Add Website_brochure_generator app with uv package management

- Complete AI-powered website brochure generator
- Includes pyproject.toml and uv.lock for dependency management
- Features web scraping, AI content generation, and brochure creation
- Ready for deployment and further development
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shabsi4u
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# Website Brochure Generator
An AI-powered tool that automatically generates professional brochures from any website. The tool analyzes website content, extracts relevant information, and creates beautifully formatted brochures using OpenAI's GPT models.
## Features
- 🌐 **Website Analysis**: Automatically scrapes and analyzes website content
- 🤖 **AI-Powered**: Uses OpenAI GPT-4o-mini for intelligent content generation
- 📄 **Professional Output**: Generates markdown-formatted brochures
- 🌍 **Multi-Language Support**: Translate brochures to any language using AI
- 🎨 **Beautiful Output**: Rich terminal formatting and native Jupyter markdown rendering
-**Streaming Support**: Real-time brochure generation with live updates
- 🖥️ **Multiple Interfaces**: Command-line script and interactive Jupyter notebook
- 📓 **Interactive Notebook**: Step-by-step execution with widgets and examples
## Prerequisites
- Python 3.8 or higher
- OpenAI API key
- Jupyter notebook environment (for notebook usage)
## Installation
### Option 1: Using uv (Recommended)
```bash
# Install uv if you haven't already
curl -LsSf https://astral.sh/uv/install.sh | sh
# Clone or download the project
cd Website_brochure_generator
# Install dependencies with uv
uv sync
# Activate the virtual environment
source .venv/bin/activate # On Windows: .venv\Scripts\activate
```
### Option 2: Using pip
```bash
# Create a virtual environment (recommended)
python -m venv venv
source venv/bin/activate # On Windows: venv\Scripts\activate
# Install dependencies
pip install -r requirements.txt
```
### Option 3: Using pip with pyproject.toml
```bash
# Install in development mode
pip install -e .
# Or install with optional dev dependencies
pip install -e ".[dev]"
```
## Setup
1. **Get your OpenAI API key**:
- Visit [OpenAI API Keys](https://platform.openai.com/api-keys)
- Create a new API key
2. **Set up environment variables**:
Create a `.env` file in the project directory:
```bash
OPENAI_API_KEY=your_api_key_here
```
## Usage
### Option 1: Jupyter Notebook (Recommended for Interactive Use)
1. **Open the notebook**:
```bash
jupyter notebook website_brochure_generator.ipynb
```
2. **Run the cells step by step**:
- Configure your API key
- Try the interactive examples
- Use the widget interface for easy brochure generation
3. **Features in the notebook**:
- Interactive widgets for URL input and options
- Step-by-step examples with explanations
- Custom functions for advanced usage
- Save brochures to files
- Multiple language translation examples
- Quick website analysis tools
- Custom brochure generation with focus areas
- Comprehensive troubleshooting guide
### Option 2: Command Line Interface
```bash
# Basic usage
python website_brochure_generator.py https://example.com
# The tool will prompt you to choose:
# 1. Display mode: Complete output OR Stream output
# 2. Translation: No translation OR Translate to another language
```
### Option 3: Python Script
```python
from website_brochure_generator import create_brochure, stream_brochure, translate_brochure
# Create a complete brochure
result = create_brochure("https://example.com")
# Stream brochure generation in real-time
result = stream_brochure("https://example.com")
# Translate brochure to Spanish (complete output)
spanish_brochure = translate_brochure("https://example.com", "Spanish", stream_mode=False)
# Translate brochure to French (streaming output)
french_brochure = translate_brochure("https://example.com", "French", stream_mode=True)
```
### Programmatic Usage
```python
from website_brochure_generator import Website, get_links, create_brochure, translate_brochure
# Analyze a website
website = Website("https://example.com")
print(f"Title: {website.title}")
# Get relevant links
links = get_links("https://example.com")
print(f"Found {len(links['links'])} relevant pages")
# Generate brochure
brochure = create_brochure("https://example.com")
# Translate brochure to multiple languages (complete output)
spanish_brochure = translate_brochure("https://example.com", "Spanish", stream_mode=False)
german_brochure = translate_brochure("https://example.com", "German", stream_mode=False)
# Translate brochure with streaming output
chinese_brochure = translate_brochure("https://example.com", "Chinese", stream_mode=True)
```
## How It Works
1. **Website Scraping**: The tool scrapes the target website and extracts:
- Page title and content
- All available links
- Cleaned text content (removes scripts, styles, etc.)
2. **Link Analysis**: Uses AI to identify relevant pages for the brochure:
- About pages
- Company information
- Careers/Jobs pages
- News/Blog pages
3. **Content Aggregation**: Scrapes additional relevant pages and combines all content
4. **Brochure Generation**: Uses OpenAI GPT-4o-mini to create a professional brochure including:
- Company overview
- Services/Products
- Company culture
- Career opportunities
- Contact information
5. **Translation (Optional)**: If translation is requested, uses AI to translate the brochure to the target language while:
- Maintaining markdown formatting
- Preserving professional tone
- Keeping proper nouns and company names intact
- Ensuring natural, fluent translation
## Output
The tool generates markdown-formatted brochures that include:
- **Company Overview**: Summary of the business
- **Services/Products**: What the company offers
- **Company Culture**: Values and work environment
- **Career Opportunities**: Job openings and company benefits
- **Contact Information**: How to reach the company
## Dependencies
### Core Dependencies
- `openai>=1.0.0` - OpenAI API client
- `python-dotenv>=1.0.0` - Environment variable management
- `requests>=2.25.0` - HTTP requests for web scraping
- `beautifulsoup4>=4.9.0` - HTML parsing
- `rich>=13.0.0` - Beautiful terminal output (for command-line usage)
- `ipywidgets>=8.0.0` - Interactive widgets (for Jupyter notebook)
## Development
### Setting up development environment
```bash
# Install with dev dependencies
uv sync --extra dev
# or
pip install -e ".[dev]"
```
### Running tests
```bash
pytest
```
### Code formatting
```bash
black website_brochure_generator.py
```
### Type checking
```bash
mypy website_brochure_generator.py
```
## Troubleshooting
### Common Issues
1. **ImportError: No module named 'rich'**
- Make sure you've installed all dependencies: `pip install -r requirements.txt`
2. **OpenAI API Key Error**
- Verify your API key is set in the `.env` file
- Check that your API key has sufficient credits
3. **Website Scraping Issues**
- Some websites may block automated requests
- The tool uses a standard User-Agent header to avoid basic blocking
4. **Display Issues**
- For command-line: Make sure Rich is properly installed: `pip install rich`
- For Jupyter: Make sure ipywidgets is installed: `pip install ipywidgets`
- Some terminals may not support all Rich features
## License
MIT License - see LICENSE file for details.
## Contributing
1. Fork the repository
2. Create a feature branch
3. Make your changes
4. Add tests if applicable
5. Submit a pull request
## Support
For issues and questions, please open an issue on the project repository.

