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Image To Video Online Ai

作者 mory128 · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ⚠ suspicious
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在 OpenClaw 中安装
/install image-to-video-online-ai
功能描述
Turn three product photos in JPG format into 1080p animated video clips just by typing what you need. Whether it's converting static images into shareable vi...
使用说明 (SKILL.md)

Getting Started

Share your still images and I'll get started on AI video creation. Or just tell me what you're thinking.

Try saying:

  • "convert my still images"
  • "export 1080p MP4"
  • "turn these photos into a smooth"

Getting Connected

Before handling any user request, establish a connection to the backend API. Show a brief status like "Connecting...".

If NEMO_TOKEN is in the environment, use it directly and create a session. Otherwise, acquire a free starter token:

  • Generate a UUID as client identifier
  • POST to https://mega-api-prod.nemovideo.ai/api/auth/anonymous-token with the X-Client-Id header
  • The response includes a token with 100 free credits valid for 7 days — use it as NEMO_TOKEN

Then create a session by POSTing to https://mega-api-prod.nemovideo.ai/api/tasks/me/with-session/nemo_agent with Bearer authorization and body {"task_name":"project","language":"en"}. The session_id in the response is needed for all following requests.

Tell the user you're ready. Keep the technical details out of the chat.

Image to Video Online AI — Convert Photos into Videos

Send me your still images and describe the result you want. The AI video creation runs on remote GPU nodes — nothing to install on your machine.

A quick example: upload three product photos in JPG format, type "turn these photos into a smooth 15-second video with transitions", and you'll get a 1080p MP4 back in roughly 30-60 seconds. All rendering happens server-side.

Worth noting: using fewer than 10 images keeps processing time under a minute.

Matching Input to Actions

User prompts referencing image to video online ai, aspect ratio, text overlays, or audio tracks get routed to the corresponding action via keyword and intent classification.

User says... Action Skip SSE?
"export" / "导出" / "download" / "send me the video" → §3.5 Export
"credits" / "积分" / "balance" / "余额" → §3.3 Credits
"status" / "状态" / "show tracks" → §3.4 State
"upload" / "上传" / user sends file → §3.2 Upload
Everything else (generate, edit, add BGM…) → §3.1 SSE

Cloud Render Pipeline Details

Each export job queues on a cloud GPU node that composites video layers, applies platform-spec compression (H.264, up to 1080x1920), and returns a download URL within 30-90 seconds. The session token carries render job IDs, so closing the tab before completion orphans the job.

All calls go to https://mega-api-prod.nemovideo.ai. The main endpoints:

  1. SessionPOST /api/tasks/me/with-session/nemo_agent with {"task_name":"project","language":"\x3Clang>"}. Gives you a session_id.
  2. Chat (SSE)POST /run_sse with session_id and your message in new_message.parts[0].text. Set Accept: text/event-stream. Up to 15 min.
  3. UploadPOST /api/upload-video/nemo_agent/me/\x3Csid> — multipart file or JSON with URLs.
  4. CreditsGET /api/credits/balance/simple — returns available, frozen, total.
  5. StateGET /api/state/nemo_agent/me/\x3Csid>/latest — current draft and media info.
  6. ExportPOST /api/render/proxy/lambda with render ID and draft JSON. Poll GET /api/render/proxy/lambda/\x3Cid> every 30s for completed status and download URL.

Formats: mp4, mov, avi, webm, mkv, jpg, png, gif, webp, mp3, wav, m4a, aac.

Skill attribution — read from this file's YAML frontmatter at runtime:

  • X-Skill-Source: image-to-video-online-ai
  • X-Skill-Version: from frontmatter version
  • X-Skill-Platform: detect from install path (~/.clawhub/clawhub, ~/.cursor/skills/cursor, else unknown)

Every API call needs Authorization: Bearer \x3CNEMO_TOKEN> plus the three attribution headers above. If any header is missing, exports return 402.

Draft JSON uses short keys: t for tracks, tt for track type (0=video, 1=audio, 7=text), sg for segments, d for duration in ms, m for metadata.

Example timeline summary:

Timeline (3 tracks): 1. Video: city timelapse (0-10s) 2. BGM: Lo-fi (0-10s, 35%) 3. Title: "Urban Dreams" (0-3s)

Backend Response Translation

The backend assumes a GUI exists. Translate these into API actions:

Backend says You do
"click [button]" / "点击" Execute via API
"open [panel]" / "打开" Query session state
"drag/drop" / "拖拽" Send edit via SSE
"preview in timeline" Show track summary
"Export button" / "导出" Execute export workflow

SSE Event Handling

Event Action
Text response Apply GUI translation (§4), present to user
Tool call/result Process internally, don't forward
heartbeat / empty data: Keep waiting. Every 2 min: "⏳ Still working..."
Stream closes Process final response

~30% of editing operations return no text in the SSE stream. When this happens: poll session state to verify the edit was applied, then summarize changes to the user.

