From a0f3c64de435ba83d6af51ba16d50063984a3b4a Mon Sep 17 00:00:00 2001 From: channec2 Date: Fri, 23 May 2025 12:20:42 -0400 Subject: [PATCH] add alternate week 4, day 4 which works on windows --- .../day4 - using windows.ipynb | 799 ++++++++++++++++++ 1 file changed, 799 insertions(+) create mode 100644 week4/community-contributions/day4 - using windows.ipynb diff --git a/week4/community-contributions/day4 - using windows.ipynb b/week4/community-contributions/day4 - using windows.ipynb new file mode 100644 index 0000000..c8871b1 --- /dev/null +++ b/week4/community-contributions/day4 - using windows.ipynb @@ -0,0 +1,799 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "830865a5", + "metadata": {}, + "source": [ + "# Code Generator - Windows\n", + "\n", + "Re-codes day4 excercise to build on windows\n", + "\n", + "### Section 1: Manually Generate and Execute CPP Code" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "f8559090", + "metadata": {}, + "outputs": [], + "source": [ + "# imports\n", + "\n", + "import os\n", + "import io\n", + "import sys\n", + "import json\n", + "import requests\n", + "from dotenv import load_dotenv\n", + "from openai import OpenAI\n", + "import google.generativeai\n", + "import anthropic\n", + "from IPython.display import Markdown, display, update_display\n", + "import gradio as gr\n", + "import subprocess\n", + "from huggingface_hub import login, InferenceClient\n", + "from transformers import AutoTokenizer\n", + "import platform" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "858b5e7b", + "metadata": {}, + "outputs": [], + "source": [ + "# environment\n", + "\n", + "load_dotenv(override=True)\n", + "os.environ['OPENAI_API_KEY'] = os.getenv('OPENAI_API_KEY', 'your-key-if-not-using-env')\n", + "os.environ['ANTHROPIC_API_KEY'] = os.getenv('ANTHROPIC_API_KEY', 'your-key-if-not-using-env')\n", + "os.environ['HF_TOKEN'] = os.getenv('HF_TOKEN', 'your-key-if-not-using-env')" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "98c45ca8", + "metadata": {}, + "outputs": [], + "source": [ + "# initialize\n", + "\n", + "openai = OpenAI()\n", + "claude = anthropic.Anthropic()\n", + "hf_token = os.environ['HF_TOKEN']\n", + "login(hf_token, add_to_git_credential=True)\n", + "\n", + "# models\n", + "OPENAI_MODEL = \"gpt-4o\"\n", + "CLAUDE_MODEL = \"claude-3-5-sonnet-20240620\"\n", + "CODE_QWEN_MODEL = \"Qwen/CodeQwen1.5-7B-Chat\"\n", + "CODE_GEMMA_MODEL = \"Gemini/CodeGemma-7B-IT\"\n", + "\n", + "# huggingface inference clients\n", + "# CODE_QWEN_URL = \"https://h1vdol7jxhje3mpn.us-east-1.aws.endpoints.huggingface.cloud\"\n", + "CODE_QWEN_URL = \"https://mb4mgfmpql2yrady.us-east-1.aws.endpoints.huggingface.cloud\"\n", + "CODE_GEMMA_URL = \"https://c5hggiyqachmgnqg.us-east-1.aws.endpoints.huggingface.cloud\"\n", + "\n", + "# path to your visual studio build tools VsDevCmd.bat file - initialize environment\n", + "VISUAL_STUDIO_BUILD_TOOLS_PATH = \"C:\\\\Program Files (x86)\\\\Microsoft Visual Studio\\\\2022\\\\BuildTools\\\\Common7\\\\Tools\\\\VsDevCmd.bat\"\n", + "\n", + "# prefix of the output files, e.g., \"optimized_d4win.cpp\", \"optimized_d4win.exe\", etc.\n", + "OUTPUT_FILE_NAME_BASE = \"optimized_d4win\"" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "ac5efb13", + "metadata": {}, + "outputs": [], + "source": [ + "# System message\n", + "\n", + "system_message = \"You are an assistant that reimplements Python code in high performance C++ for an M1 Mac. \"\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. Keep implementations of random number generators identical so that results match exactly.\"" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "ce3ce9da", + "metadata": {}, + "outputs": [], + "source": [ + "# build user prompts and message structures for openai and claude models\n", + "\n", + "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\n", + "\n", + "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": "1ea427ef", + "metadata": {}, + "outputs": [], + "source": [ + "# write to a file called .cpp\n", + "\n", + "def write_output(cpp):\n", + " code = cpp.replace(\"```cpp\",\"\").replace(\"```\",\"\")\n", + " with open(f\"{OUTPUT_FILE_NAME_BASE}.cpp\", \"w\") as f:\n", + " f.write(code)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "4d1198b4", + "metadata": {}, + "outputs": [], + "source": [ + "# reade the contents