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Generator Hindi

作者 linmillsd7 · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ✓ 安全检测通过
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在 OpenClaw 中安装
/install generator-hindi
功能描述
Turn a 2-minute English explainer video into 1080p Hindi dubbed videos just by typing what you need. Whether it's generating Hindi language videos from exist...
使用说明 (SKILL.md)

Getting Started

Send me your video clips and I'll handle the Hindi video generation. Or just describe what you're after.

Try saying:

  • "generate a 2-minute English explainer video into a 1080p MP4"
  • "generate a Hindi version of this video with dubbed audio and Hindi subtitles"
  • "generating Hindi language videos from existing content for Indian content creators"

First-Time Connection

When a user first opens this skill, connect to the processing backend automatically. Briefly let them know (e.g. "Setting up...").

Authentication: Check if NEMO_TOKEN is set in the environment. If it is, skip to step 2.

  1. Obtain a free token: Generate a random UUID as client identifier. POST to https://mega-api-prod.nemovideo.ai/api/auth/anonymous-token with header X-Client-Id set to that UUID. The response data.token is your NEMO_TOKEN — 100 free credits, valid 7 days.
  2. Create a session: POST to https://mega-api-prod.nemovideo.ai/api/tasks/me/with-session/nemo_agent with Authorization: Bearer \x3Ctoken>, Content-Type: application/json, and body {"task_name":"project","language":"\x3Cdetected>"}. Store the returned session_id for all subsequent requests.

Keep setup communication brief. Don't display raw API responses or token values to the user.

Generator Hindi — Generate Hindi Language Videos

Drop your video clips in the chat and tell me what you need. I'll handle the Hindi video generation on cloud GPUs — you don't need anything installed locally.

Here's a typical use: you send a a 2-minute English explainer video, ask for generate a Hindi version of this video with dubbed audio and Hindi subtitles, 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 clips under 3 minutes produce more accurate Hindi lip-sync results.

Matching Input to Actions

User prompts referencing generator hindi, 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 calls go to https://mega-api-prod.nemovideo.ai. The main endpoints:

  1. SessionPOST /api/tasks/me/with-session/nemo_agent with {"task_name":"project","language":"\x3Clang>"}. Gives you a session_id.
  2. Chat (SSE)POST /run_sse with session_id and your message in new_message.parts[0].text. Set Accept: text/event-stream. Up to 15 min.
  3. UploadPOST /api/upload-video/nemo_agent/me/\x3Csid> — multipart file or JSON with URLs.
  4. CreditsGET /api/credits/balance/simple — returns available, frozen, total.
  5. StateGET /api/state/nemo_agent/me/\x3Csid>/latest — current draft and media info.
  6. ExportPOST /api/render/proxy/lambda with render ID and draft JSON. Poll GET /api/render/proxy/lambda/\x3Cid> every 30s for completed status and download URL.

Formats: mp4, mov, avi, webm, mkv, jpg, png, gif, webp, mp3, wav, m4a, aac.

Three attribution headers are required on every request and must match this file's frontmatter:

Header Value
X-Skill-Source generator-hindi
X-Skill-Version frontmatter version
X-Skill-Platform auto-detect: clawhub / cursor / unknown from install path

Every API call needs Authorization: Bearer \x3CNEMO_TOKEN> plus the three attribution headers above. If any header is missing, exports return 402.

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)

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

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.

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

Common Workflows

Quick edit: Upload → "generate a Hindi version of this video with dubbed audio and Hindi subtitles" → 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 Hindi version of this video with dubbed audio and Hindi subtitles" — concrete instructions get better results.

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

Export as MP4 for widest compatibility.

安全使用建议
This appears safe to install if you trust NemoVideo and the skill publisher. Before using it, confirm you are comfortable sending your video clips, audio, prompts, and draft state to the external nemovideo.ai service, and keep the NEMO_TOKEN private.
功能分析
Type: OpenClaw Skill Name: generator-hindi Version: 1.0.0 The skill is a legitimate integration for a video dubbing and generation service hosted at nemovideo.ai. It provides detailed instructions for the AI agent to manage authentication, session state, and video processing tasks via a cloud API. No evidence of data exfiltration, unauthorized file access, or malicious execution was found; the requested environment variables and configuration paths are consistent with the skill's stated purpose.
能力评估
Purpose & Capability
The described capabilities match the stated purpose of generating Hindi dubbed videos, but the work is performed by a third-party cloud service rather than locally.
Instruction Scope
The skill instructs the agent to create a backend session automatically and route upload, edit, export, credits, and status requests to NemoVideo API endpoints. This is disclosed and purpose-aligned.
Install Mechanism
There is no install spec or executable code to review, and the source/homepage metadata is sparse. The main reviewable behavior is in SKILL.md instructions.
Credentials
External API access, media upload, SSE processing, polling, and export downloads are proportionate for a cloud video generation skill, but users should expect their media to leave the local environment.
Persistence & Privilege
The skill uses a NEMO_TOKEN bearer credential and stores a session_id for subsequent requests. This is expected for the service but should be understood before use.
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 generator-hindi
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /generator-hindi 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
generator-hindi 1.0.0 - Initial release: Quickly turn 2-minute English explainer videos into 1080p Hindi-dubbed videos with optional Hindi subtitles. - Simple workflow: Just upload video clips and describe your output; the rest is automated — no manual editing or local installs required. - Automatic backend/session setup with guided authentication, free token acquisition, and streamlined user communication. - Cloud GPU rendering supports fast export in major video/audio/image formats (mp4, mov, avi, webm, mkv, jpg, png, gif, webp, mp3, wav, m4a, aac). - Full support for Hindi video generation, batch processing, timeline editing, and preview summaries, with robust error handling and tips for best results. - Includes credit management, session state tracking, and simple export with branded attribution.
元数据
Slug generator-hindi
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

Generator Hindi 是什么?

Turn a 2-minute English explainer video into 1080p Hindi dubbed videos just by typing what you need. Whether it's generating Hindi language videos from exist... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 60 次。

如何安装 Generator Hindi?

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

Generator Hindi 是免费的吗?

是的,Generator Hindi 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。

Generator Hindi 支持哪些平台?

Generator Hindi 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 Generator Hindi?

由 linmillsd7(@linmillsd7)开发并维护,当前版本 v1.0.0。

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