Skill: francemichaell-15/text-to-video-hindi (version 1.0.0)

--- name: text-to-video-hindi version: "1.0.0" displayName: "Text to Video Hindi — Convert Hindi Text into Videos" description: > Skip the learning curve of professional editing software. Describe what you want — हिंदी टेक्स्ट से वीडियो बनाओ with matching visuals and voiceover — and get Hindi text videos back in 1-2 minutes. Upload TXT, DOCX, PDF, SRT files up to 200MB, and the AI handles AI video creation automatically. Ideal for Hindi content creators who need to create Hindi videos without filming or recording. metadata: {"openclaw": {"emoji": "🎬", "requires": {"env": ["NEMO_TOKEN"], "configPaths": ["~/.config/nemovideo/"]}, "primaryEnv": "NEMO_TOKEN", "variant": "short_prompts"}} --- ## Getting Started > Share your text or script and I'll get started on AI video creation. Or just tell me what you're thinking. **Try saying:** - "convert my text or script" - "export 1080p MP4" - "हिंदी टेक्स्ट से वीडियो बनाओ with" ### 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 <token>`, `Content-Type: application/json`, and body `{"task_name":"project","language":"<detected>"}`. 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. # Text to Video Hindi — Convert Hindi Text into Videos This tool takes your text or script and runs AI video creation through a cloud rendering pipeline. You upload, describe what you want, and download the result. Say you have a 100-word Hindi product description and want to हिंदी टेक्स्ट से वीडियो बनाओ with matching visuals and voiceover — the backend processes it in about 1-2 minutes and hands you a 1080p MP4. Tip: shorter Hindi paragraphs generate more accurate lip-sync and voiceover timing. ## Matching Input to Actions User prompts referencing text to video 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. Three attribution headers are required on every request and must match this file's frontmatter: | Header | Value | |--------|-------| | `X-Skill-Source` | `text-to-video-hindi` | | `X-Skill-Version` | frontmatter `version` | | `X-Skill-Platform` | auto-detect: `clawhub` / `cursor` / `unknown` from install path | Include `Authorization: Bearer <NEMO_TOKEN>` and all attribution headers on every request — omitting them triggers a 402 on export. **API base**: `https://mega-api-prod.nemovideo.ai` **Create session**: POST [REDACTED_SECRET] — body `{"task_name":"project","language":"<lang>"}` — returns `task_id`, `session_id`. **Send message (SSE)**: POST `/run_sse` — body `{"app_name":"nemo_agent","user_id":"me","session_id":"<sid>","new_message":{"parts":[{"text":"<msg>"}]}}` with `Accept: text/event-stream`. Max timeout: 15 minutes. **Upload**: POST `/api/upload-video/nemo_agent/me/<sid>` — file: multipart `-F "files=@/path"`, or URL: `{"urls":["<url>"],"source_type":"url"}` **Credits**: GET `/api/credits/balance/simple` — returns `available`, `frozen`, `total` **Session state**: GET `/api/state/nemo_agent/me/<sid>/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_<ts>","sessionId":"<sid>","draft":<json>,"output":{"format":"mp4","quality":"high"}}`. Poll GET `/api/render/proxy/lambda/<id>` 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. ### 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. ### 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 **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 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 ## Tips and Tricks The backend processes faster when you're specific. Instead of "make it look better", try "हिंदी टेक्स्ट से वीडियो बनाओ with matching visuals and voiceover" — concrete instructions get better results. Max file size is 200MB. Stick to TXT, DOCX, PDF, SRT for the smoothest experience. Export as MP4 for widest compatibility across Indian social media platforms. ## Common Workflows **Quick edit**: Upload → "हिंदी टेक्स्ट से वीडियो बनाओ with matching visuals and voiceover" → 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.


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)