of the output file called .cpp\n", + "def read_output():\n", + " with open(f\"{OUTPUT_FILE_NAME_BASE}.cpp\", \"r\") as f:\n", + " return f.read()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "7d3d9650", + "metadata": {}, + "outputs": [], + "source": [ + "# optimize code using openai and claude\n", + "\n", + "def optimize_gpt(python): \n", + " stream = openai.chat.completions.create(model=OPENAI_MODEL, messages=messages_for(python), stream=True)\n", + " reply = \"\"\n", + " for chunk in stream:\n", + " fragment = chunk.choices[0].delta.content or \"\"\n", + " reply += fragment\n", + " print(fragment, end='', flush=True)\n", + " write_output(reply)\n", + " \n", + "def optimize_claude(python):\n", + " result = claude.messages.stream(\n", + " model=CLAUDE_MODEL,\n", + " max_tokens=2000,\n", + " system=system_message,\n", + " messages=[{\"role\": \"user\", \"content\": user_prompt_for(python)}],\n", + " )\n", + " reply = \"\"\n", + " with result as stream:\n", + " for text in stream.text_stream:\n", + " reply += text\n", + " print(text, end=\"\", flush=True)\n", + " write_output(reply)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "523d1481", + "metadata": {}, + "outputs": [], + "source": [ + "# generate build c++ comiple and run commands based on your platform\n", + "# Borrowed from @CloudLlama's contribution!\n", + "\n", + "def run_cmd(command_to_run):\n", + " try:\n", + " run_result = subprocess.run(command_to_run, check=True, text=True, capture_output=True)\n", + " return run_result.stdout if run_result.stdout else \"SUCCESS\"\n", + " except:\n", + " return \"\"\n", + " \n", + "def c_compiler_cmd(filename_base):\n", + " my_platform = platform.system()\n", + " my_compiler = []\n", + " \n", + " try: \n", + " if my_platform == \"Windows\":\n", + " if os.path.isfile(VISUAL_STUDIO_BUILD_TOOLS_PATH):\n", + " compile_cmd = [\"cmd\", \"/c\", VISUAL_STUDIO_BUILD_TOOLS_PATH, \"&\", \"cl\", f\"{filename_base}.cpp\"]\n", + " my_compiler = [\"Windows\", \"Visual Studio Build Tools\", compile_cmd]\n", + " \n", + " if not my_compiler:\n", + " my_compiler=[my_platform, \"Unavailable\", []]\n", + " \n", + " elif my_platform == \"Linux\":\n", + " compile_cmd = [\"g++\", f\"{filename_base}.cpp\", \"-o\", filename_base]\n", + " my_compiler = [\"Linux\", \"GCC (g++)\", compile_cmd]\n", + " \n", + " if not my_compiler:\n", + " compile_cmd = [\"clang++\", f\"{filename_base}.cpp\", \"-o\", filename_base]\n", + " my_compiler = [\"Linux\", \"Clang++\", compile_cmd]\n", + " \n", + " if not my_compiler:\n", + " my_compiler=[my_platform, \"Unavailable\", []]\n", + " \n", + " elif my_platform == \"Darwin\":\n", + " compile_cmd = [\"clang++\", \"-Ofast\", \"-std=c++17\", \"-march=armv8.5-a\", \"-mtune=apple-m1\", \"-mcpu=apple-m1\", \"-o\", filename_base, f\"{filename_base}.cpp\"]\n", + " my_compiler = [\"Macintosh\", \"Clang++\", compile_cmd]\n", + " \n", + " if not my_compiler:\n", + " my_compiler=[my_platform, \"Unavailable\", []]\n", + " except:\n", + " my_compiler=[my_platform, \"Unavailable\", []]\n", + " \n", + " if my_compiler:\n", + " return my_compiler\n", + " else:\n", + " return [\"Unknown\", \"Unavailable\", []] " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "43d84759", + "metadata": {}, + "outputs": [], + "source": [ + "# compile and execute the C++ code\n", + "\n", + "def execute_cpp(code):\n", + " filename_base = OUTPUT_FILE_NAME_BASE\n", + " compiler_cmd = c_compiler_cmd(filename_base)\n", + " write_output(code)\n", + " \n", + " try:\n", + " if os.path.isfile(f\"./{filename_base}.exe\"):\n", + " os.remove(f\"./{filename_base}.exe\")\n", + " if os.path.isfile(f\"./{filename_base}\"):\n", + " os.remove(f\"./{filename_base}\")\n", + " compile_result = subprocess.run(compiler_cmd[2], check=True, text=True, capture_output=True)\n", + " run_cmd = [f\"./{filename_base}\"]\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": "a658a7ba", + "metadata": {}, + "outputs": [], + "source": [ + "# simple pypton code to optimize\n", + "\n", + "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": "876bfe68", + "metadata": {}, + "outputs": [], + "source": [ + "# execute the simple python code\n", + "\n", + "exec(pi)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "98c553c8", + "metadata": {}, + "outputs": [], + "source": [ + "# optimize the simple python code with