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Add ZeroScript_AI_TestExecutor notebook
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‎examples/cookbooks/ZeroScript_AI_TestExecutor.ipynb‎

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{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {
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"id": "_T4g3t5sLoag"
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},
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"source": [
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"# ZeroScript: AI-Powered Browser Test Automation using PraisonAI Agent & OpenAI"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {
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"id": "O4PKfpalLsmn"
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},
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"source": [
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"# Description"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {
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"id": "CEG1pfumLysm"
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},
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"source": [
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"AI-powered browser testing using PraisonAI Agent and OpenAI. Executes YAML-defined test cases, captures screenshots, logs interactions, and generates JSON reports. Ideal for intelligent, automated UI testing.\n",
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"\n"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {
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"id": "lbgxOG4gL1Wf"
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},
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"source": [
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"[![Open in Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/DhivyaBharathy-web/PraisonAI/blob/main/examples/cookbooks/ZeroScript_AI_TestExecutor.ipynb)\n"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {
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"id": "WCJqMUzXIndh"
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},
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"source": [
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"# Dependencies"
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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": 34,
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"metadata": {
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"id": "9AQhJ59cJPmR"
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},
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"outputs": [],
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"source": [
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"!pip install --quiet praisonaiagents browser-use python-dotenv pyyaml openai\n"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {
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"id": "QD-dF-6_It1z"
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},
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"source": [
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"# Environment Setup"
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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": 35,
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"metadata": {
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"colab": {
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"base_uri": "https://localhost:8080/"
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},
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"id": "QkRQDli4JhCV",
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"outputId": "4b8957ed-a37a-4b11-8585-3537a0437d40"
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},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"True"
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]
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},
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"execution_count": 35,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"import os\n",
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"from dotenv import load_dotenv\n",
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"\n",
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"os.environ[\"OPENAI_API_KEY\"] = \"Enter your key\" # replace with actual key\n",
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"load_dotenv()\n"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {
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"id": "ELuogWnrIw3o"
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},
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"source": [
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"# Create my_secrets.py"
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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": 36,
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"metadata": {
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"id": "sG6tO_v0Jm5N"
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},
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"outputs": [],
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"source": [
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"with open(\"my_secrets.py\", \"w\") as f:\n",
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" f.write('''sensitive_data = {\n",
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" \"username\": \"standard_user\",\n",
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" \"password\": \"secret_sauce\"\n",
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"}''')\n"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {
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"id": "rDB_viedIzRR"
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},
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"source": [
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"# Create views.py"
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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": 37,
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"metadata": {
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"id": "CtwcybdbJoV8"
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},
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"outputs": [],
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"source": [
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"with open(\"views.py\", \"w\") as f:\n",
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" f.write('''\n",
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"from pydantic import BaseModel\n",
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"\n",
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"class TestResult(BaseModel):\n",
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" status: str\n",
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" message: str = \"\"\n",
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"''')\n"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {
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"id": "YTRmBpTiI1kd"
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},
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"source": [
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"# Create agent.py"
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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": 38,
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"metadata": {
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"id": "zdJJGt6TJpvr"
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},
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"outputs": [],
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"source": [
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"with open(\"agent.py\", \"w\") as f:\n",
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" f.write('''\n",
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"import os\n",
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"from praisonaiagents import Agent\n",
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"from browser_use import Browser, BrowserConfig, Controller\n",
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"from browser_use.browser.context import BrowserContext, BrowserContextConfig\n",
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"from openai import OpenAI\n",
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"from views import TestResult\n",
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"from my_secrets import sensitive_data\n",
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"\n",
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"# Browser setup\n",
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"browser = Browser(config=BrowserConfig(headless=True))\n",
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"context_cfg = BrowserContextConfig(save_recording_path=\"data/recordings\")\n",
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"controller = Controller(output_model=TestResult)\n",
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"\n",
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"async def browser_use(task: str):\n",
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" context = BrowserContext(browser=browser, config=context_cfg)\n",
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" agent = Agent(\n",
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" task=task,\n",
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" llm=OpenAI(api_key=os.getenv(\"OPENAI_API_KEY\"), model=\"gpt-4\"),\n",
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" browser_context=context,\n",
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" sensitive_data=sensitive_data,\n",
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" controller=controller,\n",
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" save_conversation_path=\"data/conversations/convo\",\n",
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" extend_system_message=(\n",
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" \"You are a professional software tester. Execute browser test steps precisely.\"\n",
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" )\n",
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" )\n",
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" response = await agent.run()\n",
