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import os
import gradio as gr
import copy
from llama_cpp import Llama
from huggingface_hub import hf_hub_download  
 

llm = Llama(
    model_path = "./dpo-internlm2-1_8b.Q4_K_M.gguf",
    n_ctx=2048,
    n_threads=2,
    seed=57199,
    batch_size=1024,
    cache=True
) 
 

def generate_text(
    message,
    history: list[tuple[str, str]],
    system_message,
    max_tokens,
    temperature,
    top_p,
):
    temp = ""
    input_prompt = f"<s> <|im_start|>system:{system_message}<|im_end|>"
    for interaction in history:
        input_prompt = input_prompt + "<|im_start|>user:" + str(interaction[0]) + "<|im_end|><|im_start|>" + "assistant:" + str(interaction[1]) + "<|im_end|>"

    input_prompt = input_prompt + "<|im_start|>user:" + str(message) + "<|im_end|><|im_start|>assistant:"

    output = llm(
        input_prompt,
        temperature=temperature,
        top_p=top_p,
        top_k=40,
        repeat_penalty=1.2,
        max_tokens=max_tokens,
        stop=["<|im_end|>", "[UNUSED_TOKEN_145]"],
        stream=True,
        
    )
    for out in output:
        stream = copy.deepcopy(out)
        temp += stream["choices"][0]["text"]
        yield temp


demo = gr.ChatInterface(
    generate_text,
    title="DPO-Internlm2-1_8B",
    description="Running LLM with llama-cpp-python",
    theme = gr.themes.Soft(),
    examples=[
        ['How to setup a human base on Mars? Give short answer.'],
        ['Explain theory of relativity to me like I’m 8 years old.'],
        ['What is 9,000 * 9,000?'],
        ['Write a pun-filled happy birthday message to my friend Alex.'],
        ['Justify why a penguin might make a good king of the jungle.']
    ],
    cache_examples=False,
    retry_btn=None,
    undo_btn="Delete Previous",
    clear_btn="Clear",
    additional_inputs=[
        gr.Textbox(value="You are a friendly Chatbot.", label="System message"),
        gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens"),
        gr.Slider(minimum=0.1, maximum=4.0, value=0.3, step=0.1, label="Temperature"),
        gr.Slider(
            minimum=0.1,
            maximum=1.0,
            value=0.90,
            step=0.05,
            label="Top-p (nucleus sampling)",
        ),
    ],
)


if __name__ == "__main__":
    demo.launch()