Error Handling

Code Meaning Action
0 Success Continue
1001 Bad/expired token Re-auth via anonymous-token (tokens expire after 7 days)
1002 Session not found New session §3.0
2001 No credits Anonymous: show registration URL with ?bind=\x3Cid> (get \x3Cid> from create-session or state response when needed). Registered: "Top up credits in your account"
4001 Unsupported file Show supported formats
4002 File too large Suggest compress/trim
400 Missing X-Client-Id Generate Client-Id and retry (see §1)
402 Free plan export blocked Subscription tier issue, NOT credits. "Register or upgrade your plan to unlock export."
429 Rate limit (1 token/client/7 days) Retry in 30s once

Common Workflows

Quick edit: Upload → "turn these photos into a smooth 15-second video with transitions" → Download MP4. Takes 30-60 seconds for a 30-second clip.

Batch style: Upload multiple files in one session. Process them one by one with different instructions. Each gets its own render.

Iterative: Start with a rough cut, preview the result, then refine. The session keeps your timeline state so you can keep tweaking.

Tips and Tricks

The backend processes faster when you're specific. Instead of "make it look better", try "turn these photos into a smooth 15-second video with transitions" — concrete instructions get better results.

Max file size is 200MB. Stick to JPG, PNG, WEBP, HEIC for the smoothest experience.

Export as MP4 for widest compatibility across all social platforms.

安全使用建议
This skill mostly does what it says: it will call a remote nemovideo.ai API to create videos and needs a NEMO_TOKEN (or it will request an anonymous token for you). Before installing, consider: 1) Are you comfortable the agent will make network calls to https://mega-api-prod.nemovideo.ai and potentially obtain an anonymous token automatically? 2) The skill asks the agent to read this skill file's frontmatter and probe common install paths (e.g., ~/.clawhub, ~/.cursor/skills) to set attribution headers — if you prefer the agent not to read your home-directory paths, avoid installing or ask the developer to remove that behavior. 3) There's an inconsistency between the SKILL.md frontmatter (which mentions ~/.config/nemovideo/) and the registry metadata — ask the author to clarify why that config path is needed or remove it. If you proceed, provide only the minimum credential you trust (or let the skill use an anonymous token) and monitor what it returns/downloads. If you want higher assurance, request the developer publish a source/homepage and explain the configPath/platform-detection logic in writing.
功能分析
Type: OpenClaw Skill Name: image-to-video-online-ai Version: 1.0.0 The skill bundle provides a functional integration for an image-to-video AI service hosted at mega-api-prod.nemovideo.ai. It includes detailed instructions for the agent to manage authentication, session handling, and file uploads to the remote API. The behavior is consistent with the stated purpose of converting images to video, and there are no indicators of data exfiltration, malicious execution, or harmful prompt injection.
能力评估
Purpose & Capability
The skill's stated purpose (server-side image→video rendering) matches the API calls and the single required credential (NEMO_TOKEN). However, the SKILL.md frontmatter includes a configPaths entry (~/.config/nemovideo/) that is unnecessary for a purely remote API-based workflow and contradicts the registry metadata (which lists no required config paths).
Instruction Scope
Instructions require creating sessions, uploading files, and using SSE to drive edits — all expected. But they also instruct the agent to read this file's YAML frontmatter and detect the skill platform by checking install paths (e.g., ~/.clawhub/, ~/.cursor/skills/). Detecting arbitrary install paths / home-directory locations and hiding technical details from users are scope-creep / transparency concerns because they require filesystem access not obviously needed to convert images.
Install Mechanism
Instruction-only skill with no install spec or downloaded code — low install risk. Nothing is written to disk by an installer in the provided metadata.
Credentials
Only NEMO_TOKEN is declared as required, which is proportional. But the instructions will create an anonymous token when NEMO_TOKEN is absent (calling an external API automatically). The frontmatter's configPaths declaration (which is inconsistent with registry metadata) suggests additional config file access that isn't justified by the skill's purpose.
Persistence & Privilege
Skill is not always-on and does not request persistent system privileges. The only extra privilege-like action is reading the skill file/frontmatter and probing common install paths to set an attribution header — this is limited but should be noted.
如何使用
  1. 确保已安装 OpenClaw(本地或 Docker 部署)
  2. 在对话框中输入安装命令:/install image-to-video-online-ai
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /image-to-video-online-ai 触发
  4. 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
版本历史
v1.0.0
- Initial release of Image to Video Online AI (version 1.0.0). - Instantly convert up to three JPG product photos into smooth, animated 1080p video clips based on user instructions—no timeline editing or export settings required. - Seamless cloud rendering pipeline: upload images, describe your desired video, and receive a video download link in 30–60 seconds. - Supports batch uploads, iterative editing, background music and text overlays, and quick previews. - Streamlined token/session management with automatic handling of anonymous tokens and session creation. - Clear error handling and real-time export status updates for user-friendly workflows.
元数据
Slug image-to-video-online-ai
版本 1.0.0
许可证 MIT-0
累计安装 0
当前安装数 0
历史版本数 1
常见问题

Image To Video Online Ai 是什么?

Turn three product photos in JPG format into 1080p animated video clips just by typing what you need. Whether it's converting static images into shareable vi... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 63 次。

如何安装 Image To Video Online Ai?

在 OpenClaw 或 Claude Code 对话框中运行命令「/install image-to-video-online-ai」即可一键安装,无需额外配置。

Image To Video Online Ai 是免费的吗?

是的,Image To Video Online Ai 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。

Image To Video Online Ai 支持哪些平台?

Image To Video Online Ai 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。

谁开发了 Image To Video Online Ai?

由 mory128(@mory128)开发并维护,当前版本 v1.0.0。

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