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import gradio as gr
from transformers import GPT2LMHeadModel, GPT2Tokenizer
import torch
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 = model.config.eos_token_id
def chat_with_gpt2(user_input):
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,
num_return_sequences=1,
do_sample=True,
temperature=0.7,
top_k=50,
top_p=0.95,
pad_token_id=tokenizer.eos_token_id
)
response = tokenizer.decode(outputs[0], skip_special_tokens=True)
return response[len(prompt):].strip()
interface = gr.Interface(
fn=chat_with_gpt2,
inputs=gr.Textbox(lines=3, placeholder="Ask about your trip..."),
outputs="text",
title="Trip Planner Chatbot",
description="Ask anything related to your travel plans!"
)
interface.launch()
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