Merge branch 'ed-donner:main' into main
This commit is contained in:
Tochi Nwachukwu
GitHub
4800
week4/community-contributions/Cosmus_Week_4_Exercise.ipynb
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4800
week4/community-contributions/Cosmus_Week_4_Exercise.ipynb
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week4/community-contributions/Exercise_week4_jom.ipynb
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week4/community-contributions/Exercise_week4_jom.ipynb
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@@ -0,0 +1,264 @@
|
||||
{
|
||||
"cells": [
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "fee27f39",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"# imports\n",
|
||||
"\n",
|
||||
"import os\n",
|
||||
"from dotenv import load_dotenv\n",
|
||||
"from openai import OpenAI\n",
|
||||
"import gradio as gr\n",
|
||||
"\n",
|
||||
"load_dotenv(override=True)\n",
|
||||
"openai_api_key = os.getenv('OPENAI_API_KEY')\n",
|
||||
"anthropic_api_key = os.getenv('ANTHROPIC_API_KEY')\n",
|
||||
"google_api_key = os.getenv('GOOGLE_API_KEY')\n",
|
||||
"ollama_api_key = os.getenv('OLLAMA_API_KEY')\n",
|
||||
"\n",
|
||||
"if openai_api_key:\n",
|
||||
" print(f\"OpenAI API Key exists and begins {openai_api_key[:8]}\")\n",
|
||||
"else:\n",
|
||||
" print(\"OpenAI API Key not set\")\n",
|
||||
" \n",
|
||||
"if anthropic_api_key:\n",
|
||||
" print(f\"Anthropic API Key exists and begins {anthropic_api_key[:7]}\")\n",
|
||||
"else:\n",
|
||||
" print(\"Anthropic API Key not set (and this is optional)\")\n",
|
||||
"\n",
|
||||
"if google_api_key:\n",
|
||||
" print(f\"Google API Key exists and begins {google_api_key[:2]}\")\n",
|
||||
"else:\n",
|
||||
" print(\"Google API Key not set (and this is optional)\")\n",
|
||||
"\n",
|
||||
"if ollama_api_key:\n",
|
||||
" print(f\"OLLAMA API Key exists and begins {ollama_api_key[:2]}\")\n",
|
||||
"else:\n",
|
||||
" print(\"OLLAMA API Key not set (and this is optional)\")\n",
|
||||
"\n",
|
||||
"# Connect to client libraries\n",
|
||||
"\n",
|
||||
"openai = OpenAI()\n",
|
||||
"\n",
|
||||
"anthropic_url = \"https://api.anthropic.com/v1/\"\n",
|
||||
"gemini_url = \"https://generativelanguage.googleapis.com/v1beta/openai/\"\n",
|
||||
"ollama_url = \"http://localhost:11434/v1\"\n",
|
||||
"\n",
|
||||
"anthropic = OpenAI(api_key=anthropic_api_key, base_url=anthropic_url)\n",
|
||||
"gemini = OpenAI(api_key=google_api_key, base_url=gemini_url)\n",
|
||||
"ollama = OpenAI(api_key=ollama_api_key, base_url=ollama_url)\n",
|
||||
"\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "d26f4175",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"models = [\"gpt-5\", \"claude-sonnet-4-5-20250929\", \"gemini-2.5-pro\", \"gpt-oss:20b-cloud\", ]\n",
|
||||
"\n",
|
||||
"clients = {\"gpt-5\": openai, \"claude-sonnet-4-5-20250929\": anthropic, \"gemini-2.5-pro\": gemini, \"gpt-oss:20b-cloud\": ollama}\n",
|
||||
"\n",
|
||||
"# Want to keep costs ultra-low? Replace this with models of your choice, using the examples from yesterday"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "76563884",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"system_prompt_doc = \"\"\"You are an expert Python developer and code reviewer.\n",
|
||||