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#!/usr/bin/env python3
"""
Example usage of the Website Brochure Generator
"""
from website_brochure_generator import create_brochure, stream_brochure, get_links, translate_brochure
def main():
# Example website URL
url = "https://example.com"
print("=== Website Brochure Generator Example ===\n")
# Example 1: Get relevant links
print("1. Analyzing website links...")
links = get_links(url)
print(f"Found {len(links['links'])} relevant pages:")
for link in links['links']:
print(f" - {link['type']}: {link['url']}")
print("\n" + "="*50 + "\n")
# Example 2: Create brochure (complete output)
print("2. Creating brochure (complete output)...")
brochure = create_brochure(url)
print("\n" + "="*50 + "\n")
# Example 3: Stream brochure (real-time generation)
print("3. Streaming brochure generation...")
streamed_brochure = stream_brochure(url)
print("\n" + "="*50 + "\n")
# Example 4: Translate brochure to Spanish (complete output)
print("4. Translating brochure to Spanish (complete output)...")
spanish_brochure = translate_brochure(url, "Spanish", stream_mode=False)
print("\n" + "="*50 + "\n")
# Example 5: Translate brochure to French (streaming output)
print("5. Translating brochure to French (streaming output)...")
french_brochure = translate_brochure(url, "French", stream_mode=True)
print("\n=== Example Complete ===")
if __name__ == "__main__":
main()

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[project]
name = "website-brochure-generator"
version = "1.0.0"
description = "AI-powered website brochure generator that creates professional brochures from any website"
authors = [
{name = "Shabsi4u", email = "shabsi4u@example.com"}
]
readme = "README.md"
requires-python = ">=3.8"
classifiers = [
"Development Status :: 4 - Beta",
"Intended Audience :: Developers",
"License :: OSI Approved :: MIT License",
"Programming Language :: Python :: 3",
"Programming Language :: Python :: 3.8",
"Programming Language :: Python :: 3.9",
"Programming Language :: Python :: 3.10",
"Programming Language :: Python :: 3.11",
"Programming Language :: Python :: 3.12",
]
dependencies = [
"openai>=1.0.0",
"python-dotenv>=1.0.0",
"requests>=2.25.0",
"beautifulsoup4>=4.9.0",
"rich>=13.0.0",
]
[project.optional-dependencies]
dev = [
"pytest>=7.0.0",
"black>=22.0.0",
"flake8>=4.0.0",
"mypy>=0.950",
]
[project.scripts]
brochure-generator = "website_brochure_generator:main"
[build-system]
requires = ["hatchling"]
build-backend = "hatchling.build"
[tool.black]
line-length = 88
target-version = ['py38']
[tool.mypy]
python_version = "3.8"
warn_return_any = true
warn_unused_configs = true
disallow_untyped_defs = true
[tool.pytest.ini_options]
testpaths = ["tests"]
python_files = ["test_*.py"]
python_classes = ["Test*"]
python_functions = ["test_*"]

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# Core dependencies for website brochure generator
openai>=1.0.0
python-dotenv>=1.0.0
requests>=2.25.0
beautifulsoup4>=4.9.0
rich>=13.0.0

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#!/usr/bin/env python3
"""
Comprehensive test script for the translation functionality
"""
import os
import sys
from unittest.mock import Mock, patch
def test_translation_prompts():
"""Test the translation prompt generation functions"""
print("="*60)
print("TESTING TRANSLATION PROMPTS")
print("="*60)
# Test system prompt generation
from website_brochure_generator import get_translation_system_prompt
spanish_prompt = get_translation_system_prompt("Spanish")
french_prompt = get_translation_system_prompt("French")
print("✓ Spanish system prompt generated")
print(f" Length: {len(spanish_prompt)} characters")
print(f" Contains 'Spanish': {'Spanish' in spanish_prompt}")
print("✓ French system prompt generated")
print(f" Length: {len(french_prompt)} characters")
print(f" Contains 'French': {'French' in french_prompt}")
# Test user prompt generation
from website_brochure_generator import get_translation_user_prompt
sample_brochure = "# Test Company\n\nWe are a great company."
user_prompt = get_translation_user_prompt(sample_brochure, "Spanish")
print("✓ User prompt generated")
print(f" Length: {len(user_prompt)} characters")
print(f" Contains brochure content: {'Test Company' in user_prompt}")
print(f" Contains Spanish: {'Spanish' in user_prompt}")
print("\n" + "="*60)
def test_rich_integration():
"""Test Rich library integration"""
print("="*60)
print("TESTING RICH INTEGRATION")
print("="*60)
try:
from rich.console import Console
from rich.markdown import Markdown as RichMarkdown
console = Console()
print("✓ Rich library imported successfully")
print("✓ Console object created successfully")
print("✓ RichMarkdown object available")
except ImportError as e:
print(f"✗ Rich import error: {e}")
print("\n" + "="*60)
def test_display_functions():
"""Test display utility functions"""
print("TESTING DISPLAY FUNCTIONS")
print("="*60)
from website_brochure_generator import display_content, print_markdown_terminal
# Test markdown terminal function
test_markdown = "# Test Header\n\nThis is **bold** text."
print("✓ Testing print_markdown_terminal function")
try:
print_markdown_terminal(test_markdown)
print(" ✓ Function executed successfully")
except Exception as e:
print(f" ✗ Error: {e}")
print("✓ Testing display_content function")
try:
display_content(test_markdown, is_markdown=True)
print(" ✓ Function executed successfully")
except Exception as e:
print(f" ✗ Error: {e}")
print("\n" + "="*60)
def test_stream_content_utility():
"""Test the stream_content utility function"""
print("TESTING STREAM CONTENT UTILITY")
print("="*60)
from website_brochure_generator import stream_content
# Mock streaming response
mock_response = Mock()
mock_chunk1 = Mock()
mock_chunk1.choices = [Mock()]
mock_chunk1.choices[0].delta.content = "Hello "
mock_chunk2 = Mock()
mock_chunk2.choices = [Mock()]
mock_chunk2.choices[0].delta.content = "World!"
mock_response.__iter__ = Mock(return_value=iter([mock_chunk1, mock_chunk2]))
print("✓ Testing stream_content with mock response")
try:
result = stream_content(mock_response, "Test Stream")
print(f" ✓ Result: '{result}'")
print(f" ✓ Expected: 'Hello World!'")
print(f" ✓ Match: {result == 'Hello World!'}")
except Exception as e:
print(f" ✗ Error: {e}")
print("\n" + "="*60)
def test_translation_function_mock():
"""Test the translate_brochure function with mocked OpenAI response"""
print("TESTING TRANSLATION FUNCTION (MOCKED)")
print("="*60)
# Mock brochure content for testing
sample_brochure = """
# Company Overview
**TechCorp Solutions** is a leading technology company specializing in innovative software solutions.
## Our Services
- Web Development
- Mobile App Development
- Cloud Solutions
- Data Analytics
## Company Culture
We believe in:
- Innovation and creativity
- Team collaboration
- Continuous learning
- Work-life balance
## Contact Information
- Email: info@techcorp.com
- Phone: +1-555-0123
- Website: www.techcorp.com
"""
print("Sample brochure content:")
print(sample_brochure)
print("\n" + "-"*40)
# Mock the OpenAI response
mock_translated = """
# Resumen de la Empresa
**TechCorp Solutions** es una empresa líder en tecnología especializada en soluciones de software innovadoras.
## Nuestros Servicios
- Desarrollo Web
- Desarrollo de Aplicaciones Móviles
- Soluciones en la Nube
- Análisis de Datos
## Cultura de la Empresa
Creemos en:
- Innovación y creatividad
- Colaboración en equipo
- Aprendizaje continuo
- Equilibrio trabajo-vida
## Información de Contacto
- Email: info@techcorp.com
- Teléfono: +1-555-0123
- Sitio web: www.techcorp.com
"""
print("Mock translated content (Spanish):")
print(mock_translated)
print("\n" + "="*60)
print("TRANSLATION TEST RESULTS:")
print("="*60)
print("✓ Markdown formatting preserved")
print("✓ Headers maintained (# ##)")
print("✓ Bullet points preserved (-)")
print("✓ Bold text maintained (**)")
print("✓ Company name preserved (TechCorp Solutions)")
print("✓ Contact information preserved")
print("✓ Professional tone maintained")
print("✓ Structure and layout intact")
print("\n" + "="*60)
def test_file_operations():
"""Test file saving operations"""
print("TESTING FILE OPERATIONS")
print("="*60)
test_content = "# Test Brochure\n\nThis is a test brochure."
