From the uDemy course on LLM engineering.
https://www.udemy.com/course/llm-engineering-master-ai-and-large-language-models
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1276 lines
45 KiB
1276 lines
45 KiB
{ |
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"cells": [ |
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{ |
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"cell_type": "code", |
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"execution_count": null, |
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"id": "6d67dba5-38ec-459a-9132-4a56c6a814cd", |
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"metadata": {}, |
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"outputs": [], |
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"source": [ |
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"Comment and Unit Test Generater \n", |
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"\n", |
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"The requirement: \n", |
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"* use an LLM to generate docstring and comments for Python code\n", |
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"* use an LLM to generate unit test\n", |
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"\n", |
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"This is my week 4 day 5 project." |
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] |
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}, |
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{ |
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"cell_type": "code", |
|
"execution_count": 24, |
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"id": "ea1841f6-4afc-4d29-ace8-5ca5a3915c8c", |
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"metadata": {}, |
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"outputs": [], |
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"source": [ |
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"# imports\n", |
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"\n", |
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"import os\n", |
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"import io\n", |
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"import sys\n", |
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"import json\n", |
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"import requests\n", |
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"from dotenv import load_dotenv\n", |
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"from openai import OpenAI\n", |
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"import google.generativeai\n", |
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"import anthropic\n", |
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"from IPython.display import Markdown, display, update_display\n", |
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"import gradio as gr\n", |
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"import subprocess\n", |
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"from huggingface_hub import login, InferenceClient\n", |
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"from transformers import AutoTokenizer" |
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] |
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}, |
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{ |
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"cell_type": "code", |
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"execution_count": 3, |
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"id": "11957fd3-6c61-4496-aef1-8223cb9ec4ce", |
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"metadata": {}, |
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"outputs": [], |
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"source": [ |
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"# environment\n", |
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"\n", |
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"load_dotenv()\n", |
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"os.environ['OPENAI_API_KEY'] = os.getenv('OPENAI_API_KEY', 'your-key-if-not-using-env')\n", |
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"os.environ['ANTHROPIC_API_KEY'] = os.getenv('ANTHROPIC_API_KEY', 'your-key-if-not-using-env')\n", |
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"os.environ['HF_TOKEN'] = os.getenv('HF_TOKEN', 'your-key-if-not-using-env')" |
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] |
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}, |
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{ |
|
"cell_type": "code", |
|
"execution_count": 4, |
|
"id": "ee7b08fd-e678-4234-895e-4e3a925e60f0", |
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"metadata": {}, |
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"outputs": [], |
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"source": [ |
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"# initialize\n", |
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"\n", |
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"openai = OpenAI()\n", |
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"claude = anthropic.Anthropic()\n", |
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"OPENAI_MODEL = \"gpt-4o\"\n", |
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"CLAUDE_MODEL = \"claude-3-5-sonnet-20240620\"" |
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] |
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}, |
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{ |
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"cell_type": "code", |
|
"execution_count": 25, |
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"id": "c8023255-9c98-4fbc-92e4-c553bed3b605", |
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"metadata": {}, |
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"outputs": [ |
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{ |
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"name": "stderr", |
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"output_type": "stream", |
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"text": [ |
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"Note: Environment variable`HF_TOKEN` is set and is the current active token independently from the token you've just configured.\n" |
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] |
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} |
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], |
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"source": [ |
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"hf_token = os.environ['HF_TOKEN']\n", |
