app.py

import torch
import gradio as gr

# Load your trained Apple model
checkpoint = torch.load("apple_model.pth")
model = YourModelClass(len(checkpoint["word2idx"]))  # replace with your class
model.load_state_dict(checkpoint["model_state"])
word2idx = checkpoint["word2idx"]
idx2word = checkpoint["idx2word"]

# Tokenizer & vectorizer
def tokenize(text):
    return text.lower().split()

def vectorize(sentence):
    vec = torch.zeros(len(word2idx))
    for word in tokenize(sentence):
        if word in word2idx:
            vec[word2idx[word]] += 1
    return vec

# Chat function
def chatbot(input_text):
    x = vectorize(input_text)
    output = model(x)
    top_words = torch.topk(output, 6).indices
    response = " ".join(idx2word[i.item()] for i in top_words)
    return response

# Gradio Interface
iface = gr.Interface(
    fn=chatbot,
    inputs=gr.Textbox(label="You"),
    outputs=gr.Textbox(label="Apple"),
    title="Apple Chatbot",
    description="Chat with Apple, your AI assistant!"
)

iface.launch()