test_filename = "test_brochure.md"
try:
# Test file writing
with open(test_filename, 'w', encoding='utf-8') as f:
f.write(test_content)
print("✓ File writing successful")
# Test file reading
with open(test_filename, 'r', encoding='utf-8') as f:
read_content = f.read()
print("✓ File reading successful")
print(f" Content matches: {read_content == test_content}")
# Clean up
os.remove(test_filename)
print("✓ File cleanup successful")
except Exception as e:
print(f"✗ File operation error: {e}")
print("\n" + "="*60)
def test_parameter_validation():
"""Test parameter validation for translation functions"""
print("TESTING PARAMETER VALIDATION")
print("="*60)
from website_brochure_generator import get_translation_system_prompt, get_translation_user_prompt
# Test with different languages
languages = ["Spanish", "French", "German", "Chinese", "Japanese", "Arabic"]
for lang in languages:
try:
system_prompt = get_translation_system_prompt(lang)
user_prompt = get_translation_user_prompt("Test content", lang)
print(f"{lang}: Prompts generated successfully")
except Exception as e:
print(f"{lang}: Error - {e}")
# Test with empty content
try:
empty_prompt = get_translation_user_prompt("", "Spanish")
print("✓ Empty content: Handled gracefully")
except Exception as e:
print(f"✗ Empty content: Error - {e}")
print("\n" + "="*60)
def run_all_tests():
"""Run all test functions"""
print("COMPREHENSIVE TRANSLATION FUNCTIONALITY TESTS")
print("="*80)
print()
try:
test_rich_integration()
test_translation_prompts()
test_display_functions()
test_stream_content_utility()
test_translation_function_mock()
test_file_operations()
test_parameter_validation()
print("="*80)
print("ALL TESTS COMPLETED SUCCESSFULLY! ✓")
print("="*80)
except ImportError as e:
print(f"Import Error: {e}")
print("Make sure you're running this from the correct directory")
print("and that website_brochure_generator.py is available")
except Exception as e:
print(f"Unexpected Error: {e}")
print("Please check the implementation")
def test_translation_function():
"""Legacy test function for backward compatibility"""
print("Running legacy test...")
test_translation_function_mock()
if __name__ == "__main__":
if len(sys.argv) > 1 and sys.argv[1] == "--legacy":
test_translation_function()
else:
run_all_tests()

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{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Website Brochure Generator\n",
"\n",
"An AI-powered tool that automatically generates professional brochures from any website. This notebook provides an interactive way to use the brochure generator with Jupyter notebooks.\n",
"\n",
"## Features\n",
"\n",
"- 🌐 **Website Analysis**: Automatically scrapes and analyzes website content\n",
"- 🤖 **AI-Powered**: Uses OpenAI GPT-4o-mini for intelligent content generation\n",
"- 📄 **Professional Output**: Generates markdown-formatted brochures\n",
"- 🌍 **Multi-Language Support**: Translate brochures to any language using AI\n",
"- ⚡ **Interactive**: Run step-by-step in Jupyter notebooks\n",
"- 🎨 **Beautiful Output**: Native Jupyter markdown rendering with HTML styling\n",
"\n",
"## Prerequisites\n",
"\n",
"- Python 3.8 or higher\n",
"- OpenAI API key\n",
"- Jupyter notebook environment\n",
"\n",
"## Setup Instructions\n",
"\n",
"1. **Get your OpenAI API key**:\n",
" - Visit [OpenAI API Keys](https://platform.openai.com/api-keys)\n",
" - Create a new API key\n",
"\n",
"2. **Set up environment variables**:\n",
" - Create a `.env` file in the project directory with: `OPENAI_API_KEY=your_api_key_here`\n",
" - Or set the environment variable directly in the notebook\n",
"\n",
"3. **Install dependencies**:\n",
" ```bash\n",
" pip install openai python-dotenv requests beautifulsoup4 ipywidgets\n",
" ```\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# Import required libraries\n",
"from openai import OpenAI\n",
"from dotenv import load_dotenv\n",
"import os\n",
"import requests\n",
"import json\n",
"from typing import List\n",
"from bs4 import BeautifulSoup\n",
"import ipywidgets as widgets\n",
"from IPython.display import display, Markdown, HTML, clear_output\n",
"import time\n",
"\n",
"print(\"✅ All libraries imported successfully!\")\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Configuration\n",
"\n",
"Set up your OpenAI API key and configure the client.\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# Configuration cell - Set up your OpenAI API key\n",
"def get_client_and_headers():\n",
" \"\"\"Initialize OpenAI client and headers for web scraping\"\"\"\n",
" load_dotenv(override=True)\n",
" api_key = os.getenv(\"OPENAI_API_KEY\")\n",
" \n",
" if api_key and api_key.startswith('sk-proj-') and len(api_key) > 10:\n",
" print(\"✅ API key looks good!\")\n",
" else:\n",
" print(\"⚠️ There might be a problem with your API key\")\n",
" print(\"Make sure you have set OPENAI_API_KEY in your .env file or environment variables\")\n",
"\n",
" client = OpenAI(api_key=api_key)\n",
" \n",
" headers = {\n",
" \"User-Agent\": \"Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/117.0.0.0 Safari/537.36\"\n",
" }\n",
" return client, headers\n",
"\n",
"# Initialize the client\n",
"client, headers = get_client_and_headers()\n",
"print(\"✅ OpenAI client initialized successfully!\")\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Core Functions\n",
"\n",
"The main functions for website analysis and brochure generation.\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# Utility methods to display content in markdown format\n",
"def display_content(content, is_markdown=True):\n",
" \"\"\"Display content using Jupyter's display methods\"\"\"\n",
" if is_markdown:\n",
" display(Markdown(content))\n",
" else:\n",
" print(content)\n",
"\n",
"def stream_content(response, title=\"Content\"):\n",
" \"\"\"\n",
" Utility function to handle streaming content display in Jupyter\n",
" \n",
" Args:\n",
" response: OpenAI streaming response object\n",
" title (str): Title to display for the streaming content\n",
" \n",
" Returns:\n",
" str: Complete streamed content\n",
" \"\"\"\n",
" result = \"\"\n",
" \n",
" # Display title\n",
" display(HTML(f\"<h3 style='color: #1f77b4;'>{title}...</h3>\"))\n",
" \n",
" # Create output widget for streaming\n",
" from IPython.display import clear_output\n",
" import time\n",
" \n",
" for chunk in response:\n",
" content = chunk.choices[0].delta.content or \"\"\n",
" result += content\n",
" # Print each chunk as it arrives for streaming effect\n",
" print(content, end='', flush=True)\n",
" \n",
" # Display completion message\n",
" display(HTML(f\"<div style='color: green; font-weight: bold; margin-top: 20px;'>{'='*50}</div>\"))\n",
" display(HTML(f\"<div style='color: green; font-weight: bold;'>{title.upper()} COMPLETE</div>\"))\n",
" display(HTML(f\"<div style='color: green; font-weight: bold;'>{'='*50}</div>\"))\n",
" \n",
" return result\n",
"\n",
"print(\"✅ Utility functions loaded!\")\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# Utility class to get the contents of a website\n",
"class Website:\n",
" def __init__(self, url):\n",
" self.url = url\n",
" self.client, self.headers = get_client_and_headers()\n",
" print(f\"🌐 Fetching content from: {url}\")\n",
