moneyprinterturbo-expert

name

moneyprinterturbo-expert

description

Expert knowledge of the MoneyPrinterTurbo codebase: the full AI short-video generation pipeline (LLM script -> search terms -> TTS audio -> subtitles -> stock-video sourcing -> clipping/concat -> final compositing), its FastAPI service, Streamlit WebUI, configuration system, and deployment. Use when working on, debugging, extending, or explaining anything in this repository: adding LLM/TTS/video-source providers, fixing subtitle timing, changing video composition, configuring config.toml, task/state management, or Docker setup.

MoneyPrinterTurbo Expert

MoneyPrinterTurbo generates complete short videos (9:16, 16:9 or 1:1) from a single subject string: an LLM writes the script, TTS narrates it, subtitles are aligned to the speech, stock footage is fetched and cut to match the audio, and everything is composited with MoviePy/FFmpeg into final-{n}.mp4.

Mental model (read this first)

One orchestrator drives everything: app/services/task.py::start(task_id, params, stop_at="video"). It runs the stages below in order, persisting progress into a state store after each one. stop_at checkpoints (script, terms, audio, subtitle, materials, video) let callers run a partial pipeline (this is how the /audio and /subtitle API endpoints reuse the same code path).

#	Stage	Service / key function	Output
1	Script	llm.py::generate_script()	plain-text script
2	Search terms	llm.py::generate_terms()	JSON list of English terms
3	TTS audio	voice.py::tts()	audio.mp3 + SubMaker timings
4	Subtitles	voice.py::create_subtitle() or subtitle.py::create() (whisper)	subtitle.srt
5	Materials	material.py::download_videos()	cached stock clips
6	Combine	video.py::combine_videos()	combined-{n}.mp4
7	Composite	video.py::generate_video()	final-{n}.mp4

All task artifacts live in storage/tasks/{task_id}/. Stock-video cache lives in storage/cache_videos/ (configurable via material_directory).

The single source of truth for request parameters is app/models/schema.py::VideoParams (Pydantic). Enums: VideoAspect (16:9→1920x1080, 9:16→1080x1920, 1:1), VideoConcatMode (random/sequential), VideoTransitionMode (Shuffle, FadeIn, FadeOut, SlideIn, SlideOut). Task states in app/models/const.py: -1 failed, 4 processing, 1 complete.

Entry points

• WebUI: streamlit run webui/Main.py (port 8501). i18n JSON in webui/i18n/ (de, en, pt, ru, tr, vi, zh).
• API: python main.py → uvicorn/FastAPI on port 8080 (app/asgi.py, routes in app/router.py + app/controllers/v1/video.py).
• CLI: cli.py.

Reference files (load on demand)

• pipeline.md — deep dive into every stage: LLM prompt engineering, all TTS providers and SubMaker subtitle alignment, whisper fallback + Levenshtein correction, material sourcing, clip selection/letterboxing/transitions, FFmpeg concat, final compositing and subtitle rendering.
• configuration.md — full config.toml reference: 20+ LLM providers, TTS/voice naming conventions, video sources and API keys, whisper, redis, proxy, codec settings.
• api-and-webui.md — REST endpoints, task queue and concurrency limits, memory vs redis task managers, state store, Streamlit UI structure and i18n.
• patterns.md — reusable engineering techniques this repo teaches: thread-safe API key rotation, hardware-codec fallback with runtime detection, TTS streaming timeout via daemon thread + queue, duration estimation for no-voice mode, subtitle/script alignment, rounded subtitle backgrounds with PIL.
• recipes.md — step-by-step guides: run locally / via Docker, add a new LLM provider, add a new TTS provider, add a new stock video source, add a transition effect, debug common failures.
• examples.md — copy-paste-ready practical examples: CLI invocations, full API request/poll/download flows, driving the pipeline from Python, config.toml presets (free / local / production), subtitle styling and prompt-customization payloads, quota-free smoke tests.
• local-setup-guide.md — dispatch guide (in Portuguese) for an agent installing and running everything on the user's PC: Docker vs native Python paths per OS, free API keys, config, WebUI launch and visual verification, troubleshooting. Use when the task is "set this up on my machine".

Conventions and gotchas (always relevant)

• Config is read once from config.toml at repo root by app/config/config.py; copy config.example.toml to start. Never commit real API keys.
• PYTHONPATH must include the repo root; FFmpeg binary resolution order is IMAGEIO_FFMPEG_EXE env var → system PATH → bundled imageio_ffmpeg.
• Subtitle fonts come from resource/fonts/ (default STHeitiMedium.ttc); BGM from resource/songs/ (bgm_type = "random" picks one at random).
• Docker images patch the ImageMagick policy.xml — required for MoviePy text rendering; replicate this in any new image.
• File uploads/downloads must go through app/utils/file_security.py::resolve_path_within_directory() to prevent path traversal. Keep this invariant when adding endpoints.
• Hardware encoders (h264_nvenc, h264_amf, h264_qsv, ...) are optional; every write path must keep the automatic libx264 fallback (video.py::_write_videofile_with_codec_fallback).
• Tests live in test/services/; run with pytest from the repo root.