Repository: FujiwaraChoki/MoneyPrinterV2
Branch: main
Commit: aa1d8f645022
Files: 34
Total size: 163.3 KB
Directory structure:
gitextract_fa8ip_7i/
├── .github/
│ └── FUNDING.yml
├── .gitignore
├── .python-version
├── AGENTS.md
├── CLAUDE.md
├── CODE_OF_CONDUCT.md
├── CONTRIBUTING.md
├── LICENSE
├── README.md
├── assets/
│ └── banner.txt
├── config.example.json
├── docs/
│ ├── AffiliateMarketing.md
│ ├── Configuration.md
│ ├── Roadmap.md
│ ├── TwitterBot.md
│ └── YouTube.md
├── requirements.txt
├── scripts/
│ ├── preflight_local.py
│ ├── setup_local.sh
│ └── upload_video.sh
└── src/
├── art.py
├── cache.py
├── classes/
│ ├── AFM.py
│ ├── Outreach.py
│ ├── Tts.py
│ ├── Twitter.py
│ └── YouTube.py
├── config.py
├── constants.py
├── cron.py
├── llm_provider.py
├── main.py
├── status.py
└── utils.py
================================================
FILE CONTENTS
================================================
================================================
FILE: .github/FUNDING.yml
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# These are supported funding model platforms
github: [FujiwaraChoki]
================================================
FILE: .gitignore
================================================
__pycache__
config.json
.mp/
venv/
Songs/
google-maps-scraper-0.9.7/
niche.txt
*.exe
auto.sh
.DS_Store
================================================
FILE: .python-version
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3.12
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FILE: AGENTS.md
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# Repository Guidelines
## Project Structure & Module Organization
- `src/` contains the application code. Use `src/main.py` as the interactive entrypoint.
- `src/classes/` holds provider-specific components (for example `YouTube.py`, `Twitter.py`, `Tts.py`, `AFM.py`, `Outreach.py`).
- Shared utilities and configuration live in modules like `src/config.py`, `src/utils.py`, `src/cache.py`, and `src/constants.py`.
- `scripts/` contains helper workflows such as setup, preflight checks, and upload helpers.
- `docs/` contains feature documentation; `assets/` and `fonts/` contain static resources.
## Build, Test, and Development Commands
- `bash scripts/setup_local.sh`: bootstrap local development (creates `venv`, installs deps, seeds `config.json`, runs preflight).
- `source venv/bin/activate && pip install -r requirements.txt`: manual dependency install/update.
- `python3 scripts/preflight_local.py`: validate local provider/config readiness before running tasks.
- `python3 src/main.py`: start the CLI app.
- `bash scripts/upload_video.sh`: run direct script-based upload flow from repo root.
## Coding Style & Naming Conventions
- Target Python 3.12 (project requirement in `README.md`).
- Use 4-space indentation and follow existing Python conventions:
- `snake_case` for functions/variables
- `PascalCase` for classes
- `UPPER_SNAKE_CASE` for constants
- Keep new business logic in focused modules under `src/`; keep provider/integration code in `src/classes/`.
- Prefer small, explicit functions and preserve existing CLI-first behavior.
## Testing Guidelines
- There is currently no enforced automated test suite or coverage threshold.
- Minimum validation for changes:
- Run `python3 scripts/preflight_local.py`
- Smoke-test impacted flows via `python3 src/main.py`
- When adding tests, place them in a top-level `tests/` directory with names like `test_<module>.py`.
## Commit & Pull Request Guidelines
- Follow the existing commit style: imperative summaries like `Fix ...`, `Update ...`, optionally with issue refs (for example `(#128)`).
- Open PRs against `main`.
- Link each PR to an issue, keep scope to one feature/fix, and use a clear title + description.
- Mark not-ready PRs with `WIP` and remove it when ready for review.
## Security & Configuration Tips
- Treat `config.json` as environment-specific; do not commit real API keys or private profile paths.
- Start from `config.example.json` and prefer environment variables where supported (for example `GEMINI_API_KEY`).
================================================
FILE: CLAUDE.md
================================================
# CLAUDE.md
This file provides guidance to Claude Code (claude.ai/code) when working with code in this repository.
## Project Overview
MoneyPrinterV2 (MPV2) is a Python 3.12 CLI tool that automates four online workflows:
1. **YouTube Shorts** — generate video (LLM script → TTS → images → MoviePy composite) and upload via Selenium
2. **Twitter/X Bot** — generate and post tweets via Selenium
3. **Affiliate Marketing** — scrape Amazon product info, generate pitch, share on Twitter
4. **Local Business Outreach** — scrape Google Maps (Go binary), extract emails, send cold outreach via SMTP
There is no web UI, no REST API, no test suite, no CI, and no linting config.
## Running the Application
```bash
# First-time setup
cp config.example.json config.json # then fill in values
python -m venv venv && source venv/bin/activate
pip install -r requirements.txt
# macOS quick setup (auto-configures Ollama, ImageMagick, Firefox profile)
bash scripts/setup_local.sh
# Preflight check (validates services are reachable)
python scripts/preflight_local.py
# Run
python src/main.py
```
The app **must** be run from the project root. `python src/main.py` adds `src/` to `sys.path`, so all imports use bare module names (e.g., `from config import *`, not `from src.config import *`).
## Architecture
### Entry Points
- `src/main.py` — interactive menu loop (primary)
- `src/cron.py` — headless runner invoked by the scheduler as a subprocess: `python src/cron.py <platform> <account_uuid>`
### Provider Pattern
Two service categories use a string-based dispatch pattern configured in `config.json`:
| Category | Config key | Options |
|---|---|---|
| LLM | `ollama_model` | Ollama (via `ollama` Python SDK). If empty, user picks from available models at startup. |
| Image gen | — | `nanobanana2` (Gemini image API) |
| STT | `stt_provider` | `local_whisper`, `third_party_assemblyai` |
LLM always uses the local Ollama server. Image generation always uses Nano Banana 2.
### Key Modules
- **`src/llm_provider.py`** — unified `generate_text(prompt)` function using the Ollama Python SDK
- **`src/config.py`** — 30+ getter functions, each re-reads `config.json` on every call (no caching). `ROOT_DIR` = project root, computed as `os.path.dirname(sys.path[0])`
- **`src/cache.py`** — JSON file persistence in `.mp/` directory (accounts, videos, posts, products)
- **`src/constants.py`** — menu strings, Selenium selectors (YouTube Studio, X.com, Amazon)
- **`src/classes/YouTube.py`** — most complex class; full pipeline: topic → script → metadata → image prompts → images → TTS → subtitles → MoviePy combine → Selenium upload
- **`src/classes/Twitter.py`** — Selenium automation against x.com
- **`src/classes/AFM.py`** — Amazon scraping + LLM pitch generation
- **`src/classes/Outreach.py`** — Google Maps scraper (requires Go) + email sending via yagmail
- **`src/classes/Tts.py`** — KittenTTS wrapper
### Data Storage
All persistent state lives in `.mp/` at the project root as JSON files (`youtube.json`, `twitter.json`, `afm.json`). This directory also serves as scratch space for temporary WAV, PNG, SRT, and MP4 files — non-JSON files are cleaned on each run by `rem_temp_files()`.
### Browser Automation
Selenium uses pre-authenticated Firefox profiles (never handles login). The profile path is stored per-account in the cache JSON and also in `config.json` as a default.
### CRON Scheduling
Uses Python's `schedule` library (in-process, not OS cron). The scheduled job spawns `subprocess.run(["python", "src/cron.py", platform, account_id])`.
## Configuration
All config lives in `config.json` at the project root. See `config.example.json` for the full template and `docs/Configuration.md` for reference. Key external dependencies to configure:
- **ImageMagick** — required for MoviePy subtitle rendering (`imagemagick_path`)
- **Firefox profile** — must be pre-logged-in to target platforms (`firefox_profile`)
- **Ollama** — for LLM text generation (via `ollama` Python SDK)
- **Nano Banana 2** — for image generation (Gemini image API)
- **Go** — only needed for Outreach (Google Maps scraper)
## Contributing
PRs go against `main`. One feature/fix per PR. Open an issue first. Use `WIP` label for in-progress PRs.
================================================
FILE: CODE_OF_CONDUCT.md
================================================
# Contributor Code of Conduct
Our values guide us in our day-to-day interactions and decision-making. Our open source projects are no exception. Trust, respect, collaboration and transparency are core values we believe should live and breathe within our projects. Our community welcomes participants from around the world with different experiences, unique perspectives, and great ideas to share.
## Our Pledge
In the interest of fostering an open and welcoming environment, we as contributors and maintainers pledge to making participation in our project and our community a harassment-free experience for everyone, regardless of age, body size, disability, ethnicity, sex characteristics, gender identity and expression, level of experience, education, socio-economic status, nationality, personal appearance, race, religion, or sexual identity and orientation.
## Our Standards
Examples of behavior that contributes to creating a positive environment include:
- Using welcoming and inclusive language
- Being respectful of differing viewpoints and experiences
- Gracefully accepting constructive criticism
- Attempting collaboration before conflict
- Focusing on what is best for the community
- Showing empathy towards other community members
Examples of unacceptable behavior by participants include:
- Violence, threats of violence, or inciting others to commit self-harm
- The use of sexualized language or imagery and unwelcome sexual attention or advances
- Trolling, intentionally spreading misinformation, insulting/derogatory comments, and personal or political attacks
- Public or private harassment
- Publishing others' private information, such as a physical or electronic address, without explicit permission
- Abuse of the reporting process to intentionally harass or exclude others
- Advocating for, or encouraging, any of the above behavior
- Other conduct which could reasonably be considered inappropriate in a professional setting
## Our Responsibilities
Project maintainers are responsible for clarifying the standards of acceptable behavior and are expected to take appropriate and fair corrective action in response to any instances of unacceptable behavior.
Project maintainers have the right and responsibility to remove, edit, or reject comments, commits, code, wiki edits, issues, and other contributions that are not aligned to this Code of Conduct, or to ban temporarily or permanently any contributor for other behaviors that they deem inappropriate, threatening, offensive, or harmful.
## Enforcement
Instances of abusive, harassing, or otherwise unacceptable behavior may be reported by contacting us anonymously through [our discord](https://dsc.gg/fuji-community). All complaints will be reviewed and investigated and will result in a response that is deemed necessary and appropriate to the circumstances. The project team is obligated to maintain confidentiality with regard to the reporter of an incident.
Project maintainers who do not follow or enforce the Code of Conduct in good faith may face temporary or permanent repercussions as determined by other members of the project's leadership.
If you are unsure whether an incident is a violation, or whether the space where the incident took place is covered by our Code of Conduct, **we encourage you to still report it**. We would prefer to have a few extra reports where we decide to take no action, than to leave an incident go unnoticed and unresolved that may result in an individual or group to feel like they can no longer participate in the community. Reports deemed as not a violation will also allow us to improve our Code of Conduct and processes surrounding it. If you witness a dangerous situation or someone in distress, we encourage you to report even if you are only an observer.
## Attribution
This Code of Conduct is adapted from the [Contributor Covenant](https://www.contributor-covenant.org/), [version 1.4](https://www.contributor-covenant.org/version/1/4/code-of-conduct.html).
================================================
FILE: CONTRIBUTING.md
================================================
# Contributing
MoneyPrinterV2 is an open source project and we encourage contributions. However, we ask that you follow these guidelines when opening a Pull Request (PR):
1. **The `main` branch is the default branch.** All PRs should be opened against the `main` branch.
2. **All PRs should be opened against an issue.** If there is no issue for your PR, please open one first and then open a PR against it.
3. **All PRs should be opened with a clear title and description.** The title should be a short description of the changes and the description should be a more detailed explanation of the changes.
4. **Only one feature or bug fix per PR.** If you have multiple changes, please open multiple PRs.
5. **All PRs should be opened with the `WIP` label if they are not ready to be merged.** If your PR is not ready to be merged, please open it with the `WIP` label and remove the label when it is ready to be merged.
If you have any questions about contributing, please open an issue and ask. We are happy to help you get started.
# Code of Conduct
We have adopted a Code of Conduct that we expect project participants to adhere to. Please read [the full text](CODE_OF_CONDUCT.md) so that you can understand what actions will and will not be tolerated.
================================================
FILE: LICENSE
================================================
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How to Apply These Terms to Your New Programs
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<https://www.gnu.org/licenses/>.
================================================
FILE: README.md
================================================
# MoneyPrinter V2
> ♥︎ **Sponsor**: The Best AI Chat App: [shiori.ai](https://www.shiori.ai)
---
> 𝕏 Also, follow me on X: [@DevBySami](https://x.com/DevBySami).
[](https://github.com/FujiwaraChoki/MoneyPrinterV2)
[](https://www.buymeacoffee.com/fujicodes)
[](https://github.com/FujiwaraChoki/MoneyPrinterV2/blob/main/LICENSE)
[](https://github.com/FujiwaraChoki/MoneyPrinterV2/issues)
[](https://github.com/FujiwaraChoki/MoneyPrinterV2/stargazers)
[](https://dsc.gg/fuji-community)
An Application that automates the process of making money online.
MPV2 (MoneyPrinter Version 2) is, as the name suggests, the second version of the MoneyPrinter project. It is a complete rewrite of the original project, with a focus on a wider range of features and a more modular architecture.
> **Note:** MPV2 needs Python 3.12 to function effectively.
> Watch the YouTube video [here](https://youtu.be/wAZ_ZSuIqfk)
## Features
- [x] Twitter Bot (with CRON Jobs => `scheduler`)
- [x] YouTube Shorts Automater (with CRON Jobs => `scheduler`)
- [x] Affiliate Marketing (Amazon + Twitter)
- [x] Find local businesses & cold outreach
## Versions
MoneyPrinter has different versions for multiple languages developed by the community for the community. Here are some known versions:
- Chinese: [MoneyPrinterTurbo](https://github.com/harry0703/MoneyPrinterTurbo)
If you would like to submit your own version/fork of MoneyPrinter, please open an issue describing the changes you made to the fork.
## Installation
> ⚠️ If you are planning to reach out to scraped businesses per E-Mail, please first install the [Go Programming Language](https://golang.org/).
```bash
git clone https://github.com/FujiwaraChoki/MoneyPrinterV2.git
cd MoneyPrinterV2
# Copy Example Configuration and fill out values in config.json
cp config.example.json config.json
# Create a virtual environment
python -m venv venv
# Activate the virtual environment - Windows
.\venv\Scripts\activate
# Activate the virtual environment - Unix
source venv/bin/activate
# Install the requirements
pip install -r requirements.txt
```
## Usage
```bash
# Run the application
python src/main.py
```
## Documentation
All relevant document can be found [here](docs/).
## Scripts
For easier usage, there are some scripts in the `scripts` directory, that can be used to directly access the core functionality of MPV2, without the need of user interaction.
All scripts need to be run from the root directory of the project, e.g. `bash scripts/upload_video.sh`.
## Contributing
Please read [CONTRIBUTING.md](CONTRIBUTING.md) for details on our code of conduct, and the process for submitting pull requests to us. Check out [docs/Roadmap.md](docs/Roadmap.md) for a list of features that need to be implemented.
## Code of Conduct
Please read [CODE_OF_CONDUCT.md](CODE_OF_CONDUCT.md) for details on our code of conduct, and the process for submitting pull requests to us.
## License
MoneyPrinterV2 is licensed under `Affero General Public License v3.0`. See [LICENSE](LICENSE) for more information.
## Acknowledgments
- [KittenTTS](https://github.com/KittenML/KittenTTS)
- [gpt4free](https://github.com/xtekky/gpt4free)
## Disclaimer
This project is for educational purposes only. The author will not be responsible for any misuse of the information provided. All the information on this website is published in good faith and for general information purpose only. The author does not make any warranties about the completeness, reliability, and accuracy of this information. Any action you take upon the information you find on this website (FujiwaraChoki/MoneyPrinterV2), is strictly at your own risk. The author will not be liable for any losses and/or damages in connection with the use of our website.