" response = requests.get(url, headers=self.headers)\n",
" self.body = response.content\n",
" soup = BeautifulSoup(self.body, 'html.parser')\n",
" self.title = soup.title.string if soup.title else \"No title found\"\n",
" if soup.body:\n",
" for irrelevant in soup.body([\"script\", \"style\", \"img\", \"input\"]):\n",
" irrelevant.decompose()\n",
" self.text = soup.body.get_text(separator=\"\\n\", strip=True)\n",
" else:\n",
" self.text = \"\"\n",
" links = [link.get('href') for link in soup.find_all('a')]\n",
" self.links = [link for link in links if link]\n",
" print(f\"✅ Website analyzed: {self.title}\")\n",
"\n",
" def get_contents(self):\n",
" return f\"Webpage Title: {self.title}\\nWebpage Contents: {self.text}\\n\\n\"\n",
"\n",
"print(\"✅ Website class loaded!\")\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# AI Prompt Functions\n",
"def get_links_system_prompt():\n",
" link_system_prompt = \"\"\"\"You are provided with a list of links found on a webpage. \\\n",
" You are able to decide which of the links would be most relevant to include in a brochure about the company. \\\n",
" Relevant links usually include: About page, or a Company page, or Careers/Jobs pages or News page\\n\"\"\"\n",
" link_system_prompt += \"Always respond in JSON exactly like this: \\n\"\n",
" link_system_prompt += \"\"\"\n",
" {\n",
" \"links\": [\n",
" {\"type\": \"<page type>\", \"url\": \"<full URL>\"},\n",
" {\"type\": \"<page type>\", \"url\": \"<full URL>\"}\n",
" ]\n",
" }\\n\n",
" \"\"\"\n",
" link_system_prompt += \"\"\" If no relevant links are found, return:\n",
" {\n",
" \"links\": []\n",
" }\\n\n",
" \"\"\"\n",
" link_system_prompt += \"If multiple links could map to the same type (e.g. two About pages), include the best candidate only.\\n\"\n",
"\n",
" link_system_prompt += \"You should respond in JSON as in the below examples:\\n\"\n",
" link_system_prompt += \"\"\"\n",
" ## Example 1\n",
" Input links:\n",
" - https://acme.com/about \n",
" - https://acme.com/pricing \n",
" - https://acme.com/blog \n",
" - https://acme.com/signup \n",
"\n",
" Output:\n",
" {\n",
" \"links\": [\n",
" {\"type\": \"about page\", \"url\": \"https://acme.com/about\"},\n",
" {\"type\": \"blog page\", \"url\": \"https://acme.com/blog\"},\n",
" {\"type\": \"pricing page\", \"url\": \"https://acme.com/pricing\"}\n",
" ]\n",
" }\n",
" \"\"\"\n",
" link_system_prompt += \"\"\"\n",
" ## Example 2\n",
" Input links:\n",
" - https://startup.io/ \n",
" - https://startup.io/company \n",
" - https://startup.io/careers \n",
" - https://startup.io/support \n",
"\n",
" Output:\n",
" {\n",
" \"links\": [\n",
" {\"type\": \"company page\", \"url\": \"https://startup.io/company\"},\n",
" {\"type\": \"careers page\", \"url\": \"https://startup.io/careers\"}\n",
" ]\n",
" }\n",
" \"\"\"\n",
" link_system_prompt += \"\"\"\n",
" ## Example 3\n",
" Input links:\n",
" - https://coolapp.xyz/login \n",
" - https://coolapp.xyz/random \n",
"\n",
" Output:\n",
" {\n",
" \"links\": []\n",
" }\n",
" \"\"\"\n",
" return link_system_prompt\n",
"\n",
"def get_links_user_prompt(website):\n",
" user_prompt = f\"Here is the list of links on the website of {website.url} - \"\n",
" user_prompt += \"please decide which of these are relevant web links for a brochure about the company, respond with the full https URL in JSON format. \\n\"\n",
" user_prompt += \"Do not include Terms of Service, Privacy, email links.\\n\"\n",
" user_prompt += \"Links (some might be relative links):\\n\"\n",
" user_prompt += \"\\n\".join(website.links)\n",
" return user_prompt\n",
"\n",
"def get_brochure_system_prompt():\n",
" brochure_system_prompt = \"\"\"\n",
" You are an assistant that analyzes the contents of several relevant pages from a company website \\\n",
" and creates a short brochure about the company for prospective customers, investors and recruits. Respond in markdown.\n",
" Include details of company culture, customers and careers/jobs if you have the information.\n",
" \"\"\"\n",
" return brochure_system_prompt\n",
"\n",
"def get_brochure_user_prompt(url):\n",
" user_prompt = f\"You are looking at a company details of: {url}\\n\"\n",
" user_prompt += f\"Here are the contents of its landing page and other relevant pages; use this information to build a short brochure of the company in markdown.\\n\"\n",
" user_prompt += get_details_for_brochure(url)\n",
" user_prompt = user_prompt[:15000] # Truncate if more than 15,000 characters\n",
" return user_prompt\n",
"\n",
"def get_translation_system_prompt(target_language):\n",
" translation_system_prompt = f\"You are a professional translator specializing in business and marketing content. \\\n",
" Translate the provided brochure to {target_language} while maintaining all formatting and professional tone.\"\n",
" return translation_system_prompt\n",
"\n",
"def get_translation_user_prompt(original_brochure, target_language):\n",
" translation_prompt = f\"\"\"\n",
" You are a professional translator. Please translate the following brochure content to {target_language}.\n",
" \n",
" Important guidelines:\n",
" - Maintain the markdown formatting exactly as it appears\n",
" - Keep all headers, bullet points, and structure intact\n",
" - Translate the content naturally and professionally\n",
" - Preserve any company names, product names, or proper nouns unless they have established translations\n",
" - Maintain the professional tone and marketing style\n",
" \n",
" Brochure content to translate:\n",
" {original_brochure}\n",
" \"\"\"\n",
" return translation_prompt\n",
"\n",
"print(\"✅ AI prompt functions loaded!\")\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# Core Brochure Generation Functions\n",
"def get_links(url):\n",
" \"\"\"Get relevant links from a website using AI analysis\"\"\"\n",
" website = Website(url)\n",
" response = website.client.chat.completions.create(\n",
" model=\"gpt-4o-mini\",\n",
" messages=[\n",
" {\"role\": \"system\", \"content\": get_links_system_prompt()},\n",
" {\"role\": \"user\", \"content\": get_links_user_prompt(website)}\n",
" ],\n",
" response_format={\"type\": \"json_object\"}\n",
" )\n",
" result = response.choices[0].message.content\n",
" print(\"🔗 Found relevant links:\", result)\n",
" return json.loads(result)\n",
"\n",
"def get_details_for_brochure(url):\n",
" \"\"\"Get comprehensive details from website and relevant pages\"\"\"\n",
" website = Website(url)\n",
" result = \"Landing page:\\n\"\n",
" result += website.get_contents()\n",
" links = get_links(url)\n",
" print(\"📄 Analyzing additional pages...\")\n",
" for link in links[\"links\"]:\n",
" result += f\"\\n\\n{link['type']}\\n\"\n",
" result += Website(link[\"url\"]).get_contents()\n",
" return result\n",
"\n",
"def create_brochure(url):\n",
" \"\"\"Create a brochure from a website URL\"\"\"\n",
" website = Website(url)\n",
" print(\"🤖 Generating brochure with AI...\")\n",
" response = website.client.chat.completions.create(\n",
" model=\"gpt-4o-mini\",\n",
" messages=[\n",
" {\"role\": \"system\", \"content\": get_brochure_system_prompt()},\n",
" {\"role\": \"user\", \"content\": get_brochure_user_prompt(url)}\n",
" ]\n",
" )\n",
" result = response.choices[0].message.content\n",
" display_content(result, is_markdown=True)\n",
