aitoolmaker 0.1.0

A framework for automatically generating and running Streamlit-based AI tools and chatbots

AIToolMaker

AIToolMaker is a powerful Python framework that automatically generates and runs Streamlit-based AI tools and chatbots, or exports them as full HTML/CSS/JS websites.

Features

• Instant Tool Generation: Create AI-powered tools with a single command
• Multiple Output Formats: Generate Streamlit apps or standalone websites
• 6 Pre-built Tools: Chatbot, Blog Generator, Data Analyzer, SQL Generator, Document Summarizer, Web Summarizer
• Run Immediately: Option to run tools instantly without exporting code
• Auto-branding: Automatic name and logo generation
• Multi-API Support: Works with Gemini, OpenAI, and Anthropic APIs

Installation

pip install aitoolmaker

Or install from source:

git clone https://github.com/MoustafaMohamed01/aitoolmaker.git
cd aitoolmaker
pip install -e .

Quick Start

Python API

from aitoolmaker import AIToolMaker

# Initialize
tool = AIToolMaker(
    api_key="YOUR_GEMINI_API_KEY",
    model="gemini-2.0-flash"
)

# Generate and run a chatbot
tool.create_tool(
    tool_type="chatbot",
    output="streamlit",
    run=True,
    name="My AI Assistant"
)

Command Line

# Create a blog generator
aitoolmaker create --tool blog_generator --api-key YOUR_KEY --output streamlit

# Create and run immediately
aitoolmaker create --tool chatbot --api-key YOUR_KEY --run

# Generate a website
aitoolmaker create --tool sql_generator --api-key YOUR_KEY --output website

Available Tools

Tool	Description
chatbot	Professional AI assistant with conversation history
blog_generator	AI-powered blog writer with keyword optimization
data_analyzer	Ask questions about CSV data using AI
sql_generator	Generate SQL queries from natural language
document_summarizer	Summarize PDF and Word documents
web_summarizer	Summarize website content

Usage Examples

Generate Multiple Tools

from aitoolmaker import AIToolMaker

api_key = "YOUR_API_KEY"
tools = ["chatbot", "blog_generator", "sql_generator"]

for tool_type in tools:
    maker = AIToolMaker(api_key=api_key, model="gemini-2.0-flash")
    result = maker.create_tool(
        tool_type=tool_type,
        output="streamlit",
        output_dir=f"./generated_{tool_type}"
    )
    print(f"{tool_type} created at {result['output_dir']}")

Custom Branding

from aitoolmaker import AIToolMaker

maker = AIToolMaker(api_key="YOUR_KEY", model="gemini-2.0-flash")

result = maker.create_tool(
    tool_type="data_analyzer",
    output="streamlit",
    name="DataMaster Pro",
    logo="./my_logo.png",
    output_dir="./my_data_tool"
)

Generate Website

from aitoolmaker import AIToolMaker

maker = AIToolMaker(api_key="YOUR_KEY", model="gemini-2.0-flash")

result = maker.create_tool(
    tool_type="sql_generator",
    output="website",
    name="SQL Wizard",
    output_dir="./sql_website"
)

CLI Usage

List Available Tools

aitoolmaker list

Get Tool Information

aitoolmaker info chatbot

Create Tool with Options

aitoolmaker create \
  --tool document_summarizer \
  --api-key YOUR_KEY \
  --model gemini-2.0-flash \
  --name "DocSummarizer Pro" \
  --logo ./logo.png \
  --output-dir ./my_summarizer

Generated Output Structure

Streamlit App

generated_chatbot/
├── app.py              # Main Streamlit application
├── api_key.py          # API key configuration
├── requirements.txt    # Python dependencies
├── README.md           # Usage instructions
└── utils.py            # Utility functions (if needed)

Website

generated_chatbot_website/
├── index.html          # Main HTML file
├── css/
│   └── style.css       # Stylesheet
├── js/
│   └── app.js          # JavaScript logic
├── assets/
│   └── logo.png        # Logo image
└── README.md           # Deployment instructions

Use Cases

• Rapid Prototyping: Quickly create AI tool prototypes
• Client Demos: Generate custom-branded demos
• Internal Tools: Build internal AI tools for teams
• Learning: Study production-ready AI code
• Deployment: Export portable, deployment-ready code

Contributing

Contributions are welcome! To add a new tool:

1. Create a template file in core/templates/your_tool.py
2. Define the template constant
3. Register it in core/templates/__init__.py
4. Update SUPPORTED_TOOLS in __init__.py

License

MIT License - See LICENSE file for details

Acknowledgments

• Built with Streamlit
• Powered by Google Gemini

Support

• Issues: GitHub Issues
• Email: [e-mail]

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Made by the Moustafa Mohamed

• Linkedin Moustafa Mohamed
• Github MoustafaMohamed01
• Kaggle moustafamohamed01