From 84c8aded5e4b1aec2ffa0a012b986b76777b4c89 Mon Sep 17 00:00:00 2001
From: Elena Shirokova <elena.s.shirokova@gmail.com>
Date: Sat, 18 Jan 2025 14:39:53 +0100
Subject: [PATCH] adding the notebook for unit tests generation assignment

---
 .../unit-tests-generator.ipynb                | 432 ++++++++++++++++++
 1 file changed, 432 insertions(+)
 create mode 100644 week4/community-contributions/unit-tests-generator.ipynb

diff --git a/week4/community-contributions/unit-tests-generator.ipynb b/week4/community-contributions/unit-tests-generator.ipynb
new file mode 100644
index 0000000..4825544
--- /dev/null
+++ b/week4/community-contributions/unit-tests-generator.ipynb
@@ -0,0 +1,432 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Requirements\n",
+    "\n",
+    "1. Install pytest and pytest-cov library\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "!pipenv install pytest pytest-cov"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# imports\n",
+    "import re\n",
+    "import os\n",
+    "import sys\n",
+    "import textwrap\n",
+    "from dotenv import load_dotenv\n",
+    "from openai import OpenAI\n",
+    "import anthropic\n",
+    "import gradio as gr\n",
+    "from pathlib import Path\n",
+    "import subprocess\n",
+    "from IPython.display import Markdown"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Initialization\n",
+    "\n",
+    "load_dotenv()\n",
+    "\n",
+    "openai_api_key = os.getenv('OPENAI_API_KEY')\n",
+    "os.environ['ANTHROPIC_API_KEY'] = os.getenv('ANTHROPIC_API_KEY', 'your-key-if-not-using-env')\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",
+    "OPENAI_MODEL = \"gpt-4o-mini\"\n",
+    "CLAUDE_MODEL = \"claude-3-5-sonnet-20240620\"\n",
+    "openai = OpenAI()\n",
+    "claude = anthropic.Anthropic()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "OLLAMA_API = \"http://localhost:11434/api/chat\"\n",
+    "HEADERS = {\"Content-Type\": \"application/json\"}\n",
+    "OLLAMA_MODEL = \"llama3.2\""
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Code execution"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "\n",
+    "def extract_code(text):\n",
+    "    # Regular expression to find text between ``python and ``\n",
+    "    match = re.search(r\"```python(.*?)```\", text, re.DOTALL)\n",
+    "\n",
+    "    if match:\n",
+    "        code = match.group(0).strip()  # Extract and strip extra spaces\n",
+    "    else:\n",
+    "        code = \"\"\n",
+    "        print(\"No matching substring found.\")\n",
+    "\n",
+    "    return code.replace(\"```python\\n\", \"\").replace(\"```\", \"\")\n",
+    "\n",
+    "\n",
+    "def execute_coverage_report(python_interpreter=sys.executable):\n",
+    "    if not python_interpreter:\n",
+    "        raise EnvironmentError(\"Python interpreter not found in the specified virtual environment.\")\n",
+    "    # test_code_path = Path(\"tests\")\n",
+    "    # command = [\"pytest\", \"-cov\",\"--capture=no\"]\n",
+    "    command = [\"coverage\", \"run\", \"-m\", \"pytest\"]\n",
+    "    # command =[\"pytest\", \"--cov=your_package\", \"--cov-report=term-missing\"]\n",
+    "\n",
+    "    try:\n",
+    "        result = subprocess.run(command, check=True, capture_output=True, text=True)\n",
+    "        print(\"Tests ran successfully!\")\n",
+    "        print(result.stdout)\n",
+    "        return result.stdout\n",
+    "    except subprocess.CalledProcessError as e:\n",
+    "        print(\"Some tests failed!\")\n",
+    "        print(\"Output:\\n\", e.stdout)\n",
+    "        print(\"Errors:\\n\", e.stderr)\n",
+    "        # Extracting failed test information\n",
+    "        failed_tests = []\n",
+    "        for line in e.stdout.splitlines():\n",
+    "            if \"FAILED\" in line and \"::\" in line:\n",
+    "                failed_tests.append(line.strip())\n",
+    "        if failed_tests:\n",
+    "            print(\"Failed Tests:\")\n",
+    "            for test in failed_tests:\n",
+    "                print(test)\n",
+    "        return failed_tests\n",
+    "\n",
+    "def save_unit_tests(code):\n",
+    "\n",
+    "    match = re.search(r\"def\\s+(\\w+)\\(\", code, re.DOTALL)\n",
+    "\n",
+    "    if match:\n",
+    "        function_name = match.group(1).strip()  # Extract and strip extra spaces\n",
+    "    else:\n",
+    "        function_name = \"\"\n",
+    "        print(\"No matching substring found.\")\n",
+    "\n",
+    "    test_code_path = Path(\"tests\")\n",
+    "    (test_code_path / f\"test_{function_name}.py\").write_text(extract_code(code))\n",
+    "    Path(\"tests\", \"test_code.py\").unlink()\n",
+    "    \n",
+    "\n",
+    "def execute_tests_in_venv(code_to_test, tests, python_interpreter=sys.executable):\n",