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"login(hf_token, add_to_git_credential=True)" |
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] |
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}, |
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{ |
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"cell_type": "code", |
|
"execution_count": 28, |
|
"id": "f8ce3f5e-74c4-4d35-bfbc-91c5be85e094", |
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"metadata": {}, |
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"outputs": [], |
|
"source": [ |
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"code_qwen = \"Qwen/CodeQwen1.5-7B-Chat\"\n", |
|
"CODE_QWEN_URL = \"https://g39mbjooiiwkbgyz.us-east-1.aws.endpoints.huggingface.cloud\"" |
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] |
|
}, |
|
{ |
|
"cell_type": "code", |
|
"execution_count": 49, |
|
"id": "1bbc66b6-52ae-465e-a368-edc8f097fe9d", |
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"metadata": {}, |
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"outputs": [], |
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"source": [ |
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"def system_prompt_for_comment():\n", |
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" system=\"\"\"\n", |
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" You are a Python documentation expert. When writing documentation:\n", |
|
" - Follow PEP 257 and Google docstring style guidelines\n", |
|
" - Write clear, concise explanations\n", |
|
" - Include practical examples\n", |
|
" - Highlight edge cases and limitations\n", |
|
" - Use type hints in docstrings\n", |
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" - Add inline comments only for complex logic\n", |
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" - Never skip documenting parameters or return values\n", |
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" - Validate that all documentation is accurate and complete\n", |
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" \"\"\"\n", |
|
" return system" |
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] |
|
}, |
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{ |
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"cell_type": "code", |
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"execution_count": 50, |
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"id": "b089f87b-53ae-40ad-8d06-b9924bb998a0", |
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"metadata": {}, |
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"outputs": [], |
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"source": [ |
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"def system_prompt_for_unit_test():\n", |
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" system=\"\"\"\n", |
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" You are an expert Python testing engineer who specializes in creating comprehensive unit tests. Follow these principles:\n", |
|
" - Use pytest as the testing framework\n", |
|
" - Follow the Arrange-Act-Assert pattern\n", |
|
" - Test both valid and invalid inputs\n", |
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" - Include edge cases and boundary conditions\n", |
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" - Write descriptive test names that explain the scenario being tested\n", |
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" - Create independent tests that don't rely on each other\n", |
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" - Use appropriate fixtures and parametrize when needed\n", |
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" - Add clear comments explaining complex test logic\n", |
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" - Cover error cases and exceptions\n", |
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" - Achieve high code coverage while maintaining meaningful tests\n", |
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" \"\"\"\n", |
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" return system" |
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] |
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}, |
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{ |
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"cell_type": "code", |
|
"execution_count": 51, |
|
"id": "22193622-f3a0-4894-a6c4-eb6d88097861", |
|
"metadata": {}, |
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"outputs": [], |
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"source": [ |
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"def user_prompt_for_comment(code):\n", |
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" user = f\"\"\"\n", |
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" Please document this Python code with:\n", |
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" \n", |
|
" 1. A docstring containing:\n", |
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" - A clear description of purpose and functionality\n", |
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" - All parameters with types and descriptions\n", |
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" - Return values with types\n", |
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" - Exceptions that may be raised\n", |
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" - At least one usage example\n", |
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" - Any important notes or limitations\n", |
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" \n", |
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" 2. Strategic inline comments for:\n", |
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" - Complex algorithms or business logic\n", |
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" - Non-obvious implementation choices\n", |
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" - Performance considerations\n", |
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" - Edge cases\n", |
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" \n", |
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" Here's the code to document:\n", |
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" \\n{code}\n", |
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" \"\"\"\n", |
|
" return user;" |
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] |
|
}, |
|
{ |
|
"cell_type": "code", |
|
"execution_count": 52, |
|
"id": "81e61752-ec2f-44c1-86a2-ff3234a0358c", |
|
"metadata": {}, |
|
"outputs": [], |
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"source": [ |
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"def user_prompt_for_unit_test(code):\n", |
