# Gradio UI
import re
import gradio as gr
import tempfile
import os
from openai import OpenAI
from dotenv import load_dotenv
import subprocess
import shutil
from timeit import default_timer as timer

def install_rust():
    subprocess.run("curl --proto '=https' --tlsv1.2 -sSf https://sh.rustup.rs | sh -s -- -y", shell=True)
    subprocess.run("source $HOME/.cargo/env", shell=True)

install_rust()

# Load environment variables

os.environ['PATH'] += f':{os.path.expanduser("~/.cargo/bin")}'

load_dotenv()
os.environ['OPENAI_API_KEY'] = os.getenv('OPENAI_API_KEY')
OPENAI_MODEL = "gpt-4o"

# TranslateCode and ExecuteCode class implementations

class TranslateCode:
    def __init__(self, openai_client, model):
        self.openai = openai_client
        self.model = model

    def user_prompt_for(self, python, lang_select):
        user_prompt = f"Rewrite this Python code in {lang_select} with the fastest possible implementation that produces identical output in the least time. "
        user_prompt += f"Respond only with {lang_select} code; do not explain your work; only return {lang_select} code. "
        user_prompt += "Pay attention to number types to ensure no int overflows. Remember to include all necessary dependencies and libraries.\n\n"
        user_prompt += "If translating to Rust, make sure to include the necessary packages and crates."
        user_prompt += python
        return user_prompt

    def messages_for(self, python, lang_select):
        # System message for OpenAI API
        system_message = "You are an assistant that reimplements Python code in high performance code for a Windows PC. "
        system_message += "Respond only with code; do not provide any explanations. "
        system_message += "The response needs to produce an identical output in the fastest possible time."

        return [
            {"role": "system", "content": system_message},
            {"role": "user", "content": self.user_prompt_for(python, lang_select)}
        ]

    def translate_code(self, code_file, lang_select):
        stream = self.openai.chat.completions.create(model=self.model, messages=self.messages_for(code_file, lang_select), stream=True)
        code = ""
        for chunk in stream:
            fragment = chunk.choices[0].delta.content or ""
            code += fragment
        pattern = r"```(c|cpp|rust|javascript)\n"
        code = re.sub(pattern, "", code).replace("```", "")
        return code


class ExecuteCode:
    def __init__(self, translator):
        self.translator = translator

    def extract_dependencies(self, code):
        try:
            dependency_pattern = r"""
            (?:use\s+(?!std::)[a-zA-Z_][a-zA-Z0-9_]*::|extern\s+crate\s+(?!std)[a-zA-Z_][a-zA-Z0-9_]*);?
            |
            \#include\s*<([a-zA-Z_][a-zA-Z0-9_/.]*)>
            |
            (?:import\s+.*\s+from\s+['"]([a-zA-Z_][a-zA-Z0-9_/.]*)['"]
            |require\s*\(\s*['"]([a-zA-Z_][a-zA-Z0-9_/.]*)['"]\s*\))
        """
            matches = re.findall(dependency_pattern, code, re.VERBOSE)
            dependencies = [match for match in matches if any(match)]
            return dependencies if matches else []
        except re.error as e:
            raise ValueError(f"Regex error while extracting dependencies: {e}")

    def execute_code(self, code_file, lang_select):
        if lang_select == "Rust":
            rust_code = self.translator.translate_code(code_file, lang_select)
            try:
                dependencies = self.extract_dependencies(rust_code)
                temp_dir = tempfile.mkdtemp()
                src_dir = os.path.join(temp_dir, "src")
                os.makedirs(src_dir, exist_ok=True)
                cargo_toml = f"""
                [package]
                name = "temp_project"
                version = "0.1.0"
                edition = "2021"