================================================
FILE: assets/banner.txt
================================================
__ __ _____ _ _ __ _____
| \/ | | __ \ (_) | | \ \ / /__ \
| \ / | ___ _ __ ___ _ _| |__) | __ _ _ __ | |_ ___ _ __ \ \ / / ) |
| |\/| |/ _ \| '_ \ / _ \ | | | ___/ '__| | '_ \| __/ _ \ '__| \ \/ / / /
| | | | (_) | | | | __/ |_| | | | | | | | | | || __/ | \ / / /_
|_| |_|\___/|_| |_|\___|\__, |_| |_| |_|_| |_|\__\___|_| \/ |____|
__/ |
|___/
================================================
FILE: config.example.json
================================================
{
"verbose": true,
"firefox_profile": "",
"headless": false,
"ollama_base_url": "http://127.0.0.1:11434",
"ollama_model": "",
"twitter_language": "English",
"nanobanana2_api_base_url": "https://generativelanguage.googleapis.com/v1beta",
"nanobanana2_api_key": "",
"nanobanana2_model": "gemini-3.1-flash-image-preview",
"nanobanana2_aspect_ratio": "9:16",
"threads": 2,
"zip_url": "",
"is_for_kids": false,
"google_maps_scraper": "https://github.com/gosom/google-maps-scraper/archive/refs/tags/v0.9.7.zip",
"email": {
"smtp_server": "smtp.gmail.com",
"smtp_port": 587,
"username": "",
"password": ""
},
"google_maps_scraper_niche": "",
"scraper_timeout": 300,
"outreach_message_subject": "I have a question...",
"outreach_message_body_file": "outreach_message.html",
"stt_provider": "local_whisper",
"whisper_model": "base",
"whisper_device": "auto",
"whisper_compute_type": "int8",
"assembly_ai_api_key": "",
"tts_voice": "Jasper",
"font": "bold_font.ttf",
"imagemagick_path": "Path to magick.exe or on linux/macOS just /usr/bin/convert",
"script_sentence_length": 4
}
================================================
FILE: docs/AffiliateMarketing.md
================================================
# AFM
This class is responsible for the Affiliate Marketing part of MPV2. It uses Ollama (as all other classes) as its way to utilize the power of LLMs, in this case, to generate tweets, based on information about an **Amazon Product**. MPV2 will scrape the page of the product, and save the **product title**, and **product features**, thus having enough information to be able to create a pitch for the product, and post it on Twitter.
## Relevant Configuration
In your `config.json`, you need the following attributes filled out, so that the bot can function correctly.
```json
{
"firefox_profile": "The path to your Firefox profile (used to log in to Twitter)",
"headless": true,
"ollama_base_url": "http://127.0.0.1:11434",
"threads": 4
}
```
## Roadmap
Here are some features that are planned for the future:
- [ ] Scrape more information about the product, to be able to create a more detailed pitch.
- [ ] Join online communities related to the product, and post a pitch (with a link to the product) there.
- [ ] Reply to tweets that are related to the product, with a pitch for the product.
================================================
FILE: docs/Configuration.md
================================================
# Configuration
All your configurations will be in a file in the root directory, called `config.json`, which is a copy of `config.example.json`. You can change the values in `config.json` to your liking.
## Values
- `verbose`: `boolean` - If `true`, the application will print out more information.
- `firefox_profile`: `string` - The path to your Firefox profile. This is used to use your Social Media Accounts without having to log in every time you run the application.
- `headless`: `boolean` - If `true`, the application will run in headless mode. This means that the browser will not be visible.
- `ollama_base_url`: `string` - Base URL of your local Ollama server (default: `http://127.0.0.1:11434`).
- `ollama_model`: `string` - Ollama model to use for text generation (e.g. `llama3.2:3b`). If empty, the app queries Ollama at startup and lets you pick from the available models interactively.
- `twitter_language`: `string` - The language that will be used to generate & post tweets.
- `nanobanana2_api_base_url`: `string` - Nano Banana 2 API base URL (default: `https://generativelanguage.googleapis.com/v1beta`).
- `nanobanana2_api_key`: `string` - API key for Nano Banana 2 (Gemini image API). If empty, MPV2 falls back to environment variable `GEMINI_API_KEY`.
- `nanobanana2_model`: `string` - Nano Banana 2 model name (default: `gemini-3.1-flash-image-preview`).
- `nanobanana2_aspect_ratio`: `string` - Aspect ratio for generated images (default: `9:16`).
- `threads`: `number` - The amount of threads that will be used to execute operations, e.g. writing to a file using MoviePy.
- `is_for_kids`: `boolean` - If `true`, the application will upload the video to YouTube Shorts as a video for kids.
- `google_maps_scraper`: `string` - The URL to the Google Maps scraper. This will be used to scrape Google Maps for local businesses. It is recommended to use the default value.
- `zip_url`: `string` - The URL to the ZIP file that contains the to be used Songs for the YouTube Shorts Automater.
- `email`: `object`:
- `smtp_server`: `string` - Your SMTP server.
- `smtp_port`: `number` - The port of your SMTP server.
- `username`: `string` - Your email address.
- `password`: `string` - Your email password.
- `google_maps_scraper_niche`: `string` - The niche you want to scrape Google Maps for.
- `scraper_timeout`: `number` - The timeout for the Google Maps scraper.
- `outreach_message_subject`: `string` - The subject of your outreach message. `{{COMPANY_NAME}}` will be replaced with the company name.
- `outreach_message_body_file`: `string` - The file that contains the body of your outreach message, should be HTML. `{{COMPANY_NAME}}` will be replaced with the company name.
- `stt_provider`: `string` - Provider for subtitle transcription. Default is `local_whisper`. Options:
* `local_whisper`
* `third_party_assemblyai`
- `whisper_model`: `string` - Whisper model for local transcription (for example `base`, `small`, `medium`, `large-v3`).
- `whisper_device`: `string` - Device for local Whisper (`auto`, `cpu`, `cuda`).
- `whisper_compute_type`: `string` - Compute type for local Whisper (`int8`, `float16`, etc.).
- `assembly_ai_api_key`: `string` - Your Assembly AI API key. Get yours from [here](https://www.assemblyai.com/app/).
- `tts_voice`: `string` - Voice for KittenTTS text-to-speech. Default is `Jasper`. Options: `Bella`, `Jasper`, `Luna`, `Bruno`, `Rosie`, `Hugo`, `Kiki`, `Leo`.
- `font`: `string` - The font that will be used to generate images. This should be a `.ttf` file in the `fonts/` directory.
- `imagemagick_path`: `string` - The path to the ImageMagick binary. This is used by MoviePy to manipulate images. Install ImageMagick from [here](https://imagemagick.org/script/download.php) and set the path to the `magick.exe` on Windows, or on Linux/MacOS the path to `convert` (usually /usr/bin/convert).
- `script_sentence_length`: `number` - The number of sentences in the generated video script (default: `4`).
## Example
```json
{
"verbose": true,
"firefox_profile": "",
"headless": false,
"ollama_base_url": "http://127.0.0.1:11434",
"ollama_model": "",
"twitter_language": "English",
"nanobanana2_api_base_url": "https://generativelanguage.googleapis.com/v1beta",
"nanobanana2_api_key": "",
"nanobanana2_model": "gemini-3.1-flash-image-preview",
"nanobanana2_aspect_ratio": "9:16",
"threads": 2,
"zip_url": "",
"is_for_kids": false,
"google_maps_scraper": "https://github.com/gosom/google-maps-scraper/archive/refs/tags/v0.9.7.zip",
"email": {
"smtp_server": "smtp.gmail.com",
"smtp_port": 587,
"username": "",
"password": ""
},
"google_maps_scraper_niche": "",
"scraper_timeout": 300,
"outreach_message_subject": "I have a question...",
"outreach_message_body_file": "outreach_message.html",
"stt_provider": "local_whisper",
"whisper_model": "base",
"whisper_device": "auto",
"whisper_compute_type": "int8",
"assembly_ai_api_key": "",
"tts_voice": "Jasper",
"font": "bold_font.ttf",
"imagemagick_path": "Path to magick.exe or on linux/macOS just /usr/bin/convert",
"script_sentence_length": 4
}
```
## Environment Variable Fallbacks
- `GEMINI_API_KEY`: used when `nanobanana2_api_key` is empty.
Example:
```bash
export GEMINI_API_KEY="your_api_key_here"
```
================================================
FILE: docs/Roadmap.md
================================================
# MPV2 Roadmap
This document outlines the features that need to be implemented in MPV2.
## Features
- [ ] Automated Cold Calling
- [ ] Item Flipping (such as sneakers)
- [ ] Create a Short based on long-form content
- [ ] Subtitles for Shorts
## Adding a new feature
If you want to add a new feature to MPV2, please create a new issue and label it with `enhancement`. After that, create a new branch and start working on the feature. Once you are done, create a pull request and assign it to the issue you created earlier.
## Contributing
Please read [CONTRIBUTING.md](CONTRIBUTING.md) for details on our code of conduct, and the process for submitting pull requests to us.
================================================
FILE: docs/TwitterBot.md
================================================
# Twitter Bot
This bot is designed to automate the process of growing a Twitter account. Once you created a new account, provide the path to the Firefox Profile and the bot will start posting tweets based on the subject you provided during the account creation.
## Relevant Configuration
In your `config.json`, you need the following attributes filled out, so that the bot can function correctly.
```json
{
"twitter_language": "Any Language, formatting doesn't matter",
"headless": true,
"llm": "The Large Language Model you want to use, check Configuration.md for more information",
}
```
================================================
FILE: docs/YouTube.md
================================================
# YouTube Shorts Automater
MPV2 uses a similar implementation of V1 (see [MPV1](https://github.com/FujiwaraChoki/MoneyPrinter)), to generate Video-Files and upload them to YouTube Shorts.
In contrast to V1, V2 uses AI generated images as the visuals for the video, instead of using stock footage. This makes the videos more unique and less likely to be flagged by YouTube. V2 also supports music right from the get-go.
## Relevant Configuration
In your `config.json`, you need the following attributes filled out, so that the bot can function correctly.
```json
{
"firefox_profile": "The path to your Firefox profile (used to log in to YouTube)",
"headless": true,
"llm": "The Large Language Model you want to use to generate the video script.",
"image_model": "What AI Model you want to use to generate images.",
"threads": 4,
"is_for_kids": true
}
```
## Roadmap
Here are some features that are planned for the future:
- [ ] Subtitles (using either AssemblyAI or locally assembling them)
================================================
FILE: requirements.txt
================================================
wheel
termcolor
schedule
kittentts @ https://github.com/KittenML/KittenTTS/releases/download/0.8.1/kittentts-0.8.1-py3-none-any.whl
soundfile
prettytable
webdriver_manager
selenium_firefox
selenium
ollama
moviepy
Pillow>=10.0.0
yagmail
assemblyai
faster-whisper
srt_equalizer
undetected_chromedriver
platformdirs
================================================
FILE: scripts/preflight_local.py
================================================
#!/usr/bin/env python3
import json
import os
import sys
from typing import Tuple
import requests
ROOT_DIR = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
CONFIG_PATH = os.path.join(ROOT_DIR, "config.json")
def ok(msg: str) -> None:
print(f"[OK] {msg}")
def warn(msg: str) -> None:
print(f"[WARN] {msg}")
def fail(msg: str) -> None:
print(f"[FAIL] {msg}")
def check_url(url: str, timeout: int = 3) -> Tuple[bool, str]:
try:
response = requests.get(url, timeout=timeout)
return True, f"HTTP {response.status_code}"
except Exception as exc:
return False, str(exc)
def main() -> int:
if not os.path.exists(CONFIG_PATH):
fail(f"Missing config file: {CONFIG_PATH}")
return 1
with open(CONFIG_PATH, "r", encoding="utf-8") as f:
cfg = json.load(f)
failures = 0
stt_provider = str(cfg.get("stt_provider", "local_whisper")).lower()
ok(f"stt_provider={stt_provider}")
imagemagick_path = cfg.get("imagemagick_path", "")
if imagemagick_path and os.path.exists(imagemagick_path):
ok(f"imagemagick_path exists: {imagemagick_path}")
else:
warn(
"imagemagick_path is not set to a valid executable path. "
"MoviePy subtitle rendering may fail."
)
firefox_profile = cfg.get("firefox_profile", "")
if firefox_profile:
if os.path.isdir(firefox_profile):
ok(f"firefox_profile exists: {firefox_profile}")
else:
warn(f"firefox_profile does not exist: {firefox_profile}")
else:
warn("firefox_profile is empty. Twitter/YouTube automation requires this.")
# Ollama (LLM)
base = str(cfg.get("ollama_base_url", "http://127.0.0.1:11434")).rstrip("/")
reachable, detail = check_url(f"{base}/api/tags")
if not reachable:
fail(f"Ollama is not reachable at {base}: {detail}")
failures += 1
else:
ok(f"Ollama reachable at {base}")
try:
tags = requests.get(f"{base}/api/tags", timeout=5).json()
models = [m.get("name") for m in tags.get("models", [])]
if models:
ok(f"Ollama models available: {', '.join(models[:10])}")
else:
warn("No models found on Ollama. Pull a model first (e.g. 'ollama pull llama3.2:3b').")
except Exception as exc:
warn(f"Could not validate Ollama model list: {exc}")
# Nano Banana 2 (image generation)
api_key = cfg.get("nanobanana2_api_key", "") or os.environ.get("GEMINI_API_KEY", "")
nb2_base = str(
cfg.get(
"nanobanana2_api_base_url",
"https://generativelanguage.googleapis.com/v1beta",
)
).rstrip("/")
if api_key:
ok("nanobanana2_api_key is set")
else:
fail("nanobanana2_api_key is empty (and GEMINI_API_KEY is not set)")
failures += 1
reachable, detail = check_url(nb2_base, timeout=8)
if not reachable:
warn(f"Nano Banana 2 base URL could not be reached: {detail}")
else:
ok(f"Nano Banana 2 base URL reachable: {nb2_base}")
if stt_provider == "local_whisper":
try:
import faster_whisper # noqa: F401
ok("faster-whisper is installed")
except Exception as exc:
fail(f"faster-whisper is not importable: {exc}")
failures += 1
if failures:
print("")
print(f"Preflight completed with {failures} blocking issue(s).")
return 1
print("")
print("Preflight passed. Local setup looks ready.")
return 0
if __name__ == "__main__":
sys.exit(main())
================================================
FILE: scripts/setup_local.sh
================================================
#!/usr/bin/env bash
set -euo pipefail
ROOT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")/.." && pwd)"
cd "$ROOT_DIR"
echo "[setup] Root: $ROOT_DIR"
if [[ ! -f "config.json" ]]; then
cp config.example.json config.json
echo "[setup] Created config.json from config.example.json"
fi
PYTHON_BIN="${ROOT_DIR}/venv/bin/python"
if [[ ! -x "$PYTHON_BIN" ]]; then
python3 -m venv venv
echo "[setup] Created virtual environment at venv/"
fi
"$PYTHON_BIN" -m ensurepip --upgrade >/dev/null 2>&1 || true
"$PYTHON_BIN" -m pip install --upgrade pip setuptools wheel
"$PYTHON_BIN" -m pip install -r requirements.txt
MAGICK_PATH="$(command -v magick || true)"
if [[ -z "$MAGICK_PATH" ]]; then
MAGICK_PATH="$(command -v convert || true)"
fi
FIREFOX_PROFILE=""
if [[ -d "$HOME/Library/Application Support/Firefox/Profiles" ]]; then
FIREFOX_PROFILE="$(find "$HOME/Library/Application Support/Firefox/Profiles" -maxdepth 1 -type d -name "*default-release*" | head -n 1 || true)"
if [[ -z "$FIREFOX_PROFILE" ]]; then
FIREFOX_PROFILE="$(find "$HOME/Library/Application Support/Firefox/Profiles" -maxdepth 1 -type d | tail -n +2 | head -n 1 || true)"
fi
fi
OLLAMA_MODELS_JSON="$(curl -sS http://127.0.0.1:11434/api/tags || true)"
MAGICK_PATH="$MAGICK_PATH" FIREFOX_PROFILE="$FIREFOX_PROFILE" "$PYTHON_BIN" - <<'PY'
import json
import os
import subprocess
ROOT_DIR = os.getcwd()
cfg_path = os.path.join(ROOT_DIR, "config.json")
with open(cfg_path, "r", encoding="utf-8") as f:
cfg = json.load(f)
# Set defaults per service without overriding explicit user choices.
cfg.setdefault("llm_provider", "local_ollama")
cfg.setdefault("image_provider", "local_automatic1111")
cfg.setdefault("stt_provider", "local_whisper")
cfg.setdefault("ollama_base_url", "http://127.0.0.1:11434")
cfg.setdefault("automatic1111_base_url", "http://127.0.0.1:7860")
cfg.setdefault("cloudflare_worker_url", "")
cfg.setdefault("whisper_model", "base")
cfg.setdefault("whisper_device", "auto")
cfg.setdefault("whisper_compute_type", "int8")
magick_path = os.environ.get("MAGICK_PATH", "")
if magick_path:
cfg["imagemagick_path"] = magick_path
firefox_profile = os.environ.get("FIREFOX_PROFILE", "")
if firefox_profile and not cfg.get("firefox_profile"):
cfg["firefox_profile"] = firefox_profile
# Pick a reasonable installed Ollama model.
ollama_model = cfg.get("ollama_model", "llama3.2:3b")
installed = []
try:
out = subprocess.check_output(
["curl", "-sS", "http://127.0.0.1:11434/api/tags"],
text=True,
)
payload = json.loads(out)
installed = [m.get("name") for m in payload.get("models", []) if m.get("name")]
except Exception:
installed = []
if installed:
preferred = [
"glm-4.7-flash:latest",
"qwen3:14b",
"phi4:latest",
"phi4:14b",
"gpt-oss:20b",
"deepseek-r1:32b",
]
selected = None
for candidate in preferred:
if candidate in installed:
selected = candidate
break
if selected is None:
selected = installed[0]
if ollama_model not in installed or ollama_model != selected:
cfg["ollama_model"] = selected
with open(cfg_path, "w", encoding="utf-8") as f:
json.dump(cfg, f, indent=2)
f.write("\n")
print(f"[setup] Updated {cfg_path}")
print(f"[setup] llm_provider={cfg.get('llm_provider')} model={cfg.get('ollama_model')}")
print(f"[setup] image_provider={cfg.get('image_provider')}")
print(f"[setup] stt_provider={cfg.get('stt_provider')}")
PY
echo "[setup] Running local preflight..."