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" await context.close()\n",
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" return response\n",
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"''')\n"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {
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"id": "-LZtQIE3I4-_"
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},
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"source": [
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"# Create Sample Test YAML"
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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": 39,
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"metadata": {
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"colab": {
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"base_uri": "https://localhost:8080/"
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},
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"id": "l1OdXYI-JreK",
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"outputId": "62323fcd-c74f-498f-defc-2c170fa8983e"
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},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"350"
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]
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},
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"execution_count": 39,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"from pathlib import Path\n",
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"tests_dir = Path(\"tests\")\n",
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"tests_dir.mkdir(exist_ok=True)\n",
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"yaml_content = \"\"\"\n",
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"hooks:\n",
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" beforeEach: |\n",
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" Navigate to https://www.saucedemo.com\n",
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" afterEach: |\n",
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" Take screenshot\n",
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"\n",
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"tests:\n",
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" - id: \"login_test_001\"\n",
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" name: \"Valid Login Test\"\n",
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" instructions: |\n",
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" 1. Enter standard_user in username field\n",
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" 2. Enter secret_sauce in password field\n",
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" 3. Click login button\n",
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" 4. Verify page contains text \"Products\"\n",
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"\"\"\"\n",
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"(Path(\"tests/login_test.yml\")).write_text(yaml_content)\n"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {
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"id": "sUjy-7OdI7p_"
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},
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"source": [
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"# Run Tests"
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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": 40,
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"metadata": {
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"colab": {
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"base_uri": "https://localhost:8080/"
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},
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"id": "Agkiwh7xJtY3",
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"outputId": "759aa77c-fd65-49b8-b239-550588059478"
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},
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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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"Exception ignored in: <function BrowserSession.__del__ at 0x7e2f540fb100>\n",
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"Traceback (most recent call last):\n",
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" File \"/usr/local/lib/python3.11/dist-packages/browser_use/browser/session.py\", line 497, in __del__\n",
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" status = f'🪓 killing pid={self.browser_pid}...' if (self.browser_pid and owns_browser) else '☠️'\n",
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" ^^^^^^^^^^^^^^^^\n",
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" File \"/usr/local/lib/python3.11/dist-packages/pydantic/main.py\", line 991, in __getattr__\n",
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" raise AttributeError(f'{type(self).__name__!r} object has no attribute {item!r}')\n",
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"AttributeError: 'BrowserSession' object has no attribute 'browser_pid'\n"
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]
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},
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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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"✅ Report saved to data/reports/report_20250630_092319.json\n"
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]
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}
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],
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"source": [
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"import asyncio, yaml, json, base64, shutil\n",
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"from agent import browser_use, browser\n",
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"from pathlib import Path\n",
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"from datetime import datetime\n",
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"\n",
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"# Clean or create data dirs\n",
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"for sub in [\"recordings\", \"conversations\", \"screenshots\", \"reports\"]:\n",
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" d = Path(\"data\") / sub\n",
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" if d.exists(): shutil.rmtree(d)\n",
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" d.mkdir(parents=True, exist_ok=True)\n",
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"\n",
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"async def execute_test_file(path):\n",
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" cfg = yaml.safe_load(Path(path).read_text())\n",
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" hooks, results = cfg.get(\"hooks\", {}), []\n",
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" for t in cfg[\"tests\"]:\n",
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" task = f\"{hooks.get('beforeEach','')}\\n{t['instructions']}\\n{hooks.get('afterEach','')}\"\n",
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" res = {\"id\": t[\"id\"], \"name\": t[\"name\"]}\n",
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" try:\n",
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" r = await browser_use(task)\n",
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" imgs = r.screenshots()\n",
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" if imgs:\n",
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" out = Path(\"data/screenshots\") / f\"{t['id']}.png\"\n",
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" out.write_bytes(base64.b64decode(imgs[-1]))\n",
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" result_obj = r.final_result() if hasattr(r, \"final_result\") else str(r)\n",
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" res[\"result\"] = result_obj.dict() if hasattr(result_obj, \"dict\") else str(result_obj)\n",
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" except Exception as e:\n",
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" res[\"error\"] = str(e)\n",
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" results.append(res)\n",
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" return results\n",
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"\n",
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"async def main():\n",
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" all_results = []\n",
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" for file in Path(\"tests\").glob(\"*.yml\"):\n",
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" all_results.extend(await execute_test_file(str(file)))\n",
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" report = Path(\"data/reports\") / f\"report_{datetime.now():%Y%m%d_%H%M%S}.json\"\n",
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" report.write_text(json.dumps(all_results, indent=2))\n",
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" await browser.close()\n",
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" print(f\"✅ Report saved to {report}\")\n",
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"\n",
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"await main()\n"
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]
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}
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],
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"metadata": {
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"colab": {
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"provenance": []
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},
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"kernelspec": {
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"display_name": "Python 3",
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"name": "python3"
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},
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"language_info": {
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"name": "python"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 0
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}

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