Outcasts AppPromoVideo Outcasts

ai desktop image-generation marketing promo prompt screenshot video video-generation

Use this command to install Outcasts AppPromoVideo with WinGet:

winget install --id=Outcasts.AppPromoVideo -e

AppPromoVideo is a desktop tool for making promotional videos of your own software with video-generation AIs. Point it at an app repository and a few UI screenshots, and it produces a scene-by-scene brief - copy lines, motion and video prompts, and reference images in which the real screenshots are composited onto AI-generated backdrops, so the product UI stays faithful to the original. The output is meant to be pasted directly into an image-to-video service; the tool does not render the video itself. Code analysis is delegated to a locally installed LLM CLI, and reference images can be generated with OpenAI Images, Gemini, or a local ComfyUI.

English | 日本語

🎬 Outcasts AppPromoVideo

A desktop tool that takes an existing app repository and UI snapshots and outputs scene-by-scene prompts and reference images ready to paste into video-generation AIs

> "Ready-to-paste output."
> Not clever copywriting — prompts with the right granularity to paste directly into video-generation UIs, and reference images that stay faithful to your snapshots.
> It doesn't create the video itself. It crafts the ultimate "brief" for video-generation AIs.

💡 Why AppPromoVideo?

Trying to create an app promo video with video-generation AIs (MiniMax / Runway / Luma, etc.) quickly hits two walls:

Prompt trial-and-error: Scene breakdown, camera work, duration allocation, and English prompt assembly take enormous effort.
Drift from the real app: Generic prompts produce UI, tone, and style that look nothing like the actual app.

AppPromoVideo solves both at once — just feed it a repository and UI screenshots.

Three Core Values

🎯 Ready-to-Paste Output
English motion prompts for MiniMax image-to-video, plus full prompts for generic text-to-video. One-click copy to clipboard and paste straight into any video-generation UI.
🎨 Visually Faithful Reference Images
Extracts a color palette and style anchors from UI snapshots. Generates reference images faithful to the real app by compositing AI-generated backdrops with actual screenshots (rounded corners, drop shadows, headline overlays).
🛡️ Secure Local CLI Execution (Secure & Sandboxed)
Instead of calling LLM HTTP APIs directly, launches a locally authenticated CLI (claude -p / Aider / custom, etc.) as a safe subprocess. Thorough sandboxing with Windows Job Objects / Unix pgids for reliable termination of descendant processes and read-only filesystem boundaries.

🔄 Pipeline Overview

> The LLM writes, Rust inspects, the CLI scans, the model paints the stage, and Rust composites the screen.

flowchart LR
    subgraph Input ["📥 1. Input"]
        Repo["📂 App Repository(code, README, config)"]
        Snap["🖼️ UI Snapshots(real screen captures)"]
    end

    subgraph Pipeline ["⚙️ 2. Pipeline (Rust / CLI)"]
        Brief["RepoBrief Extraction(codebase compression)"]
        LLM["🤖 Local LLM CLI(Claude / Aider / custom)*secure subprocess*"]
        Inspect["Rust Inspection Loop(JSON Schema / duration / English check)"]
        Brief --&gt; LLM --&gt; Inspect
    end

    subgraph ImageGen ["🎨 3. Reference Image Compositing"]
        Palette["Palette &amp; Style Anchor Extraction"]
        Compose["Backdrop Compositing &amp; Headline Overlay(ComfyUI / Gemini / OpenAI)"]
        Palette --&gt; Compose
    end

    subgraph Output ["📦 4. Output Package"]
        Scene["🎬 Scene-by-Scene Prompts(MiniMax i2v / Generic)"]
        RefImg["🖼️ Style Reference Images(backdrop + real UI composite)"]
        Pkg["📄 promo.json + Markdown"]
    end

    Repo --&gt; Brief
    Snap --&gt; Palette
    Snap --&gt; Compose
    Inspect --&gt; Scene
    Compose --&gt; RefImg
    Scene --&gt; Pkg
    RefImg --&gt; Pkg

✨ Key Features

Automatic scene-by-scene prompt generation: Supports durations of 15s / 30s / 60s and aspect ratios of 16:9 / 9:16 / 1:1.
One-click clipboard copy: Copy only the motion prompt for MiniMax (image-to-video), or the full prompt with ratio/duration on separate lines for generic text-to-video.
Multi-provider image generation: ComfyUI (local, no API key required), Gemini, and OpenAI (images/edits) supported.
Headline / caption overlay: Layout catchphrases onto images with configurable font, position, and style.
History (Runs): Past generations are safely isolated under runs// and recallable at any time.
GUI & CLI: Ships with both a Tauri 2 desktop app and a promo CLI for terminal / scripted automation.