"$PYTHON_BIN" scripts/preflight_local.py || true
echo ""
echo "[setup] Done."
echo "[setup] Start app with: source venv/bin/activate && python3 src/main.py"
================================================
FILE: scripts/upload_video.sh
================================================
#!/bin/bash
# Script to generate & Upload a video to YT Shorts
# Check which interpreter to use (python)
if [ -x "$(command -v python3)" ]; then
PYTHON=python3
else
PYTHON=python
fi
# Read .mp/youtube.json file, loop through accounts array, get each id and print every id
youtube_ids=$($PYTHON -c "import json; print('\n'.join([account['id'] for account in json.load(open('.mp/youtube.json'))['accounts']]))")
echo "What account do you want to upload the video to?"
# Print the ids
for id in $youtube_ids; do
echo $id
done
# Ask for the id
read -p "Enter the id: " id
# Check if the id is in the list
if [[ " ${youtube_ids[@]} " =~ " ${id} " ]]; then
echo "ID found"
else
echo "ID not found"
exit 1
fi
# Run python script
$PYTHON src/cron.py youtube $id
================================================
FILE: src/art.py
================================================
from config import ROOT_DIR
from termcolor import colored
def print_banner() -> None:
"""
Prints the introductory ASCII Art Banner.
Returns:
None
"""
with open(f"{ROOT_DIR}/assets/banner.txt", "r") as file:
print(colored(file.read(), "green"))
================================================
FILE: src/cache.py
================================================
import os
import json
from typing import List
from config import ROOT_DIR
def get_cache_path() -> str:
"""
Gets the path to the cache file.
Returns:
path (str): The path to the cache folder
"""
return os.path.join(ROOT_DIR, '.mp')
def get_afm_cache_path() -> str:
"""
Gets the path to the Affiliate Marketing cache file.
Returns:
path (str): The path to the AFM cache folder
"""
return os.path.join(get_cache_path(), 'afm.json')
def get_twitter_cache_path() -> str:
"""
Gets the path to the Twitter cache file.
Returns:
path (str): The path to the Twitter cache folder
"""
return os.path.join(get_cache_path(), 'twitter.json')
def get_youtube_cache_path() -> str:
"""
Gets the path to the YouTube cache file.
Returns:
path (str): The path to the YouTube cache folder
"""
return os.path.join(get_cache_path(), 'youtube.json')
def get_provider_cache_path(provider: str) -> str:
"""
Gets the cache path for a supported account provider.
Args:
provider (str): The provider name ("twitter" or "youtube")
Returns:
path (str): The provider-specific cache path
Raises:
ValueError: If the provider is unsupported
"""
if provider == "twitter":
return get_twitter_cache_path()
if provider == "youtube":
return get_youtube_cache_path()
raise ValueError(f"Unsupported provider '{provider}'. Expected 'twitter' or 'youtube'.")
def get_accounts(provider: str) -> List[dict]:
"""
Gets the accounts from the cache.
Args:
provider (str): The provider to get the accounts for
Returns:
account (List[dict]): The accounts
"""
cache_path = get_provider_cache_path(provider)
if not os.path.exists(cache_path):
# Create the cache file
with open(cache_path, 'w') as file:
json.dump({
"accounts": []
}, file, indent=4)
with open(cache_path, 'r') as file:
parsed = json.load(file)
if parsed is None:
return []
if 'accounts' not in parsed:
return []
# Get accounts dictionary
return parsed['accounts']
def add_account(provider: str, account: dict) -> None:
"""
Adds an account to the cache.
Args:
provider (str): The provider to add the account to ("twitter" or "youtube")
account (dict): The account to add
Returns:
None
"""
cache_path = get_provider_cache_path(provider)
# Get the current accounts
accounts = get_accounts(provider)
# Add the new account
accounts.append(account)
# Write the new accounts to the cache
with open(cache_path, 'w') as file:
json.dump({
"accounts": accounts
}, file, indent=4)
def remove_account(provider: str, account_id: str) -> None:
"""
Removes an account from the cache.
Args:
provider (str): The provider to remove the account from ("twitter" or "youtube")
account_id (str): The ID of the account to remove
Returns:
None
"""
# Get the current accounts
accounts = get_accounts(provider)
# Remove the account
accounts = [account for account in accounts if account['id'] != account_id]
# Write the new accounts to the cache
cache_path = get_provider_cache_path(provider)
with open(cache_path, 'w') as file:
json.dump({
"accounts": accounts
}, file, indent=4)
def get_products() -> List[dict]:
"""
Gets the products from the cache.
Returns:
products (List[dict]): The products
"""
if not os.path.exists(get_afm_cache_path()):
# Create the cache file
with open(get_afm_cache_path(), 'w') as file:
json.dump({
"products": []
}, file, indent=4)
with open(get_afm_cache_path(), 'r') as file:
parsed = json.load(file)
# Get the products
return parsed["products"]
def add_product(product: dict) -> None:
"""
Adds a product to the cache.
Args:
product (dict): The product to add
Returns:
None
"""
# Get the current products
products = get_products()
# Add the new product
products.append(product)
# Write the new products to the cache
with open(get_afm_cache_path(), 'w') as file:
json.dump({
"products": products
}, file, indent=4)
def get_results_cache_path() -> str:
"""
Gets the path to the results cache file.
Returns:
path (str): The path to the results cache folder
"""
return os.path.join(get_cache_path(), 'scraper_results.csv')
================================================
FILE: src/classes/AFM.py
================================================
import os
from urllib.parse import urlparse
from typing import Any
from status import *
from config import *
from constants import *
from llm_provider import generate_text
from .Twitter import Twitter
from selenium_firefox import *
from selenium import webdriver
from selenium.webdriver.common.by import By
from selenium.webdriver.firefox.service import Service
from selenium.webdriver.firefox.options import Options
from webdriver_manager.firefox import GeckoDriverManager
class AffiliateMarketing:
"""
This class will be used to handle all the affiliate marketing related operations.
"""
def __init__(
self,
affiliate_link: str,
fp_profile_path: str,
twitter_account_uuid: str,
account_nickname: str,
topic: str,
) -> None:
"""
Initializes the Affiliate Marketing class.
Args:
affiliate_link (str): The affiliate link
fp_profile_path (str): The path to the Firefox profile
twitter_account_uuid (str): The Twitter account UUID
account_nickname (str): The account nickname
topic (str): The topic of the product
Returns:
None
"""
self._fp_profile_path: str = fp_profile_path
# Initialize the Firefox profile
self.options: Options = Options()
# Set headless state of browser
if get_headless():
self.options.add_argument("--headless")
if not os.path.isdir(fp_profile_path):
raise ValueError(
f"Firefox profile path does not exist or is not a directory: {fp_profile_path}"
)
# Set the profile path
self.options.add_argument("-profile")
self.options.add_argument(fp_profile_path)
# Set the service
self.service: Service = Service(GeckoDriverManager().install())
# Initialize the browser
self.browser: webdriver.Firefox = webdriver.Firefox(
service=self.service, options=self.options
)
# Set the affiliate link
self.affiliate_link: str = affiliate_link
parsed_link = urlparse(self.affiliate_link)
if parsed_link.scheme not in ["http", "https"] or not parsed_link.netloc:
raise ValueError(
f"Affiliate link is invalid. Expected a full URL, got: {self.affiliate_link}"
)
# Set the Twitter account UUID
self.account_uuid: str = twitter_account_uuid
# Set the Twitter account nickname
self.account_nickname: str = account_nickname
# Set the Twitter topic
self.topic: str = topic
# Scrape the product information
self.scrape_product_information()
def scrape_product_information(self) -> None:
"""
This method will be used to scrape the product
information from the affiliate link.
"""
# Open the affiliate link
self.browser.get(self.affiliate_link)
# Get the product name
product_title: str = self.browser.find_element(
By.ID, AMAZON_PRODUCT_TITLE_ID
).text
# Get the features of the product
features: Any = self.browser.find_elements(By.ID, AMAZON_FEATURE_BULLETS_ID)
if get_verbose():
info(f"Product Title: {product_title}")
if get_verbose():
info(f"Features: {features}")
# Set the product title
self.product_title: str = product_title
# Set the features
self.features: Any = features
def generate_response(self, prompt: str) -> str:
"""
This method will be used to generate the response for the user.
Args:
prompt (str): The prompt for the user.
Returns:
response (str): The response for the user.
"""
return generate_text(prompt)
def generate_pitch(self) -> str:
"""
This method will be used to generate a pitch for the product.
Returns:
pitch (str): The pitch for the product.
"""
# Generate the response
pitch: str = (
self.generate_response(
f'I want to promote this product on my website. Generate a brief pitch about this product, return nothing else except the pitch. Information:\nTitle: "{self.product_title}"\nFeatures: "{str(self.features)}"'
)
+ "\nYou can buy the product here: "
+ self.affiliate_link
)
self.pitch: str = pitch
# Return the response
return pitch
def share_pitch(self, where: str) -> None:
"""
This method will be used to share the pitch on the specified platform.
Args:
where (str): The platform where the pitch will be shared.
"""
if where == "twitter":
# Initialize the Twitter class
twitter: Twitter = Twitter(
self.account_uuid,
self.account_nickname,
self._fp_profile_path,
self.topic,
)
# Share the pitch
twitter.post(self.pitch)
def quit(self) -> None:
"""
This method will be used to quit the browser.
"""
# Quit the browser
self.browser.quit()
================================================
FILE: src/classes/Outreach.py
================================================
import os
import io
import re
import csv
import time
import glob
import shlex
import zipfile
import yagmail
import requests
import subprocess
import platform
from cache import *
from status import *
from config import *
class Outreach:
"""
Class that houses the methods to reach out to businesses.
"""
def __init__(self) -> None:
"""
Constructor for the Outreach class.
Returns:
None
"""
# Check if go is installed
self.go_installed = os.system("go version") == 0
# Set niche
self.niche = get_google_maps_scraper_niche()
# Set email credentials
self.email_creds = get_email_credentials()
def _find_scraper_dir(self) -> str:
candidates = sorted(glob.glob("google-maps-scraper-*"))
for candidate in candidates:
if os.path.isdir(candidate) and os.path.exists(
os.path.join(candidate, "go.mod")
):
return candidate
return ""
def is_go_installed(self) -> bool:
"""
Check if go is installed.
Returns:
bool: True if go is installed, False otherwise.
"""
# Check if go is installed
try:
subprocess.call(["go", "version"])
return True
except Exception as e:
return False
def unzip_file(self, zip_link: str) -> None:
"""
Unzip the file.
Args:
zip_link (str): The link to the zip file.
Returns:
None
"""
if self._find_scraper_dir():
info("=> Scraper already unzipped. Skipping unzip.")
return
r = requests.get(zip_link)
z = zipfile.ZipFile(io.BytesIO(r.content))
for member in z.namelist():
if ".." in member or member.startswith("/"):
warning(f"Skipping suspicious path in archive: {member}")
continue
z.extract(member)
def build_scraper(self) -> None:
"""
Build the scraper.
Returns:
None
"""
binary_name = (
"google-maps-scraper.exe"
if platform.system() == "Windows"
else "google-maps-scraper"
)
if os.path.exists(binary_name):
print(colored("=> Scraper already built. Skipping build.", "blue"))
return
scraper_dir = self._find_scraper_dir()
if not scraper_dir:
raise FileNotFoundError(
"Could not locate extracted google-maps-scraper directory."
)
subprocess.run(["go", "mod", "download"], cwd=scraper_dir, check=True)
subprocess.run(["go", "build"], cwd=scraper_dir, check=True)
built_binary = os.path.join(scraper_dir, binary_name)
if not os.path.exists(built_binary):
raise FileNotFoundError(f"Expected built scraper binary at: {built_binary}")
os.replace(built_binary, binary_name)
def run_scraper_with_args_for_30_seconds(self, args: str, timeout=300) -> None:
"""
Run the scraper with the specified arguments for 30 seconds.
Args:
args (str): The arguments to run the scraper with.
timeout (int): The time to run the scraper for.
Returns:
None
"""
info(" => Running scraper...")
binary_name = (
"google-maps-scraper.exe"
if platform.system() == "Windows"
else "google-maps-scraper"
)
command = [os.path.join(os.getcwd(), binary_name)] + shlex.split(args)
try:
scraper_process = subprocess.run(command, timeout=float(timeout))
if scraper_process.returncode == 0:
print(colored("=> Scraper finished successfully.", "green"))
else:
print(colored("=> Scraper finished with an error.", "red"))
except subprocess.TimeoutExpired:
print(colored("=> Scraper timed out.", "red"))
except Exception as e:
print(colored("An error occurred while running the scraper:", "red"))
print(str(e))
def get_items_from_file(self, file_name: str) -> list:
"""
Read and return items from a file.
Args:
file_name (str): The name of the file to read from.
Returns:
list: The items from the file.
"""
# Read and return items from a file
with open(file_name, "r", errors="ignore") as f:
items = f.readlines()
items = [item.strip() for item in items[1:]]
return items
def set_email_for_website(self, index: int, website: str, output_file: str):
"""Extracts an email address from a website and updates a CSV file with it.
This method sends a GET request to the specified website, searches for the
first email address in the HTML content, and appends it to the specified
row in a CSV file. If no email address is found, no changes are made to
the CSV file.
Args:
index (int): The row index in the CSV file where the email should be appended.
website (str): The URL of the website to extract the email address from.
output_file (str): The path to the CSV file to update with the extracted email."""
# Extract and set an email for a website
email = ""
r = requests.get(website)
if r.status_code == 200:
# Define a regular expression pattern to match email addresses
email_pattern = r"\b[A-Za-z0-9._%+-]+@[A-Za-z0-9.-]+\.[A-Z|a-z]{2,7}\b"
# Find all email addresses in the HTML string
email_addresses = re.findall(email_pattern, r.text)
email = email_addresses[0] if len(email_addresses) > 0 else ""
if email:
print(f"=> Setting email {email} for website {website}")
with open(output_file, "r", newline="", errors="ignore") as csvfile:
csvreader = csv.reader(csvfile)
items = list(csvreader)
items[index].append(email)
with open(output_file, "w", newline="", errors="ignore") as csvfile:
csvwriter = csv.writer(csvfile)
csvwriter.writerows(items)
def start(self) -> None:
"""
Start the outreach process.