"Your job is to read the user's provided function, and return:\n",
|
||||
"1. A concise, PEP-257-compliant docstring summarizing what the function does, clarifying types, parameters, return values, and side effects.\n",
|
||||
"2. Helpful inline comments that improve both readability and maintainability, without restating what the code obviously does.\n",
|
||||
"\n",
|
||||
"Only output the function, not explanations or additional text. \n",
|
||||
"Do not modify variable names or refactor the function logic.\n",
|
||||
"Your response should improve the code's clarity and documentation, making it easier for others to understand and maintain.\n",
|
||||
"Don't be extremely verbose.\n",
|
||||
"Your answer should be at a {level} level of expertise.\n",
|
||||
"\"\"\"\n",
|
||||
"\n",
|
||||
"system_prompt_tests = \"\"\"You are a seasoned Python developer and testing expert.\n",
|
||||
"Your task is to read the user's provided function, and generate:\n",
|
||||
"1. A concise set of meaningful unit tests that thoroughly validate the function's correctness, including typical, edge, and error cases.\n",
|
||||
"2. The tests should be written for pytest (or unittest if pytest is not appropriate), use clear, descriptive names, and avoid unnecessary complexity.\n",
|
||||
"3. If dependencies or mocking are needed, include minimal necessary setup code (but avoid over-mocking).\n",
|
||||
"\n",
|
||||
"Only output the relevant test code, not explanations or extra text.\n",
|
||||
"Do not change the original function; focus solely on comprehensive, maintainable test coverage that other developers can easily understand and extend.\n",
|
||||
"\"\"\"\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "1bd82e96",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"def generate_documentation(code, model, level):\n",
|
||||
" response = clients[model].chat.completions.create(\n",
|
||||
" model=model,\n",
|
||||
" messages=[\n",
|
||||
" {\"role\": \"system\", \"content\": system_prompt_doc.format(level=level)},\n",
|
||||
" {\"role\": \"user\", \"content\": code}\n",
|
||||
" ],\n",
|
||||
" stream=True\n",
|
||||
" )\n",
|
||||
" output = \"\"\n",
|
||||
" for chunk in response:\n",
|
||||
" output += chunk.choices[0].delta.content or \"\"\n",
|
||||
" yield output.replace(\"```python\", \"\").replace(\"```\", \"\")\n",
|
||||
"\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "b01b3421",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"def generate_tests(code, model ):\n",
|
||||
" response = clients[model].chat.completions.create(\n",
|
||||
" model=model,\n",
|
||||
" messages=[\n",
|
||||
" {\"role\": \"system\", \"content\": system_prompt_tests},\n",
|
||||
" {\"role\": \"user\", \"content\": code}\n",
|
||||
" ],\n",
|
||||
" stream=True\n",
|
||||
" )\n",
|
||||
" output = \"\"\n",
|
||||
" for chunk in response:\n",
|
||||
" output += chunk.choices[0].delta.content or \"\"\n",
|
||||
" yield output.replace(\"```python\", \"\").replace(\"```\", \"\")\n",
|
||||
"\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "16b71915",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"vscode_dark = gr.themes.Monochrome(\n",
|
||||
" primary_hue=\"blue\",\n",
|
||||
" secondary_hue=\"slate\",\n",
|
||||
" neutral_hue=\"slate\",\n",
|
||||
