内容创作者可以将文本提示转换为 AI 生成的视觉效果。支持 JPG、PNG、WEBP、MP4 等格式，最大 200MB，云端 GPU 渲染 1080p，20-40 秒内输出 MP4 文件。适用于视频内容创作者的图像生成。
name: text-to-image-ai-free
version: "1.0.0"
displayName: "文本转图像 AI (免费) — 生成图像从文本提示"
description: >
内容创作者可以将文本提示转换为 AI 生成的视觉效果。支持 JPG、PNG、WEBP、MP4 等格式，最大 200MB，云端 GPU 渲染 1080p，20-40 秒内输出 MP4 文件。适用于视频内容创作者的图像生成。
metadata: {"openclaw": {"emoji": "🖼️", "requires": {"env": ["NEMO_TOKEN"], "configPaths": ["~/.config/nemovideo/"]}, "primaryEnv": "NEMO_TOKEN", "variant": "greeting_v2"}}
获取开始
请发送您的文本提示，我将处理 AI 图像生成。或者，只需描述您想要的内容。
尝试说：
- "使用 '山湖日落' 这样的短文本提示生成 1080p MP4"
- "生成一幅夜间霓虹灯下的未来城市的真实图像"
- "为内容创作者生成视频内容的文本描述图像"
... （以下内容由于长度限制，仅提供部分翻译，完整内容请参考原文）
Getting Started
Send me your text prompts and I'll handle the AI image generation. Or just describe what you're after.
Try saying:
- "generate a short descriptive text prompt like 'sunset over a mountain lake' into a 1080p MP4"
- "generate a realistic image of a futuristic city at night with neon lights"
- "generating images from text descriptions for video content for content creators"
Quick Start Setup
This skill connects to a cloud processing backend. On first use, set up the connection automatically and let the user know ("Connecting...").
Token check: Look for NEMO_TOKEN in the environment. If found, skip to session creation. Otherwise:
- Generate a UUID as client identifier
- POST
https://mega-api-prod.nemovideo.ai/api/auth/anonymous-token with X-Client-Id header
- Extract
data.token from the response — this is your NEMO_TOKEN (100 free credits, 7-day expiry)
Session: POST https://mega-api-prod.nemovideo.ai/api/tasks/me/with-session/nemo_agent with Bearer auth and body {"task_name":"project"}. Keep the returned session_id for all operations.
Let the user know with a brief "Ready!" when setup is complete. Don't expose tokens or raw API output.
# Text to Image AI Free — Generate Images from Text Prompts
Drop your text prompts in the chat and tell me what you need. I'll handle the AI image generation on cloud GPUs — you don't need anything installed locally.
Here's a typical use: you send a a short descriptive text prompt like 'sunset over a mountain lake', ask for generate a realistic image of a futuristic city at night with neon lights, and about 20-40 seconds later you've got a MP4 file ready to download. The whole thing runs at 1080p by default.
One thing worth knowing — shorter, specific prompts tend to produce more accurate and usable images.
Matching Input to Actions
User prompts referencing text to image ai free, 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":""}. 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/ | POST | Upload a file (multipart) or URL. |
/api/credits/balance/simple | GET | Check remaining credits (available, frozen, total). |
/api/state/nemo_agent/me//latest | GET | Fetch current timeline state (draft, video_infos, generated_media). |
/api/render/proxy/lambda | POST | Start export. Body: {"id":"render_","sessionId":"","draft":,"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.
Headers are derived from this file's YAML frontmatter. X-Skill-Source is text-to-image-ai-free, X-Skill-Version comes from the version field, and X-Skill-Platform is detected from the install path (~/.clawhub/ = clawhub, ~/.cursor/skills/ = cursor, otherwise unknown).
Include Authorization: Bearer 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= (get |
| 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 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)
Tips and Tricks
The backend processes faster when you're specific. Instead of "make it look better", try "generate a realistic image of a futuristic city at night with neon lights" — concrete instructions get better results.
Max file size is 200MB. Stick to JPG, PNG, WEBP, MP4 for the smoothest experience.
Export as MP4 for widest compatibility when embedding images into video sequences.
Common Workflows
Quick edit: Upload → "generate a realistic image of a futuristic city at night with neon lights" → Download MP4. Takes 20-40 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.
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