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import argparse | |
import gradio as gr | |
from ui import chat | |
def main(args): | |
demo = gr.ChatInterface( | |
fn=chat, | |
examples=["hello", "how are you?", "What is Large Language Model?"], | |
title="Gradio π€ TGI", | |
description="This space is a template that you can fork/duplicate for your own usage. " | |
"This space let you build LLM powered idea on top of [Gradio](https://www.gradio.app/) " | |
"and open LLM served locally by [TGI(Text Generation Inference)](https://huggingface.co/docs/text-generation-inference/en/index). " | |
"To use this space, [duplicate]() this space, set which model you want to use (i.e. mistralai/Mistral-7B-Instruct-v0.2), then " | |
"you are all good to go. Just focus on the implementation of your idea π‘. For your convenience, this space also provides " | |
"some handy [utility functions](https://huggingface.co/spaces/chansung/gradio_together_tgi/blob/main/app/gen/openllm.py) to aynchronously generate text by interacting with the locally served LLM.", | |
multimodal=False | |
) | |
demo.queue().launch(server_name="0.0.0.0", server_port=args.port) | |
if __name__ == "__main__": | |
parser = argparse.ArgumentParser(description="This is my Gradio app's description") | |
parser.add_argument("--port", type=int, default=7860, help="Port to expose Gradio app") | |
args = parser.parse_args() | |
main(args) | |