Sarvam STT

Sarvam AI provides streaming speech-to-text built for Indian languages. The plugin uses WebSocket streaming with built-in voice activity detection for turn events.

Vision Agents uses Stream Video for real-time WebRTC transport by default. External WebRTC transports are supported as well. Most AI providers offer free tiers to get started.

Get your Sarvam API key from the Sarvam dashboard.

Sarvam also provides text-to-speech and an LLM. You can use all three in the same agent.

Installation

uv add "vision-agents[sarvam]"

Quick start

from vision_agents.core import Agent, User
from vision_agents.plugins import sarvam, getstream, smart_turn

agent = Agent(
    edge=getstream.Edge(),
    agent_user=User(name="Sarvam Agent", id="agent"),
    instructions="Reply in the same language the user speaks.",
    llm=sarvam.LLM(model="sarvam-m"),
    stt=sarvam.STT(language="hi-IN"),
    tts=sarvam.TTS(speaker="shubh"),
    turn_detection=smart_turn.TurnDetection(),
)

Set SARVAM_API_KEY in your environment or pass api_key directly.

Parameters

stt = sarvam.STT(
    model="saaras:v3",
    language="hi-IN",
    mode="transcribe",
    sample_rate=16000,
    high_vad_sensitivity=False,
)

Name	Type	Default	Description
model	str	"saaras:v3"	Streaming model (saaras:v3, saarika:v2.5, saaras:v2.5)
language	str	None	Language code (e.g. hi-IN, en-IN). None for auto-detect
mode	str	None	transcribe, translate, verbatim, translit, or codemix (saaras:v3 only)
sample_rate	int	16000	Input sample rate — 8000 or 16000 Hz
high_vad_sensitivity	bool	False	Increase VAD sensitivity for noisy input
vad_signals	bool	True	Emit speech start/end events for turn detection
prompt	str	None	Optional biasing prompt sent after connect (saaras:v2.5 and saaras:v3 only)
api_key	str	None	API key (defaults to SARVAM_API_KEY env var)

Next steps

Sarvam TTS

Streaming text-to-speech for Indian languages

Sarvam LLM

Chat completions with Sarvam models