").set(\n",
|
||||
" body_background_fill=\"#1e1e1e\",\n",
|
||||
" body_background_fill_dark=\"#1e1e1e\",\n",
|
||||
" block_background_fill=\"#252526\",\n",
|
||||
" block_background_fill_dark=\"#252526\",\n",
|
||||
" block_border_color=\"#3e3e42\",\n",
|
||||
" block_border_color_dark=\"#3e3e42\",\n",
|
||||
" border_color_primary=\"#3e3e42\",\n",
|
||||
" block_label_background_fill=\"#252526\",\n",
|
||||
" block_label_background_fill_dark=\"#252526\",\n",
|
||||
" block_label_text_color=\"#cccccc\",\n",
|
||||
" block_label_text_color_dark=\"#cccccc\",\n",
|
||||
" block_title_text_color=\"#cccccc\",\n",
|
||||
" block_title_text_color_dark=\"#cccccc\",\n",
|
||||
" body_text_color=\"#d4d4d4\",\n",
|
||||
" body_text_color_dark=\"#d4d4d4\",\n",
|
||||
" button_primary_background_fill=\"#0e639c\",\n",
|
||||
" button_primary_background_fill_dark=\"#0e639c\",\n",
|
||||
" button_primary_background_fill_hover=\"#1177bb\",\n",
|
||||
" button_primary_background_fill_hover_dark=\"#1177bb\",\n",
|
||||
" button_primary_text_color=\"#ffffff\",\n",
|
||||
" button_primary_text_color_dark=\"#ffffff\",\n",
|
||||
" input_background_fill=\"#3c3c3c\",\n",
|
||||
" input_background_fill_dark=\"#3c3c3c\",\n",
|
||||
" color_accent=\"#007acc\",\n",
|
||||
" color_accent_soft=\"#094771\",\n",
|
||||
")\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "23311022",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"import gradio as gr\n",
|
||||
"\n",
|
||||
"with gr.Blocks(theme=vscode_dark, css=\"\"\"\n",
|
||||
" .gradio-container {font-family: 'Consolas', 'Monaco', monospace;}\n",
|
||||
" h1 {color: #d4d4d4 !important;}\n",
|
||||
"\"\"\") as ui:\n",
|
||||
" gr.Markdown(\"# 🧑💻 Python Code Reviewer & Test Generator\", elem_id=\"app-title\")\n",
|
||||
" with gr.Tab(\"Docstring & Comments\") as tab1:\n",
|
||||
" gr.Markdown(\"# Function Docstring & Comment Helper\\nPaste your function below and get helpful docstrings and inline comments!\")\n",
|
||||
"\n",
|
||||
" with gr.Row():\n",
|
||||
" code_input_1 = gr.Code(label=\"Paste your Python function here\", lines=10, language=\"python\")\n",
|
||||
" code_output = gr.Code(label=\"Function with improved docstring and comments\", lines=10, language=\"python\")\n",
|
||||
" \n",
|
||||
" with gr.Row(equal_height=True):\n",
|
||||
" level_radio = gr.Radio(choices=[\"Junior\", \"Mid\", \"Senior\"], value=\"Mid\", label=\"Reviewer level\", interactive=True)\n",
|
||||
" model_dropdown = gr.Dropdown(choices=models, value=models[-1], label=\"Select model\")\n",
|
||||
" submit_doc_btn = gr.Button(\"Generate docstring & comments\", scale=0.5)\n",
|
||||
"\n",
|
||||
" submit_doc_btn.click(\n",
|
||||
" generate_documentation, \n",
|
||||
" inputs=[code_input_1, model_dropdown, level_radio], \n",
|
||||
" outputs=code_output\n",
|
||||
" )\n",
|
||||
"\n",
|
||||
" with gr.Tab(\"Unit Tests\") as tab2:\n",
|
||||
" gr.Markdown(\"# Unit Test Generator\\nPaste your function below and get auto-generated unit tests!\")\n",
|
||||
"\n",
|
||||
" with gr.Row():\n",
|
||||
" code_input_2 = gr.Code(label=\"Paste your Python function here\", lines=10, language=\"python\")\n",
|
||||
" code_output_2 = gr.Code(label=\"Generated tests\", lines=10, language=\"python\")\n",
|
||||
" \n",
|
||||
