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

llm = Llama(
    model_path=hf_hub_download(
        repo_id=os.environ.get("REPO_ID", "Lyte/Llama-3.1-8B-Instruct-Reasoner-1o1_v0.3"),
        filename=os.environ.get("MODEL_FILE", "unsloth.Q4_K_M.gguf"),
    ),
    n_ctx=4096,
    n_gpu_layers=-1,
)

# Updated training prompt
training_prompt = """<|start_header_id|>system<|end_header_id|>
You are a world-class AI system, capable of complex reasoning and reflection and correcting your mistakes. Reason through the query/question, and then provide your final response. If you detect that you made a mistake in your reasoning at any point, correct yourself.<|eot_id|><|start_header_id|>user<|end_header_id|>
{}<|eot_id|><|start_header_id|>assistant<|end_header_id|>
{}"""

EOS_TOKEN = "<|eot_id|>"

def generate_text(
    message,
    history: list[tuple[str, str]],
    max_tokens,
    temperature,
    top_p,
):
    temp = ""
    input_prompt = ""
    for user_input, assistant_response in history:
        input_prompt += training_prompt.format(user_input, assistant_response)
    input_prompt += training_prompt.format(message, "")
    
    output = llm(
        input_prompt,
        temperature=temperature,
        top_p=top_p,
        top_k=40,
        repeat_penalty=1.1,
        max_tokens=max_tokens,
        stop=[
            EOS_TOKEN,
            "<|endoftext|>"
        ],
        stream=True,
    )
    
    # Stream and yield the response
    for out in output:
        stream = copy.deepcopy(out)
        temp += stream["choices"][0]["text"]
        yield temp

demo = gr.ChatInterface(
    generate_text,
    title="Llama-3.1-8B-Instruct-Reasoner",
    description="Running LLM with https://github.com/abetlen/llama-cpp-python",
    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.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens"),
        gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"),
        gr.Slider(
            minimum=0.1,
            maximum=1.0,
            value=0.95,
            step=0.05,
            label="Top-p (nucleus sampling)",
        ),
    ],
)

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