🚀 Quick Start

Requirements

OS: Windows / macOS / Linux (cross-platform)
Rust: 2024 edition / rust-version 1.85 or later
Node.js: Stable (LTS recommended; for frontend build)
Local LLM CLI: An authenticated CLI on PATH — claude (Claude Code CLI, default), agy, aider, or a custom command. agy cannot disable write tools on its side, so the app can only detect and stop disallowed tools after the fact; use claude for repositories you don't trust

Build & Launch (GUI)

# 1. Clone the repository
git clone https://github.com/betyourluck/AppPromoVideo.git
cd AppPromoVideo

# 2. Run Rust workspace tests
cargo test --workspace

# 3. Launch GUI (Tauri 2 + Vue 3)
cd app
npm install
npm run tauri dev

> [!TIP] > If you hit a build error caused by sccache, run with RUSTC_WRAPPER= unset.

# Frontend unit tests / type check / build
cd app
npx vitest run
npm run build

# Backend unit tests / lint
cd app/src-tauri
cargo test
cargo clippy

🖥️ How to Use the GUI

+-----------------------------------------------------------------------------------------+
| [TopBar] AppPromoVideo                              [Runs] [Settings] [Theme] [Min/Max/X] |
+-----------------------+---------------------------------+-------------------------------+
| 📁 InputPane           | 🎬 ScenePanel                   | 📜 LogPanel                   |
|                       |                                 |                               |
| - Repository selection| - App summary &amp; differentiators | - Real-time progress logs     |
| - UI snapshots        | - Scene list (Prompt &amp; Image)   | - CLI subprocess tracing      |
| - Duration / ratio /  | - Copy (MiniMax / All)          | - Errors &amp; warnings           |
|   language            | - Reference image trigger       |                               |
| [ ▶ Analyze → Build   | [ 💾 Export to folder ]         |                               |
|     Scenes ]          |                                 |                               |
+-----------------------+---------------------------------+-------------------------------+

Launch & connectivity check: On startup the app automatically checks LLM CLI connectivity/authentication (check_cli).
Configure inputs (InputPane):
- Specify the target repository path.
- Add UI screenshots (file picker / drag & drop / clipboard paste).
- Set the video concept, duration (15 / 30 / 60s), aspect ratio (16:9 / 9:16 / 1:1), and copy language.
Analyze & build scenes:
- Click "Analyze → Build Scenes" to run run_pipeline.
- The right pane (LogPanel) streams subprocess progress in real time.
Review & copy prompts (ScenePanel):
- View the app summary, differentiators, and per-scene prompts.
- Copy individual scenes or all at once, formatted for the copy target (MiniMax / generic).
Generate reference images:
- Optionally run "Generate Reference Images" to create visual reference images (OpenAI / Gemini / ComfyUI).
Export artifacts:
- Use "Open Folder" or "Export to Folder" to save the complete output package.

⌨️ CLI (`promo`) Usage

A promo CLI binary is included for terminal and scripted automation.

# Run analyze → scene composition → image generation → package export in one go
cargo run -p pipeline --bin promo -- run  --concept "An innovative task management tool"

# Output only the RepoBrief (compressed summary manifest) for a repository (no LLM)
cargo run -p pipeline --bin promo -- brief 

# Generate additional reference / scene images for an existing promo.json
cargo run -p pipeline --bin promo -- images promo_out/promo.json --images comfy

# Test headline overlay (visual check, no LLM)
cargo run -p pipeline --bin promo -- caption in.png "Noto Sans JP" 0 "Sync instantly." out.png

# Test backdrop + screenshot compositing (visual check, no LLM)
cargo run -p pipeline --bin promo -- compose backdrop.png screenshot.png out.png 16:9

# List available fonts
cargo run -p pipeline --bin promo -- fonts

📦 Output Package Layout

Each run is fully isolated under a unique runs// directory.

