app.py

import torch
from transformers import pipeline, AutoTokenizer
import gradio as gr

# Load models and tokenizer
models = [pipeline("text-generation", model="TinyLlama/TinyLlama-1.1B-Chat-v1.0", device=-1) for _ in range(3)]
tokenizer = models[0].tokenizer

# Function for generating text using the ensemble of models
def generate_text(prompt):
    messages = [
        {"role": "system", "content": "You are a friendly chatbot who always responds in the style of a pirate. Use pirate vocabulary and mannerisms in your replies."},
        {"role": "user", "content": prompt},
    ]
    prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)

    responses = []
    for model in models:
        with torch.no_grad():
            outputs = model(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
            response = outputs[0]['generated_text']
            responses.append(response)

    averaged_text = ''
    for i in range(min(len(response) for response in responses)):
        token_counts = {}
        for response in responses:
            token = response[i]
            token_counts[token] = token_counts.get(token, 0) + 1
        most_frequent_tokens = sorted(token_counts.items(), key=lambda x: x[1], reverse=True)
        averaged_token = most_frequent_tokens[0][0]  # Choose the most frequent token
        averaged_text += averaged_token

    return averaged_text

# Define the Gradio block for the application
block = gr.Blocks()
with block:
    input_text = gr.Textbox(lines=2, label="Enter your prompt")
    output_text = gr.Textbox(label="Generated Text")

    def update_output_text(input_text):
        output_text.value = generate_text(input_text)

    input_text.change(update_output_text, inputs=[input_text], outputs=[output_text])

# Set up the Hugging Face Gradio App with custom styles (optional)
iface = gr.Interface.load("app::block", title="Pirate Chatbot", css="#gradio-container {font-family: 'Courier New', monospace;}")

# Launch the interface when running app.py directly
if __name__ == "__main__":
    iface.launch()