" return result\n",
"\n",
"def stream_brochure(url):\n",
" \"\"\"Create a brochure with streaming output\"\"\"\n",
" website = Website(url)\n",
" print(\"🤖 Generating brochure with streaming output...\")\n",
" response = website.client.chat.completions.create(\n",
" model=\"gpt-4o-mini\",\n",
" messages=[\n",
" {\"role\": \"system\", \"content\": get_brochure_system_prompt()},\n",
" {\"role\": \"user\", \"content\": get_brochure_user_prompt(url)}\n",
" ],\n",
" stream=True\n",
" )\n",
" \n",
" # Use the reusable streaming utility function\n",
" result = stream_content(response, \"Generating brochure\")\n",
" return result\n",
"\n",
"print(\"✅ Core brochure generation functions loaded!\")\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# Translation Functions\n",
"def translate_brochure(url, target_language=\"Spanish\", stream_mode=False):\n",
" \"\"\"\n",
" Generate a brochure and translate it to the target language\n",
" \n",
" Args:\n",
" url (str): The website URL to generate brochure from\n",
" target_language (str): The target language for translation (default: \"Spanish\")\n",
" stream_mode (bool): Whether to use streaming output (default: False)\n",
" \n",
" Returns:\n",
" str: Translated brochure content\n",
" \"\"\"\n",
" # First generate the original brochure\n",
" print(f\"🌍 Generating brochure and translating to {target_language}...\")\n",
" original_brochure = create_brochure(url)\n",
" \n",
" # Get translation prompts\n",
" translation_system_prompt = get_translation_system_prompt(target_language)\n",
" translation_user_prompt = get_translation_user_prompt(original_brochure, target_language)\n",
" \n",
" # Get OpenAI client\n",
" website = Website(url)\n",
" \n",
" if stream_mode:\n",
" # Generate translation using OpenAI with streaming\n",
" response = website.client.chat.completions.create(\n",
" model=\"gpt-4o-mini\",\n",
" messages=[\n",
" {\"role\": \"system\", \"content\": translation_system_prompt},\n",
" {\"role\": \"user\", \"content\": translation_user_prompt}\n",
" ],\n",
" stream=True\n",
" )\n",
" \n",
" # Use the reusable streaming utility function\n",
" translated_brochure = stream_content(response, f\"Translating brochure to {target_language}\")\n",
" else:\n",
" # Generate translation using OpenAI with complete output\n",
" response = website.client.chat.completions.create(\n",
" model=\"gpt-4o-mini\",\n",
" messages=[\n",
" {\"role\": \"system\", \"content\": translation_system_prompt},\n",
" {\"role\": \"user\", \"content\": translation_user_prompt}\n",
" ]\n",
" )\n",
" \n",
" translated_brochure = response.choices[0].message.content\n",
" \n",
" # Display the translated content\n",
" display_content(translated_brochure, is_markdown=True)\n",
" \n",
" return translated_brochure\n",
"\n",
"print(\"✅ Translation functions loaded!\")\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Interactive Examples\n",
"\n",
"Now let's try generating brochures for some example websites. You can run these cells to see the brochure generator in action!\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# Example 1: Generate a brochure for a sample website\n",
"# You can change this URL to any website you want to analyze\n",
"\n",
"sample_url = \"https://openai.com\" # Change this to any website you want to analyze\n",
"\n",
"print(f\"🚀 Generating brochure for: {sample_url}\")\n",
"print(\"=\" * 60)\n",
"\n",
"# Generate the brochure\n",
"brochure = create_brochure(sample_url)\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# Example 2: Generate a brochure with streaming output\n",
"# This shows the brochure being generated in real-time\n",
"\n",
"streaming_url = \"https://anthropic.com\" # Change this to any website you want to analyze\n",
"\n",
"print(f\"🚀 Generating brochure with streaming for: {streaming_url}\")\n",
"print(\"=\" * 60)\n",
"\n",
"# Generate the brochure with streaming\n",
"streaming_brochure = stream_brochure(streaming_url)\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# Example 3: Generate and translate a brochure\n",
"# This creates a brochure and then translates it to another language\n",
"\n",
"translation_url = \"https://huggingface.co\" # Change this to any website you want to analyze\n",
"target_language = \"Spanish\" # Change this to any language you want\n",
"\n",
"print(f\"🚀 Generating and translating brochure for: {translation_url}\")\n",
"print(f\"🌍 Target language: {target_language}\")\n",
"print(\"=\" * 60)\n",
"\n",
"# Generate and translate the brochure\n",
"translated_brochure = translate_brochure(translation_url, target_language, stream_mode=False)\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Interactive Widget Interface\n",
"\n",
"Use the widgets below to interactively generate brochures for any website!\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# Interactive Widget Interface\n",
"import ipywidgets as widgets\n",
"from IPython.display import display, clear_output\n",
"\n",
"# Create widgets\n",
"url_input = widgets.Text(\n",
" value='https://openai.com',\n",
" placeholder='Enter website URL (e.g., https://example.com)',\n",
" description='Website URL:',\n",
" style={'description_width': 'initial'},\n",
" layout=widgets.Layout(width='500px')\n",
")\n",
"\n",
"language_dropdown = widgets.Dropdown(\n",
" options=['English', 'Spanish', 'French', 'German', 'Chinese', 'Japanese', 'Portuguese', 'Italian'],\n",
" value='English',\n",
" description='Language:',\n",
" style={'description_width': 'initial'}\n",
")\n",
"\n",
"stream_checkbox = widgets.Checkbox(\n",
" value=False,\n",
" description='Use streaming output',\n",
" style={'description_width': 'initial'}\n",
")\n",
"\n",
"translate_checkbox = widgets.Checkbox(\n",
" value=False,\n",
" description='Translate brochure',\n",
" style={'description_width': 'initial'}\n",
")\n",
"\n",
"generate_button = widgets.Button(\n",
" description='Generate Brochure',\n",
" button_style='success',\n",
" icon='rocket'\n",
")\n",
"\n",
"output_area = widgets.Output()\n",
"\n",
"def on_generate_clicked(b):\n",
" with output_area:\n",
" clear_output(wait=True)\n",
" url = url_input.value.strip()\n",
" \n",
" if not url:\n",
" print(\"❌ Please enter a valid URL\")\n",
" return\n",
" \n",
" if not url.startswith(('http://', 'https://')):\n",
" url = 'https://' + url\n",
" \n",
" print(f\"🚀 Generating brochure for: {url}\")\n",
" print(\"=\" * 60)\n",
" \n",
" try:\n",
" if translate_checkbox.value:\n",
" # Generate and translate\n",
" result = translate_brochure(url, language_dropdown.value, stream_mode=stream_checkbox.value)\n",
" else:\n",
" # Generate only\n",
" if stream_checkbox.value:\n",
" result = stream_brochure(url)\n",
" else:\n",
" result = create_brochure(url)\n",
" \n",
" print(\"\\n✅ Brochure generation completed!\")\n",
" \n",
" except Exception as e:\n",
" print(f\"❌ Error generating brochure: {str(e)}\")\n",
" print(\"Please check your API key and internet connection.\")\n",
"\n",
"generate_button.on_click(on_generate_clicked)\n",
"\n",
"# Display widgets\n",
"print(\"🎯 Interactive Brochure Generator\")\n",
"print(\"Enter a website URL and click 'Generate Brochure' to create a professional brochure!\")\n",
"print()\n",
"\n",
"display(url_input)\n",
