Create app.py

app.py

@@ -0,0 +1,35 @@
+from flask import Flask, render_template, request, jsonify
+import torch
+from transformers import GPT2LMHeadModel, GPT2Tokenizer
+
+app = Flask(__name__)
+
+# Load the LSTM-based language model
+model_path = "your_model.pth"  # Replace with your model path
+tokenizer = GPT2Tokenizer.from_pretrained("gpt2")
+model = GPT2LMHeadModel.from_pretrained("gpt2")
+model.load_state_dict(torch.load(model_path))
+
+# Set the model to evaluation mode
+model.eval()
+
+# Function to generate text using the model
+def generate_text(prompt):
+    input_ids = tokenizer.encode(prompt, return_tensors="pt")
+    output = model.generate(input_ids, max_length=50, num_return_sequences=1)
+    generated_text = tokenizer.decode(output[0], skip_special_tokens=True)
+    return generated_text
+
+@app.route("/")
+def home():
+    return render_template("index.html")
+
+@app.route("/generate", methods=["POST"])
+def generate():
+    data = request.json
+    user_input = data["input_text"]
+    generated_text = generate_text(user_input)
+    return jsonify({"generated_text": generated_text})
+
+if __name__ == "__main__":
+    app.run(debug=True)