{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "3d3cb3c4-9046-4f64-9188-ee20ae324fd1",
   "metadata": {},
   "source": [
    "# Code Generator\n",
    "\n",
    "The requirement: use a Frontier model to generate high performance C++ code from Python code\n",
    "\n",
    "# Important Note\n",
    "Used an open-source model gemini-1.5-pro ,can try 2.0 flash too\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "6f2c3e03-f38a-4bf2-98e8-696fb3d428c9",
   "metadata": {},
   "outputs": [],
   "source": [
    "# imports\n",
    "\n",
    "import os\n",
    "import io\n",
    "import sys\n",
    "from dotenv import load_dotenv\n",
    "import google.generativeai\n",
    "from IPython.display import Markdown, display, update_display\n",
    "import gradio as gr\n",
    "import subprocess"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e437f3d1-39c4-47fd-919f-c2119d602d72",
   "metadata": {},
   "outputs": [],
   "source": [
    "# environment\n",
    "\n",
    "load_dotenv()\n",
    "google_api_key = os.getenv('GOOGLE_API_KEY')\n",
    "if google_api_key:\n",
    "    print(f\"Google API Key exists\")\n",
    "else:\n",
    "    print(\"Google API Key not set\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "1724ddb6-0059-46a3-bcf9-587c0c93cb2a",
   "metadata": {},
   "outputs": [],
   "source": [
    "google.generativeai.configure()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b62738c1-9857-40fc-91e8-dfd46483ea50",
   "metadata": {},
   "outputs": [],
   "source": [
    "system_message = \"You are an assistant that reimplements Python code in high performance C++ for an Windows system. \"\n",
    "system_message += \"Respond only with C++ code; use comments sparingly and do not provide any explanation other than occasional comments. \"\n",
    "system_message += \"The C++ response needs to produce an identical output in the fastest possible time.\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "bd431141-8602-4c68-9a1d-a7c0a6f13fa3",
   "metadata": {},
   "outputs": [],
   "source": [
    "def user_prompt_for(python):\n",
    "    user_prompt = \"Rewrite this Python code in C++ with the fastest possible implementation that produces identical output in the least time. \"\n",
    "    user_prompt += \"Respond only with C++ code; do not explain your work other than a few comments. \"\n",
    "    user_prompt += \"Pay attention to number types to ensure no int overflows. Remember to #include all necessary C++ packages such as iomanip.\\n\\n\"\n",
    "    user_prompt += python\n",
    "    return user_prompt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d5f48451-4cd4-46ea-a41d-531a3c7db2a8",
   "metadata": {},
   "outputs": [],
   "source": [
    "def messages_for(python):\n",
    "    return [\n",
    "        {\"role\": \"system\", \"content\": system_message},\n",
    "        {\"role\": \"user\", \"content\": user_prompt_for(python)}\n",
    "    ]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "83fd2170-14ea-4fb6-906e-c3c5cfce1ecc",
   "metadata": {},
   "outputs": [],
   "source": [
    "# write to a file called optimized.cpp\n",
    "\n",
    "def write_output(cpp):\n",
    "    code = cpp.replace(\"```cpp\",\"\").replace(\"```\",\"\")\n",
    "    with open(\"optimized.cpp\", \"w\") as f:\n",
    "        f.write(code)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "1ff08067-c9df-4981-8ab5-99eb2c2fd2c7",
   "metadata": {},
   "outputs": [],
   "source": [
    "def optimize_google(python):\n",
    "    # Initialize empty reply string\n",
    "    reply = \"\"\n",
    "    \n",
    "    # The API for Gemini has a slightly different structure\n",
    "    gemini = google.generativeai.GenerativeModel(\n",
    "        model_name='gemini-1.5-pro',\n",
    "        system_instruction=system_message\n",
    "    )\n",
    "    \n",
    "    response = gemini.generate_content(\n",
    "        user_prompt_for(python),\n",
    "        stream=True\n",
    "    )\n",
    "    \n",
    "    # Process the stream\n",
    "    for chunk in response:\n",
    "        # Extract text from the chunk\n",
    "        if chunk.text:\n",
    "            reply += chunk.text\n",
    "            print(chunk.text, end=\"\", flush=True)\n",
    "    \n",
    "    # Write the complete response to output\n",
    "    write_output(reply)\n",
    "    \n",
    "    # return reply"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "8e8c7ba2-4ee9-4523-b0f1-cc7a91798bba",
   "metadata": {},
   "outputs": [],
   "source": [
    "pi = \"\"\"\n",
    "import time\n",
    "\n",
    "def calculate(iterations, param1, param2):\n",