Returns:
None
"""
# Check if go is installed
if not self.is_go_installed():
error("Go is not installed. Please install go and try again.")
return
# Unzip the scraper
self.unzip_file(get_google_maps_scraper_zip_url())
# Build the scraper
self.build_scraper()
# Write the niche to a file
with open("niche.txt", "w") as f:
f.write(self.niche)
output_path = get_results_cache_path()
message_subject = get_outreach_message_subject()
message_body = get_outreach_message_body_file()
# Run
self.run_scraper_with_args_for_30_seconds(
f'-input niche.txt -results "{output_path}"', timeout=get_scraper_timeout()
)
if not os.path.exists(output_path):
error(
f" => Scraper output not found at {output_path}. Check scraper logs and configuration."
)
os.remove("niche.txt")
return
# Get the items from the file
items = self.get_items_from_file(output_path)
success(f" => Scraped {len(items)} items.")
# Remove the niche file
os.remove("niche.txt")
time.sleep(2)
# Create a yagmail SMTP client outside the loop
yag = yagmail.SMTP(
user=self.email_creds["username"],
password=self.email_creds["password"],
host=self.email_creds["smtp_server"],
port=self.email_creds["smtp_port"],
)
# Get the email for each business
for index, item in enumerate(items, start=1):
try:
# Check if the item"s website is valid
website = item.split(",")
website = [w for w in website if w.startswith("http")]
website = website[0] if len(website) > 0 else ""
if website != "":
test_r = requests.get(website)
if test_r.status_code == 200:
self.set_email_for_website(index, website, output_path)
# Send emails using the existing SMTP connection
receiver_email = item.split(",")[-1]
if "@" not in receiver_email:
warning(f" => No email provided. Skipping...")
continue
company_name = item.split(",")[0]
subject = message_subject.replace(
"{{COMPANY_NAME}}", company_name
)
body = (
open(message_body, "r")
.read()
.replace("{{COMPANY_NAME}}", company_name)
)
info(f" => Sending email to {receiver_email}...")
yag.send(
to=receiver_email,
subject=subject,
contents=body,
)
success(f" => Sent email to {receiver_email}")
else:
warning(f" => Website {website} is invalid. Skipping...")
except Exception as err:
error(f" => Error: {err}...")
continue
================================================
FILE: src/classes/Tts.py
================================================
import os
import soundfile as sf
from kittentts import KittenTTS as KittenModel
from config import ROOT_DIR, get_tts_voice
KITTEN_MODEL = "KittenML/kitten-tts-mini-0.8"
KITTEN_SAMPLE_RATE = 24000
class TTS:
def __init__(self) -> None:
self._model = KittenModel(KITTEN_MODEL)
self._voice = get_tts_voice()
def synthesize(self, text, output_file=os.path.join(ROOT_DIR, ".mp", "audio.wav")):
audio = self._model.generate(text, voice=self._voice)
sf.write(output_file, audio, KITTEN_SAMPLE_RATE)
return output_file
================================================
FILE: src/classes/Twitter.py
================================================
import re
import sys
import time
import os
import json
from cache import *
from config import *
from status import *
from llm_provider import generate_text
from typing import List, Optional
from datetime import datetime
from termcolor import colored
from selenium_firefox import *
from selenium import webdriver
from selenium.webdriver.common.by import By
from selenium.webdriver.firefox.service import Service
from selenium.webdriver.firefox.options import Options
from webdriver_manager.firefox import GeckoDriverManager
from selenium.webdriver.support.ui import WebDriverWait
from selenium.webdriver.support import expected_conditions as EC
class Twitter:
"""
Class for the Bot, that grows a Twitter account.
"""
def __init__(
self, account_uuid: str, account_nickname: str, fp_profile_path: str, topic: str
) -> None:
"""
Initializes the Twitter Bot.
Args:
account_uuid (str): The account UUID
account_nickname (str): The account nickname
fp_profile_path (str): The path to the Firefox profile
Returns:
None
"""
self.account_uuid: str = account_uuid
self.account_nickname: str = account_nickname
self.fp_profile_path: str = fp_profile_path
self.topic: str = topic
# Initialize the Firefox profile
self.options: Options = Options()
# Set headless state of browser
if get_headless():
self.options.add_argument("--headless")
if not os.path.isdir(fp_profile_path):
raise ValueError(
f"Firefox profile path does not exist or is not a directory: {fp_profile_path}"
)
# Set the profile path
self.options.add_argument("-profile")
self.options.add_argument(fp_profile_path)
# Set the service
self.service: Service = Service(GeckoDriverManager().install())
# Initialize the browser
self.browser: webdriver.Firefox = webdriver.Firefox(
service=self.service, options=self.options
)
self.wait: WebDriverWait = WebDriverWait(self.browser, 30)
def post(self, text: Optional[str] = None) -> None:
"""
Starts the Twitter Bot.
Args:
text (str): The text to post
Returns:
None
"""
bot: webdriver.Firefox = self.browser
verbose: bool = get_verbose()
bot.get("https://x.com/compose/post")
post_content: str = text if text is not None else self.generate_post()
now: datetime = datetime.now()
print(colored(" => Posting to Twitter:", "blue"), post_content[:30] + "...")
body = post_content
text_box = None
text_box_selectors = [
(By.CSS_SELECTOR, "div[data-testid='tweetTextarea_0'][role='textbox']"),
(By.XPATH, "//div[@data-testid='tweetTextarea_0']//div[@role='textbox']"),
(By.XPATH, "//div[@role='textbox']"),
]
for selector in text_box_selectors:
try:
text_box = self.wait.until(EC.element_to_be_clickable(selector))
text_box.click()
text_box.send_keys(body)
break
except Exception:
continue
if text_box is None:
raise RuntimeError(
"Could not find tweet text box. Ensure you are logged into X in this Firefox profile."
)
post_button = None
post_button_selectors = [
(By.XPATH, "//button[@data-testid='tweetButtonInline']"),
(By.XPATH, "//button[@data-testid='tweetButton']"),
(By.XPATH, "//span[text()='Post']/ancestor::button"),
]
for selector in post_button_selectors:
try:
post_button = self.wait.until(EC.element_to_be_clickable(selector))
post_button.click()
break
except Exception:
continue
if post_button is None:
raise RuntimeError("Could not find the Post button on X compose screen.")
if verbose:
print(colored(" => Pressed [ENTER] Button on Twitter..", "blue"))
time.sleep(2)
# Add the post to the cache
self.add_post({"content": body, "date": now.strftime("%m/%d/%Y, %H:%M:%S")})
success("Posted to Twitter successfully!")
def get_posts(self) -> List[dict]:
"""
Gets the posts from the cache.
Returns:
posts (List[dict]): The posts
"""
if not os.path.exists(get_twitter_cache_path()):
# Create the cache file
with open(get_twitter_cache_path(), "w") as file:
json.dump({"accounts": []}, file, indent=4)
with open(get_twitter_cache_path(), "r") as file:
parsed = json.load(file)
# Find our account
accounts = parsed["accounts"]
for account in accounts:
if account["id"] == self.account_uuid:
posts = account["posts"]
if posts is None:
return []
# Return the posts
return posts
return []
def add_post(self, post: dict) -> None:
"""
Adds a post to the cache.
Args:
post (dict): The post to add
Returns:
None
"""
posts = self.get_posts()
posts.append(post)
with open(get_twitter_cache_path(), "r") as file:
previous_json = json.loads(file.read())
# Find our account
accounts = previous_json["accounts"]
for account in accounts:
if account["id"] == self.account_uuid:
account["posts"].append(post)
# Commit changes
with open(get_twitter_cache_path(), "w") as f:
f.write(json.dumps(previous_json))
def generate_post(self) -> str:
"""
Generates a post for the Twitter account based on the topic.
Returns:
post (str): The post
"""
completion = generate_text(
f"Generate a Twitter post about: {self.topic} in {get_twitter_language()}. "
"The Limit is 2 sentences. Choose a specific sub-topic of the provided topic."
)
if get_verbose():
info("Generating a post...")
if completion is None:
error("Failed to generate a post. Please try again.")
sys.exit(1)
# Apply Regex to remove all *
completion = re.sub(r"\*", "", completion).replace('"', "")
if get_verbose():
info(f"Length of post: {len(completion)}")
if len(completion) >= 260:
return completion[:257].rsplit(" ", 1)[0] + "..."
return completion
================================================
FILE: src/classes/YouTube.py
================================================
import re
import base64
import json
import time
import os
import requests
import assemblyai as aai
from utils import *
from cache import *
from .Tts import TTS
from llm_provider import generate_text
from config import *
from status import *
from uuid import uuid4
from constants import *
from typing import List
from moviepy.editor import *
from termcolor import colored
from selenium_firefox import *
from selenium import webdriver
from moviepy.video.fx.all import crop
from moviepy.config import change_settings
from selenium.webdriver.common.by import By
from selenium.webdriver.firefox.service import Service
from selenium.webdriver.firefox.options import Options
from moviepy.video.tools.subtitles import SubtitlesClip
from webdriver_manager.firefox import GeckoDriverManager
from datetime import datetime
# Set ImageMagick Path
change_settings({"IMAGEMAGICK_BINARY": get_imagemagick_path()})
class YouTube:
"""
Class for YouTube Automation.
Steps to create a YouTube Short:
1. Generate a topic [DONE]
2. Generate a script [DONE]
3. Generate metadata (Title, Description, Tags) [DONE]
4. Generate AI Image Prompts [DONE]
4. Generate Images based on generated Prompts [DONE]
5. Convert Text-to-Speech [DONE]
6. Show images each for n seconds, n: Duration of TTS / Amount of images [DONE]
7. Combine Concatenated Images with the Text-to-Speech [DONE]
"""
def __init__(
self,
account_uuid: str,
account_nickname: str,
fp_profile_path: str,
niche: str,
language: str,
) -> None:
"""
Constructor for YouTube Class.
Args:
account_uuid (str): The unique identifier for the YouTube account.
account_nickname (str): The nickname for the YouTube account.
fp_profile_path (str): Path to the firefox profile that is logged into the specificed YouTube Account.
niche (str): The niche of the provided YouTube Channel.
language (str): The language of the Automation.
Returns:
None
"""
self._account_uuid: str = account_uuid
self._account_nickname: str = account_nickname
self._fp_profile_path: str = fp_profile_path
self._niche: str = niche
self._language: str = language
self.images = []
# Initialize the Firefox profile
self.options: Options = Options()
# Set headless state of browser
if get_headless():
self.options.add_argument("--headless")
if not os.path.isdir(self._fp_profile_path):
raise ValueError(
f"Firefox profile path does not exist or is not a directory: {self._fp_profile_path}"
)
self.options.add_argument("-profile")
self.options.add_argument(self._fp_profile_path)
# Set the service
self.service: Service = Service(GeckoDriverManager().install())
# Initialize the browser
self.browser: webdriver.Firefox = webdriver.Firefox(
service=self.service, options=self.options
)
@property
def niche(self) -> str:
"""
Getter Method for the niche.
Returns:
niche (str): The niche
"""
return self._niche
@property
def language(self) -> str:
"""
Getter Method for the language to use.
Returns:
language (str): The language
"""
return self._language
def generate_response(self, prompt: str, model_name: str = None) -> str:
"""
Generates an LLM Response based on a prompt and the user-provided model.
Args:
prompt (str): The prompt to use in the text generation.
Returns:
response (str): The generated AI Repsonse.
"""
return generate_text(prompt, model_name=model_name)
def generate_topic(self) -> str:
"""
Generates a topic based on the YouTube Channel niche.
Returns:
topic (str): The generated topic.
"""
completion = self.generate_response(
f"Please generate a specific video idea that takes about the following topic: {self.niche}. Make it exactly one sentence. Only return the topic, nothing else."
)
if not completion:
error("Failed to generate Topic.")
self.subject = completion
return completion
def generate_script(self) -> str:
"""
Generate a script for a video, depending on the subject of the video, the number of paragraphs, and the AI model.
Returns:
script (str): The script of the video.
"""
sentence_length = get_script_sentence_length()
prompt = f"""
Generate a script for a video in {sentence_length} sentences, depending on the subject of the video.
The script is to be returned as a string with the specified number of paragraphs.
Here is an example of a string:
"This is an example string."
Do not under any circumstance reference this prompt in your response.
Get straight to the point, don't start with unnecessary things like, "welcome to this video".
Obviously, the script should be related to the subject of the video.
YOU MUST NOT EXCEED THE {sentence_length} SENTENCES LIMIT. MAKE SURE THE {sentence_length} SENTENCES ARE SHORT.
YOU MUST NOT INCLUDE ANY TYPE OF MARKDOWN OR FORMATTING IN THE SCRIPT, NEVER USE A TITLE.
YOU MUST WRITE THE SCRIPT IN THE LANGUAGE SPECIFIED IN [LANGUAGE].
ONLY RETURN THE RAW CONTENT OF THE SCRIPT. DO NOT INCLUDE "VOICEOVER", "NARRATOR" OR SIMILAR INDICATORS OF WHAT SHOULD BE SPOKEN AT THE BEGINNING OF EACH PARAGRAPH OR LINE. YOU MUST NOT MENTION THE PROMPT, OR ANYTHING ABOUT THE SCRIPT ITSELF. ALSO, NEVER TALK ABOUT THE AMOUNT OF PARAGRAPHS OR LINES. JUST WRITE THE SCRIPT
Subject: {self.subject}
Language: {self.language}
"""
completion = self.generate_response(prompt)
# Apply regex to remove *
completion = re.sub(r"\*", "", completion)
if not completion:
error("The generated script is empty.")
return
if len(completion) > 5000:
if get_verbose():
warning("Generated Script is too long. Retrying...")
return self.generate_script()
self.script = completion
return completion
def generate_metadata(self) -> dict:
"""
Generates Video metadata for the to-be-uploaded YouTube Short (Title, Description).
Returns:
metadata (dict): The generated metadata.
"""
title = self.generate_response(
f"Please generate a YouTube Video Title for the following subject, including hashtags: {self.subject}. Only return the title, nothing else. Limit the title under 100 characters."
)
if len(title) > 100:
if get_verbose():
warning("Generated Title is too long. Retrying...")
return self.generate_metadata()
description = self.generate_response(
f"Please generate a YouTube Video Description for the following script: {self.script}. Only return the description, nothing else."
)
self.metadata = {"title": title, "description": description}
return self.metadata
def generate_prompts(self) -> List[str]:
"""
Generates AI Image Prompts based on the provided Video Script.
Returns:
image_prompts (List[str]): Generated List of image prompts.
"""
n_prompts = len(self.script) / 3
prompt = f"""
Generate {n_prompts} Image Prompts for AI Image Generation,
depending on the subject of a video.
Subject: {self.subject}
The image prompts are to be returned as
a JSON-Array of strings.
Each search term should consist of a full sentence,
always add the main subject of the video.
Be emotional and use interesting adjectives to make the
Image Prompt as detailed as possible.
YOU MUST ONLY RETURN THE JSON-ARRAY OF STRINGS.
YOU MUST NOT RETURN ANYTHING ELSE.
YOU MUST NOT RETURN THE SCRIPT.
The search terms must be related to the subject of the video.
Here is an example of a JSON-Array of strings:
["image prompt 1", "image prompt 2", "image prompt 3"]
For context, here is the full text:
{self.script}
"""
completion = (
str(self.generate_response(prompt))
.replace("```json", "")
.replace("```", "")
)
image_prompts = []
if "image_prompts" in completion:
image_prompts = json.loads(completion)["image_prompts"]
else:
try:
image_prompts = json.loads(completion)
if get_verbose():
info(f" => Generated Image Prompts: {image_prompts}")
except Exception:
if get_verbose():
warning(
"LLM returned an unformatted response. Attempting to clean..."
)
# Get everything between [ and ], and turn it into a list
r = re.compile(r"\[.*\]")
image_prompts = r.findall(completion)
if len(image_prompts) == 0:
if get_verbose():
warning("Failed to generate Image Prompts. Retrying...")
return self.generate_prompts()
if len(image_prompts) > n_prompts:
image_prompts = image_prompts[: int(n_prompts)]
self.image_prompts = image_prompts
success(f"Generated {len(image_prompts)} Image Prompts.")
return image_prompts
def _persist_image(self, image_bytes: bytes, provider_label: str) -> str:
"""
Writes generated image bytes to a PNG file in .mp.
