Ai Video Generator Free Leonardo
/install ai-video-generator-free-leonardo
Getting Started
Share your text prompts or images and I'll get started on AI video generation. Or just tell me what you're thinking.
Try saying:
- "generate my text prompts or images"
- "export 1080p MP4"
- "generate a 15-second video from this"
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-tokenwith theX-Client-Idheader - The response includes a
tokenwith 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 Generator Free Leonardo — Generate Videos from Text or Images
Drop your text prompts or 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 product photo with a short description, ask for generate a 15-second video from this image and text prompt, and about 1-2 minutes later you've got a MP4 file ready to download. The whole thing runs at 1080p by default.
One thing worth knowing — shorter prompts with clear subjects produce more consistent results.
Matching Input to Actions
User prompts referencing ai video generator free leonardo, 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.
Skill attribution — read from this file's YAML frontmatter at runtime:
X-Skill-Source:ai-video-generator-free-leonardoX-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.
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.
Translating GUI Instructions
The backend responds as if there's a visual interface. Map its instructions to API calls:
- "click" or "点击" → execute the action via the relevant endpoint
- "open" or "打开" → query session state to get the data
- "drag/drop" or "拖拽" → send the edit command through SSE
- "preview in timeline" → show a text summary of current tracks
- "Export" or "导出" → run the export workflow
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)
Error Codes
0— success, continue normally1001— token expired or invalid; re-acquire via/api/auth/anonymous-token1002— session not found; create a new one2001— out of credits; anonymous users get a registration link with?bind=\x3Cid>, registered users top up4001— unsupported file type; show accepted formats4002— file too large; suggest compressing or trimming400— missingX-Client-Id; generate one and retry402— free plan export blocked; not a credit issue, subscription tier429— rate limited; wait 30s and retry once
Common Workflows
Quick edit: Upload → "generate a 15-second video from this image and text prompt" → Download MP4. Takes 1-2 minutes 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 "generate a 15-second video from this image and text prompt" — concrete instructions get better results.
Max file size is 200MB. Stick to JPG, PNG, MP4, WebM for the smoothest experience.
Export as MP4 for widest compatibility.
- 确保已安装 OpenClaw(本地或 Docker 部署)
- 在对话框中输入安装命令:
/install ai-video-generator-free-leonardo - 安装完成后,直接呼叫该 Skill 的名称或使用
/ai-video-generator-free-leonardo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
Ai Video Generator Free Leonardo 是什么?
generate text prompts or images into AI generated videos with this skill. Works with JPG, PNG, MP4, WebM files up to 200MB. content creators use it for gener... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 74 次。
如何安装 Ai Video Generator Free Leonardo?
在 OpenClaw 或 Claude Code 对话框中运行命令「/install ai-video-generator-free-leonardo」即可一键安装,无需额外配置。
Ai Video Generator Free Leonardo 是免费的吗?
是的,Ai Video Generator Free Leonardo 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。
Ai Video Generator Free Leonardo 支持哪些平台?
Ai Video Generator Free Leonardo 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 Generator Free Leonardo?
由 peandrover adam(@peand-rover)开发并维护,当前版本 v1.0.0。