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ai-subtitle-bangla（ai 字幕孟加拉语）

Agent Skill

ai-subtitle-bangla 用于记录任务执行中的错误、用户纠正、经验和能力缺口，适合在 OpenClaw 中希望让 Agent 持续沉淀问题、修正和最佳实践时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态，以及是否会触发联网、命令执行或文件读写。

总安装

1,473

周安装

GitHub Stars

公开资料未说明

下载量

516

OpenClaw

安装说明

本站只整理中文说明和来源信息，不托管安装包，也不代用户安装。

GitHub

来源数

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手，先确认命令和权限，再让它执行。

请帮我安装这个 Agent Skill：ai-subtitle-bangla（ai 字幕 孟加拉语）
来源仓库：https://github.com/tk8544-b/ai-subtitle-bangla
安装命令：
openclaw skills install ai-subtitle-bangla
安装前请先检查当前环境是否支持对应 CLI，并向我确认将要执行的命令、安装目录、联网范围和文件读写权限；确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill；本站只展示命令，不托管安装包，也不自动执行。

ClawHubOpenClaw

openclaw skills install ai-subtitle-bangla

简介

自动生成孟加拉语字幕，降低多语种内容制作门槛。

跳过专业软件学习曲线，直达字幕生成环节。ai-subtitle-bangla 属于效率类 Skill，可作为该场景下的辅助能力补充。
适用于南亚市场本地化视频内容快速上线需求。
孟加拉语识别准确率受发音标准度影响较大。
生成字幕需经母语者校对，避免文化语境误解风险。

SKILL.md

name: ai-subtitle-bangla
version: 1.0.0
displayName: AI Subtitle Bangla — Generate Bangla Subtitles Automatically
description: >
metadata: {"openclaw": {"emoji": "🎬", "requires": {"env": ["NEMO_TOKEN"], "configPaths": ["~/.config/nemovideo/"]}, "primaryEnv": "NEMO_TOKEN", "variant": "short_prompts"}}

Getting Started

Share your video files and I'll get started on AI subtitle generation. Or just tell me what you're thinking.

Try saying:

"add my video files"
"export 1080p MP4"
"generate Bangla subtitles for my video"

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: <uuid>. 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.

AI Subtitle Bangla — Generate Bangla Subtitles Automatically

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

A quick example: upload a 3-minute Bengali YouTube video, type "generate Bangla subtitles for my video automatically", and you'll get a 1080p MP4 back in roughly 1-2 minutes. All rendering happens server-side.

Worth noting: shorter clips under 5 minutes produce the most accurate Bangla subtitle sync.

Matching Input to Actions

User prompts referencing ai subtitle bangla, 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:

Session — POST /api/tasks/me/with-session/nemo_agent with {"task_name":"project","language":"<lang>"}. Gives you a session_id.
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.
Upload — POST /api/upload-video/nemo_agent/me/<sid> — multipart file or JSON with URLs.
Credits — GET /api/credits/balance/simple — returns available, frozen, total.
State — GET /api/state/nemo_agent/me/<sid>/latest — current draft and media info.
Export — POST /api/render/proxy/lambda with render ID and draft JSON. Poll GET /api/render/proxy/lambda/<id> 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`	`ai-subtitle-bangla`
`X-Skill-Version`	frontmatter `version`
`X-Skill-Platform`	auto-detect: `clawhub` / `cursor` / `unknown` from install path

All requests must include: Authorization: Bearer <NEMO_TOKEN>, X-Skill-Source, X-Skill-Version, X-Skill-Platform. Missing attribution headers will cause export to fail with 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=<id>, 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 Bangla subtitles for my video automatically" → 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 Bangla subtitles for my video automatically" — 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 across Bengali social platforms.

适合场景

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用户想查找某类 Agent Skill 时

需要根据任务场景推荐可安装能力包时

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明，方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用；具体调用方式请以来源页面和 README 为准。

平台分布

OpenClaw

83.85%

按下载量换算433

安全审计

VirusTotal

可疑

ClawScan

通过

Static analysis

通过

权限和风险

敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置，应进入高风险复核队列，默认不自动发布。

安装前确认

本站仅展示第三方公开信息，不托管安装包，不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在 warning/failed 结果，不能写成本站确认安全。当前只有一个来源，正式发布前建议补源仓库或其他目录站核验。

来源信息

GitHub 仓库

github.com

/tk8544-b/ai-subtitle-bangla

SKILL.md 来源

clawhub.ai