openai\n", + "\n", + "optimize_gpt(pi)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "db5a1fc3", + "metadata": {}, + "outputs": [], + "source": [ + "# compile and run the openai optimized code\n", + "\n", + "cpp_code = read_output()\n", + "execute_cpp(cpp_code)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "3cd5c138", + "metadata": {}, + "outputs": [], + "source": [ + "# optimize the simple python code with claude\n", + "\n", + "optimize_claude(pi)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "110a7c11", + "metadata": {}, + "outputs": [], + "source": [ + "# compile and run the claude optimized code\n", + "\n", + "cpp_code = read_output()\n", + "execute_cpp(cpp_code)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "dceaa0db", + "metadata": {}, + "outputs": [], + "source": [ + "# hard pypton code to optimize\n", + "\n", + "pi_hard = \"\"\"# Be careful to support large number sizes\n", + "\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": "371edd71", + "metadata": {}, + "outputs": [], + "source": [ + "# execute the simple python code\n", + "\n", + "exec(pi_hard)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "9b0a7233", + "metadata": {}, + "outputs": [], + "source": [ + "# optimize the hard python code with openai\n", + "\n", + "optimize_gpt(pi_hard)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "281e959c", + "metadata": {}, + "outputs": [], + "source": [ + "# compile and run the openai optimized code\n", + "\n", + "cpp_code = read_output()\n", + "execute_cpp(cpp_code)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "8d2712ce", + "metadata": {}, + "outputs": [], + "source": [ + "# optimize the hard python code with claude\n", + "\n", + "optimize_claude(pi_hard)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "444549a7", + "metadata": {}, + "outputs": [], + "source": [ + "# compile and run the openai optimized code\n", + "\n", + "cpp_code = read_output()\n", + "execute_cpp(cpp_code)" + ] + }, + { + "cell_type": "markdown", + "id": "6aec3927", + "metadata": {}, + "source": [ + "### Section 2: Using Gradio Interface to Generate and Execute CPP Code" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "6607743c", + "metadata": {}, + "outputs": [], + "source": [ + "# configure streaming responses from openai and claude\n", + "\n", + "def stream_gpt(python): \n", + " stream = openai.chat.completions.create(model=OPENAI_MODEL, messages=messages_for(python), stream=True)\n", + " reply = \"\"\n", + " for chunk in stream:\n", + " fragment = chunk.choices[0].delta.content or \"\"\n", + " reply += fragment\n", + " yield reply.replace('```cpp\\n','').replace('```','')\n", + " \n", + "def stream_claude(python):\n", + " result = claude.messages.stream(\n", + " model=CLAUDE_MODEL,\n", + " max_tokens=2000,\n", + " system=system_message,\n", + " messages=[{\"role\": \"user\", \"content\": user_prompt_for(python)}],\n", + " )\n", + " reply = \"\"\n", + " with result as stream:\n", + " for text in stream.text_stream:\n", + " reply += text\n", + " yield reply.replace('```cpp\\n','').replace('```','')" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "052a713e", + "metadata": {}, + "outputs": [], + "source": [ + "# optimize code based on selected model\n", + "\n", + "def optimize(python, model):\n", + " if model==\"GPT\":\n", + " result = stream_gpt(python)\n", + " elif model==\"Claude\":\n", + " result = stream_claude(python)\n", + " else:\n", + " raise ValueError(\"Unknown model\")\n", + " for stream_so_far in result:\n", + " yield stream_so_far " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "27479cab", + "metadata": {}, + "outputs": [], + "source": [ + "# use gradio to optimize python code from the UI\n", + "\n", + "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([\"GPT\", \"Claude\"], label=\"Select model\", value=\"GPT\")\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": "7b39125a", + "metadata": {}, + "outputs": [], + "source": [ + "# execute python code\n", + "\n", + "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": "d5cb0f55", + "metadata": {}, + "outputs": [], + "source": [ + "# css to color by code type\n", + "\n", + "css = \"\"\"\n", + ".python {background-color: #306998;}\n", + ".cpp {background-color: #050;}\n", + "\"\"\"" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "66e5ef37", + "metadata": {}, + "outputs": [], + "source": [ + "# add ability to run python code, compile and run c++ code in gradio\n", + "\n", + "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([\"GPT\", \"Claude\"], label=\"Select model\", value=\"GPT\")\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": "markdown", + "id": "b4d29c1c", + "metadata": {}, + "source": [ + "### Section 3: Add HuggingFace-hosted Open Source Models to Gradio App" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "8ec5e4cb", + "metadata": {}, + "outputs": [], + "source": [ + "# initilize code qwen huggingface endpoint\n", + "\n", + "tokenizer = AutoTokenizer.from_pretrained(CODE_QWEN_MODEL)\n", + "messages = messages_for(pi)\n", + "text = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "4c3ac865", + "metadata": {}, + "outputs": [], + "source": [ + "# inspect the message template (text)\n", + "\n", + "print(text)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "8a1de956", + "metadata": {}, + "outputs": [], + "source": [ + "# manually call the huggingface endpoint, generate c++ with code qwen\n", + "\n", + "client = InferenceClient(CODE_QWEN_URL, token=hf_token)\n", + "stream = client.text_generation(text, stream=True, details=True, max_new_tokens=3000)\n", + "for r in stream:\n", + " print(r.token.text, end = \"\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "20d310dc", + "metadata": {}, + "outputs": [], + "source": [ + "# configure streaming responses from code qwen\n", + "\n", + "def stream_code_qwen(python):\n", + " tokenizer = AutoTokenizer.from_pretrained(CODE_QWEN_MODEL)\n", + " messages = messages_for(python)\n", + " text = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)\n", + " client = InferenceClient(CODE_QWEN_URL, token=hf_token)\n", + " stream = client.text_generation(text, stream=True, details=True, max_new_tokens=3000)\n", + " result = \"\"\n", + " for r in stream:\n", + " result += r.token.text\n", + " yield result " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "1340cd15", + "metadata": {}, + "outputs": [], + "source": [ + "# update optimize function to include code qwen\n", + "\n", + "def optimize(python, model):\n", + " if model==\"GPT\":\n", + " result = stream_gpt(python)\n", + " elif model==\"Claude\":\n", + " result = stream_claude(python)\n", + " elif model==\"CodeQwen\":\n", + " result = stream_code_qwen(python)\n", + " else:\n", + " raise ValueError(\"Unknown model\")\n", + " for stream_so_far in result:\n", + " yield stream_so_far " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "6761f4ea", + "metadata": {}, + "outputs": [], + "source": [ + "# select the python code sample and return the code\n", + "\n", + "def select_sample_program(sample_program):\n", + " if sample_program==\"pi\":\n", + " return pi\n", + " elif sample_program==\"pi_hard\":\n", + " return pi_hard\n", + " else:\n", + " return \"Type your Python program here\"" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "74ecb73b", + "metadata": {}, + "outputs": [], + "source": [ + "# run the updated gradio UI with code qwen\n", + "\n", + "compiler_cmd = c_compiler_cmd(\"optimized\")\n", + "\n", + "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", + " with gr.Column():\n", + " sample_program = gr.Radio([\"pi\", \"pi_hard\"], label=\"Sample program\", value=\"pi\")\n", + " model = gr.Dropdown([\"GPT\", \"Claude\", \"CodeQwen\"], label=\"Select model\", value=\"GPT\")\n", + " with gr.Column():\n", + " architecture = gr.Radio([compiler_cmd[0]], label=\"Architecture\", interactive=False, value=compiler_cmd[0])\n", + " compiler = gr.Radio([compiler_cmd[1]], label=\"Compiler\", interactive=False, value=compiler_cmd[1])\n", + " with gr.Row():\n", + " convert = gr.Button(\"Convert code\")\n", + " with gr.Row():\n", + " python_run = gr.Button(\"Run Python\")\n", + " if not compiler_cmd[1] == \"Unavailable\":\n", + " cpp_run = gr.Button(\"Run C++\")\n", + " else:\n", + " cpp_run = gr.Button(\"No compiler to run C++\", interactive=False)\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", + " sample_program.change(select_sample_program, inputs=[sample_program], outputs=[python])\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)" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "llms", + "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": "3.11.12" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +}