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Text To Image Ai Free

该 Skill 接收文本提示词,调用云端 GPU 服务生成图像;也可上传图片或视频,按会话维护时间线状态,并按需导出 1080p MP4。需配置 NEMO_TOKEN,首次使用会自动获取匿名令牌并创建会话,全流程依赖网络与云端服务。

tk8544-b
tk8544-b
热度 32.12
最近更新 2026-05-11 09:55:14
分类:创作依赖:第三方 API / 读写文件应用场景:图像生成 / 视频编辑 / API 集成

安装技能

复制下面的话术发给你的 Agent,它会通过 secure-skills 检索并安装该技能。

执行命令安装此 skill: npx secure-skills-cli add text-to-image-ai-free
Metadata
name
text-to-image-ai-free
version
1.0.0
displayName
Text to Image AI Free — Generate Images from Text Prompts
description
content creators generate text prompts into AI generated visuals using this skill. Accepts JPG, PNG, WEBP, MP4 up to 200MB, renders on cloud GPUs at 1080p, and returns MP4 files in 20-40 seconds. Designed for generating images from text descriptions for video content.
metadata
{"openclaw":{"emoji":"🖼️","requires":{"env":["NEMO_TOKEN"],"configPaths":["~/.config/nemovideo/"]},"primaryEnv":"NEMO_TOKEN","variant":"greeting_v2"}}

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":"<lang>"}. 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/<sid> POST Upload a file (multipart) or URL.
/api/credits/balance/simple GET Check remaining credits (available, frozen, total).
/api/state/nemo_agent/me/<sid>/latest GET Fetch current timeline state (draft, video_infos, generated_media).
/api/render/proxy/lambda POST Start export. Body: {"id":"render_<ts>","sessionId":"<sid>","draft":<json>,"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 <NEMO_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=<id> (get <id> 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 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.