[Python Automation] One-Click Project Setup Tool v1.0

Product Theme Product name: [Python Automation] One-Click Project Setup Tool v1.0 Problem it solves: after cloning a project from GitHub, you still have to manually parse dependencies, build a virtual environment, generate config files, and initialize the database — one tedious step at a time. Approach: 1. Parse the README.md of an already-cloned project with an LLM (OpenAI-compatible API) to auto-extract required dependencies and environment variables. 2. Auto-detect poetry vs pip based on whether poetry.lock exists, generate pyproject.toml or requirements.txt, and install packages in one shot. 3. Run the database init script (a SQL file) automatically so the app is ready to launch. This tool cuts out the repetitive "getting ready to code" work and gives you a repeatable setup process every time you start on a new project. Suggested Price $13 Sales Copy From clone to coding, instantly. Fully automated project setup. Ever cloned a repo from GitHub and then lost 20 minutes to environment setup, dependency checks, and config files before you could write a single line of code? Stop reading READMEs line by line and typing out .env files by hand. This tool takes you from "just cloned" to "ready to code" automatically. What it does * Smart README parsing: an LLM reads your README.md and pulls out the exact environment variables and dependencies you need. * One-shot environment setup: generates pyproject.toml or requirements.txt and installs everything for you (auto-detects poetry when a poetry.lock is present). * Automatic database initialization: skips the manual SQL commands and gets your database ready to go. How to use it 1. Set up: put your LLM API key in an environment variable and place the target project's README.md next to the script. 2. Run: execute the script — parsing, environment setup, and database initialization all happen automatically. 3. Start coding: the moment you see the success message, you're ready to work. Requirements - OS: Windows / macOS / Linux (WSL2 supported) - Python: 3.10+ - Required libraries: pip install rich requests python-dotenv - External tools: - sqlite3 CLI (only required if you use the database-init feature; preinstalled on macOS, install from the official site on Windows, sudo apt install sqlite3 on Ubuntu/WSL2) - poetry (only required for projects that already use a poetry.lock; pip install poetry) Environment Variables | Variable | Required | Description | |---|---|---| | LLM_API_KEY | Required | Your LLM API key (defaults to an OpenAI-compatible API) | | LLM_API_URL | Optional | LLM API endpoint (default: OpenAI Chat Completions API; can be pointed at Azure OpenAI or a local LLM server) | | LLM_MODEL | Optional | Model name to use (default: gpt-4o-mini) | | DATABASE_FILE | Optional | Path to the SQL file used for database initialization (default: init_db.sql) | Why it's worth it Every new project you join costs you setup time you'll never get back. This tool turns that repeated overhead into a single command, so the time you save on your very first few projects already pays for it.

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