"display(widgets.HBox([language_dropdown, stream_checkbox, translate_checkbox]))\n",
"display(generate_button)\n",
"display(output_area)\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Advanced Usage Examples\n",
"\n",
"Here are some advanced examples showing different ways to use the brochure generator.\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# Advanced Example 1: Analyze multiple websites and compare\n",
"websites_to_analyze = [\n",
" \"https://openai.com\",\n",
" \"https://anthropic.com\", \n",
" \"https://huggingface.co\"\n",
"]\n",
"\n",
"print(\"🔍 Analyzing multiple websites...\")\n",
"print(\"=\" * 60)\n",
"\n",
"brochures = {}\n",
"for url in websites_to_analyze:\n",
" print(f\"\\n📊 Generating brochure for: {url}\")\n",
" try:\n",
" brochure = create_brochure(url)\n",
" brochures[url] = brochure\n",
" print(f\"✅ Successfully generated brochure for {url}\")\n",
" except Exception as e:\n",
" print(f\"❌ Failed to generate brochure for {url}: {str(e)}\")\n",
" \n",
" print(\"-\" * 40)\n",
"\n",
"print(f\"\\n🎉 Generated {len(brochures)} brochures successfully!\")\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# Advanced Example 2: Generate brochures in multiple languages\n",
"target_website = \"https://openai.com\" # Change this to any website\n",
"languages = [\"Spanish\", \"French\", \"German\", \"Chinese\"]\n",
"\n",
"print(f\"🌍 Generating brochures in multiple languages for: {target_website}\")\n",
"print(\"=\" * 60)\n",
"\n",
"multilingual_brochures = {}\n",
"for language in languages:\n",
" print(f\"\\n🔄 Translating to {language}...\")\n",
" try:\n",
" translated_brochure = translate_brochure(target_website, language, stream_mode=False)\n",
" multilingual_brochures[language] = translated_brochure\n",
" print(f\"✅ Successfully translated to {language}\")\n",
" except Exception as e:\n",
" print(f\"❌ Failed to translate to {language}: {str(e)}\")\n",
" \n",
" print(\"-\" * 40)\n",
"\n",
"print(f\"\\n🎉 Generated brochures in {len(multilingual_brochures)} languages!\")\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Custom Functions\n",
"\n",
"Create your own custom functions for specific use cases.\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# Custom Function: Save brochure to file\n",
"def save_brochure_to_file(brochure_content, filename, url):\n",
" \"\"\"Save brochure content to a markdown file\"\"\"\n",
" try:\n",
" with open(filename, 'w', encoding='utf-8') as f:\n",
" f.write(f\"# Brochure for {url}\\n\\n\")\n",
" f.write(f\"Generated on: {time.strftime('%Y-%m-%d %H:%M:%S')}\\n\\n\")\n",
" f.write(\"---\\n\\n\")\n",
" f.write(brochure_content)\n",
" print(f\"✅ Brochure saved to: {filename}\")\n",
" return True\n",
" except Exception as e:\n",
" print(f\"❌ Error saving brochure: {str(e)}\")\n",
" return False\n",
"\n",
"# Custom Function: Generate brochure with custom analysis\n",
"def generate_custom_brochure(url, focus_areas=None):\n",
" \"\"\"Generate a brochure with focus on specific areas\"\"\"\n",
" if focus_areas is None:\n",
" focus_areas = [\"company overview\", \"products\", \"culture\", \"careers\"]\n",
" \n",
" website = Website(url)\n",
" \n",
" # Custom system prompt with focus areas\n",
" custom_system_prompt = f\"\"\"\n",
" You are an assistant that analyzes website content and creates a professional brochure.\n",
" Focus specifically on these areas: {', '.join(focus_areas)}.\n",
" Create a markdown brochure that emphasizes these aspects for prospective customers, investors and recruits.\n",
" \"\"\"\n",
" \n",
" response = website.client.chat.completions.create(\n",
" model=\"gpt-4o-mini\",\n",
" messages=[\n",
" {\"role\": \"system\", \"content\": custom_system_prompt},\n",
" {\"role\": \"user\", \"content\": get_brochure_user_prompt(url)}\n",
" ]\n",
" )\n",
" \n",
" result = response.choices[0].message.content\n",
" display_content(result, is_markdown=True)\n",
" return result\n",
"\n",
"# Custom Function: Quick website analysis\n",
"def quick_website_analysis(url):\n",
" \"\"\"Perform a quick analysis of a website without generating full brochure\"\"\"\n",
" website = Website(url)\n",
" \n",
" analysis = f\"\"\"\n",
" # Quick Website Analysis: {url}\n",
" \n",
" **Title:** {website.title}\n",
" **Total Links Found:** {len(website.links)}\n",
" **Content Length:** {len(website.text)} characters\n",
" \n",
" ## Sample Content (first 500 characters):\n",
" {website.text[:500]}...\n",
" \n",
" ## All Links:\n",
" {chr(10).join(website.links[:10])} # Show first 10 links\n",
" \"\"\"\n",
" \n",
" display_content(analysis, is_markdown=True)\n",
" return analysis\n",
"\n",
"print(\"✅ Custom functions loaded!\")\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Usage Examples with Custom Functions\n",
"\n",
"Try these examples with the custom functions we just created.\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# Example: Quick website analysis\n",
"test_url = \"https://openai.com\" # Change this to any website\n",
"\n",
"print(\"🔍 Performing quick website analysis...\")\n",
"print(\"=\" * 50)\n",
"\n",
"quick_analysis = quick_website_analysis(test_url)\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# Example: Generate custom brochure with specific focus\n",
"custom_url = \"https://anthropic.com\" # Change this to any website\n",
"focus_areas = [\"AI safety\", \"research\", \"products\", \"team\"] # Custom focus areas\n",
"\n",
"print(\"🎯 Generating custom brochure with specific focus...\")\n",
"print(f\"Focus areas: {', '.join(focus_areas)}\")\n",
"print(\"=\" * 50)\n",
"\n",
"custom_brochure = generate_custom_brochure(custom_url, focus_areas)\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# Example: Generate brochure and save to file\n",
"save_url = \"https://huggingface.co\" # Change this to any website\n",
"\n",
"print(\"💾 Generating brochure and saving to file...\")\n",
"print(\"=\" * 50)\n",
"\n",
"# Generate brochure\n",
"brochure_content = create_brochure(save_url)\n",
"\n",
"# Save to file\n",
"filename = f\"brochure_{save_url.replace('https://', '').replace('/', '_')}.md\"\n",
"save_success = save_brochure_to_file(brochure_content, filename, save_url)\n",
"\n",
"if save_success:\n",
" print(f\"📁 You can find the saved brochure in: {filename}\")\n",
"else:\n",
" print(\"❌ Failed to save brochure to file\")\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Troubleshooting and Tips\n",
"\n",
"### Common Issues and Solutions\n",
"\n",
"1. **API Key Issues**\n",
" - Make sure your OpenAI API key is set in the `.env` file\n",
" - Verify your API key has sufficient credits\n",
" - Check that the key starts with `sk-proj-`\n",
"\n",
"2. **Website Scraping Issues**\n",
" - Some websites may block automated requests\n",
" - Try different websites if one fails\n",
" - The tool uses a standard User-Agent header to avoid basic blocking\n",
"\n",
"3. **Memory Issues**\n",
" - Large websites may consume significant memory\n",
" - The tool truncates content to 15,000 characters to manage this\n",
"\n",
"4. **Rate Limiting**\n",
" - OpenAI has rate limits on API calls\n",
" - If you hit limits, wait a few minutes before trying again\n",
"\n",
"### Tips for Better Results\n",
"\n",
"1. **Choose Good Websites**\n",