Args:
image_bytes (bytes): Image payload
provider_label (str): Label for logging
Returns:
path (str): Absolute image path
"""
image_path = os.path.join(ROOT_DIR, ".mp", str(uuid4()) + ".png")
with open(image_path, "wb") as image_file:
image_file.write(image_bytes)
if get_verbose():
info(f' => Wrote image from {provider_label} to "{image_path}"')
self.images.append(image_path)
return image_path
def generate_image_nanobanana2(self, prompt: str) -> str:
"""
Generates an AI Image using Nano Banana 2 API (Gemini image API).
Args:
prompt (str): Prompt for image generation
Returns:
path (str): The path to the generated image.
"""
print(f"Generating Image using Nano Banana 2 API: {prompt}")
api_key = get_nanobanana2_api_key()
if not api_key:
error("nanobanana2_api_key is not configured.")
return None
base_url = get_nanobanana2_api_base_url().rstrip("/")
model = get_nanobanana2_model()
aspect_ratio = get_nanobanana2_aspect_ratio()
endpoint = f"{base_url}/models/{model}:generateContent"
payload = {
"contents": [{"parts": [{"text": prompt}]}],
"generationConfig": {
"responseModalities": ["IMAGE"],
"imageConfig": {"aspectRatio": aspect_ratio},
},
}
try:
response = requests.post(
endpoint,
headers={"x-goog-api-key": api_key, "Content-Type": "application/json"},
json=payload,
timeout=300,
)
response.raise_for_status()
body = response.json()
candidates = body.get("candidates", [])
for candidate in candidates:
content = candidate.get("content", {})
for part in content.get("parts", []):
inline_data = part.get("inlineData") or part.get("inline_data")
if not inline_data:
continue
data = inline_data.get("data")
mime_type = inline_data.get("mimeType") or inline_data.get("mime_type", "")
if data and str(mime_type).startswith("image/"):
image_bytes = base64.b64decode(data)
return self._persist_image(image_bytes, "Nano Banana 2 API")
if get_verbose():
warning(f"Nano Banana 2 did not return an image payload. Response: {body}")
return None
except Exception as e:
if get_verbose():
warning(f"Failed to generate image with Nano Banana 2 API: {str(e)}")
return None
def generate_image(self, prompt: str) -> str:
"""
Generates an AI Image based on the given prompt using Nano Banana 2.
Args:
prompt (str): Reference for image generation
Returns:
path (str): The path to the generated image.
"""
return self.generate_image_nanobanana2(prompt)
def generate_script_to_speech(self, tts_instance: TTS) -> str:
"""
Converts the generated script into Speech using KittenTTS and returns the path to the wav file.
Args:
tts_instance (tts): Instance of TTS Class.
Returns:
path_to_wav (str): Path to generated audio (WAV Format).
"""
path = os.path.join(ROOT_DIR, ".mp", str(uuid4()) + ".wav")
# Clean script, remove every character that is not a word character, a space, a period, a question mark, or an exclamation mark.
self.script = re.sub(r"[^\w\s.?!]", "", self.script)
tts_instance.synthesize(self.script, path)
self.tts_path = path
if get_verbose():
info(f' => Wrote TTS to "{path}"')
return path
def add_video(self, video: dict) -> None:
"""
Adds a video to the cache.
Args:
video (dict): The video to add
Returns:
None
"""
videos = self.get_videos()
videos.append(video)
cache = get_youtube_cache_path()
with open(cache, "r") as file:
previous_json = json.loads(file.read())
# Find our account
accounts = previous_json["accounts"]
for account in accounts:
if account["id"] == self._account_uuid:
account["videos"].append(video)
# Commit changes
with open(cache, "w") as f:
f.write(json.dumps(previous_json))
def generate_subtitles(self, audio_path: str) -> str:
"""
Generates subtitles for the audio using the configured STT provider.
Args:
audio_path (str): The path to the audio file.
Returns:
path (str): The path to the generated SRT File.
"""
provider = str(get_stt_provider() or "local_whisper").lower()
if provider == "local_whisper":
return self.generate_subtitles_local_whisper(audio_path)
if provider == "third_party_assemblyai":
return self.generate_subtitles_assemblyai(audio_path)
warning(f"Unknown stt_provider '{provider}'. Falling back to local_whisper.")
return self.generate_subtitles_local_whisper(audio_path)
def generate_subtitles_assemblyai(self, audio_path: str) -> str:
"""
Generates subtitles using AssemblyAI.
Args:
audio_path (str): Audio file path
Returns:
path (str): Path to SRT file
"""
aai.settings.api_key = get_assemblyai_api_key()
config = aai.TranscriptionConfig()
transcriber = aai.Transcriber(config=config)
transcript = transcriber.transcribe(audio_path)
subtitles = transcript.export_subtitles_srt()
srt_path = os.path.join(ROOT_DIR, ".mp", str(uuid4()) + ".srt")
with open(srt_path, "w") as file:
file.write(subtitles)
return srt_path
def _format_srt_timestamp(self, seconds: float) -> str:
"""
Formats a timestamp in seconds to SRT format.
Args:
seconds (float): Seconds
Returns:
ts (str): HH:MM:SS,mmm
"""
total_millis = max(0, int(round(seconds * 1000)))
hours = total_millis // 3600000
minutes = (total_millis % 3600000) // 60000
secs = (total_millis % 60000) // 1000
millis = total_millis % 1000
return f"{hours:02d}:{minutes:02d}:{secs:02d},{millis:03d}"
def generate_subtitles_local_whisper(self, audio_path: str) -> str:
"""
Generates subtitles using local Whisper (faster-whisper).
Args:
audio_path (str): Audio file path
Returns:
path (str): Path to SRT file
"""
try:
from faster_whisper import WhisperModel
except ImportError:
error(
"Local STT selected but 'faster-whisper' is not installed. "
"Install it or switch stt_provider to third_party_assemblyai."
)
raise
model = WhisperModel(
get_whisper_model(),
device=get_whisper_device(),
compute_type=get_whisper_compute_type(),
)
segments, _ = model.transcribe(audio_path, vad_filter=True)
lines = []
for idx, segment in enumerate(segments, start=1):
start = self._format_srt_timestamp(segment.start)
end = self._format_srt_timestamp(segment.end)
text = str(segment.text).strip()
if not text:
continue
lines.append(str(idx))
lines.append(f"{start} --> {end}")
lines.append(text)
lines.append("")
subtitles = "\n".join(lines)
srt_path = os.path.join(ROOT_DIR, ".mp", str(uuid4()) + ".srt")
with open(srt_path, "w", encoding="utf-8") as file:
file.write(subtitles)
return srt_path
def combine(self) -> str:
"""
Combines everything into the final video.
Returns:
path (str): The path to the generated MP4 File.
"""
combined_image_path = os.path.join(ROOT_DIR, ".mp", str(uuid4()) + ".mp4")
threads = get_threads()
tts_clip = AudioFileClip(self.tts_path)
max_duration = tts_clip.duration
req_dur = max_duration / len(self.images)
# Make a generator that returns a TextClip when called with consecutive
generator = lambda txt: TextClip(
txt,
font=os.path.join(get_fonts_dir(), get_font()),
fontsize=100,
color="#FFFF00",
stroke_color="black",
stroke_width=5,
size=(1080, 1920),
method="caption",
)
print(colored("[+] Combining images...", "blue"))
clips = []
tot_dur = 0
# Add downloaded clips over and over until the duration of the audio (max_duration) has been reached
while tot_dur < max_duration:
for image_path in self.images:
clip = ImageClip(image_path)
clip.duration = req_dur
clip = clip.set_fps(30)
# Not all images are same size,
# so we need to resize them
if round((clip.w / clip.h), 4) < 0.5625:
if get_verbose():
info(f" => Resizing Image: {image_path} to 1080x1920")
clip = crop(
clip,
width=clip.w,
height=round(clip.w / 0.5625),
x_center=clip.w / 2,
y_center=clip.h / 2,
)
else:
if get_verbose():
info(f" => Resizing Image: {image_path} to 1920x1080")
clip = crop(
clip,
width=round(0.5625 * clip.h),
height=clip.h,
x_center=clip.w / 2,
y_center=clip.h / 2,
)
clip = clip.resize((1080, 1920))
# FX (Fade In)
# clip = clip.fadein(2)
clips.append(clip)
tot_dur += clip.duration
final_clip = concatenate_videoclips(clips)
final_clip = final_clip.set_fps(30)
random_song = choose_random_song()
subtitles = None
try:
subtitles_path = self.generate_subtitles(self.tts_path)
equalize_subtitles(subtitles_path, 10)
subtitles = SubtitlesClip(subtitles_path, generator)
subtitles.set_pos(("center", "center"))
except Exception as e:
warning(f"Failed to generate subtitles, continuing without subtitles: {e}")
random_song_clip = AudioFileClip(random_song).set_fps(44100)
# Turn down volume
random_song_clip = random_song_clip.fx(afx.volumex, 0.1)
comp_audio = CompositeAudioClip([tts_clip.set_fps(44100), random_song_clip])
final_clip = final_clip.set_audio(comp_audio)
final_clip = final_clip.set_duration(tts_clip.duration)
if subtitles is not None:
final_clip = CompositeVideoClip([final_clip, subtitles])
final_clip.write_videofile(combined_image_path, threads=threads)
success(f'Wrote Video to "{combined_image_path}"')
return combined_image_path
def generate_video(self, tts_instance: TTS) -> str:
"""
Generates a YouTube Short based on the provided niche and language.
Args:
tts_instance (TTS): Instance of TTS Class.
Returns:
path (str): The path to the generated MP4 File.
"""
# Generate the Topic
self.generate_topic()
# Generate the Script
self.generate_script()
# Generate the Metadata
self.generate_metadata()
# Generate the Image Prompts
self.generate_prompts()
# Generate the Images
for prompt in self.image_prompts:
self.generate_image(prompt)
# Generate the TTS
self.generate_script_to_speech(tts_instance)
# Combine everything
path = self.combine()
if get_verbose():
info(f" => Generated Video: {path}")
self.video_path = os.path.abspath(path)
return path
def get_channel_id(self) -> str:
"""
Gets the Channel ID of the YouTube Account.
Returns:
channel_id (str): The Channel ID.
"""
driver = self.browser
driver.get("https://studio.youtube.com")
time.sleep(2)
channel_id = driver.current_url.split("/")[-1]
self.channel_id = channel_id
return channel_id
def upload_video(self) -> bool:
"""
Uploads the video to YouTube.
Returns:
success (bool): Whether the upload was successful or not.
"""
try:
self.get_channel_id()
driver = self.browser
verbose = get_verbose()
# Go to youtube.com/upload
driver.get("https://www.youtube.com/upload")
# Set video file
FILE_PICKER_TAG = "ytcp-uploads-file-picker"
file_picker = driver.find_element(By.TAG_NAME, FILE_PICKER_TAG)
INPUT_TAG = "input"
file_input = file_picker.find_element(By.TAG_NAME, INPUT_TAG)
file_input.send_keys(self.video_path)
# Wait for upload to finish
time.sleep(5)
# Set title
textboxes = driver.find_elements(By.ID, YOUTUBE_TEXTBOX_ID)
title_el = textboxes[0]
description_el = textboxes[-1]
if verbose:
info("\t=> Setting title...")
title_el.click()
time.sleep(1)
title_el.clear()
title_el.send_keys(self.metadata["title"])
if verbose:
info("\t=> Setting description...")
# Set description
time.sleep(10)
description_el.click()
time.sleep(0.5)
description_el.clear()
description_el.send_keys(self.metadata["description"])
time.sleep(0.5)
# Set `made for kids` option
if verbose:
info("\t=> Setting `made for kids` option...")
is_for_kids_checkbox = driver.find_element(
By.NAME, YOUTUBE_MADE_FOR_KIDS_NAME
)
is_not_for_kids_checkbox = driver.find_element(
By.NAME, YOUTUBE_NOT_MADE_FOR_KIDS_NAME
)
if not get_is_for_kids():
is_not_for_kids_checkbox.click()
else:
is_for_kids_checkbox.click()
time.sleep(0.5)
# Click next
if verbose:
info("\t=> Clicking next...")
next_button = driver.find_element(By.ID, YOUTUBE_NEXT_BUTTON_ID)
next_button.click()
# Click next again
if verbose:
info("\t=> Clicking next again...")
next_button = driver.find_element(By.ID, YOUTUBE_NEXT_BUTTON_ID)
next_button.click()
# Wait for 2 seconds
time.sleep(2)
# Click next again
if verbose:
info("\t=> Clicking next again...")
next_button = driver.find_element(By.ID, YOUTUBE_NEXT_BUTTON_ID)
next_button.click()
# Set as unlisted
if verbose:
info("\t=> Setting as unlisted...")
radio_button = driver.find_elements(By.XPATH, YOUTUBE_RADIO_BUTTON_XPATH)
radio_button[2].click()
if verbose:
info("\t=> Clicking done button...")
# Click done button
done_button = driver.find_element(By.ID, YOUTUBE_DONE_BUTTON_ID)
done_button.click()
# Wait for 2 seconds
time.sleep(2)
# Get latest video
if verbose:
info("\t=> Getting video URL...")
# Get the latest uploaded video URL
driver.get(
f"https://studio.youtube.com/channel/{self.channel_id}/videos/short"
)
time.sleep(2)
videos = driver.find_elements(By.TAG_NAME, "ytcp-video-row")
first_video = videos[0]
anchor_tag = first_video.find_element(By.TAG_NAME, "a")
href = anchor_tag.get_attribute("href")
if verbose:
info(f"\t=> Extracting video ID from URL: {href}")
video_id = href.split("/")[-2]
# Build URL
url = build_url(video_id)
self.uploaded_video_url = url
if verbose:
success(f" => Uploaded Video: {url}")
# Add video to cache
self.add_video(
{
"title": self.metadata["title"],
"description": self.metadata["description"],
"url": url,
"date": datetime.now().strftime("%Y-%m-%d %H:%M:%S"),
}
)
# Close the browser
driver.quit()
return True
except:
self.browser.quit()
return False
def get_videos(self) -> List[dict]:
"""
Gets the uploaded videos from the YouTube Channel.
Returns:
videos (List[dict]): The uploaded videos.
"""
if not os.path.exists(get_youtube_cache_path()):
# Create the cache file
with open(get_youtube_cache_path(), "w") as file:
json.dump({"videos": []}, file, indent=4)
return []
videos = []
# Read the cache file
with open(get_youtube_cache_path(), "r") as file:
previous_json = json.loads(file.read())
# Find our account
accounts = previous_json["accounts"]
for account in accounts:
if account["id"] == self._account_uuid:
videos = account["videos"]
return videos
================================================
FILE: src/config.py
================================================
import os
import sys
import json
import srt_equalizer
from termcolor import colored
ROOT_DIR = os.path.dirname(sys.path[0])
def assert_folder_structure() -> None:
"""
Make sure that the nessecary folder structure is present.
Returns:
None
"""
# Create the .mp folder
if not os.path.exists(os.path.join(ROOT_DIR, ".mp")):
if get_verbose():
print(colored(f"=> Creating .mp folder at {os.path.join(ROOT_DIR, '.mp')}", "green"))
os.makedirs(os.path.join(ROOT_DIR, ".mp"))
def get_first_time_running() -> bool:
"""
Checks if the program is running for the first time by checking if .mp folder exists.
Returns:
exists (bool): True if the program is running for the first time, False otherwise
"""
return not os.path.exists(os.path.join(ROOT_DIR, ".mp"))
def get_email_credentials() -> dict:
"""
Gets the email credentials from the config file.
Returns:
credentials (dict): The email credentials
"""
with open(os.path.join(ROOT_DIR, "config.json"), "r") as file:
return json.load(file)["email"]
def get_verbose() -> bool:
"""
Gets the verbose flag from the config file.
Returns:
verbose (bool): The verbose flag
"""
with open(os.path.join(ROOT_DIR, "config.json"), "r") as file:
return json.load(file)["verbose"]
def get_firefox_profile_path() -> str:
"""
Gets the path to the Firefox profile.