" with gr.Row(equal_height=True):\n",
|
||||
" model_dropdown_2 = gr.Dropdown(choices=models, value=models[-1], label=\"Select model\")\n",
|
||||
" submit_test_btn = gr.Button(\"Generate unit tests\", scale=0.5)\n",
|
||||
"\n",
|
||||
" submit_test_btn.click(\n",
|
||||
" generate_tests, \n",
|
||||
" inputs=[code_input_2, model_dropdown_2], \n",
|
||||
" outputs=code_output_2\n",
|
||||
" )\n",
|
||||
" \n",
|
||||
" tab2.select(lambda x: x, inputs=code_input_1, outputs=code_input_2)\n",
|
||||
" tab1.select(lambda x: x, inputs=code_input_2, outputs=code_input_1)\n",
|
||||
"\n",
|
||||
"ui.launch(share=False, inbrowser=True)"
|
||||
]
|
||||
}
|
||||
],
|
||||
"metadata": {
|
||||
"kernelspec": {
|
||||
"display_name": ".venv",
|
||||
"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": "3.12.8"
|
||||
}
|
||||
},
|
||||
"nbformat": 4,
|
||||
"nbformat_minor": 5
|
||||
}
|
||||
@@ -0,0 +1,346 @@
|
||||
{
|
||||
"cells": [
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 13,
|
||||
"id": "d7ac40dd",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"import os\n",
|
||||
"from openai import OpenAI\n",
|
||||
"from dotenv import load_dotenv\n",
|
||||
"import gradio as gr\n",
|
||||
"import io\n",
|
||||
"import sys \n",
|
||||
"import subprocess"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 14,
|
||||
"id": "f0737df3",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"load_dotenv(override=True)\n",
|
||||
"openai_api_key = os.getenv('OPENAI_API_KEY')\n",
|
||||
"anthropic_api_key = os.getenv('ANTHROPIC_API_KEY')\n",
|
||||
"google_api_key = os.getenv('GOOGLE_API_KEY')\n",
|
||||
"ds_api_key = os.getenv('DEEPSEEK_API_KEY')\n",
|
||||
"grok_api_key = os.getenv('GROK_API_KEY')\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 15,
|
||||
"id": "834d1fa7",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"MODEL_MAP = {\n",
|
||||
" \"GPT\": {\n",
|
||||
" \"model\": \"gpt-4o-mini\",\n",
|
||||
" \"key\": openai_api_key,\n",
|
||||
" \"endpoint\": \"https://api.openai.com/v1\",\n",
|
||||
" },\n",
|
||||
" \"CLAUDE_3_5_SONNET\": {\n",
|
||||
" \"model\": \"claude-3-5-sonnet-20240620\",\n",
|
||||
" \"key\": anthropic_api_key,\n",
|
||||
" \"endpoint\": \"https://api.anthropic.com/v1\"\n",
|
||||
" },\n",
|
||||
" \"Grok\": {\n",
|
||||
" \"model\": \"grok-beta\",\n",
|
||||
" \"key\": grok_api_key,\n",
|
||||
" \"endpoint\": \"https://api.grok.com/v1\"\n",
|
||||
" }, \n",
|
||||
" \"DeepSeek\": {\n",
|
||||
" \"model\": \"deepseek-coder\",\n",
|
||||
" \"key\": ds_api_key,\n",
|
||||
" \"endpoint\": \"https://api.deepseek.com/v1\",\n",
|
||||
" },\n",
|
||||
" \"Google\": {\n",
|
||||
" \"model\": \"gemini-2.0-flash-exp\",\n",
|
||||
" \"key\": google_api_key,\n",
|
||||
" \"endpoint\": \"https://generativelanguage.googleapis.com/v1beta/openai\"\n",
|
||||
" },\n",
|
||||
"}"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "87d0508f",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"class PortCode:\n",
|
||||
" def __init__(self, progress=None, model_name=MODEL_MAP[\"GPT\"]):\n",
|
||||
" self.progress = progress\n",
|
||||
" self.model_deets = model_name\n",
|
||||
" self.model = OpenAI(\n",
|
||||
" api_key=model_name[\"key\"],\n",
|
||||
" base_url=model_name[\"endpoint\"]\n",
|
||||