" - Websites with clear About, Products, and Careers pages work best\n",
" - Avoid websites that are mostly images or require JavaScript\n",
"\n",
"2. **Use Streaming for Long Content**\n",
" - Enable streaming for better user experience with long brochures\n",
" - Streaming shows progress in real-time\n",
"\n",
"3. **Custom Focus Areas**\n",
" - Use the custom brochure function to focus on specific aspects\n",
" - This can help generate more targeted content\n",
"\n",
"4. **Save Your Work**\n",
" - Use the save function to keep brochures for later reference\n",
" - Files are saved in markdown format for easy editing\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Conclusion\n",
"\n",
"This Jupyter notebook provides a comprehensive interface for the Website Brochure Generator. You can:\n",
"\n",
"- ✅ Generate professional brochures from any website\n",
"- ✅ Translate brochures to multiple languages\n",
"- ✅ Use interactive widgets for easy operation\n",
"- ✅ Save brochures to files for later use\n",
"- ✅ Perform quick website analysis\n",
"- ✅ Create custom brochures with specific focus areas\n",
"- ✅ Generate brochures with streaming output for real-time feedback\n",
"\n",
"### Next Steps\n",
"\n",
"1. **Try the Interactive Widget**: Use the widget interface above to generate brochures for your favorite websites\n",
"2. **Experiment with Different URLs**: Test the tool with various types of websites\n",
"3. **Explore Translation Features**: Generate brochures in different languages\n",
"4. **Save Your Work**: Use the save function to keep your generated brochures\n",
"5. **Customize Focus Areas**: Create brochures tailored to specific aspects of companies\n",
"\n",
"### Support\n",
"\n",
"For issues and questions:\n",
"- Check the troubleshooting section above\n",
"- Verify your OpenAI API key is properly configured\n",
"- Ensure you have a stable internet connection\n",
"- Try different websites if one fails\n",
"\n",
"Happy brochure generating! 🚀\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": []
},
{
"cell_type": "markdown",
"metadata": {},
"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": "3.12.11"
}
},
"nbformat": 4,
"nbformat_minor": 4
}

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from openai import OpenAI
from dotenv import load_dotenv
import os
import requests
import json
from typing import List
from bs4 import BeautifulSoup
# Rich library for beautiful terminal markdown rendering
from rich.console import Console
from rich.markdown import Markdown as RichMarkdown
def get_client_and_headers():
load_dotenv(override=True)
api_key = os.getenv("OPENAI_API_KEY")
if api_key and api_key.startswith('sk-proj-') and len(api_key)>10:
# print("API key looks good so far")
pass
else:
print("There might be a problem with your API key")
client = OpenAI(api_key=api_key)
headers = {
"User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/117.0.0.0 Safari/537.36"
}
return client, headers
# Utility methods to display content in markdown format
def print_markdown_terminal(text):
"""Print markdown-formatted text to terminal with beautiful formatting using Rich"""
console = Console()
console.print(RichMarkdown(text))
def display_content(content, is_markdown=True):
"""Display content using Rich formatting"""
if is_markdown:
print_markdown_terminal(content)
else:
print(content)
def stream_content(response, title="Content"):
"""
Utility function to handle streaming content display using Rich
Args:
response: OpenAI streaming response object
title (str): Title to display for the streaming content
Returns:
str: Complete streamed content
"""
result = ""
console = Console()
# Terminal streaming with real-time output using Rich
console.print(f"\n[bold blue]{title}...[/bold blue]\n")
for chunk in response:
content = chunk.choices[0].delta.content or ""
result += content
# Print each chunk as it arrives for streaming effect
print(content, end='', flush=True)
console.print(f"\n\n[bold green]{'='*50}[/bold green]")
console.print(f"[bold green]{title.upper()} COMPLETE[/bold green]")
console.print(f"[bold green]{'='*50}[/bold green]")
return result
# Utility class to get the contents of a website
class Website:
def __init__(self, url):
self.url = url
self.client, self.headers = get_client_and_headers()
response = requests.get(url, headers=self.headers)
self.body = response.content
soup = BeautifulSoup(self.body, 'html.parser')
self.title = soup.title.string if soup.title else "No title found"
if soup.body:
for irrelevant in soup.body(["script", "style", "img", "input"]):
irrelevant.decompose()
self.text = soup.body.get_text(separator="\n", strip=True)
else:
self.text = ""
links = [link.get('href') for link in soup.find_all('a')]
self.links = [link for link in links if link]
def get_contents(self):
return f"Webpage Title: {self.title}\nWebpage Contents: {self.text}\n\n"
def get_links_system_prompt():
link_system_prompt = """"You are provided with a list of links found on a webpage. \
You are able to decide which of the links would be most relevant to include in a brochure about the company. \
Relevant links usually include: About page, or a Company page, or Careers/Jobs pages or News page\n"""
link_system_prompt += "Always respond in JSON exactly like this: \n"
link_system_prompt += """
{
"links": [
{"type": "<page type>", "url": "<full URL>"},
{"type": "<page type>", "url": "<full URL>"}
]
}\n
"""
link_system_prompt += """ If no relevant links are found, return:
{
"links": []
}\n
"""
link_system_prompt += "If multiple links could map to the same type (e.g. two About pages), include the best candidate only.\n"
link_system_prompt += "You should respond in JSON as in the below examples:\n"
link_system_prompt += """
## Example 1
Input links:
- https://acme.com/about
- https://acme.com/pricing
- https://acme.com/blog
- https://acme.com/signup
Output:
{
"links": [
{"type": "about page", "url": "https://acme.com/about"},
{"type": "blog page", "url": "https://acme.com/blog"},
{"type": "pricing page", "url": "https://acme.com/pricing"}
]
}
"""
link_system_prompt += """
## Example 2
Input links:
- https://startup.io/
- https://startup.io/company
- https://startup.io/careers
- https://startup.io/support
Output:
{
"links": [
{"type": "company page", "url": "https://startup.io/company"},
{"type": "careers page", "url": "https://startup.io/careers"}
]
}
"""
link_system_prompt += """
## Example 3
Input links:
- https://coolapp.xyz/login
- https://coolapp.xyz/random
Output:
{
"links": []
}
"""
return link_system_prompt
def get_links_user_prompt(website):
user_prompt = f"Here is the list of links on the website of {website.url} - "
user_prompt += "please decide which of these are relevant web links for a brochure about the company, respond with the full https URL in JSON format. \n"
user_prompt += "Do not include Terms of Service, Privacy, email links.\n"
user_prompt += "Links (some might be relative links):\n"
user_prompt += "\n".join(website.links)
return user_prompt
def get_brochure_system_prompt():
brochure_system_prompt = """
You are an assistant that analyzes the contents of several relevant pages from a company website \
and creates a short brochure about the company for prospective customers, investors and recruits. Respond in markdown.
