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Free Video Generation Model Api

作者 francemichaell-15 · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ⚠ suspicious
74
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当前安装
1
版本数
在 OpenClaw 中安装
/install free-video-generation-model-api
功能描述
Skip the learning curve of professional editing software. Describe what you want — generate a 10-second video clip of a futuristic city at night from a text...
使用说明 (SKILL.md)

Getting Started

Got text prompts to work with? Send it over and tell me what you need — I'll take care of the AI video generation.

Try saying:

  • "generate a short text description of a sunset beach scene into a 1080p MP4"
  • "generate a 10-second video clip of a futuristic city at night from a text prompt"
  • "generating short videos from text prompts via a free API for developers and creators"

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.

Free Video Generation Model API — Generate Videos from Text Prompts

Send me your text prompts and describe the result you want. The AI video generation runs on remote GPU nodes — nothing to install on your machine.

A quick example: upload a short text description of a sunset beach scene, type "generate a 10-second video clip of a futuristic city at night from a text prompt", and you'll get a 1080p MP4 back in roughly 30-90 seconds. All rendering happens server-side.

Worth noting: shorter prompts with clear scene descriptions produce more consistent results.

Matching Input to Actions

User prompts referencing free video generation model api, 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.

All requests must include: Authorization: Bearer \x3CNEMO_TOKEN>, X-Skill-Source, X-Skill-Version, X-Skill-Platform. Missing attribution headers will cause export to fail with 402.

Headers are derived from this file's YAML frontmatter. X-Skill-Source is free-video-generation-model-api, 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).

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.

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

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

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.

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 → "generate a 10-second video clip of a futuristic city at night from a text prompt" → 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 "generate a 10-second video clip of a futuristic city at night from a text prompt" — concrete instructions get better results.

Max file size is 500MB. Stick to MP4, MOV, WebM, GIF for the smoothest experience.

Export as MP4 for widest compatibility across platforms and players.

安全使用建议
This skill appears to implement a remote text→video API and asks for one API token (NEMO_TOKEN). Before installing: 1) Be cautious because the publisher/source is unknown and no homepage is provided — verify the domain (mega-api-prod.nemovideo.ai) and the service's reputation. 2) Prefer providing an ephemeral or limited-scope token (not your primary production credentials). 3) Expect the skill to contact the external API, generate anonymous tokens, and save session IDs/tokens; confirm where the agent persists those values (memory vs disk) and whether they are encrypted. 4) Note the SKILL.md references reading install paths/config directories — if you are concerned about filesystem probing, run the skill in a restricted/sandboxed environment. 5) If you need stronger assurance, request the publisher/source code or documentation and confirm the endpoints and data handling policy before use.
功能分析
Type: OpenClaw Skill Name: free-video-generation-model-api Version: 1.0.0 The skill bundle provides a legitimate interface for an AI agent to interact with the NemoVideo AI video generation API. It contains detailed instructions for session management, anonymous token acquisition, and handling server-sent events (SSE) for video processing. The instructions include security-conscious directives (e.g., not displaying raw tokens) and use standard HTTP methods for communication with the domain mega-api-prod.nemovideo.ai. No evidence of malicious intent, data exfiltration, or unauthorized command execution was found.
能力评估
Purpose & Capability
The skill claims to generate short videos from text and its instructions call a remote video-generation API (POSTs, uploads, render endpoints) and request a single API credential (NEMO_TOKEN). That is coherent with the stated purpose. However: the skill metadata in the packaged SKILL.md references a config path (~/.config/nemovideo/) and install-path detection for X-Skill-Platform even though the registry metadata lists no config paths — an inconsistency worth noting.
Instruction Scope
Runtime instructions require contacting an external domain (https://mega-api-prod.nemovideo.ai), generating an anonymous token if no NEMO_TOKEN is present, saving a session_id, and determining an install path to derive an X-Skill-Platform header (checking ~/.clawhub/, ~/.cursor/skills/, etc.). The install-path check implies filesystem probes beyond purely handling user prompts. The instructions also say to persist tokens/session state but do not specify storage scope or protections. These behaviors are plausible for an API client but expand scope beyond simple text→video conversion and are not fully justified or documented.
Install Mechanism
This is an instruction-only skill with no install spec and no code files. That is lower-risk from an installation perspective because nothing is downloaded or written to disk by an installer step.
Credentials
Only one environment variable is declared (NEMO_TOKEN) which fits an API client. However the skill's embedded frontmatter also lists a config path (~/.config/nemovideo/) and the runtime instructions expect to detect local install paths to set a header; the registry-level metadata presented to you showed no required config paths. This mismatch means the skill may try to read local paths it didn't explicitly declare, which is disproportionate unless you accept that local caching or platform detection is needed.
Persistence & Privilege
always:false and normal autonomous invocation are used (expected). The skill instructs saving session_id and the acquired token (if generated) for subsequent requests; persisting credentials/session state is typical for API clients but the SKILL.md does not specify where or how long to persist, so there is some risk that tokens or session IDs could be stored in a less-restricted location. No directive to modify other skills or system-wide config is present.
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 free-video-generation-model-api
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /free-video-generation-model-api 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 the Free Video Generation Model API skill. - Generate AI video clips from text prompts; no software setup required. - Supports uploads of MP4, MOV, WebM, and GIF files up to 500MB. - Provides a free, anonymous API token with 100 credits for 7 days. - Exports videos in multiple formats (MP4, MOV, WebM, GIF, etc.) via cloud GPU. - Includes detailed workflows, error handling, and transparent session management for developers and creators.
元数据
Slug free-video-generation-model-api
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

Free Video Generation Model Api 是什么?

Skip the learning curve of professional editing software. Describe what you want — generate a 10-second video clip of a futuristic city at night from a text... 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 Free Video Generation Model Api?

在 OpenClaw 或 Claude Code 对话框中运行命令「/install free-video-generation-model-api」即可一键安装,无需额外配置。

Free Video Generation Model Api 是免费的吗?

是的,Free Video Generation Model Api 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。

Free Video Generation Model Api 支持哪些平台?

Free Video Generation Model Api 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 Free Video Generation Model Api?

由 francemichaell-15(@francemichaell-15)开发并维护,当前版本 v1.0.0。

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