    "    result = 1.0\n",
    "    for i in range(1, iterations+1):\n",
    "        j = i * param1 - param2\n",
    "        result -= (1/j)\n",
    "        j = i * param1 + param2\n",
    "        result += (1/j)\n",
    "    return result\n",
    "\n",
    "start_time = time.time()\n",
    "result = calculate(100_000_000, 4, 1) * 4\n",
    "end_time = time.time()\n",
    "\n",
    "print(f\"Result: {result:.12f}\")\n",
    "print(f\"Execution Time: {(end_time - start_time):.6f} seconds\")\n",
    "\"\"\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "78d1afb7-ed6b-4a03-b36d-4ce8249c592e",
   "metadata": {},
   "outputs": [],
   "source": [
    "exec(pi)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "1fe1d0b6-7cc7-423b-bc4b-741a0c48c106",
   "metadata": {},
   "outputs": [],
   "source": [
    "optimize_google(pi)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d28b4ac9-0909-4b35-aee1-97613a133e8e",
   "metadata": {},
   "outputs": [],
   "source": [
    "exec(pi) #Execution Time: 16.209231 seconds"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7d0443a3-3ca2-4a7a-a6c3-c94d0aa54603",
   "metadata": {},
   "source": [
    "# Compiling C++ and executing\n",
    "\n",
    "This next cell contains the command to compile a C++ file on Windows system.  \n",
    "It compiles the file `optimized.cpp` into an executable called `optimized`  \n",
    "Then it runs the program called `optimized`\n",
    "\n",
    "The way to compile for mac users is \\\n",
    "!clang++ -O3 -std=c++17 -march=armv8.3-a -o optimized optimized.cpp \\\n",
    "!./optimized"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "9b5cfc70-df1f-44a7-b4ae-fd934f715930",
   "metadata": {},
   "outputs": [],
   "source": [
    "!g++ -o optimized optimized.cpp\n",
    "!.\\optimized #Execution Time: 3.661196 seconds"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e30fcbdf-82cf-4d50-9690-92dae69d5127",
   "metadata": {},
   "outputs": [],
   "source": [
    "python_hard = \"\"\"\n",
    "def lcg(seed, a=1664525, c=1013904223, m=2**32):\n",
    "    value = seed\n",
    "    while True:\n",
    "        value = (a * value + c) % m\n",
    "        yield value\n",
    "        \n",
    "def max_subarray_sum(n, seed, min_val, max_val):\n",
    "    lcg_gen = lcg(seed)\n",
    "    random_numbers = [next(lcg_gen) % (max_val - min_val + 1) + min_val for _ in range(n)]\n",
    "    max_sum = float('-inf')\n",
    "    for i in range(n):\n",
    "        current_sum = 0\n",
    "        for j in range(i, n):\n",
    "            current_sum += random_numbers[j]\n",
    "            if current_sum > max_sum:\n",
    "                max_sum = current_sum\n",
    "    return max_sum\n",
    "\n",
    "def total_max_subarray_sum(n, initial_seed, min_val, max_val):\n",
    "    total_sum = 0\n",
    "    lcg_gen = lcg(initial_seed)\n",
    "    for _ in range(20):\n",
    "        seed = next(lcg_gen)\n",
    "        total_sum += max_subarray_sum(n, seed, min_val, max_val)\n",
    "    return total_sum\n",
    "\n",
    "# Parameters\n",
    "n = 10000         # Number of random numbers\n",
    "initial_seed = 42 # Initial seed for the LCG\n",
    "min_val = -10     # Minimum value of random numbers\n",
    "max_val = 10      # Maximum value of random numbers\n",
    "\n",
    "# Timing the function\n",
    "import time\n",
    "start_time = time.time()\n",
    "result = total_max_subarray_sum(n, initial_seed, min_val, max_val)\n",
    "end_time = time.time()\n",
    "\n",
    "print(\"Total Maximum Subarray Sum (20 runs):\", result)\n",
    "print(\"Execution Time: {:.6f} seconds\".format(end_time - start_time))\n",
    "\"\"\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "2e8e111c-6f69-4ed0-8f86-8ed5982aa065",
   "metadata": {},
   "outputs": [],
   "source": [
    "exec(python_hard) #Execution Time: 62.297366 seconds"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "38038ac1-5cdf-49d7-a286-a5871d5af583",
   "metadata": {},
   "outputs": [],
   "source": [
    "optimize_google(python_hard)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "08cb9619-b8ae-42e7-9375-4b3918c37fd0",
   "metadata": {},
   "outputs": [],
   "source": [
    "!g++ -o optimized optimized.cpp\n",
    "!.\\optimized"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "acd17a0d-f9f1-45a6-8151-916d8e6b9e4f",
   "metadata": {},
   "outputs": [],
   "source": [
    "def stream_google(python):\n",
    "    # Initialize empty reply string\n",
    "    reply = \"\"\n",
    "    \n",
    "    # The API for Gemini has a slightly different structure\n",