Returns:
path (str): The path to the Firefox profile
"""
with open(os.path.join(ROOT_DIR, "config.json"), "r") as file:
return json.load(file)["firefox_profile"]
def get_headless() -> bool:
"""
Gets the headless flag from the config file.
Returns:
headless (bool): The headless flag
"""
with open(os.path.join(ROOT_DIR, "config.json"), "r") as file:
return json.load(file)["headless"]
def get_ollama_base_url() -> str:
"""
Gets the Ollama base URL.
Returns:
url (str): The Ollama base URL
"""
with open(os.path.join(ROOT_DIR, "config.json"), "r") as file:
return json.load(file).get("ollama_base_url", "http://127.0.0.1:11434")
def get_ollama_model() -> str:
"""
Gets the Ollama model name from the config file.
Returns:
model (str): The Ollama model name, or empty string if not set.
"""
with open(os.path.join(ROOT_DIR, "config.json"), "r") as file:
return json.load(file).get("ollama_model", "")
def get_twitter_language() -> str:
"""
Gets the Twitter language from the config file.
Returns:
language (str): The Twitter language
"""
with open(os.path.join(ROOT_DIR, "config.json"), "r") as file:
return json.load(file)["twitter_language"]
def get_nanobanana2_api_base_url() -> str:
"""
Gets the Nano Banana 2 (Gemini image) API base URL.
Returns:
url (str): API base URL
"""
with open(os.path.join(ROOT_DIR, "config.json"), "r") as file:
return json.load(file).get(
"nanobanana2_api_base_url",
"https://generativelanguage.googleapis.com/v1beta",
)
def get_nanobanana2_api_key() -> str:
"""
Gets the Nano Banana 2 API key.
Returns:
key (str): API key
"""
with open(os.path.join(ROOT_DIR, "config.json"), "r") as file:
configured = json.load(file).get("nanobanana2_api_key", "")
return configured or os.environ.get("GEMINI_API_KEY", "")
def get_nanobanana2_model() -> str:
"""
Gets the Nano Banana 2 model name.
Returns:
model (str): Model name
"""
with open(os.path.join(ROOT_DIR, "config.json"), "r") as file:
return json.load(file).get("nanobanana2_model", "gemini-3.1-flash-image-preview")
def get_nanobanana2_aspect_ratio() -> str:
"""
Gets the aspect ratio for Nano Banana 2 image generation.
Returns:
ratio (str): Aspect ratio
"""
with open(os.path.join(ROOT_DIR, "config.json"), "r") as file:
return json.load(file).get("nanobanana2_aspect_ratio", "9:16")
def get_threads() -> int:
"""
Gets the amount of threads to use for example when writing to a file with MoviePy.
Returns:
threads (int): Amount of threads
"""
with open(os.path.join(ROOT_DIR, "config.json"), "r") as file:
return json.load(file)["threads"]
def get_zip_url() -> str:
"""
Gets the URL to the zip file containing the songs.
Returns:
url (str): The URL to the zip file
"""
with open(os.path.join(ROOT_DIR, "config.json"), "r") as file:
return json.load(file)["zip_url"]
def get_is_for_kids() -> bool:
"""
Gets the is for kids flag from the config file.
Returns:
is_for_kids (bool): The is for kids flag
"""
with open(os.path.join(ROOT_DIR, "config.json"), "r") as file:
return json.load(file)["is_for_kids"]
def get_google_maps_scraper_zip_url() -> str:
"""
Gets the URL to the zip file containing the Google Maps scraper.
Returns:
url (str): The URL to the zip file
"""
with open(os.path.join(ROOT_DIR, "config.json"), "r") as file:
return json.load(file)["google_maps_scraper"]
def get_google_maps_scraper_niche() -> str:
"""
Gets the niche for the Google Maps scraper.
Returns:
niche (str): The niche
"""
with open(os.path.join(ROOT_DIR, "config.json"), "r") as file:
return json.load(file)["google_maps_scraper_niche"]
def get_scraper_timeout() -> int:
"""
Gets the timeout for the scraper.
Returns:
timeout (int): The timeout
"""
with open(os.path.join(ROOT_DIR, "config.json"), "r") as file:
return json.load(file)["scraper_timeout"] or 300
def get_outreach_message_subject() -> str:
"""
Gets the outreach message subject.
Returns:
subject (str): The outreach message subject
"""
with open(os.path.join(ROOT_DIR, "config.json"), "r") as file:
return json.load(file)["outreach_message_subject"]
def get_outreach_message_body_file() -> str:
"""
Gets the outreach message body file.
Returns:
file (str): The outreach message body file
"""
with open(os.path.join(ROOT_DIR, "config.json"), "r") as file:
return json.load(file)["outreach_message_body_file"]
def get_tts_voice() -> str:
"""
Gets the TTS voice from the config file.
Returns:
voice (str): The TTS voice
"""
with open(os.path.join(ROOT_DIR, "config.json"), "r") as file:
return json.load(file).get("tts_voice", "Jasper")
def get_assemblyai_api_key() -> str:
"""
Gets the AssemblyAI API key.
Returns:
key (str): The AssemblyAI API key
"""
with open(os.path.join(ROOT_DIR, "config.json"), "r") as file:
return json.load(file)["assembly_ai_api_key"]
def get_stt_provider() -> str:
"""
Gets the configured STT provider.
Returns:
provider (str): The STT provider
"""
with open(os.path.join(ROOT_DIR, "config.json"), "r") as file:
return json.load(file).get("stt_provider", "local_whisper")
def get_whisper_model() -> str:
"""
Gets the local Whisper model name.
Returns:
model (str): Whisper model name
"""
with open(os.path.join(ROOT_DIR, "config.json"), "r") as file:
return json.load(file).get("whisper_model", "base")
def get_whisper_device() -> str:
"""
Gets the target device for Whisper inference.
Returns:
device (str): Whisper device
"""
with open(os.path.join(ROOT_DIR, "config.json"), "r") as file:
return json.load(file).get("whisper_device", "auto")
def get_whisper_compute_type() -> str:
"""
Gets the compute type for Whisper inference.
Returns:
compute_type (str): Whisper compute type
"""
with open(os.path.join(ROOT_DIR, "config.json"), "r") as file:
return json.load(file).get("whisper_compute_type", "int8")
def equalize_subtitles(srt_path: str, max_chars: int = 10) -> None:
"""
Equalizes the subtitles in a SRT file.
Args:
srt_path (str): The path to the SRT file
max_chars (int): The maximum amount of characters in a subtitle
Returns:
None
"""
srt_equalizer.equalize_srt_file(srt_path, srt_path, max_chars)
def get_font() -> str:
"""
Gets the font from the config file.
Returns:
font (str): The font
"""
with open(os.path.join(ROOT_DIR, "config.json"), "r") as file:
return json.load(file)["font"]
def get_fonts_dir() -> str:
"""
Gets the fonts directory.
Returns:
dir (str): The fonts directory
"""
return os.path.join(ROOT_DIR, "fonts")
def get_imagemagick_path() -> str:
"""
Gets the path to ImageMagick.
Returns:
path (str): The path to ImageMagick
"""
with open(os.path.join(ROOT_DIR, "config.json"), "r") as file:
return json.load(file)["imagemagick_path"]
def get_script_sentence_length() -> int:
"""
Gets the forced script's sentence length.
In case there is no sentence length in config, returns 4 when none
Returns:
length (int): Length of script's sentence
"""
with open(os.path.join(ROOT_DIR, "config.json"), "r") as file:
config_json = json.load(file)
if (config_json.get("script_sentence_length") is not None):
return config_json["script_sentence_length"]
else:
return 4
================================================
FILE: src/constants.py
================================================
"""
This file contains all the constants used in the program.
"""
TWITTER_TEXTAREA_CLASS = "public-DraftStyleDefault-block public-DraftStyleDefault-ltr"
TWITTER_POST_BUTTON_XPATH = "/html/body/div[1]/div/div/div[2]/main/div/div/div/div[1]/div/div[3]/div/div[2]/div[1]/div/div/div/div[2]/div[2]/div[2]/div/div/div/div[3]"
OPTIONS = [
"YouTube Shorts Automation",
"Twitter Bot",
"Affiliate Marketing",
"Outreach",
"Quit"
]
TWITTER_OPTIONS = [
"Post something",
"Show all Posts",
"Setup CRON Job",
"Quit"
]
TWITTER_CRON_OPTIONS = [
"Once a day",
"Twice a day",
"Thrice a day",
"Quit"
]
YOUTUBE_OPTIONS = [
"Upload Short",
"Show all Shorts",
"Setup CRON Job",
"Quit"
]
YOUTUBE_CRON_OPTIONS = [
"Once a day",
"Twice a day",
"Thrice a day",
"Quit"
]
# YouTube Section
YOUTUBE_TEXTBOX_ID = "textbox"
YOUTUBE_MADE_FOR_KIDS_NAME = "VIDEO_MADE_FOR_KIDS_MFK"
YOUTUBE_NOT_MADE_FOR_KIDS_NAME = "VIDEO_MADE_FOR_KIDS_NOT_MFK"
YOUTUBE_NEXT_BUTTON_ID = "next-button"
YOUTUBE_RADIO_BUTTON_XPATH = "//*[@id=\"radioLabel\"]"
YOUTUBE_DONE_BUTTON_ID = "done-button"
# Amazon Section (AFM)$
AMAZON_PRODUCT_TITLE_ID = "productTitle"
AMAZON_FEATURE_BULLETS_ID = "feature-bullets"
================================================
FILE: src/cron.py
================================================
# RUN THIS N AMOUNT OF TIMES
import sys
from status import *
from cache import get_accounts
from config import get_verbose
from classes.Tts import TTS
from classes.Twitter import Twitter
from classes.YouTube import YouTube
from llm_provider import select_model
def main():
"""Main function to post content to Twitter or upload videos to YouTube.
This function determines its operation based on command-line arguments:
- If the purpose is "twitter", it initializes a Twitter account and posts a message.
- If the purpose is "youtube", it initializes a YouTube account, generates a video with TTS, and uploads it.
Command-line arguments:
sys.argv[1]: A string indicating the purpose, either "twitter" or "youtube".
sys.argv[2]: A string representing the account UUID.
The function also handles verbose output based on user settings and reports success or errors as appropriate.
Args:
None. The function uses command-line arguments accessed via sys.argv.
Returns:
None. The function performs operations based on the purpose and account UUID and does not return any value."""
purpose = str(sys.argv[1])
account_id = str(sys.argv[2])
model = str(sys.argv[3]) if len(sys.argv) > 3 else None
if model:
select_model(model)
else:
error("No Ollama model specified. Pass model name as third argument.")
sys.exit(1)
verbose = get_verbose()
if purpose == "twitter":
accounts = get_accounts("twitter")
if not account_id:
error("Account UUID cannot be empty.")
for acc in accounts:
if acc["id"] == account_id:
if verbose:
info("Initializing Twitter...")
twitter = Twitter(
acc["id"],
acc["nickname"],
acc["firefox_profile"],
acc["topic"]
)
twitter.post()
if verbose:
success("Done posting.")
break
elif purpose == "youtube":
tts = TTS()
accounts = get_accounts("youtube")
if not account_id:
error("Account UUID cannot be empty.")
for acc in accounts:
if acc["id"] == account_id:
if verbose:
info("Initializing YouTube...")
youtube = YouTube(
acc["id"],
acc["nickname"],
acc["firefox_profile"],
acc["niche"],
acc["language"]
)
youtube.generate_video(tts)
youtube.upload_video()
if verbose:
success("Uploaded Short.")
break
else:
error("Invalid Purpose, exiting...")
sys.exit(1)
if __name__ == "__main__":
main()
================================================
FILE: src/llm_provider.py
================================================
import ollama
from config import get_ollama_base_url
_selected_model: str | None = None
def _client() -> ollama.Client:
return ollama.Client(host=get_ollama_base_url())
def list_models() -> list[str]:
"""
Lists all models available on the local Ollama server.
Returns:
models (list[str]): Sorted list of model names.
"""
response = _client().list()
return sorted(m.model for m in response.models)
def select_model(model: str) -> None:
"""
Sets the model to use for all subsequent generate_text calls.
Args:
model (str): An Ollama model name (must be already pulled).
"""
global _selected_model
_selected_model = model
def get_active_model() -> str | None:
"""
Returns the currently selected model, or None if none has been selected.
"""
return _selected_model
def generate_text(prompt: str, model_name: str = None) -> str:
"""
Generates text using the local Ollama server.
Args:
prompt (str): User prompt
model_name (str): Optional model name override
Returns:
response (str): Generated text
"""
model = model_name or _selected_model
if not model:
raise RuntimeError(
"No Ollama model selected. Call select_model() first or pass model_name."
)
response = _client().chat(
model=model,
messages=[{"role": "user", "content": prompt}],
)
return response["message"]["content"].strip()
================================================
FILE: src/main.py
================================================
import schedule
import subprocess
from art import *
from cache import *
from utils import *
from config import *
from status import *
from uuid import uuid4
from constants import *
from classes.Tts import TTS
from termcolor import colored
from classes.Twitter import Twitter
from classes.YouTube import YouTube
from prettytable import PrettyTable
from classes.Outreach import Outreach
from classes.AFM import AffiliateMarketing
from llm_provider import list_models, select_model, get_active_model
def main():
"""Main entry point for the application, providing a menu-driven interface
to manage YouTube, Twitter bots, Affiliate Marketing, and Outreach tasks.
This function allows users to:
1. Start the YouTube Shorts Automater to manage YouTube accounts,
generate and upload videos, and set up CRON jobs.
2. Start a Twitter Bot to manage Twitter accounts, post tweets, and
schedule posts using CRON jobs.
3. Manage Affiliate Marketing by creating pitches and sharing them via
Twitter accounts.
4. Initiate an Outreach process for engagement and promotion tasks.
5. Exit the application.
The function continuously prompts users for input, validates it, and
executes the selected option until the user chooses to quit.
Args:
None
Returns:
None"""
# Get user input
# user_input = int(question("Select an option: "))
valid_input = False
while not valid_input:
try:
# Show user options
info("\n============ OPTIONS ============", False)
for idx, option in enumerate(OPTIONS):
print(colored(f" {idx + 1}. {option}", "cyan"))
info("=================================\n", False)
user_input = input("Select an option: ").strip()
if user_input == '':
print("\n" * 100)
raise ValueError("Empty input is not allowed.")
user_input = int(user_input)
valid_input = True
except ValueError as e:
print("\n" * 100)
print(f"Invalid input: {e}")
# Start the selected option
if user_input == 1:
info("Starting YT Shorts Automater...")
cached_accounts = get_accounts("youtube")
if len(cached_accounts) == 0:
warning("No accounts found in cache. Create one now?")
user_input = question("Yes/No: ")
if user_input.lower() == "yes":
generated_uuid = str(uuid4())
success(f" => Generated ID: {generated_uuid}")
nickname = question(" => Enter a nickname for this account: ")
fp_profile = question(" => Enter the path to the Firefox profile: ")
niche = question(" => Enter the account niche: ")
language = question(" => Enter the account language: ")
account_data = {
"id": generated_uuid,
"nickname": nickname,
"firefox_profile": fp_profile,
"niche": niche,
"language": language,
"videos": [],
}
add_account("youtube", account_data)
success("Account configured successfully!")
else:
table = PrettyTable()
table.field_names = ["ID", "UUID", "Nickname", "Niche"]
for account in cached_accounts:
table.add_row([cached_accounts.index(account) + 1, colored(account["id"], "cyan"), colored(account["nickname"], "blue"), colored(account["niche"], "green")])
print(table)
info("Type 'd' to delete an account.", False)
user_input = question("Select an account to start (or 'd' to delete): ").strip()
if user_input.lower() == "d":
delete_input = question("Enter account number to delete: ").strip()
account_to_delete = None
for account in cached_accounts:
if str(cached_accounts.index(account) + 1) == delete_input:
account_to_delete = account
break
if account_to_delete is None:
error("Invalid account selected. Please try again.", "red")
else:
confirm = question(f"Are you sure you want to delete '{account_to_delete['nickname']}'? (Yes/No): ").strip().lower()
if confirm == "yes":
remove_account("youtube", account_to_delete["id"])
success("Account removed successfully!")