" )\n",
|
||||
" self.cpp_code = \"\"\n",
|
||||
" \n",
|
||||
" def update_progress(self, value, desc=\"\"):\n",
|
||||
" if self.progress:\n",
|
||||
" self.progress(value, desc=desc)\n",
|
||||
" \n",
|
||||
" def port_python_to_cpp(self, python_code):\n",
|
||||
" self.update_progress(0.3, desc=\"Converting Python to C++...\")\n",
|
||||
" \n",
|
||||
" system_prompt = \"\"\"\n",
|
||||
" Your task is to convert Python code into high performance C++ code.\n",
|
||||
" Respond only with C++ code. Do not provide any explanation other than occasional comments.\n",
|
||||
" The C++ response needs to produce an identical output in the fastest possible time.\n",
|
||||
" \"\"\"\n",
|
||||
" \n",
|
||||
" user_prompt = f\"\"\"\n",
|
||||
" Port this Python code to C++ with the fastest possible implementation that produces identical output in the least time.\n",
|
||||
" Respond only with C++ code.\n",
|
||||
" Python code to port:\n",
|
||||
"\n",
|
||||
" ```python\n",
|
||||
" {python_code}\n",
|
||||
" ```\n",
|
||||
" \"\"\"\n",
|
||||
" \n",
|
||||
" messages = [\n",
|
||||
" {\"role\": \"system\", \"content\": system_prompt},\n",
|
||||
" {\"role\": \"user\", \"content\": user_prompt}\n",
|
||||
" ]\n",
|
||||
" \n",
|
||||
" try:\n",
|
||||
" response = self.model.chat.completions.create(\n",
|
||||
" model=self.model_deets[\"model\"],\n",
|
||||
" messages=messages\n",
|
||||
" )\n",
|
||||
" \n",
|
||||
" cpp_code = response.choices[0].message.content\n",
|
||||
" cpp_code = cpp_code.replace('```cpp', '').replace('```', '').strip()\n",
|
||||
" \n",
|
||||
" self.cpp_code = cpp_code\n",
|
||||
" \n",
|
||||
" self.update_progress(1.0, desc=\"Conversion complete!\")\n",
|
||||
" return cpp_code\n",
|
||||
" \n",
|
||||
" except Exception as e:\n",
|
||||
" error_msg = f\"Error converting code: {str(e)}\"\n",
|
||||
" self.update_progress(1.0, desc=\"Conversion failed!\")\n",
|
||||
" return error_msg\n",
|
||||
" \n",
|
||||
" def run_python_code(self, python_code):\n",
|
||||
" self.update_progress(0.1, desc=\"Running Python code...\")\n",
|
||||
" \n",
|
||||
" globals_dict = {\"__builtins__\": __builtins__}\n",
|
||||
" buffer = io.StringIO()\n",
|
||||
" old_stdout = sys.stdout\n",
|
||||
" sys.stdout = buffer\n",
|
||||
" \n",
|
||||
" try:\n",
|
||||
" exec(python_code, globals_dict)\n",
|
||||
" output = buffer.getvalue()\n",
|
||||
" self.update_progress(1.0, desc=\"Python execution complete!\")\n",
|
||||
" except Exception as e:\n",
|
||||
" output = f\"Error: {e}\"\n",
|
||||
" self.update_progress(1.0, desc=\"Python execution failed!\")\n",
|
||||
" finally:\n",
|
||||
" sys.stdout = old_stdout\n",
|
||||
" \n",
|
||||
" return output\n",
|
||||
" \n",
|
||||
" def compile_cpp(self, cpp_code=None):\n",
|
||||
" if cpp_code is None:\n",
|
||||
" cpp_code = self.cpp_code\n",
|
||||
" \n",
|
||||
" if not cpp_code:\n",
|
||||
" return \"No C++ code to compile. Please convert Python code first.\"\n",
|
||||
" \n",
|
||||
" self.update_progress(0.5, desc=\"Compiling C++ code...\")\n",
|
||||
" \n",
|
||||
" with open(\"main.cpp\", \"w\") as f:\n",
|
||||
" f.write(cpp_code)\n",
|
||||
" \n",
|
||||
" compile_command = [\n",
|
||||
" \"clang++\", \"-std=c++17\", \"-Ofast\", \"-mcpu=native\", \n",
|
||||
