# Chat

> 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. Use when this capability is needed.

- Skill: `tomevault-io/chat-2` (Agent Skill, multi-file: 2 files)
- Install (CLI): `npx skillmds@latest add tomevault-io/chat-2`
- Raw SKILL.md: https://api.skillmd.com/api/skills/tomevault-io/chat-2/raw
- Safety review: pending (external: skill-scanner PASS, skillspector PASS)
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: AI & ML
- Author: tomevault-io (https://skillmd.com/u/tomevault-io)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/tomevault-io/chat-2

---


# Chat Completions — Sarvam AI

> [!IMPORTANT]
> Auth: `api-subscription-key` header — NOT `Authorization: Bearer`. Base URL: `https://api.sarvam.ai/v1`

## Models

| Model | Context | Best For |
|-------|---------|----------|
| `sarvam-105b` | 128K | Complex reasoning, coding, agentic workflows |
| `sarvam-30b` | 64K | Real-time chat, voice agents, conversational AI |
| `sarvam-105b-32k` | 32K | Cost-efficient 105B |
| `sarvam-30b-16k` | 16K | Cost-efficient 30B |

## Quick Start (Python)

```python
from sarvamai import SarvamAI
client = SarvamAI()

response = client.chat.completions(
    model="sarvam-30b",
    messages=[{"role": "user", "content": "भारत की राजधानी क्या है?"}]
)
print(response.choices[0].message.content)
```

### Streaming (Python)

```python
for chunk in client.chat.completions(
    model="sarvam-30b",
    messages=[{"role": "user", "content": "Write a poem about India"}],
    stream=True
):
    if chunk.choices and chunk.choices[0].delta.content:
        print(chunk.choices[0].delta.content, end="", flush=True)
```

## Quick Start (JavaScript/TypeScript)

```typescript
import { SarvamAIClient } from "sarvamai";

const client = new SarvamAIClient({ apiSubscriptionKey: "YOUR_SARVAM_API_KEY" });

const response = await client.chat.completions({
    model: "sarvam-30b",
    messages: [{ role: "user", content: "भारत की राजधानी क्या है?" }]
});
console.log(response.choices[0].message.content);
```

### OpenAI-Compatible (both languages)

```python
from openai import OpenAI
client = OpenAI(api_key="your-key", base_url="https://api.sarvam.ai/v1")
response = client.chat.completions.create(model="sarvam-30b", messages=[...])
```

## Gotchas

| Gotcha | Detail |
|--------|--------|
| **SDK method** | Python: `client.chat.completions(...)`, JS: `client.chat.completions({...})` — no `.create()` in either. OpenAI SDK uses `.create()` as usual. |
| **JS constructor** | `new SarvamAIClient({ apiSubscriptionKey: "..." })` — NOT `SarvamAI()`. Key is passed explicitly. |
| **`content` can be `None`** | Models produce `reasoning_content` before `content`. If `max_tokens` is too low, reasoning consumes the budget and `content` is `None`. Omit `max_tokens` or set 500+. Check `reasoning_content` as fallback. |
| **reasoning_effort** | `reasoning_effort="low"\|"medium"\|"high"` for thinking mode. NOT `thinking=True`. |

## Full Docs

Fetch detailed parameters, tool calling, streaming, and examples from:

- **https://docs.sarvam.ai/llms.txt** — comprehensive docs index
- [Chat Completion Guide](https://docs.sarvam.ai/api-reference-docs/api-guides-tutorials/chat-completion/overview)
- [Model Specs](https://docs.sarvam.ai/api-reference-docs/getting-started/models)
- [Rate Limits](https://docs.sarvam.ai/api-reference-docs/ratelimits)

---
> Converted and distributed by [TomeVault](https://tomevault.io/claim/sarvamai) — claim your Tome and manage your conversions.
<!-- tomevault:4.0:skill_md:2026-04-14 -->