+    "    \"\"\"\n",
+    "    Execute the given Python code string within the specified virtual environment.\n",
+    "    \n",
+    "    Args:\n",
+    "    - code_str: str, the Python code to execute.\n",
+    "    - venv_dir: str, the directory path to the virtual environment created by pipenv.\n",
+    "    \"\"\"\n",
+    "    \n",
+    "    if not python_interpreter:\n",
+    "        raise EnvironmentError(\"Python interpreter not found in the specified virtual environment.\")\n",
+    "\n",
+    "    # Prepare the command to execute the code\n",
+    "    code_str = textwrap.dedent(code_to_test) + \"\\n\" + extract_code(tests)\n",
+    "    test_code_path = Path(\"tests\")\n",
+    "    test_code_path.mkdir(parents=True, exist_ok=True)\n",
+    "    (test_code_path / f\"test_code.py\").write_text(code_str)\n",
+    "    command = [\"pytest\", str(test_code_path)]\n",
+    "\n",
+    "    try:\n",
+    "        result = subprocess.run(command, check=True, capture_output=True, text=True)\n",
+    "        print(\"Tests ran successfully!\")\n",
+    "        print(result.stderr)\n",
+    "        return result.stdout\n",
+    "    except subprocess.CalledProcessError as e:\n",
+    "        print(\"Some tests failed!\")\n",
+    "        print(\"Output:\\n\", e.stdout)\n",
+    "        print(\"Errors:\\n\", e.stderr)\n",
+    "        # Extracting failed test information\n",
+    "        failed_tests = []\n",
+    "        for line in e.stdout.splitlines():\n",
+    "            if \"FAILED\" in line and \"::\" in line:\n",
+    "                failed_tests.append(line.strip())\n",
+    "        if failed_tests:\n",
+    "            print(\"Failed Tests:\")\n",
+    "            for test in failed_tests:\n",
+    "                print(test)\n",
+    "        return e.stderr\n",
+    "    "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Prompts and calls to the models"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "system_message = \"\"\"You are a helpful assistant which helps developers to write unit test cases for their code.\"\"\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def get_user_prompt(code):\n",
+    "\n",
+    "    user_prompt = \"Write for a python code the unit test cases.\"\n",
+    "    user_prompt += \"Return unit tests cases using pytest library, do not create any custom imports; do not explain your work other than a few comments.\"\n",
+    "    user_prompt += \"Do not insert the function to be tested in the output before the tests. Validate both the case where the function is executed successfully and where it is expected to fail.\"\n",
+    "    user_prompt += code\n",
+    "\n",
+    "    return user_prompt"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def stream_gpt(code):\n",
+    "\n",
+    "    user_prompt = get_user_prompt(code)\n",
+    "    stream = openai.chat.completions.create(\n",
+    "        model=OPENAI_MODEL,\n",
+    "        messages=[\n",
+    "            {\"role\": \"system\", \"content\": system_message},\n",
+    "            {\n",
+    "                \"role\": \"user\",\n",
+    "                \"content\": user_prompt,\n",
+    "            },\n",
+    "        ],\n",
+    "        stream=True,\n",
+    "    )\n",
+    "\n",
+    "    response = \"\"\n",
+    "    for chunk in stream:\n",
+    "        response += chunk.choices[0].delta.content or \"\"\n",
+    "        yield response\n",
+    "    \n",
+    "    return response\n",
+    "\n",
+    "def stream_ollama(code):\n",
+    "\n",
+    "    user_prompt = get_user_prompt(code)\n",
+    "    ollama_via_openai = OpenAI(base_url='http://localhost:11434/v1', api_key='ollama')\n",
+    "    stream = ollama_via_openai.chat.completions.create(\n",
+    "        model=OLLAMA_MODEL,\n",
+    "        messages=[\n",
+    "            {\"role\": \"system\", \"content\": system_message},\n",
+    "            {\n",
+    "                \"role\": \"user\",\n",
+    "                \"content\": user_prompt,\n",
+    "            },\n",
+    "        ],\n",
+    "        stream=True,\n",
+    "    )\n",
+    "\n",
+    "    response = \"\"\n",
+    "    for chunk in stream:\n",
+    "        response += chunk.choices[0].delta.content or \"\"\n",
+    "        yield response\n",
+    "    \n",
+    "    return response\n",
+    "\n",
+    "\n",
+    "def stream_claude(code):\n",
+    "    user_prompt = get_user_prompt(code)\n",
+    "    result = claude.messages.stream(\n",
+    "        model=CLAUDE_MODEL,\n",
+    "        max_tokens=2000,\n",
+    "        system=system_message,\n",
+    "        messages=[\n",
+    "            {\n",
+    "                \"role\": \"user\",\n",
+    "                \"content\": user_prompt,\n",