" \"-flto=thin\", \"-fvisibility=hidden\", \"-DNDEBUG\", \n",
|
||||
" \"main.cpp\", \"-o\", \"main\"\n",
|
||||
" ]\n",
|
||||
" \n",
|
||||
" try:\n",
|
||||
" subprocess.run(compile_command, check=True, text=True, capture_output=True)\n",
|
||||
" self.update_progress(1.0, desc=\"C++ compilation complete!\")\n",
|
||||
" return \"Compilation successful!\"\n",
|
||||
" \n",
|
||||
" except subprocess.CalledProcessError as e:\n",
|
||||
" error_msg = f\"Compilation error: {e.stderr}\"\n",
|
||||
" self.update_progress(1.0, desc=\"C++ compilation failed!\")\n",
|
||||
" return error_msg\n",
|
||||
" except Exception as e:\n",
|
||||
" error_msg = f\"Error: {str(e)}\"\n",
|
||||
" self.update_progress(1.0, desc=\"C++ compilation failed!\")\n",
|
||||
" return error_msg\n",
|
||||
" \n",
|
||||
" def run_cpp(self):\n",
|
||||
" self.update_progress(0.1, desc=\"Running C++ code...\")\n",
|
||||
" \n",
|
||||
" run_command = [\"./main\"]\n",
|
||||
" \n",
|
||||
" try:\n",
|
||||
" if not os.path.exists(\"./main\"):\n",
|
||||
" return \"No compiled executable found. Please compile C++ code first.\"\n",
|
||||
" \n",
|
||||
" run_result = subprocess.run(run_command, check=True, text=True, capture_output=True)\n",
|
||||
" print(\"hello .....\")\n",
|
||||
" self.update_progress(1.0, desc=\"C++ execution complete!\")\n",
|
||||
" return run_result.stdout\n",
|
||||
" \n",
|
||||
" except subprocess.CalledProcessError as e:\n",
|
||||
" error_msg = f\"Runtime error: {e.stderr}\"\n",
|
||||
" self.update_progress(1.0, desc=\"C++ execution failed!\")\n",
|
||||
" return error_msg\n",
|
||||
" except Exception as e:\n",
|
||||
" error_msg = f\"Error: {str(e)}\"\n",
|
||||
" self.update_progress(1.0, desc=\"C++ execution failed!\")\n",
|
||||
" return error_msg\n",
|
||||
" \n",
|
||||
" def compile_and_run_cpp(self, cpp_code=None):\n",
|
||||
" \"\"\"Compile and run C++ code in one step\"\"\"\n",
|
||||
" if cpp_code is None:\n",
|
||||
" cpp_code = self.cpp_code\n",
|
||||
" \n",
|
||||
" if not cpp_code:\n",
|
||||
" return \"No C++ code to compile and run. Please convert Python code first.\"\n",
|
||||
" \n",
|
||||
" compile_result = self.compile_cpp(cpp_code)\n",
|
||||
" if \"error\" in compile_result.lower():\n",
|
||||
" return compile_result\n",
|
||||
" \n",
|
||||
" return self.run_cpp()\n",
|
||||
" \n",
|
||||
" def get_cpp_code(self):\n",
|
||||
" \"\"\"Get the stored C++ code\"\"\"\n",
|
||||
" return self.cpp_code\n",
|
||||
" \n",
|
||||
" def set_cpp_code(self, cpp_code):\n",
|
||||
" \"\"\"Manually set C++ code\"\"\"\n",
|
||||
" self.cpp_code = cpp_code"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 37,
|
||||
"id": "4680573d",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"\n",
|
||||
"class Interface:\n",
|
||||
" def __init__(self):\n",
|
||||
" self.port_code = PortCode(gr.Progress())\n",
|
||||
" \n",
|
||||
" def create_interface(self):\n",
|
||||
" with gr.Blocks(title=\"Code Porter\") as interface:\n",
|
||||
" gr.Markdown(\"# 🚀 Python to C++ Converter\")\n",
|
||||
" \n",
|
||||
" with gr.Row():\n",
|
||||
" python_input = gr.TextArea(label=\"Python Code\", lines=15)\n",
|
||||
" cpp_output = gr.TextArea(label=\"C++ Code\", lines=15, interactive=False)\n",
|
||||
" \n",
|
||||
" with gr.Row():\n",
