ralphy

作者 alecs5am已验证

🎬 Give AI agents tools to create viral videos. Influence at scale, from your terminal.

122
Stars
13
Forks
HTML
语言
2026/8/23
添加时间

⚠️ 第三方软件声明

本 Skill 为第三方开源软件,独立托管于 GitHub。SkillTip 仅为信息目录,不控制或维护底层仓库。所显示的安全检查为自动化且范围有限,安装前请自行审查源码。

阅读服务条款

安装

添加到你的 Claude Code skills 目录:

# Add to your Claude Code skills
git clone https://github.com/alecs5am/ralphy

快速入门

使用 ralphy 等 Skills 的指南。

安全报告

已验证

上次扫描:—

{
  "status": "PASSED",
  "issues": []
}

README.md

RALPHY — turn your coding agent into a content farm

Turn your coding agent into a content farm.

Open-source runtime for agent-driven content production. You chat with Hermes, Claude Code, Codex, or another local coding agent; the agent drives Ralphy. Forkable, observable, reproducible.

Tests Release Latest release License: Apache 2.0 PRs welcome


What it is

Ralphy is a tool for local agents, not a CLI you operate by hand. You stay in chat — Hermes, Claude Code, Codex, or another coding agent — and describe what you want; the agent runs Ralphy for you. The CLI is the runtime that gives the agent reproducible model calls, account workspaces, shared brand assets, content units, quality gates, renders, logs, and memory.

Under the hood, two API keys (OPENROUTER_API_KEY + ELEVENLABS_API_KEY) wire up image / video / vision / LLM (OpenRouter), voice + music (ElevenLabs), HTML+GSAP composition (HyperFrames), and a local async-job queue (bun + SQLite). Direct ralphy <verb> commands stay available for setup, debugging, and power users — but driving them yourself is not the primary workflow.

Demo

See what Ralphy makes → — real rendered outputs from real projects.

Cost: ~$8–12 per 30s video. Speed: ~8 min cold-start, ~25 min for a 10-batch. Engine: HyperFrames (HTML + GSAP, deterministic Puppeteer + FFmpeg render).

Install

PlatformCommand
macOS (Homebrew)brew install alecs5am/tap/ralphy
Linux / macOS (curl)curl -fsSL https://raw.githubusercontent.com/alecs5am/ralphy/main/install.sh | sh
Windows (PowerShell)irm https://raw.githubusercontent.com/alecs5am/ralphy/main/install.ps1 | iex
Cross-platform (npm)npm install -g @alecs5am/ralphy

All four ship the same binary.

Setup is a one-time step you run once so your agent can take over from there. These two commands are agent enablement + diagnostics, not the everyday workflow:

ralphy setup          # interactive wizard — paste the two API keys + install agent skill
ralphy doctor         # verify env is green (run this when the agent reports a problem)

Expected output:

✦ ralphy v0.3.0
▸ Dependencies          ✓ bun  ✓ ffmpeg
▸ API keys              ✓ OPENROUTER_API_KEY  ✓ ELEVENLABS_API_KEY
  ✓ ready

macOS Gatekeeper warning? You used the direct-download path. Brew / npm / install.sh bypass Gatekeeper automatically. If you hit it: xattr -d com.apple.quarantine /path/to/ralphy once and you're done.

Verify your install: every Release includes a SHA256SUMS file. shasum -a 256 -c SHA256SUMS (macOS / Linux) or Get-FileHash (Windows) confirms the binary matches.

60-second tour

In practice you say "make a spring espresso ad" in chat and the agent runs these verbs for you. Here's the surface it drives, so you can see what's happening under the hood:

# 1. Create a project
ralphy new "Spring espresso ad" --id espresso-001

# 2. Find a template by free-text utterance
ralphy template suggest "talking head rant about deadlines" -p
✦ Query: "talking head rant about deadlines"
  1. ✓ talking-head  ███████████████░  0.95  strong
  2. ✓ story-time    ███████████░░░░░  0.70  strong
# 3. Scaffold from the chosen template (sourced from the hosted library)
ralphy template use talking-head --id espresso-001

# 4. Cost-preview before spending a cent
ralphy generate image --project espresso-001 --slot scene-01-bg \
  --prompt "studio packshot, white seamless, 50mm, photoreal" --dry-run

# 5. Render the project to mp4
ralphy render espresso-001

That's it. Full CLI surface in docs/cli-surface.generated.md.

Why Ralphy

What you actually get vs other ways to do this. The operator is your agent; you stay in chat.

Closed SaaS (Higgsfield, HeyGen, Captions)Other OSS (ShortGPT, MoneyPrinterTurbo)Ralphy
SourceClosedOSS (script-shaped)Apache 2.0, fork-able
Who operates itYou, in their web UIYou, hand-running a scriptYour agent — you stay in chat
Agent surfaceTheir cloud agentNoneLocal skills + playbooks; works in any agent
ModelsVendor lock-inOne model, hardcodedAny OpenRouter model — Kling / Seedance / Veo / Sora / Nano-Banana
Cost transparencySubscription black boxFree-but-you-DIY--dry-run shows the bill before you spend
ReproducibilityVibesVibesAppend-only genlogs + postmortems + templates-as-git
Quality gatesBest-effortNoneRefuse-not-warn: bad scene = no render
Reference groundingNoneNoneBuilt-in research engine (ralphy research) + guideline library
ComposerWeb canvas (theirs)MoviePy / FFmpeg scriptsHyperFrames (HTML + GSAP) — versioned in git, tested in CI

The hard rule that makes the rest work: ralphy <verb> is the only entry-point. No ad-hoc ffmpeg shell-outs, no direct provider fetches, no orphan scripts. Every model call lands in generations.jsonl, every cost in the rollup, every failure in the postmortem.

