Update app.py

app.py

@@ -2,18 +2,16 @@ import gradio as gr
 from transformers import GPT2LMHeadModel, GPT2Tokenizer
 import torch
 
-model_name = "mrm8488/GPT-2-finetuned-on-travel"
+model_name = "mrm8488/gpt2-finetuned-jhegarty-texts"
 tokenizer = GPT2Tokenizer.from_pretrained(model_name)
 model = GPT2LMHeadModel.from_pretrained(model_name)
 
 tokenizer.pad_token = tokenizer.eos_token
-model.config.pad_token_id = tokenizer.eos_token_id
-
-# Warm-up
-_ = model.generate(tokenizer.encode("Hello", return_tensors="pt"))
+model.config.pad_token_id = model.config.eos_token_id
 
 def chat_with_gpt2(user_input):
-    inputs = tokenizer.encode(user_input, return_tensors="pt", truncation=True, max_length=512)
+    prompt = f"You are a helpful travel assistant. Answer concisely and informatively. Question: {user_input}\nAnswer:"
+    inputs = tokenizer.encode(prompt, return_tensors="pt", truncation=True, max_length=512)
     outputs = model.generate(
         inputs,
         max_length=250,
@@ -25,14 +23,14 @@ def chat_with_gpt2(user_input):
         pad_token_id=tokenizer.eos_token_id
     )
     response = tokenizer.decode(outputs[0], skip_special_tokens=True)
-    return response[len(user_input):].strip()
+    return response[len(prompt):].strip()
 
 interface = gr.Interface(
     fn=chat_with_gpt2,
-    inputs=gr.Textbox(lines=3, placeholder="Ask me about your trip..."),
+    inputs=gr.Textbox(lines=3, placeholder="Ask about your trip..."),
     outputs="text",
     title="Trip Planner Chatbot",
-    description="Ask me travel questions or get suggestions for your trip!"
+    description="Ask anything related to your travel plans!"
 )
 
 interface.launch()