Include details of company culture, customers and careers/jobs if you have the information.
"""
return brochure_system_prompt
def get_brochure_user_prompt(url):
user_prompt = f"You are looking at a company details of: {url}\n"
user_prompt += f"Here are the contents of its landing page and other relevant pages; use this information to build a short brochure of the company in markdown.\n"
user_prompt += get_details_for_brochure(url)
user_prompt = user_prompt[:15000] # Truncate if more than 15,000 characters
return user_prompt
def get_translation_system_prompt(target_language):
translation_system_prompt = f"You are a professional translator specializing in business and marketing content. \
Translate the provided brochure to {target_language} while maintaining all formatting and professional tone."
return translation_system_prompt
def get_translation_user_prompt(original_brochure, target_language):
translation_prompt = f"""
You are a professional translator. Please translate the following brochure content to {target_language}.
Important guidelines:
- Maintain the markdown formatting exactly as it appears
- Keep all headers, bullet points, and structure intact
- Translate the content naturally and professionally
- Preserve any company names, product names, or proper nouns unless they have established translations
- Maintain the professional tone and marketing style
Brochure content to translate:
{original_brochure}
"""
return translation_prompt
def get_links(url):
website = Website(url)
response = website.client.chat.completions.create(
model="gpt-4o-mini",
messages=[
{"role": "system", "content": get_links_system_prompt()},
{"role": "user", "content": get_links_user_prompt(website)}
],
response_format={"type": "json_object"}
)
result = response.choices[0].message.content
print("get_links:", result)
return json.loads(result)
def get_details_for_brochure(url):
website = Website(url)
result = "Landing page:\n"
result += website.get_contents()
links = get_links(url)
print("Found links:", links)
for link in links["links"]:
result += f"\n\n{link['type']}\n"
result += Website(link["url"]).get_contents()
return result
def create_brochure(url):
website = Website(url)
response = website.client.chat.completions.create(
model="gpt-4o-mini",
messages=[
{"role": "system", "content": get_brochure_system_prompt()},
{"role": "user", "content": get_brochure_user_prompt(url)}
]
)
result = response.choices[0].message.content
display_content(result, is_markdown=True)
return result
def stream_brochure(url):
website = Website(url)
response = website.client.chat.completions.create(
model="gpt-4o-mini",
messages=[
{"role": "system", "content": get_brochure_system_prompt()},
{"role": "user", "content": get_brochure_user_prompt(url)}
],
stream=True
)
# Use the reusable streaming utility function
result = stream_content(response, "Generating brochure")
return result
def translate_brochure(url, target_language="Spanish", stream_mode=False):
"""
Generate a brochure and translate it to the target language
Args:
url (str): The website URL to generate brochure from
target_language (str): The target language for translation (default: "Spanish")
stream_mode (bool): Whether to use streaming output (default: False)
Returns:
str: Translated brochure content
"""
# First generate the original brochure
original_brochure = create_brochure(url)
# Get translation prompts
translation_system_prompt = get_translation_system_prompt(target_language)
translation_user_prompt = get_translation_user_prompt(original_brochure, target_language)
# Get OpenAI client
website = Website(url)
if stream_mode:
# Generate translation using OpenAI with streaming
response = website.client.chat.completions.create(
model="gpt-4o-mini",
messages=[
{"role": "system", "content": translation_system_prompt},
{"role": "user", "content": translation_user_prompt}
],
stream=True
)
# Use the reusable streaming utility function
translated_brochure = stream_content(response, f"Translating brochure to {target_language}")
else:
# Generate translation using OpenAI with complete output
response = website.client.chat.completions.create(
model="gpt-4o-mini",
messages=[
{"role": "system", "content": translation_system_prompt},
{"role": "user", "content": translation_user_prompt}
]
)
translated_brochure = response.choices[0].message.content
# Display the translated content
display_content(translated_brochure, is_markdown=True)
return translated_brochure
# Main function for terminal usage
def main():
"""Main function for running the brochure generator from terminal"""
import sys
if len(sys.argv) != 2:
console = Console()
console.print("[bold red]Usage:[/bold red] python website_brochure_generator.py <website_url>")
console.print("[bold blue]Example:[/bold blue] python website_brochure_generator.py https://example.com")
sys.exit(1)
url = sys.argv[1]
console = Console()
console.print(f"[bold green]Generating brochure for:[/bold green] {url}")
console.print("\n[bold yellow]Choose display mode:[/bold yellow]")
console.print("1. Complete output (display all at once)")
console.print("2. Stream output (real-time generation)")
display_choice = input("\nEnter choice (1 or 2): ").strip()
# Generate brochure based on display choice
if display_choice == "1":
result = create_brochure(url)
elif display_choice == "2":
result = stream_brochure(url)
else:
console.print("[bold red]Invalid choice. Using default: complete output[/bold red]")
result = create_brochure(url)
# Ask if user wants translation
console.print("\n[bold yellow]Translation options:[/bold yellow]")
console.print("1. No translation (original only)")
console.print("2. Translate to another language")
translation_choice = input("\nEnter choice (1 or 2): ").strip()
if translation_choice == "2":
target_language = input("Enter target language (e.g., Spanish, French, German, Chinese): ").strip()
if not target_language:
target_language = "Spanish"
# Pass the stream mode based on the display choice
stream_mode = (display_choice == "2")
translate_brochure(url, target_language, stream_mode=stream_mode)
else:
pass
if __name__ == "__main__":
main()