import re

import gradio as gr
import spaces
import torch
from transformers import AutoModelForCausalLM, AutoTokenizer


MODEL_ID = "shibsankardhara2/Qwen2.5-Coder-1.5B-Java-CSharp_V5"

print("Loading tokenizer...")
tokenizer = AutoTokenizer.from_pretrained(MODEL_ID)

if tokenizer.pad_token_id is None:
    tokenizer.pad_token_id = tokenizer.eos_token_id

print("Loading model on CPU...")
model = AutoModelForCausalLM.from_pretrained(
    MODEL_ID,
    torch_dtype=torch.float16,
    low_cpu_mem_usage=True,
)

model.eval()
print("Model loaded successfully.")


def add_java_hint(instruction: str) -> str:
    instruction = instruction.strip()

    if "java" in instruction.lower():
        return instruction

    return f"{instruction} Write the solution in Java."


def build_prompt(task: str, user_input: str) -> str:
    user_input = user_input.strip()

    if task == "Natural Language → Java":
        return (
            "### Instruction:\n\n"
            f"{add_java_hint(user_input)}\n\n"
            "### Response:\n\n"
        )

    return (
        "### Instruction\n"
        "Translate the following Java code into equivalent C#. "
        "Write the solution in C#.\n\n"
        "### Java\n"
        f"{user_input}\n\n"
        "### Response\n"
    )


def clean_output(text: str) -> str:
    text = text.strip()

    fenced = re.search(
        r"```(?:java|csharp|cs|c#)?\s*(.*?)```",
        text,
        flags=re.DOTALL | re.IGNORECASE,
    )

    if fenced:
        text = fenced.group(1).strip()

    stop_markers = [
        "### Instruction:",
        "### Instruction\n",
        "### Java:",
        "### Java\n",
        "### Response:",
        "### Response\n",
        "<|im_start|>",
        "<|im_end|>",
    ]

    for marker in stop_markers:
        if marker in text:
            text = text.split(marker, 1)[0].strip()

    return text


@spaces.GPU(duration=120)
def generate_code(task: str, user_input: str) -> str:
    if not user_input or not user_input.strip():
        return "Please enter a requirement or Java code."

    prompt = build_prompt(task, user_input)

    max_new_tokens = 300 if task == "Natural Language → Java" else 400

    try:
        model.to("cuda")

        inputs = tokenizer(
            prompt,
            return_tensors="pt",
            truncation=True,
            max_length=2048,
        ).to("cuda")

        with torch.inference_mode():
            outputs = model.generate(
                **inputs,
                max_new_tokens=max_new_tokens,
                do_sample=False,
                pad_token_id=tokenizer.eos_token_id,
                eos_token_id=tokenizer.eos_token_id,
            )

        generated_tokens = outputs[0][inputs["input_ids"].shape[1]:]

        generated_text = tokenizer.decode(
            generated_tokens,
            skip_special_tokens=True,
        )

        code = clean_output(generated_text)

        if not code:
            return "The model returned an empty response. Please try again."

        language = "java" if task == "Natural Language → Java" else "csharp"

        return f"```{language}\n{code}\n```"

    except Exception as error:
        return f"Generation failed: {type(error).__name__}: {error}"

    finally:
        model.to("cpu")
        torch.cuda.empty_cache()


def update_input(task: str):
    if task == "Natural Language → Java":
        return gr.update(
            label="Natural-language requirement",
            placeholder=(
                "Example: Write a Java method to check whether "
                "a number is prime."
            ),
            value="",
        )

    return gr.update(
        label="Java code",
        placeholder=(
            "Example:\n"
            "public static int factorial(int n) {\n"
            "    int result = 1;\n"
            "    for (int i = 2; i <= n; i++) {\n"
            "        result *= i;\n"
            "    }\n"
            "    return result;\n"
            "}"
        ),
        value="",
    )


with gr.Blocks(title="Java and C# CodeGen") as demo:
    gr.Markdown(
        """
# Java and C# CodeGen

Generate Java code from natural-language requirements or translate Java code
into equivalent C# using a fine-tuned Qwen2.5-Coder model.
"""
    )

    task = gr.Dropdown(
        choices=[
            "Natural Language → Java",
            "Java → C#",
        ],
        value="Natural Language → Java",
        label="Select task",
    )

    user_input = gr.Textbox(
        label="Natural-language requirement",
        placeholder=(
            "Example: Write a Java method to check whether "
            "a number is prime."
        ),
        lines=14,
    )

    generate_button = gr.Button(
        "Generate Code",
        variant="primary",
    )

    output = gr.Markdown()

    task.change(
        fn=update_input,
        inputs=task,
        outputs=user_input,
    )

    generate_button.click(
        fn=generate_code,
        inputs=[
            task,
            user_input,
        ],
        outputs=output,
    )

    gr.Examples(
        examples=[
            [
                "Natural Language → Java",
                "Write a Java method to calculate factorial of a number using a loop.",
            ],
            [
                "Natural Language → Java",
                "Write a Java method to reverse a string.",
            ],
            [
                "Java → C#",
                """public static int factorial(int n) {
    int result = 1;
    for (int i = 2; i <= n; i++) {
        result *= i;
    }
    return result;
}""",
            ],
        ],
        inputs=[
            task,
            user_input,
        ],
    )


if __name__ == "__main__":
    demo.queue(
        default_concurrency_limit=1,
        max_size=10,
    ).launch()