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" user = f\"\"\"\n", |
|
" Please generate unit tests for the following Python code. Include:\n", |
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" \n", |
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" 1. Test cases for:\n", |
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" - Normal/expected inputs\n", |
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" - Edge cases and boundary values\n", |
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" - Invalid inputs and error conditions\n", |
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" - Different combinations of parameters\n", |
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" - All public methods and functions\n", |
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" \n", |
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" 2. For each test:\n", |
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" - Clear test function names describing the scenario\n", |
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" - Setup code (fixtures if needed)\n", |
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" - Test data preparation\n", |
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" - Expected outcomes\n", |
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" - Assertions checking results\n", |
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" - Comments explaining complex test logic\n", |
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" \n", |
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" 3. Include any necessary:\n", |
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" - Imports\n", |
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" - Fixtures\n", |
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" - Mock objects\n", |
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" - Helper functions\n", |
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" - Test data generators\n", |
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" \n", |
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" Here's the code to test:\n", |
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" \\n{code}\n", |
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" \"\"\"\n", |
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" return user" |
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] |
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}, |
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{ |
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"cell_type": "code", |
|
"execution_count": 7, |
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"id": "f31ceed3-0eb2-4962-ab86-2d0302185560", |
|
"metadata": {}, |
|
"outputs": [], |
|
"source": [ |
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"pi = \"\"\"\n", |
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"import time\n", |
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"\n", |
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"def calculate(iterations, param1, param2):\n", |
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" result = 1.0\n", |
|
" for i in range(1, iterations+1):\n", |
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" j = i * param1 - param2\n", |
|
" result -= (1/j)\n", |
|
" j = i * param1 + param2\n", |
|
" result += (1/j)\n", |
|
" return result\n", |
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"\n", |
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"start_time = time.time()\n", |
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"result = calculate(100_000_000, 4, 1) * 4\n", |
|
"end_time = time.time()\n", |
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"\n", |
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"print(f\"Result: {result:.12f}\")\n", |
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"print(f\"Execution Time: {(end_time - start_time):.6f} seconds\")\n", |
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"\"\"\"" |
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] |
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}, |
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{ |
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"cell_type": "code", |
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"execution_count": 8, |
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"id": "192c30f5-4be6-49b7-a054-11bfcffa91e0", |
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"metadata": {}, |
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"outputs": [ |
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{ |
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"name": "stdout", |
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"output_type": "stream", |
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"text": [ |
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"Result: 3.141592658589\n", |
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"Execution Time: 58.228012 seconds\n" |
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] |
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} |
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], |
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"source": [ |
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"exec(pi)" |
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] |
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}, |
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{ |
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"cell_type": "code", |
|
"execution_count": 53, |
|
"id": "d4e920dc-4094-42d8-9255-18f2919df2d4", |
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"metadata": {}, |
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"outputs": [], |
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"source": [ |
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"def messages_for_comment(python):\n", |
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" return [\n", |
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" {\"role\": \"system\", \"content\": system_prompt_for_comment()},\n", |
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" {\"role\": \"user\", \"content\": user_prompt_for_comment(python)}\n", |
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" ]" |
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] |
|
}, |
|
{ |
|
"cell_type": "code", |
|
"execution_count": 54, |
|
"id": "77500cae-bf84-405c-8b03-2f984108951b", |
|
"metadata": {}, |
|
"outputs": [], |
|
"source": [ |
|
"def messages_for_unit_test(python):\n", |
|
" return [\n", |
|
" {\"role\": \"system\", \"content\": system_prompt_for_unit_test()},\n", |
|
" {\"role\": \"user\", \"content\": user_prompt_for_unit_test(python)}\n", |
|
" ]" |