/
└── _Promo_Package/
    └── runs/
        └── 20260914-071122/              # run_id = YYYYMMDD-HHMMSS (local time); -2, -3 … on collision
            ├── promo.json                # Summary, scene plan, prompts, and your edits — the run can be restored from this alone
            ├── scenes.md                 # Shot list and per-scene prompts (always rewritten together with promo.json)
            ├── scene_01_ref_01.png       # Reference image with the headline burned in — pass this to MiniMax
            ├── base/
            │   └── scene_01_ref_01.png   # Source material: backdrop (product cut) / picture (mood cut); re-burning starts here, no API call
            └── snapshots/
                └── snapshot_01.png       # Copies of the input UI snapshots

scene_NN_ref_MM.png and base/ appear only after you generate reference images.

🏗️ Workspace Architecture

Built as a Rust workspace (4 crates) plus a Tauri 2 desktop application.

Crate / Directory	Role	Responsibilities
`crates/promo_core`	Pure-function core domain	No process/HTTP side effects. Type definitions for `RepoBrief` / `ScenePlan`, mechanical JSON Schema generation, rescue of malformed LLM JSON (`fenced_json`), prompt text generation.
`crates/cli_runner`	Secure CLI subprocess execution	Launches a local LLM CLI as a subprocess. Safe argv construction (stdin/temp-file transport), scrubbing of auth env vars, reliable forced termination of descendants via Windows Job Objects / Unix pgids.
`crates/image_gen`	Image generation & compositing engine	Reference image generation via ComfyUI (polling), Gemini, and OpenAI. Dominant-color extraction from UI snapshots (Palette), rounded-corner / drop-shadow compositing, headline caption overlay.
`crates/pipeline`	Orchestration & CLI	I/O harness wiring the crates together. File collection, LLM interaction, Rust-side inspection loop (auto-regeneration on violation), package export, and the `promo` CLI binary itself.
`app/`	Desktop GUI	Tauri 2 + Vue 3 + TypeScript. Calls the backend via `#[tauri::command]` and receives progress in real time via Tauri Events. Settings and history UI.

🎨 Image Generation Provider Support

Provider	Integration	API Key	Status
Gemini	`models/{model}:generateContent`	Required	✅ Verified end-to-end on real hardware
OpenAI	`images/generations` (no references) / `images/edits` (with references)	Required	⚠️ Implemented; not yet verified end-to-end on real hardware
ComfyUI	Local HTTP polling (upload → `/prompt` → `/history` → `/view`)	Not required	⚠️ Implemented; not yet verified end-to-end on real hardware

⚙️ Configuration & Security

Separated config storage:
- UI settings and CLI options: %APPDATA%/jp.outcasts.apppromovideo/settings.json
- Image-generation API keys: .env in the same directory
Credential leak prevention:
- Raw API keys are never exposed to the WebView (frontend); they are held and used only on the backend (Rust side) — the frontend only receives a boolean indicating whether a key is set.
LLM CLI authentication troubleshooting:
- If the GUI repeatedly returns 401 (authentication_failed) for the LLM CLI on startup, enable "Use OAuth login" in Settings (suppresses propagation of ANTHROPIC_API_KEY to the child process).
Known constraints & pitfalls:
- Additional gotchas and workarounds are collected in failures.md (PowerShell redirect conflicts, gen becoming a reserved keyword in Rust 2024, etc.).

📚 Documentation

Detailed design principles and operational rules are maintained in the following ledgers:

📘 specs/01_promo_pipeline.md — Spec, phase plan, and grounding limits
📐 data_contract.yaml — Types, limits, enums, and invariants (canonical source)
🧭 CLAUDE.md — North star, architecture, and development rules
⚠️ failures.md — Known pitfalls, workarounds, and incident ledger
📜 history.md — Implementation log and history

📄 License

Released under the MIT License.

