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Ai Video Maker From Photos

作者 peandrover adam · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ✓ 安全检测通过
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在 OpenClaw 中安装
/install ai-video-maker-from-photos
功能描述
turn photos or images into slideshow MP4 video with this skill. Works with JPG, PNG, HEIC, WEBP files up to 200MB. social media creators and marketers use it...
使用说明 (SKILL.md)

Getting Started

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

Try saying:

  • "turn my photos or images"
  • "export 1080p MP4"
  • "turn my photos into a 30-second"

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.

AI Video Maker from Photos — Turn Photos into MP4 Videos

This tool takes your photos or images and runs AI video creation through a cloud rendering pipeline. You upload, describe what you want, and download the result.

Say you have ten vacation photos from a beach trip and want to turn my photos into a 30-second slideshow video with transitions and music — the backend processes it in about 30-60 seconds and hands you a 1080p MP4.

Tip: using 10-20 photos gives the AI enough content to build smooth transitions without overcrowding the video.

Matching Input to Actions

User prompts referencing ai video maker from photos, 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.

Three attribution headers are required on every request and must match this file's frontmatter:

Header Value
X-Skill-Source ai-video-maker-from-photos
X-Skill-Version frontmatter version
X-Skill-Platform auto-detect: clawhub / cursor / unknown from install path

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

API base: https://mega-api-prod.nemovideo.ai

Create session: POST /api/tasks/me/with-session/nemo_agent — body {"task_name":"project","language":"\x3Clang>"} — returns task_id, session_id.

Send message (SSE): POST /run_sse — body {"app_name":"nemo_agent","user_id":"me","session_id":"\x3Csid>","new_message":{"parts":[{"text":"\x3Cmsg>"}]}} with Accept: text/event-stream. Max timeout: 15 minutes.

Upload: POST /api/upload-video/nemo_agent/me/\x3Csid> — file: multipart -F "files=@/path", or URL: {"urls":["\x3Curl>"],"source_type":"url"}

Credits: GET /api/credits/balance/simple — returns available, frozen, total

Session state: GET /api/state/nemo_agent/me/\x3Csid>/latest — key fields: data.state.draft, data.state.video_infos, data.state.generated_media

Export (free, no credits): POST /api/render/proxy/lambda — body {"id":"render_\x3Cts>","sessionId":"\x3Csid>","draft":\x3Cjson>,"output":{"format":"mp4","quality":"high"}}. Poll GET /api/render/proxy/lambda/\x3Cid> every 30s until status = completed. Download URL at output.url.

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

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.

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

Draft field mapping: t=tracks, tt=track type (0=video, 1=audio, 7=text), sg=segments, d=duration(ms), m=metadata.

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

Error Codes

  • 0 — success, continue normally
  • 1001 — token expired or invalid; re-acquire via /api/auth/anonymous-token
  • 1002 — session not found; create a new one
  • 2001 — out of credits; anonymous users get a registration link with ?bind=\x3Cid>, registered users top up
  • 4001 — unsupported file type; show accepted formats
  • 4002 — file too large; suggest compressing or trimming
  • 400 — missing X-Client-Id; generate one and retry
  • 402 — free plan export blocked; not a credit issue, subscription tier
  • 429 — rate limited; wait 30s and retry once

Tips and Tricks

The backend processes faster when you're specific. Instead of "make it look better", try "turn my photos into a 30-second slideshow video with transitions and music" — concrete instructions get better results.

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

Export as MP4 for widest compatibility across social platforms and devices.

Common Workflows

Quick edit: Upload → "turn my photos into a 30-second slideshow video with transitions and music" → 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.

安全使用建议
This appears safe to use for its stated purpose if you are comfortable sending the selected photos or image URLs to NemoVideo's cloud API. Avoid uploading sensitive personal images unless you trust the provider, and prefer a dedicated or revocable NEMO_TOKEN.
功能分析
Type: OpenClaw Skill Name: ai-video-maker-from-photos Version: 1.0.0 The skill is a functional integration for an AI video generation service hosted at nemovideo.ai. It provides detailed instructions for the agent to manage authentication via tokens, handle file uploads, and coordinate cloud-based video rendering. The behavior is strictly aligned with the stated purpose of converting photos to MP4 videos, and no indicators of data exfiltration, malicious execution, or harmful prompt injection were identified in SKILL.md or _meta.json.
能力评估
Purpose & Capability
The upload, render, export, and credit-check flows match the stated purpose of creating MP4 videos from photos. Users should understand that media is processed by a third-party cloud service.
Instruction Scope
The instructions let backend responses drive some API actions such as querying state or exporting. This appears bounded to the video-rendering workflow, but users should keep uploads and exports user-directed.
Install Mechanism
No install spec or code files are present, and the static scanner had nothing suspicious to analyze.
Credentials
The NEMO_TOKEN credential or an anonymous starter token is expected for the cloud backend. The frontmatter also mentions a NemoVideo config path, but no local file access behavior is shown.
Persistence & Privilege
The skill creates backend sessions and render jobs, which is expected for cloud rendering. There is no evidence of background persistence, auto-start behavior, or privileged local writes.
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 ai-video-maker-from-photos
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /ai-video-maker-from-photos 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 AI Video Maker from Photos — Turn Photos into MP4 slideshow videos. - Turn batches of JPG, PNG, HEIC, or WEBP photos (up to 200MB) into 1080p MP4 videos in 30-60 seconds. - Automatic backend connection and session handling, including anonymous token support for new users. - Supports keyword-based workflow routing: upload, export, balance checking, and editing. - Built-in error handling for credits, session state, and file types. - Downloadable results ready for social media and marketing use.
元数据
Slug ai-video-maker-from-photos
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

Ai Video Maker From Photos 是什么?

turn photos or images into slideshow MP4 video with this skill. Works with JPG, PNG, HEIC, WEBP files up to 200MB. social media creators and marketers use it... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 20 次。

如何安装 Ai Video Maker From Photos?

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

Ai Video Maker From Photos 是免费的吗?

是的,Ai Video Maker From Photos 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。

Ai Video Maker From Photos 支持哪些平台?

Ai Video Maker From Photos 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 Ai Video Maker From Photos?

由 peandrover adam(@peand-rover)开发并维护,当前版本 v1.0.0。

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