|
] |
|
}, |
|
{ |
|
"cell_type": "code", |
|
"execution_count": 58, |
|
"id": "5ec58bf1-4a44-4c21-a71a-2cac359884e5", |
|
"metadata": {}, |
|
"outputs": [], |
|
"source": [ |
|
"def stream_comment_gpt(code):\n", |
|
" stream = openai.chat.completions.create(model=OPENAI_MODEL, messages=messages_for_comment(code), 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", |
|
" yield reply.replace('```','') \n", |
|
" " |
|
] |
|
}, |
|
{ |
|
"cell_type": "code", |
|
"execution_count": 18, |
|
"id": "47c615e2-4eb6-4ce1-ad09-7f2e6dbc3934", |
|
"metadata": {}, |
|
"outputs": [ |
|
{ |
|
"name": "stdout", |
|
"output_type": "stream", |
|
"text": [ |
|
"```python\n", |
|
"import time\n", |
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"\n", |
|
"def calculate(iterations: int, param1: float, param2: float) -> float:\n", |
|
" \"\"\"\n", |
|
" Performs a series of mathematical operations in a loop to calculate a result.\n", |
|
"\n", |
|
" This function iteratively modifies a result variable through a series of arithmetic\n", |
|
" operations. Essentially, it calculates the sum of alternating series adjustments,\n", |
|
" simulating a specific numerical approximation process.\n", |
|
"\n", |
|
" Args:\n", |
|
" iterations (int): The number of iterations to perform. Must be a positive integer.\n", |
|
" param1 (float): The factor applied for multiplication inside the iteration.\n", |
|
" param2 (float): The factor subtracted and added inside the iteration for denominator adjustment.\n", |
|
"\n", |
|
" Returns:\n", |
|
" float: The calculated result after completing all iterations.\n", |
|
"\n", |
|
" Raises:\n", |
|
" ZeroDivisionError: If any calculated denominator becomes zero during execution,\n", |
|
" which may happen if `i * param1 - param2` or `i * param1 + param2` evaluates to zero.\n", |
|
"\n", |
|
" Usage Example:\n", |
|
" result = calculate(100_000_000, 4, 1)\n", |
|
" print(f\"Calculated Result: {result * 4}\")\n", |
|
"\n", |
|
" Notes:\n", |
|
" - The function can be computationally intensive depending on the number of iterations.\n", |
|
" - Ensure that `param1` and `param2` are chosen to avoid division by zero.\n", |
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" - Floating-point precision issues might arise due to large iterations count.\n", |
|
" \"\"\"\n", |
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" \n", |
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" result = 1.0\n", |
|
" for i in range(1, iterations + 1):\n", |
|
" # Calculate modified denominator by subtracting param2\n", |
|
" j = i * param1 - param2\n", |
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" \n", |
|
" # Subtract reciprocal from the result\n", |
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" # Potential ZeroDivisionError if (i * param1 - param2) == 0\n", |
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" result -= (1 / j)\n", |
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" \n", |
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" # Calculate modified denominator by adding param2\n", |
|
" j = i * param1 + param2\n", |
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" \n", |
|
" # Add reciprocal to the result\n", |
|
" # Potential ZeroDivisionError if (i * param1 + param2) == 0\n", |
|
" result += (1 / j)\n", |
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" \n", |
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" return result\n", |
|
"\n", |
|
"\n", |
|
"start_time = time.time()\n", |
|
"result = calculate(100_000_000, 4, 1) * 4 # Scaling final result by 4 for specific use case\n", |
|
"end_time = time.time()\n", |
|
"\n", |
|
"# Output result with high precision and execution time for measurement\n", |
|
"print(f\"Result: {result:.12f}\")\n", |
|
"print(f\"Execution Time: {(end_time - start_time):.6f} seconds\")\n", |
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"```\n", |
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"\n", |
|
"### Explanation of Changes:\n", |
|
"- **Docstring**: The docstring provides a comprehensive explanation of the function's purpose and the calculations it performs, specifying parameter types and behavior.\n", |
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"- **Exceptions**: A note about `ZeroDivisionError` is included, as the calculation might lead to division by zero with certain inputs.\n", |
|
"- **Usage Example**: Demonstrates how to call the function with a specific configuration.\n", |
|
"- **Notes**: Provides guidance on potential performance concerns and precision limitations.\n", |
|
"- **Inline Comments**: Added to clarify key lines where logical computations occur and where division by zero might be a risk." |
|
] |
|
} |
|
], |
|
"source": [ |
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"stream_comment_gpt(pi)" |
|
] |
|
}, |
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{ |
|
"cell_type": "code", |
|
"execution_count": 59, |
|
"id": "0b990875-31fd-40e5-bc8c-f6099d362249", |
|
"metadata": {}, |
|
"outputs": [], |
|
"source": [ |
|
"def stream_unit_test_gpt(code):\n", |
|
" stream = openai.chat.completions.create(model=OPENAI_MODEL, messages=messages_for_unit_test(code), 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", |
|
" yield reply.replace('```','')" |
|
] |
|
}, |
|
{ |
|
"cell_type": "code", |
|
"execution_count": 73, |
|
"id": "3dc90578-4f5e-47f1-b30f-c21b5795e82f", |
|
"metadata": {}, |
|
"outputs": [ |
|
{ |
|
"data": { |
|
"text/plain": [ |
|
"<generator object stream_unit_test_gpt at 0x000002A31DC9C440>" |
|
] |
|
}, |
|
"execution_count": 73, |
|
"metadata": {}, |
|
"output_type": "execute_result" |
|
} |
|
], |
|
"source": [ |
|
"stream_unit_test_gpt(pi)" |
|
] |
|
}, |
|
{ |
|
"cell_type": "code", |
|
"execution_count": 60, |
|
"id": "17380c0f-b851-472b-a234-d86f5c219e50", |
|
"metadata": {}, |
|
"outputs": [], |
|
"source": [ |
|
"def stream_comment_claude(code):\n", |
|
" result = claude.messages.stream(\n", |
|
" model=CLAUDE_MODEL,\n", |
|
" max_tokens=2000,\n", |
|
" system=system_prompt_for_comment(),\n", |
|
" messages=[{\"role\": \"user\", \"content\": user_prompt_for_comment(code)}],\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", |
|
" yield reply.replace('```','')" |
|
] |
|
}, |
|
{ |
|
"cell_type": "code", |
|
"execution_count": 64, |
|
"id": "0a2d016d-76a2-4752-bd4d-6f93ddec46be", |
|
"metadata": {}, |
|
"outputs": [], |
|
"source": [ |
|
"def stream_unit_test_claude(code):\n", |
|
" result = claude.messages.stream(\n", |
|
" model=CLAUDE_MODEL,\n", |
|
" max_tokens=2000,\n", |
|
" system=system_prompt_for_unit_test(),\n", |
|
" messages=[{\"role\": \"user\", \"content\": user_prompt_for_unit_test(code)}],\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", |
|
" yield reply.replace('```','')" |
|
] |
|
}, |
|
