Sarvam LLM

Sarvam AI provides language models built for Indian languages. The plugin uses Sarvam’s OpenAI-compatible Chat Completions endpoint and automatically strips <think> reasoning blocks from streamed output.

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 speech-to-text and text-to-speech. 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 Hindi or English, whichever the user speaks.",
    llm=sarvam.LLM(model="sarvam-30b"),
    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

Name	Type	Default	Description
model	str	"sarvam-m"	Model id (sarvam-m, sarvam-30b, or sarvam-105b)
api_key	str	None	API key (defaults to SARVAM_API_KEY env var)
base_url	str	"https://api.sarvam.ai/v1"	Sarvam API endpoint

Available models

Model	Description
sarvam-m	Default model with hybrid thinking support
sarvam-30b	30B parameter model for balanced performance
sarvam-105b	105B parameter model for maximum capability

Sarvam-m supports “hybrid thinking” — it emits <think> reasoning blocks before the answer. The plugin automatically strips these so they don’t reach TTS.

Function calling

@agent.llm.register_function(description="Get weather for a location")
async def get_weather(location: str) -> str:
    return f"The weather in {location} is sunny and 30°C"

See the Function Calling guide for details.

Next steps

Sarvam STT

Streaming speech-to-text for Indian languages

Sarvam TTS

Streaming text-to-speech for Indian languages