                [dependencies]
            """
                for dependency in dependencies:
                    crate = dependency[0]
                    cargo_toml += f"{crate} = \"*\"\n"
                with open(os.path.join(temp_dir, "Cargo.toml"), "w") as f:
                    f.write(cargo_toml)
                main_rs_path = os.path.join(src_dir, "main.rs")
                with open(main_rs_path, "w", encoding="utf-8") as f:
                    f.write(rust_code)
                cargo_build = subprocess.run(["cargo", "build", "--release"],
                                                cwd=temp_dir,
                                                stdout=subprocess.PIPE,
                                                stderr=subprocess.PIPE,
                                                text=True)
                if cargo_build.returncode != 0:
                    return f"Cargo build failed:\n{cargo_build.stderr}", 0
                executable_path = os.path.join(temp_dir, "target", "release", "temp_project")
                start_time = timer()
                run_result = subprocess.run([executable_path],
                                            stdout=subprocess.PIPE,
                                            stderr=subprocess.PIPE,
                                            text=True)
                end_time = timer()
                execution_time = end_time - start_time
                if run_result.returncode != 0:
                    print(f"Execution failed: {run_result.stderr}")
                return run_result.stdout, execution_time
            finally:
                if temp_dir:
                    shutil.rmtree(temp_dir, ignore_errors=True)
        elif lang_select in ["C", "C++"]:
            code = self.translator.translate_code(code_file, lang_select)
            with tempfile.TemporaryDirectory() as temp_dir:
                file_extension = "c" if lang_select == "C" else "cpp"
                file_path = os.path.join(temp_dir, f"translated_code.{file_extension}")
                with open(file_path, "w") as f:
                    f.write(code)
                executable_path = os.path.join(temp_dir, "translated_code")
                compiler = "gcc" if lang_select == "C" else "g++"
                compile_result = subprocess.run([compiler, file_path, "-o", executable_path],
                                                stdout=subprocess.PIPE,
                                                stderr=subprocess.PIPE,
                                                text=True)
                if compile_result.returncode != 0:
                    return f"Compilation failed:\n{compile_result.stderr}", 0
                start_time = timer()
                run_result = subprocess.run([executable_path],
                                            stdout=subprocess.PIPE,
                                            stderr=subprocess.PIPE,
                                            text=True)
                end_time = timer()
                execution_time = end_time - start_time
                return run_result.stdout, execution_time
        elif lang_select == "Javascript":
            js_code = self.translator.translate_code(code_file, lang_select)
            with tempfile.NamedTemporaryFile(suffix='.js', delete=False) as js_file:
                js_file.write(js_code.encode("utf-8"))
                js_file.flush()
                js_file_path = js_file.name
            try:
                start_time = timer()
                run_result = subprocess.run(["node", js_file_path],
                                            stdout=subprocess.PIPE,
                                            stderr=subprocess.PIPE,
                                            text=True)
                end_time = timer()
                execution_time = end_time - start_time
                return run_result.stdout, execution_time
            finally:
                os.remove(js_file_path)
        else:
            return "Language not supported", 0


def process_code(python_code: str, target_language: str):
    """Process the uploaded Python code and return both original and translated outputs"""
    # Initialize components
    openai_client = OpenAI()
    translator = TranslateCode(openai_client, OPENAI_MODEL)
    executor = ExecuteCode(translator)
    
    # Run Python code
    python_output = ""
    python_time = 0
    try:
        with tempfile.NamedTemporaryFile(delete=False, suffix=".py") as temp_py_file:
            temp_py_file.write(python_code.encode('utf-8'))
            temp_py_file_path = temp_py_file.name
        
        start_time = timer()
        result = subprocess.run(["python", temp_py_file_path], 
                              capture_output=True, 
                              text=True)
        end_time = timer()
        
        python_output = result.stdout if result.returncode == 0 else result.stderr
        python_time = end_time - start_time
    except Exception as e:
        python_output = str(e)
    finally:
        if 'temp_py_file_path' in locals() and os.path.exists(temp_py_file_path):
            os.remove(temp_py_file_path)

    # Translate and run the code
    translated_code = translator.translate_code(python_code, target_language)
    translated_output, translated_time = executor.execute_code(translated_code, target_language)

    # Format the outputs
    python_output = python_output.replace("Â", "")
    translated_output = translated_output.replace("Â", "")
    python_result = f"Output:\n{python_output}\nExecution time: {python_time:.4f} seconds"
    translated_result = f"Output:\n{translated_output}\nExecution time: {translated_time:.4f} seconds"

    return python_code, translated_code, python_result, translated_result

def create_gradio_interface():
    with gr.Blocks(title="SyntaxShift: Code Translator") as interface:
        gr.Markdown("# SyntaxShift: Code Translator")
        gr.Markdown("It's like Google Translate, but for code. Upload a Python file or paste Python code to translate it to C, C++, Rust, or Javascript, and run the code.")
        
        with gr.Row():
            with gr.Column():
                python_code = gr.Code(
                    label="Python Code",
                    language="python",
                    lines=20
                )
                target_language = gr.Dropdown(
                    choices=["C", "C++", "Rust", "Javascript"],
                    label="Target Language",
                    value="C"
                )
                translate_button = gr.Button("Translate and Run")
            
        with gr.Row():
            with gr.Column():
                translated_code = gr.Code(
                    label="Translated Code",
                    language="python",  # This will update dynamically
                    lines=20
                )
        
        with gr.Row():
            with gr.Column():
                python_output = gr.Textbox(
                    label="Python Execution Result",
                    lines=5
                )
            with gr.Column():
                translated_output = gr.Textbox(
                    label="Translated Code Execution Result",
                    lines=5
                )

        # Update language display based on selection
        def update_language(lang):
            lang_map = {
                "C": "c",
                "C++": "cpp",
                "Rust": "rust",
                "Javascript": "javascript"
            }
            return {"language": lang_map[lang]}

        target_language.change(
            fn=update_language,
            inputs=[target_language],
            outputs=[translated_code]
        )

        # Main translation and execution flow
        translate_button.click(
            fn=process_code,
            inputs=[python_code, target_language],
            outputs=[python_code, translated_code, python_output, translated_output]
        )

    return interface

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