{ |
|
"cell_type": "code", |
|
"execution_count": 23, |
|
"id": "ee43428e-b577-4e95-944d-399f2f3b89ff", |
|
"metadata": {}, |
|
"outputs": [ |
|
{ |
|
"name": "stdout", |
|
"output_type": "stream", |
|
"text": [ |
|
"Here's the documented version of your Python code:\n", |
|
"\n", |
|
"```python\n", |
|
"import time\n", |
|
"\n", |
|
" float) -> float:rations: int, param1: float, param2:\n", |
|
" \"\"\"\n", |
|
"Calculates a series sum based on the given parameters.\n", |
|
"\n", |
|
" This function computes a series sum using the formula:\n", |
|
"i*param1 + param2) - 1/(i*param1 - param2)) for i from 1 to iterations.\n", |
|
"\n", |
|
" Args:\n", |
|
" iterations to perform. Must be positive.\n", |
|
"float): The first parameter used in the calculation.\n", |
|
"(float): The second parameter used in the calculation.\n", |
|
"\n", |
|
" Returns:\n", |
|
". float: The result of the series sum calculation\n", |
|
"\n", |
|
" Raises:\n", |
|
". ValueError: If iterations is not positive\n", |
|
"is 0 or if param2 is equal to param1.\n", |
|
"\n", |
|
" Example:\n", |
|
" = calculate(1000, 4, 1)\n", |
|
">>> print(f\"{result:.6f}\")\n", |
|
".392699 0\n", |
|
"\n", |
|
" Note:\n", |
|
" The function may be computationally expensive for large numbers of iterations.\n", |
|
", floating-point precision limitations may affect accuracy.\n", |
|
" \"\"\"\n", |
|
" if iterations <= 0:\n", |
|
" must be a positive integer\")rations\n", |
|
"\n", |
|
" result = 1.0\n", |
|
" for i in range(1, iterations + 1):\n", |
|
" the seriesalculate the denominators for both terms in\n", |
|
"1 - param2 = i * param\n", |
|
" param1 + param2\n", |
|
"\n", |
|
"d division by zero\n", |
|
" 0 or j2 == 0:==\n", |
|
" calculation\")ise ZeroDivisionError(\"Division by zero in\n", |
|
"\n", |
|
"d add the second terme first term an\n", |
|
" result -= (1 / j1)\n", |
|
" result += (1 / j2)\n", |
|
"\n", |
|
" return result\n", |
|
"\n", |
|
"# Measure execution time\n", |
|
"()art_time = time.time\n", |
|
"\n", |
|
"# Perform calculation with 100 million iterations\n", |
|
" The result is multiplied by 4 as per the original code\n", |
|
"000, 4, 1) * 4late(100_000_\n", |
|
"\n", |
|
"d_time = time.time()\n", |
|
"\n", |
|
" with high precision for the calculated value\n", |
|
"Result: {result:.12f}\")\n", |
|
"(f\"Execution Time: {(end_time - start_time):.6f} seconds\")\n", |
|
"```\n", |
|
"\n", |
|
" this documented version:\n", |
|
"\n", |
|
" been added to the `calculate` function, following Google style guidelines and including all the requested elements.\n", |
|
"\n", |
|
" hints have been added to the function signature for better clarity and to support static type checking.\n", |
|
"\n", |
|
"d to explain the key steps in the calculation process.\n", |
|
"\n", |
|
" check for positive iterations has been added to prevent invalid input.\n", |
|
"\n", |
|
" been added to handle potential errors.\n", |
|
"\n", |
|
" Comments have been added to the main script to explain the purpose of each step.\n", |
|
"\n", |
|
" documentation provides a clear understanding of the function's purpose, its parameters, return value, potential exceptions, and includes an example of usage. It also notes potential limitations regarding computational cost and floating-point precision for very large numbers of iterations." |
|
] |
|
} |
|
], |
|
"source": [ |
|
"stream_comment_claude(pi)" |
|
] |
|
}, |
|
{ |
|
"cell_type": "code", |
|
"execution_count": 63, |
|
"id": "0565e33b-9f14-48b7-ae8d-d22dc03b93c9", |
|
"metadata": {}, |
|
"outputs": [ |
|
{ |
|
"name": "stdout", |
|
"output_type": "stream", |
|
"text": [ |
|
"Here's a comprehensive set of unit tests for the given Python code using pytest:\n", |
|
"\n", |
|
"```python\n", |
|
"import pytest\n", |
|
"import time\n", |
|
" import isclose\n", |
|
"from unittest.mock import patch\n", |
|
"\n", |
|
"# Import the function to be tested\n", |
|
"# Assuming the code is in a file named your_module.py\n", |
|
"\n", |
|
"# Test data generator\n", |
|
"_data():rate_test\n", |
|
" return [\n", |
|
", 2, 1, 0.6931471805),\n", |
|
" 3, 2, 0.6931471806),\n", |
|
", 3, 0.6931471806),\n", |
|
", 1, 0.6931471806),\n", |
|
" ]\n", |
|
"\n", |
|
" datature for common test\n", |
|
"@pytest.fixture\n", |
|
"def common_data():\n", |
|
"return {\n", |
|
" 'iterations': 100,\n", |
|
" 'param1': 4,\n", |
|
" 'param2': 1\n", |
|
" }\n", |
|
"\n", |
|
"# Normal case tests\n", |
|
"rize(\"iterations, param1, param2, expected\", generate_test_data())\n", |
|
"cases(iterations, param1, param2, expected):\n", |
|
"1, param2) = calculate(iterations, param\n", |
|
"(result, expected, rel_tol=1e-9), f\"Expected {expected}, but got {result}\"\n", |
|
"\n", |
|
" cases and boundary values\n", |
|
"_cases():calculate_edge\n", |
|
"d inputsst with minimum vali\n", |
|
" 0) == 2.0 calculate(1, 1,\n", |
|
" \n", |
|
" # Test with very large iterations\n", |
|
"_result = calculate(10**8, 4, 1)\n", |
|
", 0.6931471806, rel_tol=1e-9)lt\n", |
|
"\n", |
|
"# Invalid inputs and error conditions\n", |
|
"def test_calculate_invalid_inputs():\n", |
|
" with pytest.raises(ValueError):\n", |
|
"0, 4, 1) # iterations should be positive\n", |
|
" \n", |
|
"(ZeroDivisionError):es\n", |
|
"10, 1, 1) # This will cause division by zero\n", |
|
"\n", |
|
"TypeError):test.raises(\n", |
|
"1) # iterations should be an integer\n", |
|
"\n", |
|
"# Test with different combinations of parameters\n", |
|
"rize(\"iterations, param1, param2\", [\n", |
|
"), (100, 2, 2\n", |
|
" (1000, 3, 3),\n", |
|
"(10000, 5, 5),\n", |
|
" (100000, 10, 10)\n", |
|
"])\n", |
|
" param1, param2):e_parameter_combinations(iterations,\n", |
|
" calculate(iterations, param1, param2)\n", |
|
" assert isinstance(result, float)\n", |
|
" assert result > 0\n", |
|
"\n", |
|
" execution time\n", |
|
"common_data):ulate_execution_time(\n", |
|
" time.time()me =\n", |
|
" calculate(**common_data)\n", |
|
" end_time = time.time()\n", |
|
" execution_time = end_time - start_time\n", |
|
" f\"Execution took {execution_time} seconds, which is too long\"\n", |
|
"\n", |
|
" result precision\n", |
|
"data):st_calculate_precision(common_\n", |
|
"data)esult = calculate(**common_\n", |
|
"split('.')[1]) >= 10, \"Result should have at least 10 decimal places\"\n", |
|
"\n", |
|
"# Test with mocked time function\n", |
|
".time')'time\n", |
|
"(mock_time, common_data):ocked_time\n", |
|
", 0.5] # Simulate 0.5 seconds execution time\n", |
|
"_time = time.time()\n", |
|
" = calculate(**common_data)\n", |
|
"d_time = time.time()\n", |
|
" end_time - start_time == 0.5\n", |
|
"\n", |
|
"# Helper function to test monotonicity\n", |
|
"_monotonic(lst):\n", |
|
" <= lst[i+1] for i in range(len(lst)-1)) or all(lst[i] >= lst[i+1] for i in range(len(lst)-1))\n", |
|
"\n", |
|
" increasing iterationscity with\n", |
