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

# Fix for Python 3.13: audioop was removed from the standard library.
# This try/except block handles the missing dependency if audioop-lts is installed.
try:
    import audioop
except ImportError:
    try:
        import audioop_lts as audioop
    except ImportError:
        print("Warning: audioop not found. If Gradio fails to load, install 'audioop-lts'.")

# 1. Download the model correctly
# Repo: unsloth/NVIDIA-Nemotron-3-Nano-4B-GGUF
# File: NVIDIA-Nemotron-3-Nano-4B-Q4_K_M.gguf
model_path = hf_hub_download(
    repo_id=os.environ.get("REPO_ID", "unsloth/NVIDIA-Nemotron-3-Nano-4B-GGUF"),
    filename=os.environ.get("MODEL_FILE", "NVIDIA-Nemotron-3-Nano-4B-Q4_K_M.gguf"),
)

# 2. Initialize the Llama model
llm = Llama(
    model_path=model_path,
    n_ctx=2048,
    n_gpu_layers=-1, # -1 uses all available GPU layers, change to 0 for CPU only
) 

def generate_text(
    message,
    history: list[tuple[str, str]],
    system_message,
    max_tokens,
    temperature,
    top_p,
):
    temp = ""
    # Standard ChatML / Llama format logic
    input_prompt = f"[INST] <<SYS>>\n{system_message}\n<</SYS>>\n\n "
    for interaction in history:
        input_prompt += f"{interaction[0]} [/INST] {interaction[1]} </s><s> [INST] "
    
    input_prompt += f"{message} [/INST] "

    output = llm(
        input_prompt,
        temperature=temperature,
        top_p=top_p,
        top_k=40,
        repeat_penalty=1.1,
        max_tokens=max_tokens,
        stop=[
            "[/INST]",
            "</s>",
            "<|endoftext|>",
            "USER:",
            "ASSISTANT:",
        ],
        stream=True,
    )
    
    for out in output:
        stream = copy.deepcopy(out)
        temp += stream["choices"][0]["text"]
        yield temp

# 3. Define the Gradio Interface
demo = gr.ChatInterface(
    generate_text,
    title="NVIDIA Nemotron-3 Nano (Llama-cpp)",
    description="Running NVIDIA Nemotron-3-Nano-4B via 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?']
    ],
    cache_examples=False,
    additional_inputs=[
        gr.Textbox(value="You are a helpful and friendly AI assistant.", label="System message"),
        gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens"),
        gr.Slider(minimum=0.1, maximum=2.0, 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"),
    ],
)

if __name__ == "__main__":
    demo.launch(server_name="0.0.0.0", server_port=7860)