llm-tool-maker 0.1.0

An intelligent tool-making package that leverages LLMs to analyze projects and generate tools

Tool Maker Package

An intelligent tool-making package that leverages LLMs to analyze projects and generate tools.

Overview

Tool Maker is a Python package that:

• Analyzes projects to understand their structure and capabilities
• Uses LLMs to formulate intelligent prompts and generate tools
• Can be integrated into Flask applications or used standalone
• Provides a CLI for easy command-line usage

Features

• Project Analysis: Automatically scans and analyzes project structure
• LLM Integration: Supports multiple LLM providers (OpenAI, Anthropic, local models)
• Tool Generation: Creates appropriate tools based on project capabilities
• Flask Integration: Easy integration with Flask applications
• CLI Interface: Command-line tool for quick usage

Installation

Using uv (Recommended)

# Install globally
uv tool install llm-tool-maker

# Or add to a project
uv add llm-tool-maker

From Source

git clone https://github.com/codewithwest/project_tool-maker.git
cd tool-maker
uv sync
uv run tool-maker --help

Quick Start

Standalone Usage

from tool_maker import ToolMaker

# Initialize with your LLM provider
tm = ToolMaker(
    llm_provider="openai",
    api_key="your-api-key"
)

# Analyze a project
project_info = tm.analyze_project("/path/to/project")

# Create and execute a tool
result = tm.create_and_execute_tool("Create a function to parse CSV files")
print(result)

Flask Integration

from flask import Flask, request, jsonify
from tool_maker.flask import ToolMakerExtension

app = Flask(__name__)

# Initialize Tool Maker
tm = ToolMakerExtension(
    app,
    llm_provider="openai",
    api_key="your-api-key"
)

@app.route('/analyze', methods=['POST'])
def analyze():
    project_path = request.json.get('project_path')
    return jsonify(tm.analyze_project(project_path))

@app.route('/tools', methods=['POST'])
def create_tool():
    query = request.json.get('query')
    return jsonify(tm.create_and_execute_tool(query))

Project Structure

tool_maker/
├── analyzer/      # Project analysis module
├── llm/          # LLM integration module
├── tool/         # Tool generation and execution
├── flask/        # Flask integration
└── cli/          # Command-line interface

Configuration

LLM Providers

Tool Maker supports multiple LLM providers:

# OpenAI
tm = ToolMaker(llm_provider="openai", api_key="sk-...")

# Anthropic (Claude)
tm = ToolMaker(llm_provider="anthropic", api_key="sk-...")

# Local LLM (e.g., Ollama)
tm = ToolMaker(
    llm_provider="ollama",
    base_url="http://localhost:11434",
    model="llama2"
)

Development

# Set up development environment
uv sync
uv run pytest

# Run linter
uv run ruff check .

# Format code
uv run black .

Examples

See the examples/ directory for more detailed examples:

• basic_usage.py - Standalone usage
• flask_integration.py - Flask integration
• custom_analyzer.py - Custom project analysis

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

1. Fork the repository
2. Create a feature branch (git checkout -b feature/amazing-feature)
3. Commit your changes (git commit -m 'Add some amazing feature')
4. Push to the branch (git push origin feature/amazing-feature)
5. Open a Pull Request

License

This project is licensed under the MIT License - see the LICENSE file for details.

Acknowledgments

• Built with uv for fast Python package management
• Inspired by AI-powered code generation tools