sarvam-ai
Indian AI toolkit powered by Sarvam AI — text-to-speech, speech-to-text, document intelligence, translation, transliteration, language detection, and chat…
Skill by ankitjh4
Install
Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.
npx agentmarket install skill/ankitjh4-sarvam-ai
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About
Use cases: documents
Reviews
Write a reviewNo reviews yet. Installed it? Reviews come from verified installers only. How reviews work
Permissions
What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.
- Tools
- No tools found
- Secrets
- None asked for
- Install scripts
- None found
- Runs as
- Python package
Network hosts it talks to 1
codeload.github.com· found in install command
Files it touches
~/.claude/skills/sarvam-ai
What's inside
- Skill name
sarvam-ai- Description
- Indian AI toolkit powered by Sarvam AI — text-to-speech, speech-to-text, document intelligence, translation, transliteration, language detection, and chat completion across 23 Indian languages. Use when working with Indian languages, Hindi/Tamil/Bengali text, Sarvam AI, or when the user needs translation, transcription, or TTS for South Asian languages.
- License
- MIT
- Metadata
- author: ankitjh4 · category: External · display-name: Indian AI Toolkit (Sarvam)
- Instructions
- 119 lines in SKILL.md · view on GitHub
Before installing
- Ships executable scripts
Files (7)
- README.md
- SKILL.md
- SKILL.md.bak
- document_intelligence.py · scripts/
- speech_to_text.py · scripts/
- text_processing.py · scripts/
- tts.py · scripts/
SKILL.md (first lines)
# Sarvam AI — Indian Language Toolkit Comprehensive AI toolkit for 23 Indian languages: TTS, STT, Document Intelligence, Translation, Transliteration, Language Detection, and Chat. ## Setup 1. Get a free API key at https://dashboard.sarvam.ai 2. Set environment variable: `export SARVAM_API_KEY="your-api-key"` ## Supported Languages `hi-IN` Hindi, `en-IN` English, `bn-IN` Bengali, `gu-IN` Gujarati, `kn-IN` Kannada, `ml-IN` Malayalam, `mr-IN` Marathi, `or-IN`/`od-IN` Odia, `pa-IN` Punjabi, `ta-IN` Tamil, `te-IN` Telugu, `ur-IN` Urdu, `as-IN` Assamese, `bodo-IN`/`brx-IN` Bodo, `doi-IN` Dogri, `ks-IN` Kashmiri, `kok-IN` Konkani, `mai-IN` Maithili, `mni-IN` Manipuri, `ne-IN` Nepali, `sa-IN` Sanskrit, `sat-IN` Santali, `sd-IN` Sindhi --- ## Text-to-Speech ```bash python3 scripts/tts.py "नमस्ते, आप कैसे हैं?" --language hi-IN --speaker meera ``` | Parameter | Default | Description | |-----------|---------|-------------| | `text` | — | Text to convert (max 2500 chars) | | `--language` | hi-IN | Language code | | `--speaker` | meera | Voice name | | `--output` | output.wav | Output file | | `--sample-rate` | 24000 | Audio sample rate | **Speakers** — Female: Meera, Priya, Neha, Simran, Kavya, Ishita, Shreya, and more. Male: Shubh, Aditya, Rahul, Amit, Dev, Arjun, and more. --- ## Speech-to-Text Three modes: REST (quick, <30s), WebSocket (real-time streaming), Batch (long audio, diarization). ```bash # REST — quick transcription python3 scripts/speech_to_text.py rest audio.mp3 # WebSocket — real-time streaming python3 scripts/speech_to_text.py websocket audio.wav # Batch — multiple files with speaker diarization python3 scripts/speech_to_text.py batch audio1.mp3 audio2.mp3 --diarization --num-speakers 3 --output-dir ./transcripts/ ``` **Batch workflow:** create job → upload files → start → poll status (Accepted → Pending → Running → Completed) → download results. **Formats:** WAV, MP3, AAC, AIFF, OGG, OPUS, FLAC, MP4/M4A, AMR, WMA, WebM, PCM --- ## Document Intelligence Extract text from PDFs and images (JPEG/PNG). ```bash python3 scripts/document_intelligence.py document.pdf --language hi-IN --format md python3 scripts/document_intelligence.py --job-id <id> --download -o ./output/ ``` **Formats:** `md` (default), `html`, `json`. Max 200 MB, 500 pages. --- ## Translation ```bash # Auto-detect source, translate to Hindi python3 scripts/text_processing.py translate "Hello, how are you?" --target hi-IN # Mayura model with colloquial mode python3 scripts/text_processing.py translate "What's up?" --target hi-IN --model mayura:v1 --mode modern-colloquial ``` **Models:** `sarvam-translate:v1` (23 languages), `mayura:v1` (12 languages, supports modes and transliteration) **Modes** (mayura only): `formal`, `modern-colloquial`, `classic-colloquial`, `code-mixed` --- ## Transliteration ```bash python3 scripts/text_processing.py transliterate "नमस्ते" --source hi-IN --target en-IN python3 scripts/text_processing.py transliterate "namaste" --source en-IN --target hi-IN --spoken-form ``` --- ## Language Detection ```bash python3 scripts/text_processing.py detect "नमस्ते दुনিয়া" # Output: Language: hi-IN, Script: Deva ``` --- ## Chat Completion Two models: `sarvam-105b` (flagship, complex reasoning) and `sarvam-m` (efficient, general chat). ```bash python3 scripts/text_processing.py chat "Explain quantum computing" --model sarvam-105b python3 scripts/text_processing.py chat "What is the capital of India?" --model sarvam-m --temperature 0.8 ``` --- ## Resources - Dashboard: https://dashboard.sarvam.ai - Docs: https://docs.sarvam.ai - Cookbook: https://github.com/sarvamai/sarvam-ai-cookbook
From ankitjh4/indic-ai-skills, MIT.
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Signals
- Stars
- 66
- Forks
- 10
- Open issues
- 1
- Last commit (this folder)
- Mar 25, 2026 (7 months ago)
From GitHub (fetched Oct 24, 2026).
Details
- License
- MIT
- Repository
- github.com/ankitjh4/indic-ai-skills
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
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Cite this page
sarvam-ai skill. Agent Mart. https://agentmart.dev/skills/ankitjh4-sarvam-ai (last updated 2026-10-24)