|
||||
" python_result = gr.TextArea(label=\"Python Output\", lines=4, interactive=False)\n",
|
||||
" cpp_result = gr.TextArea(label=\"C++ Output\", lines=4, interactive=False)\n",
|
||||
" \n",
|
||||
" with gr.Row():\n",
|
||||
" run_python_btn = gr.Button(\"Run Python\")\n",
|
||||
" run_cpp_btn = gr.Button(\"Run C++\")\n",
|
||||
" \n",
|
||||
" with gr.Row():\n",
|
||||
" model_dropdown = gr.Dropdown(MODEL_MAP.keys(), value=\"GPT\", label=\"Model\")\n",
|
||||
" \n",
|
||||
" with gr.Row():\n",
|
||||
" convert_btn = gr.Button(\"Convert\", variant=\"primary\")\n",
|
||||
" \n",
|
||||
" # Events\n",
|
||||
" convert_btn.click(self.convert_code, [python_input, model_dropdown], cpp_output)\n",
|
||||
" run_python_btn.click(self.run_python, python_input, python_result)\n",
|
||||
" run_cpp_btn.click(self.run_cpp, cpp_output, cpp_result)\n",
|
||||
" model_dropdown.change(self.update_model, model_dropdown, None)\n",
|
||||
" \n",
|
||||
" return interface\n",
|
||||
" \n",
|
||||
" def convert_code(self, python_code, model_name):\n",
|
||||
" self.port_code = PortCode(model_name=MODEL_MAP[model_name])\n",
|
||||
" return self.port_code.port_python_to_cpp(python_code)\n",
|
||||
" \n",
|
||||
" def run_python(self, python_code):\n",
|
||||
" return self.port_code.run_python_code(python_code)\n",
|
||||
" \n",
|
||||
" def run_cpp(self, cpp_code):\n",
|
||||
" self.port_code.set_cpp_code(cpp_code)\n",
|
||||
" return self.port_code.compile_and_run_cpp()\n",
|
||||
" \n",
|
||||
" def update_model(self, model_name):\n",
|
||||
" self.port_code = PortCode(model_name=MODEL_MAP[model_name])\n",
|
||||
" \n",
|
||||
" def launch(self, inbrowser=False):\n",
|
||||
" self.create_interface().launch(inbrowser=inbrowser)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 38,
|
||||
"id": "7ced6dc2",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"* Running on local URL: http://127.0.0.1:7906\n",
|
||||
"* To create a public link, set `share=True` in `launch()`.\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"data": {
|
||||
"text/html": [
|
||||
"<div><iframe src=\"http://127.0.0.1:7906/\" width=\"100%\" height=\"500\" allow=\"autoplay; camera; microphone; clipboard-read; clipboard-write;\" frameborder=\"0\" allowfullscreen></iframe></div>"
|
||||
],
|
||||
"text/plain": [
|
||||
"<IPython.core.display.HTML object>"
|
||||
]
|
||||
},
|
||||
"metadata": {},
|
||||
"output_type": "display_data"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"I = Interface()\n",
|
||||
"I.launch()"
|
||||
]
|
||||
}
|
||||
],
|
||||
"metadata": {
|
||||
"kernelspec": {
|
||||
"display_name": ".venv",
|
||||
"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": "3.12.12"
|
||||
}
|
||||
},
|
||||
"nbformat": 4,
|
||||
"nbformat_minor": 5
|
||||
}
|
||||
6
week4/community-contributions/solisoma/main.cpp
Normal file
6
week4/community-contributions/solisoma/main.cpp
Normal file
@@ -0,0 +1,6 @@
|
||||
#include <iostream>
|
||||
|
||||
int main() {
|
||||
std::cout << "hi" << std::endl;
|
||||
return 0;
|
||||
}
|
||||
1833
week4/community-contributions/w4d5-Trade.ipynb
Normal file
1833
week4/community-contributions/w4d5-Trade.ipynb
Normal file
File diff suppressed because it is too large
Load Diff
Reference in New Issue
Block a user