English | 日本語

🎬 Outcasts AppPromoVideo

A desktop tool that takes an existing app repository and UI snapshots and outputs scene-by-scene prompts and reference images ready to paste into video-generation AIs

💡 Why AppPromoVideo?

Trying to create an app promo video with video-generation AIs (MiniMax / Runway / Luma, etc.) quickly hits two walls:

Prompt trial-and-error: Scene breakdown, camera work, duration allocation, and English prompt assembly take enormous effort.
Drift from the real app: Generic prompts produce UI, tone, and style that look nothing like the actual app.

AppPromoVideo solves both at once — just feed it a repository and UI screenshots.

Three Core Values

🎯 Ready-to-Paste Output
English motion prompts for MiniMax image-to-video, plus full prompts for generic text-to-video. One-click copy to clipboard and paste straight into any video-generation UI.
🎨 Visually Faithful Reference Images
Extracts a color palette and style anchors from UI snapshots. Generates reference images faithful to the real app by compositing AI-generated backdrops with actual screenshots (rounded corners, drop shadows, headline overlays).
🛡️ Secure Local CLI Execution (Secure & Sandboxed)
Instead of calling LLM HTTP APIs directly, launches a locally authenticated CLI (claude -p / Aider / custom, etc.) as a safe subprocess. Thorough sandboxing with Windows Job Objects / Unix pgids for reliable termination of descendant processes and read-only filesystem boundaries.

🔄 Pipeline Overview

> The LLM writes, Rust inspects, the CLI scans, the model paints the stage, and Rust composites the screen.

flowchart LR
    subgraph Input ["📥 1. Input"]
        Repo["📂 App Repository(code, README, config)"]
        Snap["🖼️ UI Snapshots(real screen captures)"]
    end

    subgraph Pipeline ["⚙️ 2. Pipeline (Rust / CLI)"]
        Brief["RepoBrief Extraction(codebase compression)"]
        LLM["🤖 Local LLM CLI(Claude / Aider / custom)*secure subprocess*"]
        Inspect["Rust Inspection Loop(JSON Schema / duration / English check)"]
        Brief --&gt; LLM --&gt; Inspect
    end

    subgraph ImageGen ["🎨 3. Reference Image Compositing"]
        Palette["Palette &amp; Style Anchor Extraction"]
        Compose["Backdrop Compositing &amp; Headline Overlay(ComfyUI / Gemini / OpenAI)"]
        Palette --&gt; Compose
    end

    subgraph Output ["📦 4. Output Package"]
        Scene["🎬 Scene-by-Scene Prompts(MiniMax i2v / Generic)"]
        RefImg["🖼️ Style Reference Images(backdrop + real UI composite)"]
        Pkg["📄 promo.json + Markdown"]
    end

    Repo --&gt; Brief
    Snap --&gt; Palette
    Snap --&gt; Compose
    Inspect --&gt; Scene
    Compose --&gt; RefImg
    Scene --&gt; Pkg
    RefImg --&gt; Pkg

✨ Key Features

Automatic scene-by-scene prompt generation: Supports durations of 15s / 30s / 60s and aspect ratios of 16:9 / 9:16 / 1:1.
One-click clipboard copy: Copy only the motion prompt for MiniMax (image-to-video), or the full prompt with ratio/duration on separate lines for generic text-to-video.
Multi-provider image generation: ComfyUI (local, no API key required), Gemini, and OpenAI (images/edits) supported.
Headline / caption overlay: Layout catchphrases onto images with configurable font, position, and style.
History (Runs): Past generations are safely isolated under runs// and recallable at any time.
GUI & CLI: Ships with both a Tauri 2 desktop app and a promo CLI for terminal / scripted automation.

🚀 Quick Start

Requirements

OS: Windows / macOS / Linux (cross-platform)
Rust: 2024 edition / rust-version 1.85 or later
Node.js: Stable (LTS recommended; for frontend build)
Local LLM CLI: An authenticated CLI on PATH — claude (Claude Code CLI, default), agy, aider, or a custom command. agy cannot disable write tools on its side, so the app can only detect and stop disallowed tools after the fact; use claude for repositories you don't trust

Build & Launch (GUI)

# 1. Clone the repository
git clone https://github.com/betyourluck/AppPromoVideo.git
cd AppPromoVideo

# 2. Run Rust workspace tests
cargo test --workspace

# 3. Launch GUI (Tauri 2 + Vue 3)
cd app
npm install
npm run tauri dev

> [!TIP] > If you hit a build error caused by sccache, run with RUSTC_WRAPPER= unset.

