Image To Video Llm
/install image-to-video-llm
Getting Started
Share your still images and I'll get started on AI video generation. Or just tell me what you're thinking.
Try saying:
- "convert my still images"
- "export 1080p MP4"
- "turn this image into a 5-second"
Automatic Setup
On first interaction, connect to the processing API before doing anything else. Show a brief status like "Setting things up...".
Token: If NEMO_TOKEN environment variable is already set, use it and skip to Session below.
Free token: Generate a UUID as client identifier, then POST to https://mega-api-prod.nemovideo.ai/api/auth/anonymous-token with header X-Client-Id: \x3Cuuid>. The response field data.token becomes your NEMO_TOKEN (100 credits, 7-day expiry).
Session: POST to https://mega-api-prod.nemovideo.ai/api/tasks/me/with-session/nemo_agent with Bearer auth and body {"task_name":"project"}. Save session_id from the response.
Confirm to the user you're connected and ready. Don't print tokens or raw JSON.
Image to Video LLM — Convert Images Into Video Clips
Drop your still images in the chat and tell me what you need. I'll handle the AI video generation on cloud GPUs — you don't need anything installed locally.
Here's a typical use: you send a a single product photo or landscape image, ask for turn this image into a 5-second animated video clip with smooth motion, and about 30-90 seconds later you've got a MP4 file ready to download. The whole thing runs at 1080p by default.
One thing worth knowing — high-contrast images with clear subjects produce smoother, more realistic motion.
Matching Input to Actions
User prompts referencing image to video llm, 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.
Base URL: https://mega-api-prod.nemovideo.ai
| Endpoint | Method | Purpose |
|---|---|---|
/api/tasks/me/with-session/nemo_agent |
POST | Start a new editing session. Body: {"task_name":"project","language":"\x3Clang>"}. Returns session_id. |
/run_sse |
POST | Send a user message. Body includes app_name, session_id, new_message. Stream response with Accept: text/event-stream. Timeout: 15 min. |
/api/upload-video/nemo_agent/me/\x3Csid> |
POST | Upload a file (multipart) or URL. |
/api/credits/balance/simple |
GET | Check remaining credits (available, frozen, total). |
/api/state/nemo_agent/me/\x3Csid>/latest |
GET | Fetch current timeline state (draft, video_infos, generated_media). |
/api/render/proxy/lambda |
POST | Start export. Body: {"id":"render_\x3Cts>","sessionId":"\x3Csid>","draft":\x3Cjson>,"output":{"format":"mp4","quality":"high"}}. Poll status every 30s. |
Accepted file types: 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-llmX-Skill-Version: from frontmatterversionX-Skill-Platform: detect from install path (~/.clawhub/→clawhub,~/.cursor/skills/→cursor, elseunknown)
Include Authorization: Bearer \x3CNEMO_TOKEN> and all attribution headers on every request — omitting them triggers a 402 on export.
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 |
Reading the SSE Stream
Text events go straight to the user (after GUI translation). Tool calls stay internal. Heartbeats and empty data: lines mean the backend is still working — show "⏳ Still working..." every 2 minutes.
About 30% of edit operations close the stream without any text. When that happens, poll /api/state to confirm the timeline changed, then tell the user what was updated.
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)
Common Workflows
Quick edit: Upload → "turn this image into a 5-second animated video clip with smooth motion" → Download MP4. Takes 30-90 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 this image into a 5-second animated video clip with smooth motion" — concrete instructions get better results.
Max file size is 200MB. Stick to JPG, PNG, WEBP, HEIC for the smoothest experience.
Use PNG for source images to preserve quality before AI processing.
- 确保已安装 OpenClaw（本地或 Docker 部署）
- 在对话框中输入安装命令：
/install image-to-video-llm - 安装完成后，直接呼叫该 Skill 的名称或使用
/image-to-video-llm触发 - 根据 Skill 的参数说明提供必要输入，即可获得结构化输出
Image To Video Llm 是什么？
Skip the learning curve of professional editing software. Describe what you want — turn this image into a 5-second animated video clip with smooth motion — a... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件，目前累计下载 76 次。
如何安装 Image To Video Llm？
在 OpenClaw 或 Claude Code 对话框中运行命令「/install image-to-video-llm」即可一键安装，无需额外配置。
Image To Video Llm 是免费的吗？
是的，Image To Video Llm 完全免费，采用 MIT-0 许可证，可自由下载、安装和使用。
Image To Video Llm 支持哪些平台？
Image To Video Llm 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 Llm？
由 vynbosserman65（@vynbosserman65）开发并维护，当前版本 v1.0.0。