+    "            }\n",
+    "        ],\n",
+    "    )\n",
+    "    reply = \"\"\n",
+    "    with result as stream:\n",
+    "        for text in stream.text_stream:\n",
+    "            reply += text\n",
+    "            yield reply\n",
+    "            print(text, end=\"\", flush=True)\n",
+    "    return reply"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Code examples to test the inteface"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "function_to_test = \"\"\"\n",
+    "    def lengthOfLongestSubstring(s):\n",
+    "        max_length = 0\n",
+    "        substring = \"\"\n",
+    "        start_idx = 0\n",
+    "        while start_idx < len(s):\n",
+    "            string = s[start_idx:]\n",
+    "            for i, x in enumerate(string):\n",
+    "                substring += x\n",
+    "                if len(substring) == len(set((list(substring)))):\n",
+    "                    \n",
+    "                    if len(set((list(substring)))) > max_length:\n",
+    "                        \n",
+    "                        max_length = len(substring)\n",
+    "\n",
+    "            start_idx += 1\n",
+    "            substring = \"\"\n",
+    "                  \n",
+    "                \n",
+    "        return max_length\"\"\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "test_code = \"\"\"```python\n",
+    "import pytest\n",
+    "\n",
+    "# Unit tests using pytest\n",
+    "def test_lengthOfLongestSubstring():\n",
+    "    assert lengthOfLongestSubstring(\"abcabcbb\") == 3  # Case with repeating characters\n",
+    "    assert lengthOfLongestSubstring(\"bbbbb\") == 1    # Case with all same characters\n",
+    "    assert lengthOfLongestSubstring(\"pwwkew\") == 3    # Case with mixed characters\n",
+    "    assert lengthOfLongestSubstring(\"\") == 0           # Empty string case\n",
+    "    assert lengthOfLongestSubstring(\"abcdef\") == 6     # All unique characters\n",
+    "    assert lengthOfLongestSubstring(\"abca\") == 3       # Case with pattern and repeat\n",
+    "    assert lengthOfLongestSubstring(\"dvdf\") == 3       # Case with repeated characters separated\n",
+    "    assert lengthOfLongestSubstring(\"a\") == 1           # Case with single character\n",
+    "    assert lengthOfLongestSubstring(\"au\") == 2          # Case with unique two characters\n",
+    "```\"\"\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def optimize(code, model):\n",
+    "    if model == \"GPT\":\n",
+    "        result = stream_gpt(code)\n",
+    "    elif model == \"Claude\":\n",
+    "        result = stream_claude(code)\n",
+    "    elif model == \"Ollama\":\n",
+    "        result = stream_ollama(code)\n",
+    "    else:\n",
+    "        raise ValueError(\"Unknown model\")\n",
+    "    for stream_so_far in result:\n",
+    "        yield stream_so_far\n",
+    "    return result"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Gradio interface"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "with gr.Blocks() as ui:\n",
+    "    gr.Markdown(\"## Write unit tests for Python code\")\n",
+    "    with gr.Row():\n",
+    "        with gr.Column(scale=1, min_width=300):\n",
+    "            python = gr.Textbox(label=\"Python code:\", value=function_to_test, lines=10)\n",
+    "            model = gr.Dropdown([\"GPT\", \"Claude\", \"Ollama\"], label=\"Select model\", value=\"GPT\")\n",
+    "            unit_tests = gr.Button(\"Write unit tests\")\n",
+    "        with gr.Column(scale=1, min_width=300):\n",
+    "            unit_tests_out = gr.TextArea(label=\"Unit tests\", value=test_code, elem_classes=[\"python\"])\n",
+    "            unit_tests_run = gr.Button(\"Run unit tests\")\n",
+    "            coverage_run = gr.Button(\"Coverage report\")\n",
+    "            save_test_run = gr.Button(\"Save unit tests\")\n",
+    "    with gr.Row():\n",
+    "        \n",
+    "        python_out = gr.TextArea(label=\"Unit tests result\", elem_classes=[\"python\"])\n",
+    "        coverage_out = gr.TextArea(label=\"Coverage report\", elem_classes=[\"python\"])\n",
+    "        \n",
+    "\n",
+    "    unit_tests.click(optimize, inputs=[python, model], outputs=[unit_tests_out])\n",
+    "    unit_tests_run.click(execute_tests_in_venv, inputs=[python, unit_tests_out], outputs=[python_out])\n",
+    "    coverage_run.click(execute_coverage_report, outputs=[coverage_out])\n",
+    "    save_test_run.click(save_unit_tests, inputs=[unit_tests_out])\n",
+    "\n",
+    "\n",
+    "ui.launch(inbrowser=True)"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "llm_engineering-yg2xCEUG",
+   "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": "3.10.8"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}