else:
warning("Account deletion canceled.", False)
return
selected_account = None
for account in cached_accounts:
if str(cached_accounts.index(account) + 1) == user_input:
selected_account = account
if selected_account is None:
error("Invalid account selected. Please try again.", "red")
main()
else:
youtube = YouTube(
selected_account["id"],
selected_account["nickname"],
selected_account["firefox_profile"],
selected_account["niche"],
selected_account["language"]
)
while True:
rem_temp_files()
info("\n============ OPTIONS ============", False)
for idx, youtube_option in enumerate(YOUTUBE_OPTIONS):
print(colored(f" {idx + 1}. {youtube_option}", "cyan"))
info("=================================\n", False)
# Get user input
user_input = int(question("Select an option: "))
tts = TTS()
if user_input == 1:
youtube.generate_video(tts)
upload_to_yt = question("Do you want to upload this video to YouTube? (Yes/No): ")
if upload_to_yt.lower() == "yes":
youtube.upload_video()
elif user_input == 2:
videos = youtube.get_videos()
if len(videos) > 0:
videos_table = PrettyTable()
videos_table.field_names = ["ID", "Date", "Title"]
for video in videos:
videos_table.add_row([
videos.index(video) + 1,
colored(video["date"], "blue"),
colored(video["title"][:60] + "...", "green")
])
print(videos_table)
else:
warning(" No videos found.")
elif user_input == 3:
info("How often do you want to upload?")
info("\n============ OPTIONS ============", False)
for idx, cron_option in enumerate(YOUTUBE_CRON_OPTIONS):
print(colored(f" {idx + 1}. {cron_option}", "cyan"))
info("=================================\n", False)
user_input = int(question("Select an Option: "))
cron_script_path = os.path.join(ROOT_DIR, "src", "cron.py")
command = ["python", cron_script_path, "youtube", selected_account['id'], get_active_model()]
def job():
subprocess.run(command)
if user_input == 1:
# Upload Once
schedule.every(1).day.do(job)
success("Set up CRON Job.")
elif user_input == 2:
# Upload Twice a day
schedule.every().day.at("10:00").do(job)
schedule.every().day.at("16:00").do(job)
success("Set up CRON Job.")
else:
break
elif user_input == 4:
if get_verbose():
info(" => Climbing Options Ladder...", False)
break
elif user_input == 2:
info("Starting Twitter Bot...")
cached_accounts = get_accounts("twitter")
if len(cached_accounts) == 0:
warning("No accounts found in cache. Create one now?")
user_input = question("Yes/No: ")
if user_input.lower() == "yes":
generated_uuid = str(uuid4())
success(f" => Generated ID: {generated_uuid}")
nickname = question(" => Enter a nickname for this account: ")
fp_profile = question(" => Enter the path to the Firefox profile: ")
topic = question(" => Enter the account topic: ")
add_account("twitter", {
"id": generated_uuid,
"nickname": nickname,
"firefox_profile": fp_profile,
"topic": topic,
"posts": []
})
else:
table = PrettyTable()
table.field_names = ["ID", "UUID", "Nickname", "Account Topic"]
for account in cached_accounts:
table.add_row([cached_accounts.index(account) + 1, colored(account["id"], "cyan"), colored(account["nickname"], "blue"), colored(account["topic"], "green")])
print(table)
info("Type 'd' to delete an account.", False)
user_input = question("Select an account to start (or 'd' to delete): ").strip()
if user_input.lower() == "d":
delete_input = question("Enter account number to delete: ").strip()
account_to_delete = None
for account in cached_accounts:
if str(cached_accounts.index(account) + 1) == delete_input:
account_to_delete = account
break
if account_to_delete is None:
error("Invalid account selected. Please try again.", "red")
else:
confirm = question(f"Are you sure you want to delete '{account_to_delete['nickname']}'? (Yes/No): ").strip().lower()
if confirm == "yes":
remove_account("twitter", account_to_delete["id"])
success("Account removed successfully!")
else:
warning("Account deletion canceled.", False)
return
selected_account = None
for account in cached_accounts:
if str(cached_accounts.index(account) + 1) == user_input:
selected_account = account
if selected_account is None:
error("Invalid account selected. Please try again.", "red")
main()
else:
twitter = Twitter(selected_account["id"], selected_account["nickname"], selected_account["firefox_profile"], selected_account["topic"])
while True:
info("\n============ OPTIONS ============", False)
for idx, twitter_option in enumerate(TWITTER_OPTIONS):
print(colored(f" {idx + 1}. {twitter_option}", "cyan"))
info("=================================\n", False)
# Get user input
user_input = int(question("Select an option: "))
if user_input == 1:
twitter.post()
elif user_input == 2:
posts = twitter.get_posts()
posts_table = PrettyTable()
posts_table.field_names = ["ID", "Date", "Content"]
for post in posts:
posts_table.add_row([
posts.index(post) + 1,
colored(post["date"], "blue"),
colored(post["content"][:60] + "...", "green")
])
print(posts_table)
elif user_input == 3:
info("How often do you want to post?")
info("\n============ OPTIONS ============", False)
for idx, cron_option in enumerate(TWITTER_CRON_OPTIONS):
print(colored(f" {idx + 1}. {cron_option}", "cyan"))
info("=================================\n", False)
user_input = int(question("Select an Option: "))
cron_script_path = os.path.join(ROOT_DIR, "src", "cron.py")
command = ["python", cron_script_path, "twitter", selected_account['id'], get_active_model()]
def job():
subprocess.run(command)
if user_input == 1:
# Post Once a day
schedule.every(1).day.do(job)
success("Set up CRON Job.")
elif user_input == 2:
# Post twice a day
schedule.every().day.at("10:00").do(job)
schedule.every().day.at("16:00").do(job)
success("Set up CRON Job.")
elif user_input == 3:
# Post thrice a day
schedule.every().day.at("08:00").do(job)
schedule.every().day.at("12:00").do(job)
schedule.every().day.at("18:00").do(job)
success("Set up CRON Job.")
else:
break
elif user_input == 4:
if get_verbose():
info(" => Climbing Options Ladder...", False)
break
elif user_input == 3:
info("Starting Affiliate Marketing...")
cached_products = get_products()
if len(cached_products) == 0:
warning("No products found in cache. Create one now?")
user_input = question("Yes/No: ")
if user_input.lower() == "yes":
affiliate_link = question(" => Enter the affiliate link: ")
twitter_uuid = question(" => Enter the Twitter Account UUID: ")
# Find the account
account = None
for acc in get_accounts("twitter"):
if acc["id"] == twitter_uuid:
account = acc
add_product({
"id": str(uuid4()),
"affiliate_link": affiliate_link,
"twitter_uuid": twitter_uuid
})
afm = AffiliateMarketing(affiliate_link, account["firefox_profile"], account["id"], account["nickname"], account["topic"])
afm.generate_pitch()
afm.share_pitch("twitter")
else:
table = PrettyTable()
table.field_names = ["ID", "Affiliate Link", "Twitter Account UUID"]
for product in cached_products:
table.add_row([cached_products.index(product) + 1, colored(product["affiliate_link"], "cyan"), colored(product["twitter_uuid"], "blue")])
print(table)
user_input = question("Select a product to start: ")
selected_product = None
for product in cached_products:
if str(cached_products.index(product) + 1) == user_input:
selected_product = product
if selected_product is None:
error("Invalid product selected. Please try again.", "red")
main()
else:
# Find the account
account = None
for acc in get_accounts("twitter"):
if acc["id"] == selected_product["twitter_uuid"]:
account = acc
afm = AffiliateMarketing(selected_product["affiliate_link"], account["firefox_profile"], account["id"], account["nickname"], account["topic"])
afm.generate_pitch()
afm.share_pitch("twitter")
elif user_input == 4:
info("Starting Outreach...")
outreach = Outreach()
outreach.start()
elif user_input == 5:
if get_verbose():
print(colored(" => Quitting...", "blue"))
sys.exit(0)
else:
error("Invalid option selected. Please try again.", "red")
main()
if __name__ == "__main__":
# Print ASCII Banner
print_banner()
first_time = get_first_time_running()
if first_time:
print(colored("Hey! It looks like you're running MoneyPrinter V2 for the first time. Let's get you setup first!", "yellow"))
# Setup file tree
assert_folder_structure()
# Remove temporary files
rem_temp_files()
# Fetch MP3 Files
fetch_songs()
# Select Ollama model — use config value if set, otherwise pick interactively
configured_model = get_ollama_model()
if configured_model:
select_model(configured_model)
success(f"Using configured model: {configured_model}")
else:
try:
models = list_models()
except Exception as e:
error(f"Could not connect to Ollama: {e}")
sys.exit(1)
if not models:
error("No models found on Ollama. Pull a model first (e.g. 'ollama pull llama3.2:3b').")
sys.exit(1)
info("\n========== OLLAMA MODELS =========", False)
for idx, model_name in enumerate(models):
print(colored(f" {idx + 1}. {model_name}", "cyan"))
info("==================================\n", False)
model_choice = None
while model_choice is None:
raw = input(colored("Select a model: ", "magenta")).strip()
try:
choice_idx = int(raw) - 1
if 0 <= choice_idx < len(models):
model_choice = models[choice_idx]
else:
warning("Invalid selection. Try again.")
except ValueError:
warning("Please enter a number.")
select_model(model_choice)
success(f"Using model: {model_choice}")
while True:
main()
================================================
FILE: src/status.py
================================================
from termcolor import colored
def error(message: str, show_emoji: bool = True) -> None:
"""
Prints an error message.
Args:
message (str): The error message
show_emoji (bool): Whether to show the emoji
Returns:
None
"""
emoji = "❌" if show_emoji else ""
print(colored(f"{emoji} {message}", "red"))
def success(message: str, show_emoji: bool = True) -> None:
"""
Prints a success message.
Args:
message (str): The success message
show_emoji (bool): Whether to show the emoji
Returns:
None
"""
emoji = "✅" if show_emoji else ""
print(colored(f"{emoji} {message}", "green"))
def info(message: str, show_emoji: bool = True) -> None:
"""
Prints an info message.
Args:
message (str): The info message
show_emoji (bool): Whether to show the emoji
Returns:
None
"""
emoji = "ℹ️" if show_emoji else ""
print(colored(f"{emoji} {message}", "magenta"))
def warning(message: str, show_emoji: bool = True) -> None:
"""
Prints a warning message.
Args:
message (str): The warning message
show_emoji (bool): Whether to show the emoji
Returns:
None
"""
emoji = "⚠️" if show_emoji else ""
print(colored(f"{emoji} {message}", "yellow"))
def question(message: str, show_emoji: bool = True) -> str:
"""
Prints a question message and returns the user's input.
Args:
message (str): The question message
show_emoji (bool): Whether to show the emoji
Returns:
user_input (str): The user's input
"""
emoji = "❓" if show_emoji else ""
return input(colored(f"{emoji} {message}", "magenta"))
================================================
FILE: src/utils.py
================================================
import os
import random
import zipfile
import requests
import platform
from status import *
from config import *
DEFAULT_SONG_ARCHIVE_URLS = []
def close_running_selenium_instances() -> None:
"""
Closes any running Selenium instances.
Returns:
None
"""
try:
info(" => Closing running Selenium instances...")
# Kill all running Firefox instances
if platform.system() == "Windows":
os.system("taskkill /f /im firefox.exe")
else:
os.system("pkill firefox")
success(" => Closed running Selenium instances.")
except Exception as e:
error(f"Error occurred while closing running Selenium instances: {str(e)}")
def build_url(youtube_video_id: str) -> str:
"""
Builds the URL to the YouTube video.
Args:
youtube_video_id (str): The YouTube video ID.
Returns:
url (str): The URL to the YouTube video.
"""
return f"https://www.youtube.com/watch?v={youtube_video_id}"
def rem_temp_files() -> None:
"""
Removes temporary files in the `.mp` directory.
Returns:
None
"""
# Path to the `.mp` directory
mp_dir = os.path.join(ROOT_DIR, ".mp")
files = os.listdir(mp_dir)
for file in files:
if not file.endswith(".json"):
os.remove(os.path.join(mp_dir, file))
def fetch_songs() -> None:
"""
Downloads songs into songs/ directory to use with geneated videos.
Returns:
None
"""
try:
info(f" => Fetching songs...")
files_dir = os.path.join(ROOT_DIR, "Songs")
if not os.path.exists(files_dir):
os.mkdir(files_dir)
if get_verbose():
info(f" => Created directory: {files_dir}")
else:
existing_audio_files = [
name
for name in os.listdir(files_dir)
if os.path.isfile(os.path.join(files_dir, name))
and name.lower().endswith((".mp3", ".wav", ".m4a", ".aac", ".ogg"))
]
if len(existing_audio_files) > 0:
return
configured_url = get_zip_url().strip()
download_urls = [configured_url] if configured_url else []
download_urls.extend(DEFAULT_SONG_ARCHIVE_URLS)
archive_path = os.path.join(files_dir, "songs.zip")
downloaded = False
for download_url in download_urls:
try:
response = requests.get(download_url, timeout=60)
response.raise_for_status()
with open(archive_path, "wb") as file:
file.write(response.content)
SAFE_EXTENSIONS = (".mp3", ".wav", ".m4a", ".aac", ".ogg", ".flac")
with zipfile.ZipFile(archive_path, "r") as zf:
for member in zf.namelist():
basename = os.path.basename(member)
if not basename or not basename.lower().endswith(SAFE_EXTENSIONS):
warning(f"Skipping non-audio file in archive: {member}")
continue
if ".." in member or member.startswith("/"):
warning(f"Skipping suspicious path in archive: {member}")
continue
zf.extract(member, files_dir)
downloaded = True
break
except Exception as err:
warning(f"Failed to fetch songs from {download_url}: {err}")
if not downloaded:
raise RuntimeError(
"Could not download a valid songs archive from any configured URL"
)
# Remove the zip file
if os.path.exists(archive_path):
os.remove(archive_path)
success(" => Downloaded Songs to ../Songs.")
except Exception as e:
error(f"Error occurred while fetching songs: {str(e)}")
def choose_random_song() -> str:
"""
Chooses a random song from the songs/ directory.
Returns:
str: The path to the chosen song.
"""
try:
songs_dir = os.path.join(ROOT_DIR, "Songs")
songs = [
name
for name in os.listdir(songs_dir)
if os.path.isfile(os.path.join(songs_dir, name))
and name.lower().endswith((".mp3", ".wav", ".m4a", ".aac", ".ogg"))
]
if len(songs) == 0:
raise RuntimeError("No audio files found in Songs directory")
song = random.choice(songs)
success(f" => Chose song: {song}")
return os.path.join(ROOT_DIR, "Songs", song)
except Exception as e:
error(f"Error occurred while choosing random song: {str(e)}")
raise
gitextract_fa8ip_7i/
├── .github/
│ └── FUNDING.yml
├── .gitignore
├── .python-version
├── AGENTS.md
├── CLAUDE.md
├── CODE_OF_CONDUCT.md
├── CONTRIBUTING.md
├── LICENSE
├── README.md
├── assets/
│ └── banner.txt
├── config.example.json
├── docs/
│ ├── AffiliateMarketing.md
│ ├── Configuration.md
│ ├── Roadmap.md
│ ├── TwitterBot.md
│ └── YouTube.md
├── requirements.txt
├── scripts/
│ ├── preflight_local.py
│ ├── setup_local.sh
│ └── upload_video.sh
└── src/
├── art.py
├── cache.py
├── classes/
│ ├── AFM.py
│ ├── Outreach.py
│ ├── Tts.py
│ ├── Twitter.py
│ └── YouTube.py
├── config.py
├── constants.py
├── cron.py
├── llm_provider.py
├── main.py
├── status.py
└── utils.py
SYMBOL INDEX (115 symbols across 14 files)
FILE: scripts/preflight_local.py
function ok (line 14) | def ok(msg: str) -> None:
function warn (line 18) | def warn(msg: str) -> None:
function fail (line 22) | def fail(msg: str) -> None:
function check_url (line 26) | def check_url(url: str, timeout: int = 3) -> Tuple[bool, str]:
function main (line 34) | def main() -> int:
FILE: src/art.py
function print_banner (line 4) | def print_banner() -> None:
FILE: src/cache.py
function get_cache_path (line 7) | def get_cache_path() -> str:
function get_afm_cache_path (line 16) | def get_afm_cache_path() -> str:
function get_twitter_cache_path (line 25) | def get_twitter_cache_path() -> str:
function get_youtube_cache_path (line 34) | def get_youtube_cache_path() -> str:
function get_provider_cache_path (line 43) | def get_provider_cache_path(provider: str) -> str:
function get_accounts (line 63) | def get_accounts(provider: str) -> List[dict]:
function add_account (line 94) | def add_account(provider: str, account: dict) -> None:
function remove_account (line 119) | def remove_account(provider: str, account_id: str) -> None:
function get_products (line 144) | def get_products() -> List[dict]:
function add_product (line 164) | def add_product(product: dict) -> None:
function get_results_cache_path (line 186) | def get_results_cache_path() -> str:
FILE: src/classes/AFM.py
class AffiliateMarketing (line 18) | class AffiliateMarketing:
method __init__ (line 23) | def __init__(
method scrape_product_information (line 91) | def scrape_product_information(self) -> None:
method generate_response (line 119) | def generate_response(self, prompt: str) -> str:
method generate_pitch (line 131) | def generate_pitch(self) -> str:
method share_pitch (line 152) | def share_pitch(self, where: str) -> None:
method quit (line 171) | def quit(self) -> None:
FILE: src/classes/Outreach.py
class Outreach (line 19) | class Outreach:
method __init__ (line 24) | def __init__(self) -> None:
method _find_scraper_dir (line 40) | def _find_scraper_dir(self) -> str:
method is_go_installed (line 49) | def is_go_installed(self) -> bool:
method unzip_file (line 63) | def unzip_file(self, zip_link: str) -> None:
method build_scraper (line 85) | def build_scraper(self) -> None:
method run_scraper_with_args_for_30_seconds (line 116) | def run_scraper_with_args_for_30_seconds(self, args: str, timeout=300)...
method get_items_from_file (line 147) | def get_items_from_file(self, file_name: str) -> list:
method set_email_for_website (line 163) | def set_email_for_website(self, index: int, website: str, output_file:...
method start (line 199) | def start(self) -> None:
FILE: src/classes/Tts.py
class TTS (line 10) | class TTS:
method __init__ (line 11) | def __init__(self) -> None:
method synthesize (line 15) | def synthesize(self, text, output_file=os.path.join(ROOT_DIR, ".mp", "...