|
"def test_calculate_monotonicity():\n", |
|
" 1) for i in range(1, 6)]10**i, 4,\n", |
|
"), \"Results should be monotonic with increasing iterations\"\n", |
|
"\n", |
|
" Test with very small and very large parameters\n", |
|
", param1, param2\", [rize(\"iterations\n", |
|
"(100, 1e-5, 1e-5),\n", |
|
", 1e5)00, 1e5\n", |
|
"])\n", |
|
"_parameters(iterations, param1, param2):\n", |
|
"1, param2) = calculate(iterations, param\n", |
|
"result == float('inf') or result == float('-inf')), \"Result should not be infinity\"\n", |
|
"assert not isclose(result, 0, abs_tol=1e-10), \"Result should not be too close to zero\"\n", |
|
"\n", |
|
"```\n", |
|
"\n", |
|
" for the `calculate` function:range of scenarios\n", |
|
"\n", |
|
" with different inputs and expected outputs.\n", |
|
" and boundary values, including minimum valid inputs and very large iterations.\n", |
|
" Invalid inputs and error conditions, testing for expected exceptions.\n", |
|
" Different combinations of parameters to ensure the function works correctly for various inputs.\n", |
|
" to ensure the function performs within acceptable time limits.\n", |
|
" Precision test to verify the result has sufficient decimal places.\n", |
|
" A test with mocked time function to simulate and verify execution time measurement.\n", |
|
" if results are consistent with increasing iterations.\n", |
|
" with extreme parameters (very small and very large) to ensure numerical stability.\n", |
|
"\n", |
|
"rization, fixtures, and markers. It also includes necessary imports, helper functions, and a test data generator.\n", |
|
"\n", |
|
"d `test_your_module.py` in the same directory as your original code file (`your_module.py`). Then run `pytest test_your_module.py` from the command line.\n", |
|
"\n", |
|
" pytest (`pip install pytest`) before running the tests." |
|
] |
|
} |
|
], |
|
"source": [ |
|
"stream_unit_test_claude(pi)" |
|
] |
|
}, |
|
{ |
|
"cell_type": "code", |
|
"execution_count": 40, |
|
"id": "f13b3a5b-366d-4b28-adda-977a313e6b4d", |
|
"metadata": {}, |
|
"outputs": [], |
|
"source": [ |
|
"def stream_comment_model(model, model_url, code):\n", |
|
" tokenizer = AutoTokenizer.from_pretrained(model)\n", |
|
" messages = messages_for_comment(code)\n", |
|
" text = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)\n", |
|
" client = InferenceClient(model_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", |
|
" #print(r.token.text, end = \"\")\n", |
|
" result += r.token.text\n", |
|
" yield result \n", |
|
" " |
|
] |
|
}, |
|
{ |
|
"cell_type": "code", |
|
"execution_count": 67, |
|
"id": "e2efdb92-fc7a-4952-ab46-ae942cb996bf", |
|
"metadata": {}, |
|
"outputs": [], |
|
"source": [ |
|
"def stream_unit_test_model(model, model_url, code):\n", |
|
" tokenizer = AutoTokenizer.from_pretrained(model)\n", |
|
" messages = messages_for_unit_test(code)\n", |
|
" text = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)\n", |
|
" client = InferenceClient(model_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", |
|
" #print(r.token.text, end = \"\")\n", |
|
" result += r.token.text\n", |
|
" yield result \n", |
|
" " |
|
] |
|
}, |
|
{ |
|
"cell_type": "code", |
|
"execution_count": 41, |
|
"id": "0a756193-fcba-43da-a981-203c10d36488", |
|
"metadata": {}, |
|
"outputs": [ |
|
{ |
|
"data": { |
|
"text/plain": [ |
|
"<generator object stream_comment_model at 0x000002A31C666770>" |
|
] |
|
}, |
|
"execution_count": 41, |
|
"metadata": {}, |
|
"output_type": "execute_result" |
|
} |
|
], |
|
"source": [ |
|
"stream_comment_model(code_qwen, CODE_QWEN_URL, pi)" |
|
] |
|
}, |
|
{ |
|
"cell_type": "code", |
|
"execution_count": 70, |
|
"id": "12ddcbf4-6286-47a8-847b-5be78e7aa995", |
|
"metadata": {}, |
|
"outputs": [ |
|
{ |
|
"name": "stdout", |
|
"output_type": "stream", |
|
"text": [ |
|
"Here are the unit tests for the given Python code:\n", |
|
"\n", |
|
"```python\n", |
|
"import pytest\n", |
|
"import time\n", |
|
" unittest.mock import patch\n", |
|
"\n", |
|
"def calculate(iterations, param1, param2):\n", |
|
" result = 1.0\n", |
|
" for i in range(1, iterations+1):\n", |
|
" i * param1 - param2\n", |
|
"result -= (1/j)\n", |
|
" j = i * param1 + param2\n", |
|
"result += (1/j)\n", |
|
" return result\n", |
|
"\n", |
|
"@pytest.fixture\n", |
|
" mock_time():\n", |
|
"('time.time') as mock_time:\n", |
|
"yield mock_time\n", |
|
"\n", |
|
"_calculate_normal_inputs(mock_time):\n", |
|
"mock_time.return_value = 0\n", |
|
"result = calculate(100_000_000, 4, 1) * 4\n", |
|
"expected_result = 0.0\n", |
|
" == expected_result\n", |
|
"\n", |
|
"_calculate_edge_cases(mock_time):\n", |
|
" mock_time.return_value = 0\n", |
|
" calculate(0, 4, 1) * 4\n", |
|
" expected_result = 0.0\n", |
|
" result == expected_result\n", |
|
"\n", |
|
" = calculate(100_000_000, 0, 1) * 4\n", |
|
"expected_result = 0.0\n", |
|
" result == expected_result\n", |
|
"\n", |
|
" = calculate(100_000_000, 4, 0) * 4\n", |
|
"_result = 0.0\n", |
|
" assert result == expected_result\n", |
|
"\n", |
|
"def test_calculate_invalid_inputs(mock_time):\n", |
|
" mock_time.return_value = 0\n", |
|
".raises(TypeError):\n", |
|
"calculate(100_000_000, 'a', 1) * 4\n", |
|
"with pytest.raises(TypeError):\n", |
|
"100_000_000, 4, 'b') * 4\n", |
|
".raises(TypeError):\n", |
|
"calculate('a', 4, 1) * 4\n", |
|
"test.raises(TypeError):\n", |
|
"(100_000_000, 4, 1, 'c') * 4\n", |
|
"\n", |
|
"def test_calculate_different_combinations(mock_time):\n", |
|
" mock_time.return_value = 0\n", |
|
"result = calculate(100_000_000, 4, 1) * 4\n", |
|
" expected_result = 0.0\n", |
|
" result == expected_result\n", |
|
"\n", |
|
" = calculate(100_000_000, 4, -1) * 4\n", |
|
"expected_result = 0.0\n", |
|
" == expected_result\n", |
|
"\n", |
|
" calculate(100_000_000, -4, 1) * 4\n", |
|
"result = 0.0_\n", |
|
"assert result == expected_result\n", |
|
"\n", |
|
"result = calculate(100_000_000, -4, -1) * 4\n", |
|
" expected_result = 0.0\n", |
|
" result == expected_result\n", |
|
"\n", |
|
"def test_calculate_execution_time(mock_time):\n", |
|
"_time.return_value = 0\n", |
|
"_time = mock_time.return_value\n", |
|
"calculate(100_000_000, 4, 1) * 4\n", |
|
"end_time = mock_time.return_value\n", |
|
" expected_execution_time = 0.0\n", |
|
" assert (end_time - start_time) == expected_execution_time\n", |
|
"```\n", |
|
"\n", |
|
" covers all the scenarios mentioned in the problem description. It tests the function with normal inputs, edge cases, invalid inputs, different combinations of parameters, and checks the execution time.<|im_end|>" |
|
] |
|
} |
|
], |
|
"source": [ |
|
"stream_unit_test_model(code_qwen, CODE_QWEN_URL, pi)" |
|
] |
|
}, |
|
{ |
|
"cell_type": "code", |
|
"execution_count": 46, |
|
"id": "321609ee-b64a-44fc-9090-39f87e1f8e0e", |
|
"metadata": {}, |
|
"outputs": [], |
|
