import gradio as gr
from huggingface_hub import hf_hub_download
from llama_cpp import Llama
import re
from datasets import load_dataset
import random
import logging
import os
import autopep8
import textwrap

# Set up logging
logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(__name__)

# Model settings
MODEL_NAME = "leetmonkey_peft__q8_0.gguf"
REPO_ID = "sugiv/leetmonkey-peft-gguf"

def download_model(model_name):
    logger.info(f"Downloading model: {model_name}")
    model_path = hf_hub_download(
        repo_id=REPO_ID,
        filename=model_name,
        cache_dir="./models",
        force_download=True,
        resume_download=True
    )
    logger.info(f"Model downloaded: {model_path}")
    return model_path

# Download and load the 8-bit model at startup
model_path = download_model(MODEL_NAME)
llm = Llama(
    model_path=model_path,
    n_ctx=1024,
    n_threads=8,
    n_gpu_layers=-1,  # Use all available GPU layers
    verbose=False,
    n_batch=512,
    mlock=True
)
logger.info("8-bit model loaded successfully")

# Load the dataset
dataset = load_dataset("sugiv/leetmonkey_python_dataset")
train_dataset = dataset["train"]

# Generation parameters
generation_kwargs = {
    "max_tokens": 512,
    "stop": ["```", "### Instruction:", "### Response:"],
    "echo": False,
    "temperature": 0.05,
    "top_k": 10,
    "top_p": 0.9,
    "repeat_penalty": 1.1
}

def generate_solution(instruction):
    system_prompt = "You are a Python coding assistant specialized in solving LeetCode problems. Provide only the complete implementation of the given function. Ensure proper indentation and formatting. Do not include any explanations or multiple solutions."
    full_prompt = f"""### Instruction:
{system_prompt}

Implement the following function for the LeetCode problem:

{instruction}

### Response:
Here's the complete Python function implementation:

```python
"""
    
    for chunk in llm(full_prompt, stream=True, **generation_kwargs):
        yield chunk["choices"][0]["text"]

def extract_and_format_code(text):
    # Extract code between triple backticks
    code_match = re.search(r'```python\s*(.*?)\s*```', text, re.DOTALL)
    if code_match:
        code = code_match.group(1)
    else:
        code = text

    # Dedent the code to remove any common leading whitespace
    code = textwrap.dedent(code)

    # Split the code into lines
    lines = code.split('\n')

    # Ensure proper indentation
    indented_lines = []
    for line in lines:
        if line.strip().startswith('class') or line.strip().startswith('def'):
            indented_lines.append(line)  # Keep class and function definitions as is
        elif line.strip():  # If the line is not empty
            indented_lines.append('    ' + line)  # Add 4 spaces of indentation
        else:
            indented_lines.append(line)  # Keep empty lines as is

    formatted_code = '\n'.join(indented_lines)

    try:
        return autopep8.fix_code(formatted_code)
    except:
        return formatted_code


def select_random_problem():
    return random.choice(train_dataset)['instruction']

def stream_solution(problem):
    logger.info("Generating solution")
    generated_text = ""
    for token in generate_solution(problem):
        generated_text += token
        yield generated_text
    
    formatted_code = extract_and_format_code(generated_text)
    logger.info("Solution generated successfully")
    yield formatted_code

with gr.Blocks() as demo:
    gr.Markdown("# LeetCode Problem Solver (8-bit GGUF Model)")
    
    with gr.Row():
        with gr.Column():
            problem_display = gr.Textbox(label="LeetCode Problem", lines=10)
            select_problem_btn = gr.Button("Select Random Problem")
        
        with gr.Column():
            solution_display = gr.Code(label="Generated Solution", language="python", lines=25)
            generate_btn = gr.Button("Generate Solution")
    
    select_problem_btn.click(select_random_problem, outputs=problem_display)
    generate_btn.click(stream_solution, inputs=[problem_display], outputs=solution_display)

if __name__ == "__main__":
    logger.info("Starting Gradio interface")
    demo.launch(share=True)