# Frontend unit tests / type check / build
cd app
npx vitest run
npm run build

# Backend unit tests / lint
cd app/src-tauri
cargo test
cargo clippy

🖥️ How to Use the GUI

+-----------------------------------------------------------------------------------------+
| [TopBar] AppPromoVideo                              [Runs] [Settings] [Theme] [Min/Max/X] |
+-----------------------+---------------------------------+-------------------------------+
| 📁 InputPane           | 🎬 ScenePanel                   | 📜 LogPanel                   |
|                       |                                 |                               |
| - Repository selection| - App summary &amp; differentiators | - Real-time progress logs     |
| - UI snapshots        | - Scene list (Prompt &amp; Image)   | - CLI subprocess tracing      |
| - Duration / ratio /  | - Copy (MiniMax / All)          | - Errors &amp; warnings           |
|   language            | - Reference image trigger       |                               |
| [ ▶ Analyze → Build   | [ 💾 Export to folder ]         |                               |
|     Scenes ]          |                                 |                               |
+-----------------------+---------------------------------+-------------------------------+

Launch & connectivity check: On startup the app automatically checks LLM CLI connectivity/authentication (check_cli).
Configure inputs (InputPane):
- Specify the target repository path.
- Add UI screenshots (file picker / drag & drop / clipboard paste).
- Set the video concept, duration (15 / 30 / 60s), aspect ratio (16:9 / 9:16 / 1:1), and copy language.
Analyze & build scenes:
- Click "Analyze → Build Scenes" to run run_pipeline.
- The right pane (LogPanel) streams subprocess progress in real time.
Review & copy prompts (ScenePanel):
- View the app summary, differentiators, and per-scene prompts.
- Copy individual scenes or all at once, formatted for the copy target (MiniMax / generic).
Generate reference images:
- Optionally run "Generate Reference Images" to create visual reference images (OpenAI / Gemini / ComfyUI).
Export artifacts:
- Use "Open Folder" or "Export to Folder" to save the complete output package.

⌨️ CLI (`promo`) Usage

A promo CLI binary is included for terminal and scripted automation.

# Run analyze → scene composition → image generation → package export in one go
cargo run -p pipeline --bin promo -- run  --concept "An innovative task management tool"

# Output only the RepoBrief (compressed summary manifest) for a repository (no LLM)
cargo run -p pipeline --bin promo -- brief 

# Generate additional reference / scene images for an existing promo.json
cargo run -p pipeline --bin promo -- images promo_out/promo.json --images comfy

# Test headline overlay (visual check, no LLM)
cargo run -p pipeline --bin promo -- caption in.png "Noto Sans JP" 0 "Sync instantly." out.png

# Test backdrop + screenshot compositing (visual check, no LLM)
cargo run -p pipeline --bin promo -- compose backdrop.png screenshot.png out.png 16:9

# List available fonts
cargo run -p pipeline --bin promo -- fonts

📦 Output Package Layout

Each run is fully isolated under a unique runs// directory.

/
└── _Promo_Package/
    └── runs/
        └── 20260914-071122/              # run_id = YYYYMMDD-HHMMSS (local time); -2, -3 … on collision
            ├── promo.json                # Summary, scene plan, prompts, and your edits — the run can be restored from this alone
            ├── scenes.md                 # Shot list and per-scene prompts (always rewritten together with promo.json)
            ├── scene_01_ref_01.png       # Reference image with the headline burned in — pass this to MiniMax
            ├── base/
            │   └── scene_01_ref_01.png   # Source material: backdrop (product cut) / picture (mood cut); re-burning starts here, no API call
            └── snapshots/
                └── snapshot_01.png       # Copies of the input UI snapshots

scene_NN_ref_MM.png and base/ appear only after you generate reference images.

