Automatically generate and burn Bangla captions into your videos using AI-powered remote GPU rendering.
The fastest way to install a skill directly from the registry.
npx clawhub@latest install caption-generator-bangla
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
Copy this prompt to OpenClaw to install it automatically.
Help me install caption-generator-bangla using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Get the raw skill files in a ZIP archive.
Caption Generator Bangla is a powerful addition to the Openclaw Skills library, designed specifically to help users bypass the manual effort of video transcription and subtitle timing. By utilizing high-performance cloud GPU nodes, this skill allows you to generate captions in Bangla for my video prompts with incredible speed, often returning a finished 1080p MP4 in just 30 to 60 seconds. It is built for efficiency, handling complex video layers and platform-specific compression server-side so your local machine remains unburdened.
This tool is especially valuable for Bengali content creators who want to reach a broader audience through clear, accurate subtitles. As part of the Openclaw Skills ecosystem, it integrates seamlessly into your workflow, allowing you to describe your editing needs in plain language and receive professionally captioned media ready for social media distribution.
To get started with this skill in Openclaw Skills, you can either provide an existing API token or let the system generate an anonymous one for you.
# If you have a token, set it as an environment variable
export NEMO_TOKEN="your_private_token"
# The skill will automatically handle session creation on first interaction:
# POST https://mega-api-prod.nemovideo.ai/api/tasks/me/with-session/nemo_agent
Ensure your requests include the mandatory attribution headers like X-Skill-Source: caption-generator-bangla to avoid export blocks.
| Field | Type | Description |
|---|---|---|
| t | Array | List of timeline tracks (video, audio, text) |
| tt | Integer | Track type identifier (0=video, 1=audio, 7=text) |
| sg | Array | Segments containing start/end times in milliseconds |
| draft | JSON | The full session state including media metadata and track layering |
| output | Object | Export configuration including format (MP4) and quality (high) |
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