    "    gemini = google.generativeai.GenerativeModel(\n",
    "        model_name='gemini-1.5-pro',\n",
    "        system_instruction=system_message\n",
    "    )\n",
    "    \n",
    "    response = gemini.generate_content(\n",
    "        user_prompt_for(python),\n",
    "        stream=True\n",
    "    )\n",
    "    \n",
    "    # Process the stream\n",
    "    for chunk in response:\n",
    "        # Extract text from the chunk\n",
    "        if chunk.text:\n",
    "            reply += chunk.text\n",
    "            yield reply.replace('```cpp\\n','').replace('```','')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c3177229-d6cf-4df2-81a7-9e1f3b229c19",
   "metadata": {},
   "outputs": [],
   "source": [
    "def optimize(python, model):\n",
    "    result=stream_google(python)\n",
    "    for stream_so_far in result:\n",
    "        yield stream_so_far    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c2476c2d-9218-4d30-bcc9-9cc5271c3a00",
   "metadata": {},
   "outputs": [],
   "source": [
    "with gr.Blocks() as ui:\n",
    "    with gr.Row():\n",
    "        python = gr.Textbox(label=\"Python code:\", lines=10, value=pi)\n",
    "        cpp = gr.Textbox(label=\"C++ code:\", lines=10)\n",
    "    with gr.Row():\n",
    "        model = gr.Dropdown([\"Google\"], label=\"Select model\", value=\"Google\")\n",
    "        convert = gr.Button(\"Convert code\")\n",
    "\n",
    "    convert.click(optimize, inputs=[python, model], outputs=[cpp])\n",
    "\n",
    "ui.launch(inbrowser=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a30de175-af4e-428a-8942-1c41997c01f1",
   "metadata": {},
   "outputs": [],
   "source": [
    "def execute_python(code):\n",
    "        try:\n",
    "            output = io.StringIO()\n",
    "            sys.stdout = output\n",
    "            exec(code)\n",
    "        finally:\n",
    "            sys.stdout = sys.__stdout__\n",
    "        return output.getvalue()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "20c6316d-b090-42c5-9be9-7d5a178b97b3",
   "metadata": {},
   "outputs": [],
   "source": [
    "def execute_cpp(code):\n",
    "        write_output(code)\n",
    "        try:\n",
    "            # compile_cmd = [\"clang++\", \"-Ofast\", \"-std=c++17\", \"-march=armv8.5-a\", \"-mtune=apple-m1\", \"-mcpu=apple-m1\", \"-o\", \"optimized\", \"optimized.cpp\"]\n",
    "            compile_cmd = [\"g++\", \"-o\", \"optimized\", \"optimized.cpp\"]\n",
    "            compile_result = subprocess.run(compile_cmd, check=True, text=True, capture_output=True)\n",
    "            run_cmd = [\"./optimized\"]\n",
    "            run_result = subprocess.run(run_cmd, check=True, text=True, capture_output=True)\n",
    "            return run_result.stdout\n",
    "        except subprocess.CalledProcessError as e:\n",
    "            return f\"An error occurred:\\n{e.stderr}\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "950a459f-3ef6-4afd-9e83-f01c032aa21b",
   "metadata": {},
   "outputs": [],
   "source": [
    "css = \"\"\"\n",
    ".python {background-color: #306998;}\n",
    ".cpp {background-color: #050;}\n",
    "\"\"\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "bc3d90ba-716c-4b8f-989f-46c2447c42fa",
   "metadata": {},
   "outputs": [],
   "source": [
    "with gr.Blocks(css=css) as ui:\n",
    "    gr.Markdown(\"## Convert code from Python to C++\")\n",
    "    with gr.Row():\n",
    "        python = gr.Textbox(label=\"Python code:\", value=pi, lines=10)\n",
    "        cpp = gr.Textbox(label=\"C++ code:\", lines=10)\n",
    "    with gr.Row():\n",
    "        model = gr.Dropdown([\"Google\"], label=\"Select model\", value=\"Google\")\n",
    "    with gr.Row():\n",
    "        convert = gr.Button(\"Convert code\")\n",
    "    with gr.Row():\n",
    "        python_run = gr.Button(\"Run Python\")\n",
    "        cpp_run = gr.Button(\"Run C++\")\n",
    "    with gr.Row():\n",
    "        python_out = gr.TextArea(label=\"Python result:\", elem_classes=[\"python\"])\n",
    "        cpp_out = gr.TextArea(label=\"C++ result:\", elem_classes=[\"cpp\"])\n",
    "\n",
    "    convert.click(optimize, inputs=[python, model], outputs=[cpp])\n",
    "    python_run.click(execute_python, inputs=[python], outputs=[python_out])\n",
    "    cpp_run.click(execute_cpp, inputs=[cpp], outputs=[cpp_out])\n",
    "\n",
    "ui.launch(inbrowser=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c12f6115-e8a9-494e-95ce-2566854c0aa2",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.11.11"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
