chat

Generate multilingual chat completions via Sarvam AI's OpenAI-compatible API.

Updated Jun 18, 2026
One-click install
npx skills add https://github.com/abhishekmmgn/didactic-invention --skill chat-abhishekmmgn
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: chat
Source: https://github.com/abhishekmmgn/didactic-invention/tree/main/.agents/skills/chat
Command: npx skills add https://github.com/abhishekmmgn/didactic-invention --skill chat-abhishekmmgn

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Chat completions using Sarvam AI LLMs (Sarvam-105B, Sarvam-30B). Handles AI chat, text generation, reasoning, coding, and multilingual conversations in Indian languages. OpenAI-compatible API. Use when building chatbots, Q&A systems, agents, or any LLM feature targeting Indian users.

Core Features & Use Cases

  • Models: sarvam-105b (128K context) for complex reasoning and agentic workflows, sarvam-30b (64K) for real-time chat and conversational AI, sarvam-105b-32k (32K) for cost-efficient deployments, sarvam-30b-16k (16K) for lightweight use.
  • OpenAI-compatible API surface with header-based authentication using api-subscription-key and base URL: https://api.sarvam.ai/v1
  • Streaming support and multilingual conversations across Indian languages.
  • Use cases include building chatbots, Q&A systems, agents, or any LLM-powered conversational feature for Indian users.

Quick Start

Call the Sarvam API's chat.completions with model sarvam-30b and a user message to obtain a reply.

Frequently Asked Questions about chat

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I integrate multilingual chat completions for Indian languages using an OpenAI-compatible API?▼

You can implement multilingual chat completions for Indian languages by calling the Sarvam AI API at https://api.sarvam.ai/v1. This OpenAI-compatible endpoint uses header-based authentication with an api-subscription-key to process conversational AI requests.

Which Sarvam AI models should I use for real-time chat versus complex reasoning tasks?▼

For complex reasoning and agentic workflows, use the sarvam-105b model with its 128K context window. For real-time chat and conversational AI, sarvam-30b with a 64K context is recommended, while sarvam-30b-16k suits lightweight deployments.

Can I use streaming support with Sarvam AI LLMs for live chatbot responses?▼

Yes, streaming support is available when using Sarvam AI LLMs for chat completions. This allows you to stream live conversational AI responses directly through the OpenAI-compatible API surface to your chatbot or Q&A system.

Does the Sarvam AI chat completions API require any specific dependencies or component installations?▼

No specific dependencies or components are required to use the Sarvam AI chat completions API. You simply need to authenticate via the api-subscription-key header and direct your requests to the base URL to generate multilingual text.

What is the most cost-efficient way to deploy Sarvam AI models for lightweight conversational features?▼

The most cost-efficient approach for lightweight conversational features is using the sarvam-30b-16k model with its 16K context window. Alternatively, sarvam-105b-32k offers a 32K context for cost-efficient deployments requiring more capacity.

How do I authenticate API requests when building Q&A systems with Sarvam AI?▼

You authenticate API requests for Q&A systems by including the api-subscription-key in your HTTP headers. This header-based authentication method secures your calls to the Sarvam AI base URL for generating chat completions.