FILE: src/classes/Twitter.py
class Twitter (line 24) | class Twitter:
method __init__ (line 29) | def __init__(
method post (line 73) | def post(self, text: Optional[str] = None) -> None:
method get_posts (line 143) | def get_posts(self) -> List[dict]:
method add_post (line 172) | def add_post(self, post: dict) -> None:
method generate_post (line 198) | def generate_post(self) -> str:
FILE: src/classes/YouTube.py
class YouTube (line 35) | class YouTube:
method __init__ (line 50) | def __init__(
method niche (line 103) | def niche(self) -> str:
method language (line 113) | def language(self) -> str:
method generate_response (line 122) | def generate_response(self, prompt: str, model_name: str = None) -> str:
method generate_topic (line 134) | def generate_topic(self) -> str:
method generate_script (line 152) | def generate_script(self) -> str:
method generate_metadata (line 200) | def generate_metadata(self) -> dict:
method generate_prompts (line 224) | def generate_prompts(self) -> List[str]:
method _persist_image (line 297) | def _persist_image(self, image_bytes: bytes, provider_label: str) -> str:
method generate_image_nanobanana2 (line 319) | def generate_image_nanobanana2(self, prompt: str) -> str:
method generate_image (line 380) | def generate_image(self, prompt: str) -> str:
method generate_script_to_speech (line 392) | def generate_script_to_speech(self, tts_instance: TTS) -> str:
method add_video (line 416) | def add_video(self, video: dict) -> None:
method generate_subtitles (line 444) | def generate_subtitles(self, audio_path: str) -> str:
method generate_subtitles_assemblyai (line 465) | def generate_subtitles_assemblyai(self, audio_path: str) -> str:
method _format_srt_timestamp (line 488) | def _format_srt_timestamp(self, seconds: float) -> str:
method generate_subtitles_local_whisper (line 505) | def generate_subtitles_local_whisper(self, audio_path: str) -> str:
method combine (line 552) | def combine(self) -> str:
method generate_video (line 649) | def generate_video(self, tts_instance: TTS) -> str:
method get_channel_id (line 688) | def get_channel_id(self) -> str:
method upload_video (line 703) | def upload_video(self) -> bool:
method get_videos (line 855) | def get_videos(self) -> List[dict]:
FILE: src/config.py
function assert_folder_structure (line 10) | def assert_folder_structure() -> None:
function get_first_time_running (line 23) | def get_first_time_running() -> bool:
function get_email_credentials (line 32) | def get_email_credentials() -> dict:
function get_verbose (line 42) | def get_verbose() -> bool:
function get_firefox_profile_path (line 52) | def get_firefox_profile_path() -> str:
function get_headless (line 62) | def get_headless() -> bool:
function get_ollama_base_url (line 72) | def get_ollama_base_url() -> str:
function get_ollama_model (line 82) | def get_ollama_model() -> str:
function get_twitter_language (line 92) | def get_twitter_language() -> str:
function get_nanobanana2_api_base_url (line 102) | def get_nanobanana2_api_base_url() -> str:
function get_nanobanana2_api_key (line 115) | def get_nanobanana2_api_key() -> str:
function get_nanobanana2_model (line 126) | def get_nanobanana2_model() -> str:
function get_nanobanana2_aspect_ratio (line 136) | def get_nanobanana2_aspect_ratio() -> str:
function get_threads (line 146) | def get_threads() -> int:
function get_zip_url (line 156) | def get_zip_url() -> str:
function get_is_for_kids (line 166) | def get_is_for_kids() -> bool:
function get_google_maps_scraper_zip_url (line 176) | def get_google_maps_scraper_zip_url() -> str:
function get_google_maps_scraper_niche (line 186) | def get_google_maps_scraper_niche() -> str:
function get_scraper_timeout (line 196) | def get_scraper_timeout() -> int:
function get_outreach_message_subject (line 206) | def get_outreach_message_subject() -> str:
function get_outreach_message_body_file (line 216) | def get_outreach_message_body_file() -> str:
function get_tts_voice (line 226) | def get_tts_voice() -> str:
function get_assemblyai_api_key (line 236) | def get_assemblyai_api_key() -> str:
function get_stt_provider (line 246) | def get_stt_provider() -> str:
function get_whisper_model (line 256) | def get_whisper_model() -> str:
function get_whisper_device (line 266) | def get_whisper_device() -> str:
function get_whisper_compute_type (line 276) | def get_whisper_compute_type() -> str:
function equalize_subtitles (line 286) | def equalize_subtitles(srt_path: str, max_chars: int = 10) -> None:
function get_font (line 299) | def get_font() -> str:
function get_fonts_dir (line 309) | def get_fonts_dir() -> str:
function get_imagemagick_path (line 318) | def get_imagemagick_path() -> str:
function get_script_sentence_length (line 328) | def get_script_sentence_length() -> int:
FILE: src/cron.py
function main (line 12) | def main():
FILE: src/llm_provider.py
function _client (line 8) | def _client() -> ollama.Client:
function list_models (line 12) | def list_models() -> list[str]:
function select_model (line 23) | def select_model(model: str) -> None:
function get_active_model (line 34) | def get_active_model() -> str | None:
function generate_text (line 41) | def generate_text(prompt: str, model_name: str = None) -> str:
FILE: src/main.py
function main (line 20) | def main():
FILE: src/status.py
function error (line 3) | def error(message: str, show_emoji: bool = True) -> None:
function success (line 17) | def success(message: str, show_emoji: bool = True) -> None:
function info (line 31) | def info(message: str, show_emoji: bool = True) -> None:
function warning (line 45) | def warning(message: str, show_emoji: bool = True) -> None:
function question (line 59) | def question(message: str, show_emoji: bool = True) -> str:
FILE: src/utils.py
function close_running_selenium_instances (line 13) | def close_running_selenium_instances() -> None:
function build_url (line 35) | def build_url(youtube_video_id: str) -> str:
function rem_temp_files (line 48) | def rem_temp_files() -> None:
function fetch_songs (line 65) | def fetch_songs() -> None:
function choose_random_song (line 137) | def choose_random_song() -> str:
Condensed preview — 34 files, each showing path, character count, and a content snippet. Download the .json file or copy for the full structured content (176K chars).
[
{
"path": ".github/FUNDING.yml",
"chars": 71,
"preview": "# These are supported funding model platforms\n\ngithub: [FujiwaraChoki]\n"
},
{
"path": ".gitignore",
"chars": 102,
"preview": "__pycache__\nconfig.json\n.mp/\nvenv/\nSongs/\ngoogle-maps-scraper-0.9.7/\nniche.txt\n*.exe\nauto.sh\n.DS_Store"
},
{
"path": ".python-version",
"chars": 5,
"preview": "3.12\n"
},
{
"path": "AGENTS.md",
"chars": 2516,
"preview": "# Repository Guidelines\n\n## Project Structure & Module Organization\n- `src/` contains the application code. Use `src/mai"
},
{
"path": "CLAUDE.md",
"chars": 4245,
"preview": "# CLAUDE.md\n\nThis file provides guidance to Claude Code (claude.ai/code) when working with code in this repository.\n\n## "
},
{
"path": "CODE_OF_CONDUCT.md",
"chars": 4009,
"preview": "# Contributor Code of Conduct\n\nOur values guide us in our day-to-day interactions and decision-making. Our open source p"
},
{
"path": "CONTRIBUTING.md",
"chars": 1260,
"preview": "# Contributing\n\nMoneyPrinterV2 is an open source project and we encourage contributions. However, we ask that you follow"
},
{
"path": "LICENSE",
"chars": 34518,
"preview": " GNU AFFERO GENERAL PUBLIC LICENSE\n Version 3, 19 November 2007\n\n Copyright (C)"
},
{
"path": "README.md",
"chars": 4377,
"preview": "# MoneyPrinter V2\n\n> ♥︎ **Sponsor**: The Best AI Chat App: [shiori.ai](https://www.shiori.ai)\n\n---\n\n> 𝕏 Also, follow me "
},
{
"path": "assets/banner.txt",
"chars": 649,
"preview": "\n __ __ _____ _ _ __ _____ \n | \\/ | | __ \\"
},
{
"path": "config.example.json",
"chars": 1143,
"preview": "{\n \"verbose\": true,\n \"firefox_profile\": \"\",\n \"headless\": false,\n \"ollama_base_url\": \"http://127.0.0.1:11434\",\n \"oll"
},
{
"path": "docs/AffiliateMarketing.md",
"chars": 1115,
"preview": "# AFM\n\nThis class is responsible for the Affiliate Marketing part of MPV2. It uses Ollama (as all other classes) as its "
},
{
"path": "docs/Configuration.md",
"chars": 5321,
"preview": "# Configuration\n\nAll your configurations will be in a file in the root directory, called `config.json`, which is a copy "
},
{
"path": "docs/Roadmap.md",
"chars": 680,
"preview": "# MPV2 Roadmap\n\nThis document outlines the features that need to be implemented in MPV2.\n\n## Features\n\n- [ ] Automated C"
},
{
"path": "docs/TwitterBot.md",
"chars": 599,
"preview": "# Twitter Bot\n\nThis bot is designed to automate the process of growing a Twitter account. Once you created a new account"
},
{
"path": "docs/YouTube.md",
"chars": 1010,
"preview": "# YouTube Shorts Automater\n\nMPV2 uses a similar implementation of V1 (see [MPV1](https://github.com/FujiwaraChoki/MoneyP"
},
{
"path": "requirements.txt",
"chars": 313,
"preview": "wheel\ntermcolor\nschedule\nkittentts @ https://github.com/KittenML/KittenTTS/releases/download/0.8.1/kittentts-0.8.1-py3-n"
},
{
"path": "scripts/preflight_local.py",
"chars": 3662,
"preview": "#!/usr/bin/env python3\nimport json\nimport os\nimport sys\nfrom typing import Tuple\n\nimport requests\n\n\nROOT_DIR = os.path.d"
},
{
"path": "scripts/setup_local.sh",
"chars": 3713,
"preview": "#!/usr/bin/env bash\nset -euo pipefail\n\nROOT_DIR=\"$(cd \"$(dirname \"${BASH_SOURCE[0]}\")/..\" && pwd)\"\ncd \"$ROOT_DIR\"\n\necho "
},
{
"path": "scripts/upload_video.sh",
"chars": 774,
"preview": "#!/bin/bash\n\n# Script to generate & Upload a video to YT Shorts\n\n# Check which interpreter to use (python)\nif [ -x \"$(co"
},
{
"path": "src/art.py",
"chars": 282,
"preview": "from config import ROOT_DIR\nfrom termcolor import colored\n\ndef print_banner() -> None:\n \"\"\"\n Prints the introducto"
},
{
"path": "src/cache.py",
"chars": 4780,
"preview": "import os\nimport json\n\nfrom typing import List\nfrom config import ROOT_DIR\n\ndef get_cache_path() -> str:\n \"\"\"\n Get"
},
{
"path": "src/classes/AFM.py",
"chars": 5340,
"preview": "import os\nfrom urllib.parse import urlparse\nfrom typing import Any\n\nfrom status import *\nfrom config import *\nfrom const"
},
{
"path": "src/classes/Outreach.py",
"chars": 9847,
"preview": "import os\nimport io\nimport re\nimport csv\nimport time\nimport glob\nimport shlex\nimport zipfile\nimport yagmail\nimport reque"
},
{
"path": "src/classes/Tts.py",
"chars": 563,
"preview": "import os\nimport soundfile as sf\nfrom kittentts import KittenTTS as KittenModel\n\nfrom config import ROOT_DIR, get_tts_vo"
},
{
"path": "src/classes/Twitter.py",
"chars": 6935,
"preview": "import re\nimport sys\nimport time\nimport os\nimport json\n\nfrom cache import *\nfrom config import *\nfrom status import *\nfr"
},
{
"path": "src/classes/YouTube.py",
"chars": 28711,
"preview": "import re\nimport base64\nimport json\nimport time\nimport os\nimport requests\nimport assemblyai as aai\n\nfrom utils import *\n"
},
{
"path": "src/config.py",
"chars": 9568,
"preview": "import os\nimport sys\nimport json\nimport srt_equalizer\n\nfrom termcolor import colored\n\nROOT_DIR = os.path.dirname(sys.pat"
},
{
"path": "src/constants.py",
"chars": 1247,
"preview": "\"\"\"\nThis file contains all the constants used in the program.\n\"\"\"\n\nTWITTER_TEXTAREA_CLASS = \"public-DraftStyleDefault-bl"
},
{
"path": "src/cron.py",
"chars": 2928,
"preview": "# RUN THIS N AMOUNT OF TIMES\nimport sys\n\nfrom status import *\nfrom cache import get_accounts\nfrom config import get_verb"
},
{
"path": "src/llm_provider.py",
"chars": 1490,
"preview": "import ollama\n\nfrom config import get_ollama_base_url\n\n_selected_model: str | None = None\n\n\ndef _client() -> ollama.Clie"
},
{
"path": "src/main.py",
"chars": 18951,
"preview": "import schedule\nimport subprocess\n\nfrom art import *\nfrom cache import *\nfrom utils import *\nfrom config import *\nfrom s"
},
{
"path": "src/status.py",
"chars": 1735,
"preview": "from termcolor import colored\n\ndef error(message: str, show_emoji: bool = True) -> None:\n \"\"\"\n Prints an error mes"
},
{
"path": "src/utils.py",
"chars": 4754,
"preview": "import os\nimport random\nimport zipfile\nimport requests\nimport platform\n\nfrom status import *\nfrom config import *\n\nDEFAU"
}
]
About this extraction
This page contains the full source code of the FujiwaraChoki/MoneyPrinterV2 GitHub repository, extracted and formatted as plain text for AI agents and large language models (LLMs). The extraction includes 34 files (163.3 KB), approximately 37.5k tokens, and a symbol index with 115 extracted functions, classes, methods, constants, and types. Use this with OpenClaw, Claude, ChatGPT, Cursor, Windsurf, or any other AI tool that accepts text input. You can copy the full output to your clipboard or download it as a .txt file.
Extracted by GitExtract — free GitHub repo to text converter for AI. Built by Nikandr Surkov.