Architecture

graph LR
    A[Agent: Claude Code / Cursor / Codex] -->|playbooks| B[ralphy CLI]
    B --> C[Provider router]
    C --> D[OpenRouter<br/>Kling / Seedance / Veo / Sora / Nano-Banana]
    C --> E[ElevenLabs<br/>TTS + Music]
    B --> F[HyperFrames composer<br/>HTML + GSAP]
    F --> G[mp4 via Puppeteer + FFmpeg]
    B --> H[Project memory<br/>genlogs · postmortems · cost rollup]
    B --> I[Hosted template library<br/>+ guidelines in git]

5 agent roles (researcher / scenarist / art-director / editor / producer) routed via AGENTS.md. The router decides which playbook the agent reads before acting.

Documentation & community

SurfaceRead when
LibraryBrowse published units + templates with live rendered previews.
AGENTS.mdFirst. Routing rules + the "read the playbook before acting" discipline.
MODELS.mdBefore every model call. Claude's training is stale on model names.
docs/playbooks/Per-role instructions (researcher, scenarist, art-director, editor, producer).
GitHub DiscussionsQ&A, Show & Tell, Tester feedback.

Contributing

git clone https://github.com/alecs5am/ralphy.git
cd ralphy && bun install

bun test                       # unit + integration (1,000+ tests)
bun run lint                   # typecheck + project lints (errors / help-examples / skills / agents-md / cli-surface)
bun run cli:surface:build      # regenerate docs/cli-surface.generated.md
bun run build:bin              # build cross-platform binaries

A pre-commit hook runs the test suite. CI runs the same on push/PR.

PRs welcome — especially:

For non-trivial changes, open an issue first or start a discussion.

License

Apache 2.0. Use, fork, ship to prod — patent grant included.


常见问题

What is ralphy?

ralphy is an open-source ai agents skill for AI coding assistants such as Claude Code, Codex CLI, and ChatGPT, built by alecs5am. 🎬 Give AI agents tools to create viral videos. Influence at scale, from your terminal. It has 122 GitHub stars.

Is ralphy safe to use?

Yes. ralphy passed SkillsLLM's automated security scan — a dependency vulnerability audit plus prompt-injection heuristics — with no high-severity issues. You can read the full report in the Security Report section on this page.

How do I install ralphy?

Clone the repository with "git clone https://github.com/alecs5am/ralphy" and add it to your Claude Code skills directory (see the Installation section above).

What programming language is ralphy written in?

ralphy is primarily written in HTML. It is open-source under alecs5am on GitHub, so you can review or fork the full source.

Are there alternatives to ralphy?

Yes. SkillsLLM lists many other AI Agents skills you can browse and compare side by side. Open the AI Agents category from the badge at the top of this page, or use the Related Skills and comparison links further down to weigh ralphy against similar tools.

评论 (0)

暂无评论,成为第一个分享想法的人!

ECC

by affaan-m

10

The agent harness performance optimization system. Skills, instincts, memory, security, and research-first development for Claude Code, Codex, Opencode, Cursor and beyond.

242,21936,702JavaScript
AI 智能体ai-agentsanthropicclaude-code
查看详情
15

An agentic skills framework & software development methodology that works.

234,96620,863Shell
AI 智能体ai-agentsbrainstorming
查看详情

hermes-agent

by NousResearch

10

The agent that grows with you

234,43747,175Python
AI 智能体ai-agentsagent-orchestration
查看详情

The agent harness performance optimization system. Skills, instincts, memory, security, and research-first development for Claude Code, Codex, Opencode, Cursor and beyond.

185,94028,768JavaScript
AI 智能体ai-agentsanthropicclaude-code
查看详情

cc-switch

by farion1231

3

A cross-platform desktop All-in-One assistant for Claude Code, Codex, OpenCode, OpenClaw, Grok Build & Hermes Agent. Only official website: ccswitch.io

128,8688,826Rust
AI 智能体claude-codeai-tools
查看详情

claude-code

by anthropics

Claude Code is an agentic coding tool that lives in your terminal, understands your codebase, and helps you code faster by executing routine tasks, explaining complex code, and handling git workflows - all through natural language commands.

120,03119,897Shell
AI 智能体
查看详情

开发者还喜欢

基于喜欢此 Skill 的开发者投票和收藏

ECC

by affaan-m

10

The agent harness performance optimization system. Skills, instincts, memory, security, and research-first development for Claude Code, Codex, Opencode, Cursor and beyond.

242,21936,702JavaScript
AI 智能体ai-agentsanthropicclaude-code
查看详情
15

An agentic skills framework & software development methodology that works.

234,96620,863Shell
AI 智能体ai-agentsbrainstorming
查看详情

hermes-agent

by NousResearch

10

The agent that grows with you

234,43747,175Python
AI 智能体ai-agentsagent-orchestration
查看详情

n8n

by n8n-io

12

Fair-code workflow automation platform with native AI capabilities. Combine visual building with custom code, self-host or cloud, 400+ integrations.

201,88160,308TypeScript
MCP 服务器apisai-tools
查看详情

The agent harness performance optimization system. Skills, instincts, memory, security, and research-first development for Claude Code, Codex, Opencode, Cursor and beyond.

185,94028,768JavaScript
AI 智能体ai-agentsanthropicclaude-code
查看详情

cc-switch

by farion1231

3

A cross-platform desktop All-in-One assistant for Claude Code, Codex, OpenCode, OpenClaw, Grok Build & Hermes Agent. Only official website: ccswitch.io

128,8688,826Rust
AI 智能体claude-codeai-tools
查看详情