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import gradio as gr
import torch
import asyncio
from src.model.him_model import HIMModel
from config.model_config import HIMConfig
from config.environment_config import EnvironmentConfig
def initialize_model():
model_config = HIMConfig()
env_config = EnvironmentConfig()
device = torch.device("cuda" if torch.cuda.is_available() and env_config.device == "cuda" else "cpu")
model = HIMModel(model_config.to_dict()).to(device)
return model
async def chat(message: str,
system_message: str = "You are a friendly Chatbot.",
max_tokens: int = 512,
temperature: float = 0.7,
top_p: float = 0.95):
input_data = {
"message": message,
"system_message": system_message,
"parameters": {
"max_tokens": max_tokens,
"temperature": temperature,
"top_p": top_p
}
}
with torch.no_grad():
result = await model.generate_response(input_data)
return result["response"]
model = initialize_model()
interface = gr.Interface(
fn=chat,
inputs=[
gr.Textbox(label="Message"),
gr.Textbox(label="System Message", value="You are a friendly Chatbot."),
gr.Slider(minimum=1, maximum=2048, value=512, label="Max Tokens"),
gr.Slider(minimum=0.1, maximum=1.0, value=0.7, label="Temperature"),
gr.Slider(minimum=0.1, maximum=1.0, value=0.95, label="Top P")
],
outputs=gr.Textbox(label="HIM Response"),
title="Hybrid Intelligence Matrix (HIM)",
description="Interact with the HIM system for advanced cognitive processing"
)
if __name__ == "__main__":
interface.launch(server_name="0.0.0.0", server_port=7860)
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