"source": [ |
|
"def comment_code(python, model):\n", |
|
" if model==\"GPT\":\n", |
|
" result = stream_comment_gpt(python)\n", |
|
" elif model==\"Claude\":\n", |
|
" result = stream_comment_claude(python)\n", |
|
" elif model==\"CodeQwen\":\n", |
|
" result = stream_comment_model(code_qwen, CODE_QWEN_URL, 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": 69, |
|
"id": "d4c560c9-922d-4893-941f-42893373b1be", |
|
"metadata": {}, |
|
"outputs": [], |
|
"source": [ |
|
"def get_unit_test(python, model):\n", |
|
" if model==\"GPT\":\n", |
|
" result = stream_unit_test_gpt(python)\n", |
|
" elif model==\"Claude\":\n", |
|
" result = stream_unit_test_claude(python)\n", |
|
" elif model==\"CodeQwen\":\n", |
|
" result = stream_unit_test_model(code_qwen, CODE_QWEN_URL, 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": 35, |
|
"id": "f85bc777-bebe-436b-88cc-b9ecdb6306c0", |
|
"metadata": {}, |
|
"outputs": [], |
|
"source": [ |
|
"css = \"\"\"\n", |
|
".python {background-color: #306998;}\n", |
|
".cpp {background-color: #050;}\n", |
|
"\"\"\"" |
|
] |
|
}, |
|
{ |
|
"cell_type": "code", |
|
"execution_count": 74, |
|
"id": "ee27cc91-81e6-42c8-ae3c-c04161229d8c", |
|
"metadata": {}, |
|
"outputs": [ |
|
{ |
|
"name": "stdout", |
|
"output_type": "stream", |
|
"text": [ |
|
"* Running on local URL: http://127.0.0.1:7881\n", |
|
"\n", |
|
"To create a public link, set `share=True` in `launch()`.\n" |
|
] |
|
}, |
|
{ |
|
"data": { |
|
"text/html": [ |
|
"<div><iframe src=\"http://127.0.0.1:7881/\" 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" |
|
}, |
|
{ |
|
"data": { |
|
"text/plain": [] |
|
}, |
|
"execution_count": 74, |
|
"metadata": {}, |
|
"output_type": "execute_result" |
|
}, |
|
{ |
|
"name": "stdout", |
|
"output_type": "stream", |
|
"text": [ |
|
"Here are the unit tests for the given Python code:\n", |
|
"\n", |
|
"```python\n", |
|
"import pytest\n", |
|
"import time\n", |
|
" unittest.mock import patch\n", |
|
"\n", |
|
"def calculate(iterations, param1, param2):\n", |
|
" result = 1.0\n", |
|
" for i in range(1, iterations+1):\n", |
|
" i * param1 - param2\n", |
|
" result -= (1/j)\n", |
|
" i * param1 + param2\n", |
|
"result += (1/j)\n", |
|
" return result\n", |
|
"\n", |
|
"@pytest.fixture\n", |
|
" mock_time():\n", |
|
" with patch('time.time') as mock_time:\n", |
|
"ield mock_time\n", |
|
"\n", |
|
"calculate_normal_inputs(mock_time):\n", |
|
"time.return_value = 0\n", |
|
" calculate(100_000_000, 4, 1) * 4\n", |
|
"result = 0.0_\n", |
|
"assert result == expected_result\n", |
|
"\n", |
|
" test_calculate_edge_cases(mock_time):\n", |
|
"time.return_value = 0\n", |
|
" calculate(0, 4, 1) * 4\n", |
|
"_result = 0.0\n", |
|
" assert result == expected_result\n", |
|
"\n", |
|
" result = calculate(100_000_000, 0, 1) * 4\n", |
|
"result = 0.0_\n", |
|
"assert result == expected_result\n", |
|
"\n", |
|
"result = calculate(100_000_000, 4, 0) * 4\n", |
|
" expected_result = 0.0\n", |
|
"assert result == expected_result\n", |
|
"\n", |
|
" test_calculate_invalid_inputs(mock_time):\n", |
|
"_time.return_value = 0\n", |
|
"test.raises(TypeError):\n", |
|
" calculate(100_000_000, 'a', 1) * 4\n", |
|
"with pytest.raises(TypeError):\n", |
|
"ulate(100_000_000, 4, 'b') * 4\n", |
|
" pytest.raises(TypeError):\n", |
|
"ulate('a', 4, 1) * 4\n", |
|
"test.raises(TypeError):\n", |
|
" calculate(100_000_000, 4, 1, 'c') * 4\n", |
|
"\n", |
|
"_calculate_different_combinations(mock_time):\n", |
|
" mock_time.return_value = 0\n", |
|
" result = calculate(100_000_000, 4, 1) * 4\n", |
|
" expected_result = 0.0\n", |
|
" == expected_result\n", |
|
"\n", |
|
" calculate(100_000_000, 4, -1) * 4\n", |
|
"_result = 0.0\n", |
|
" assert result == expected_result\n", |
|
"\n", |
|
" result = calculate(100_000_000, -4, 1) * 4\n", |
|
" expected_result = 0.0\n", |
|
" result == expected_result\n", |
|
"\n", |
|
" calculate(100_000_000, -4, -1) * 4\n", |
|
"_result = 0.0\n", |
|
" assert result == expected_result\n", |
|
"\n", |
|
"def test_calculate_execution_time(mock_time):\n", |
|
"mock_time.return_value = 0\n", |
|
"start_time = mock_time.return_value\n", |
|
" calculate(100_000_000, 4, 1) * 4\n", |
|
" end_time = mock_time.return_value\n", |
|
" expected_execution_time = 0.0\n", |
|
" assert (end_time - start_time) == expected_execution_time\n", |
|
"```\n", |
|
"\n", |
|
" covers all the scenarios mentioned in the problem description. It tests the function with normal inputs, edge cases, invalid inputs, different combinations of parameters, and checks the execution time.<|im_end|>" |
|
] |
|
}, |
|
{ |
|
"name": "stderr", |
|
"output_type": "stream", |
|
"text": [ |
|
"Traceback (most recent call last):\n", |
|
" File \"C:\\Users\\ebaba\\.conda\\envs\\llms\\Lib\\site-packages\\gradio\\queueing.py\", line 625, in process_events\n", |
|
" response = await route_utils.call_process_api(\n", |
|
" ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n", |
|
" File \"C:\\Users\\ebaba\\.conda\\envs\\llms\\Lib\\site-packages\\gradio\\route_utils.py\", line 322, in call_process_api\n", |
|
" output = await app.get_blocks().process_api(\n", |
|
" ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n", |
|
" File \"C:\\Users\\ebaba\\.conda\\envs\\llms\\Lib\\site-packages\\gradio\\blocks.py\", line 2047, in process_api\n", |
|
" result = await self.call_function(\n", |
|
" ^^^^^^^^^^^^^^^^^^^^^^^^^\n", |
|
" File \"C:\\Users\\ebaba\\.conda\\envs\\llms\\Lib\\site-packages\\gradio\\blocks.py\", line 1606, in call_function\n", |
|
" prediction = await utils.async_iteration(iterator)\n", |
|
" ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n", |
|
" File \"C:\\Users\\ebaba\\.conda\\envs\\llms\\Lib\\site-packages\\gradio\\utils.py\", line 714, in async_iteration\n", |
|
" return await anext(iterator)\n", |
|
" ^^^^^^^^^^^^^^^^^^^^^\n", |
|
" File \"C:\\Users\\ebaba\\.conda\\envs\\llms\\Lib\\site-packages\\gradio\\utils.py\", line 708, in __anext__\n", |
|
" return await anyio.to_thread.run_sync(\n", |
|
" ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n", |
|
" File \"C:\\Users\\ebaba\\.conda\\envs\\llms\\Lib\\site-packages\\anyio\\to_thread.py\", line 56, in run_sync\n", |
|
" return await get_async_backend().run_sync_in_worker_thread(\n", |
|
" ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n", |
|
" File \"C:\\Users\\ebaba\\.conda\\envs\\llms\\Lib\\site-packages\\anyio\\_backends\\_asyncio.py\", line 2505, in run_sync_in_worker_thread\n", |
|
" return await future\n", |
|
" ^^^^^^^^^^^^\n", |
|
" File \"C:\\Users\\ebaba\\.conda\\envs\\llms\\Lib\\site-packages\\anyio\\_backends\\_asyncio.py\", line 1005, in run\n", |
|
" result = context.run(func, *args)\n", |
|
" ^^^^^^^^^^^^^^^^^^^^^^^^\n", |
|
" File \"C:\\Users\\ebaba\\.conda\\envs\\llms\\Lib\\site-packages\\gradio\\utils.py\", line 691, in run_sync_iterator_async\n", |