🏗️ Workspace Architecture

Built as a Rust workspace (4 crates) plus a Tauri 2 desktop application.

Crate / Directory	Role	Responsibilities
`crates/promo_core`	Pure-function core domain	No process/HTTP side effects. Type definitions for `RepoBrief` / `ScenePlan`, mechanical JSON Schema generation, rescue of malformed LLM JSON (`fenced_json`), prompt text generation.
`crates/cli_runner`	Secure CLI subprocess execution	Launches a local LLM CLI as a subprocess. Safe argv construction (stdin/temp-file transport), scrubbing of auth env vars, reliable forced termination of descendants via Windows Job Objects / Unix pgids.
`crates/image_gen`	Image generation & compositing engine	Reference image generation via ComfyUI (polling), Gemini, and OpenAI. Dominant-color extraction from UI snapshots (Palette), rounded-corner / drop-shadow compositing, headline caption overlay.
`crates/pipeline`	Orchestration & CLI	I/O harness wiring the crates together. File collection, LLM interaction, Rust-side inspection loop (auto-regeneration on violation), package export, and the `promo` CLI binary itself.
`app/`	Desktop GUI	Tauri 2 + Vue 3 + TypeScript. Calls the backend via `#[tauri::command]` and receives progress in real time via Tauri Events. Settings and history UI.

🎨 Image Generation Provider Support

Provider	Integration	API Key	Status
Gemini	`models/{model}:generateContent`	Required	✅ Verified end-to-end on real hardware
OpenAI	`images/generations` (no references) / `images/edits` (with references)	Required	⚠️ Implemented; not yet verified end-to-end on real hardware
ComfyUI	Local HTTP polling (upload → `/prompt` → `/history` → `/view`)	Not required	⚠️ Implemented; not yet verified end-to-end on real hardware

⚙️ Configuration & Security

Separated config storage:
- UI settings and CLI options: %APPDATA%/jp.outcasts.apppromovideo/settings.json
- Image-generation API keys: .env in the same directory
Credential leak prevention:
- Raw API keys are never exposed to the WebView (frontend); they are held and used only on the backend (Rust side) — the frontend only receives a boolean indicating whether a key is set.
LLM CLI authentication troubleshooting:
- If the GUI repeatedly returns 401 (authentication_failed) for the LLM CLI on startup, enable "Use OAuth login" in Settings (suppresses propagation of ANTHROPIC_API_KEY to the child process).
Known constraints & pitfalls:
- Additional gotchas and workarounds are collected in failures.md (PowerShell redirect conflicts, gen becoming a reserved keyword in Rust 2024, etc.).

📚 Documentation

Detailed design principles and operational rules are maintained in the following ledgers:

📘 specs/01_promo_pipeline.md — Spec, phase plan, and grounding limits
📐 data_contract.yaml — Types, limits, enums, and invariants (canonical source)
🧭 CLAUDE.md — North star, architecture, and development rules
⚠️ failures.md — Known pitfalls, workarounds, and incident ledger
📜 history.md — Implementation log and history

📄 License

Released under the MIT License.

Outcasts AppPromoVideo Outcasts

README

🎬 Outcasts AppPromoVideo

💡 Why AppPromoVideo?

Three Core Values

🔄 Pipeline Overview

✨ Key Features

🚀 Quick Start

Requirements

Build & Launch (GUI)

🖥️ How to Use the GUI

⌨️ CLI (promo) Usage

📦 Output Package Layout

🏗️ Workspace Architecture

🎨 Image Generation Provider Support

⚙️ Configuration & Security

📚 Documentation

📄 License

Outcasts AppPromoVideo Outcasts

README

🎬 Outcasts AppPromoVideo

💡 Why AppPromoVideo?

Three Core Values

🔄 Pipeline Overview

✨ Key Features

🚀 Quick Start

Requirements

Build & Launch (GUI)

🖥️ How to Use the GUI

⌨️ CLI (promo) Usage

📦 Output Package Layout

🏗️ Workspace Architecture

🎨 Image Generation Provider Support

⚙️ Configuration & Security

📚 Documentation

📄 License

⌨️ CLI (`promo`) Usage

⌨️ CLI (`promo`) Usage