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dsewell-583h0

Caption Generator Bangla

作者 dsewell-583h0 · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ⚠ suspicious
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在 OpenClaw 中安装
/install caption-generator-bangla
功能描述
Skip the learning curve of professional editing software. Describe what you want — generate captions in Bangla for my video — and get Bangla captioned videos...
使用说明 (SKILL.md)

Getting Started

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

Try saying:

  • "add a 3-minute Bengali YouTube video into a 1080p MP4"
  • "generate captions in Bangla for my video"
  • "adding Bangla subtitles to videos for Bengali content 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.

Caption Generator Bangla — Add Bangla Captions to Videos

Send me your video files and describe the result you want. The Bangla 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 captions in Bangla for my video", and you'll get a 1080p MP4 back in roughly 30-60 seconds. All rendering happens server-side.

Worth noting: shorter clips under 2 minutes produce the most accurate Bangla text recognition.

Matching Input to Actions

User prompts referencing caption generator 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.

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

Header Value
X-Skill-Source caption-generator-bangla
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.

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.

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.

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 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)

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=\x3Cid> (get \x3Cid> 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

Common Workflows

Quick edit: Upload → "generate captions in Bangla for my video" → Download MP4. Takes 30-60 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 captions in Bangla for my video" — 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 media platforms.

安全使用建议
This skill behaves like a client for an external nemo video service and will upload whatever video files you provide to https://mega-api-prod.nemovideo.ai. Before installing or using it: 1) Confirm you trust that external domain and its privacy/retention policy — you may be sending sensitive video/audio. 2) Prefer using the anonymous-token flow (temporary 7‑day token) instead of supplying a long-lived NEMO_TOKEN if you have privacy concerns. 3) Ask the skill author to explain the frontmatter config path (~/.config/nemovideo/) and why it wasn't listed in the registry metadata — does the skill read/write local config? 4) Note the skill will add attribution headers that include an auto-detected platform value (it may inspect the agent/install path); if you want to avoid exposing environment details, ask the author to provide a safe default. If you cannot verify the service owner or the endpoint's privacy/security practices, avoid uploading sensitive content or providing a permanent token.
功能分析
Type: OpenClaw Skill Name: caption-generator-bangla Version: 1.0.0 The skill bundle provides instructions for an AI agent to integrate with the NemoVideo API (mega-api-prod.nemovideo.ai) for generating Bangla captions on videos. It includes detailed workflows for authentication, session management, and video processing, with explicit instructions to protect sensitive tokens and handle API responses correctly. No malicious patterns such as data exfiltration or unauthorized execution were identified in SKILL.md or _meta.json.
能力评估
Purpose & Capability
The name/description (Bangla captioning) aligns with the runtime actions (upload video, request renders, return download URL). Requesting a NEMO_TOKEN credential for a video-processing API is reasonable. However, the SKILL.md frontmatter lists a config path (~/.config/nemovideo/) while the registry metadata earlier reported no required config paths — that mismatch should be explained (does the skill read or write that directory?).
Instruction Scope
The instructions are focused on interacting with the remote nemo API (session creation, uploads, SSE, render polling). They don't instruct the agent to read unrelated files or export unrelated secrets. One scope note: header construction requests an 'auto-detect' of platform from install path which could require the agent to inspect its environment; the frontmatter's config path implies possible file access. Those behaviors are tangential to captioning and should be clarified.
Install Mechanism
This is an instruction-only skill with no install spec and no code files — lowest-risk install surface. Nothing will be downloaded or written by an install procedure.
Credentials
Only one credential (NEMO_TOKEN) is declared as primary, which is proportionate for a hosted video-processing API. The skill also documents a procedure to obtain an anonymous token (100 credits, 7-day expiry), which reduces the need to provide a long-lived token. Still, the presence of an undeclared config path in the frontmatter (~/.config/nemovideo/) raises questions about whether the skill may read local config beyond the single env var.
Persistence & Privilege
The skill is not always-enabled and does not request system-wide persistence. Runtime state (session_id) is saved for session use per the instructions, which is expected. It does not request modifications to other skills or system settings.
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 caption-generator-bangla
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /caption-generator-bangla 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 Caption Generator Bangla — Add Bangla Captions to Videos: - Upload MP4, MOV, AVI, WebM files up to 500MB and automatically generate Bangla captions for videos. - Simple, guided process: connect, upload, instruct, and get downloadable captioned videos in 30–60 seconds. - No editing software or manual transcription required; all rendering and text recognition happen server-side on cloud GPU. - Supports checking credits, export/download, and session management. - Handles errors gracefully, provides helpful tips, and supports multiple editing workflows for Bengali content creators.
元数据
Slug caption-generator-bangla
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

Caption Generator Bangla 是什么?

Skip the learning curve of professional editing software. Describe what you want — generate captions in Bangla for my video — and get Bangla captioned videos... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 69 次。

如何安装 Caption Generator Bangla?

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

Caption Generator Bangla 是免费的吗?

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

Caption Generator Bangla 支持哪些平台?

Caption Generator Bangla 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 Caption Generator Bangla?

由 dsewell-583h0(@dsewell-583h0)开发并维护,当前版本 v1.0.0。

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