate_headline(article)
+    return render_template("index.html", headline=headline)
+
+if __name__ == "__main__":
+    # Use dynamic port for compatibility
+    port = int(os.environ.get("PORT", 5000))  # Default to 5000 if no PORT is set
+    app.run(host="0.0.0.0", port=port, debug=False)