|
" return next(iterator)\n", |
|
" ^^^^^^^^^^^^^^\n", |
|
" File \"C:\\Users\\ebaba\\.conda\\envs\\llms\\Lib\\site-packages\\gradio\\utils.py\", line 852, in gen_wrapper\n", |
|
" response = next(iterator)\n", |
|
" ^^^^^^^^^^^^^^\n", |
|
" File \"C:\\Users\\ebaba\\AppData\\Local\\Temp\\ipykernel_27660\\2822054561.py\", line 10, in get_unit_test\n", |
|
" for stream_so_far in result:\n", |
|
"TypeError: 'NoneType' object is not iterable\n" |
|
] |
|
}, |
|
{ |
|
"name": "stdout", |
|
"output_type": "stream", |
|
"text": [ |
|
"Here are the unit tests for the given Python code:\n", |
|
"\n", |
|
"```python\n", |
|
"import pytest\n", |
|
"import time\n", |
|
"est.mock import patch\n", |
|
"\n", |
|
"(iterations, param1, param2):\n", |
|
"result = 1.0\n", |
|
"for i in range(1, iterations+1):\n", |
|
"j = i * param1 - param2\n", |
|
" -= (1/j)esult\n", |
|
"j = i * param1 + param2\n", |
|
" += (1/j)esult\n", |
|
"return result\n", |
|
"\n", |
|
"pytest.fixture\n", |
|
"_time():\n", |
|
" with patch('time.time') as mock_time:\n", |
|
"ield mock_time\n", |
|
"\n", |
|
"calculate_normal_inputs(mock_time):\n", |
|
"time.return_value = 0\n", |
|
" calculate(100_000_000, 4, 1) * 4\n", |
|
"_result = 0.0\n", |
|
" assert result == expected_result\n", |
|
"\n", |
|
"def test_calculate_edge_cases(mock_time):\n", |
|
"mock_time.return_value = 0\n", |
|
"result = calculate(0, 4, 1) * 4\n", |
|
" expected_result = 0.0\n", |
|
" result == expected_result\n", |
|
"\n", |
|
" = calculate(100_000_000, 0, 1) * 4\n", |
|
"_result = 0.0\n", |
|
"assert result == expected_result\n", |
|
"\n", |
|
"result = calculate(100_000_000, 4, 0) * 4\n", |
|
" expected_result = 0.0\n", |
|
" result == expected_result\n", |
|
"\n", |
|
"_calculate_invalid_inputs(mock_time):\n", |
|
"time.return_value = 0\n", |
|
" with pytest.raises(TypeError):\n", |
|
"(100_000_000, 'a', 1) * 4\n", |
|
"ises(TypeError):ra\n", |
|
"ulate(100_000_000, 4, 'b') * 4\n", |
|
" pytest.raises(TypeError):\n", |
|
"ulate('a', 4, 1) * 4\n", |
|
" pytest.raises(TypeError):\n", |
|
"ulate(100_000_000, 4, 1, 'c') * 4\n", |
|
"\n", |
|
"calculate_different_combinations(mock_time):\n", |
|
" mock_time.return_value = 0\n", |
|
" result = calculate(100_000_000, 4, 1) * 4\n", |
|
" = 0.0pected_result\n", |
|
" result == expected_result\n", |
|
"\n", |
|
" = calculate(100_000_000, 4, -1) * 4\n", |
|
"expected_result = 0.0\n", |
|
" expected_resultt ==\n", |
|
"\n", |
|
" result = calculate(100_000_000, -4, 1) * 4\n", |
|
"result = 0.0_\n", |
|
" == expected_result\n", |
|
"\n", |
|
" calculate(100_000_000, -4, -1) * 4\n", |
|
" = 0.0pected_result\n", |
|
" result == expected_result\n", |
|
"\n", |
|
"def test_calculate_execution_time(mock_time):\n", |
|
"_time.return_value = 0\n", |
|
"_time = mock_time.return_value\n", |
|
"100_000_000, 4, 1) * 4\n", |
|
" end_time = mock_time.return_value\n", |
|
"_execution_time = 0.0\n", |
|
" (end_time - start_time) == expected_execution_time\n", |
|
"``\n", |
|
"\n", |
|
" suite covers all the scenarios mentioned in the problem description. It tests the function with normal inputs, edge cases, invalid inputs, different combinations of parameters, and checks the execution time.<|im_end|>" |
|
] |
|
}, |
|
{ |
|
"name": "stderr", |
|
"output_type": "stream", |
|
"text": [ |
|
"Traceback (most recent call last):\n", |
|
" File \"C:\\Users\\ebaba\\.conda\\envs\\llms\\Lib\\site-packages\\gradio\\queueing.py\", line 625, in process_events\n", |
|
" response = await route_utils.call_process_api(\n", |
|
" ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n", |
|
" File \"C:\\Users\\ebaba\\.conda\\envs\\llms\\Lib\\site-packages\\gradio\\route_utils.py\", line 322, in call_process_api\n", |
|
" output = await app.get_blocks().process_api(\n", |
|
" ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n", |
|
" File \"C:\\Users\\ebaba\\.conda\\envs\\llms\\Lib\\site-packages\\gradio\\blocks.py\", line 2047, in process_api\n", |
|
" result = await self.call_function(\n", |
|
" ^^^^^^^^^^^^^^^^^^^^^^^^^\n", |
|
" File \"C:\\Users\\ebaba\\.conda\\envs\\llms\\Lib\\site-packages\\gradio\\blocks.py\", line 1606, in call_function\n", |
|
" prediction = await utils.async_iteration(iterator)\n", |
|
" ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n", |
|
" File \"C:\\Users\\ebaba\\.conda\\envs\\llms\\Lib\\site-packages\\gradio\\utils.py\", line 714, in async_iteration\n", |
|
" return await anext(iterator)\n", |
|
" ^^^^^^^^^^^^^^^^^^^^^\n", |
|
" File \"C:\\Users\\ebaba\\.conda\\envs\\llms\\Lib\\site-packages\\gradio\\utils.py\", line 708, in __anext__\n", |
|
" return await anyio.to_thread.run_sync(\n", |
|
" ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n", |
|
" File \"C:\\Users\\ebaba\\.conda\\envs\\llms\\Lib\\site-packages\\anyio\\to_thread.py\", line 56, in run_sync\n", |
|
" return await get_async_backend().run_sync_in_worker_thread(\n", |
|
" ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n", |
|
" File \"C:\\Users\\ebaba\\.conda\\envs\\llms\\Lib\\site-packages\\anyio\\_backends\\_asyncio.py\", line 2505, in run_sync_in_worker_thread\n", |
|
" return await future\n", |
|
" ^^^^^^^^^^^^\n", |
|
" File \"C:\\Users\\ebaba\\.conda\\envs\\llms\\Lib\\site-packages\\anyio\\_backends\\_asyncio.py\", line 1005, in run\n", |
|
" result = context.run(func, *args)\n", |
|
" ^^^^^^^^^^^^^^^^^^^^^^^^\n", |
|
" File \"C:\\Users\\ebaba\\.conda\\envs\\llms\\Lib\\site-packages\\gradio\\utils.py\", line 691, in run_sync_iterator_async\n", |
|
" return next(iterator)\n", |
|
" ^^^^^^^^^^^^^^\n", |
|
" File \"C:\\Users\\ebaba\\.conda\\envs\\llms\\Lib\\site-packages\\gradio\\utils.py\", line 852, in gen_wrapper\n", |
|
" response = next(iterator)\n", |
|
" ^^^^^^^^^^^^^^\n", |
|
" File \"C:\\Users\\ebaba\\AppData\\Local\\Temp\\ipykernel_27660\\2822054561.py\", line 10, in get_unit_test\n", |
|
" for stream_so_far in result:\n", |
|
"TypeError: 'NoneType' object is not iterable\n" |
|
] |
|
} |
|
], |
|
"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", |
|
" result = gr.Textbox(label=\"Result code:\", lines=10)\n", |
|
" with gr.Row():\n", |
|
" model = gr.Dropdown([\"GPT\", \"Claude\",\"CodeQwen\"], label=\"Select model\", value=\"GPT\")\n", |
|
" with gr.Row():\n", |
|
" comment_button = gr.Button(\"Comment code\")\n", |
|
" with gr.Row():\n", |
|
" unit_test_button = gr.Button(\"Unit Test code\")\n", |
|
" \n", |
|
" comment_button.click(comment_code, inputs=[python, model], outputs=[result])\n", |
|
" unit_test_button.click(get_unit_test, inputs=[python, model], outputs=[result])\n", |
|
"ui.launch(inbrowser=True)" |
|
] |
|
}, |
|
{ |
|
"cell_type": "code", |
|
"execution_count": null, |
|
"id": "06e8279c-b488-4807-9bed-9d26be11c057", |
|
"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 |
|
}
|
|
|