Chat Completions Overview | Sarvam API Docs

Sarvam AI provides powerful chat completion APIs designed to build intelligent conversational AI experiences, with native support for Indian languages and deep contextual reasoning.

Our Chat Completion APIs currently support the following chat model:

Sarvam-M

Sarvam-M is a 24B parameter, open-weights language model built for multilingual, hybrid-reasoning in a text-only format.

Features

Hybrid Thinking Mode

Supports both “think” and “non-think” modes
Think mode for complex logical reasoning
Non-think mode for efficient conversations
Ideal for mathematical and coding tasks

Advanced Indic Skills

Post-trained on Indian languages
Native English proficiency
Authentic Indian cultural values
Rich understanding of local context

Superior Reasoning Capabilities

Outperforms similar-sized models
Strong performance on coding tasks
Excellent mathematical reasoning
Advanced problem-solving abilities

Seamless Chatting Experience

Full Indic script support
Romanized language support
Multilingual conversation handling
Natural language understanding

Code Examples

Basic Chat Completion

Multi-turn Conversation

Hindi (Indic Script)

Wiki Grounding

1 from sarvamai import SarvamAI
2 
3 client = SarvamAI(
4     api_subscription_key="YOUR_SARVAM_API_KEY",
5 )
6 response = client.chat.completions(messages=[
7     {"role": "user", "content": "Hey, what is the capital of India?"}
8 ])
9 print(response)

Key Considerations

Reasoning effort options: low, medium, high
- Setting any value enables thinking mode
- Higher values increase reasoning depth
Enable wiki_grounding for factual queries

API Response Format

Success Response Structure

1 {
2   "id": "chatcmpl-abc123",
3   "object": "chat.completion",
4   "created": 1699000000,
5   "model": "sarvam-m",
6   "choices": [
7     {
8       "index": 0,
9       "message": {
10         "role": "assistant",
11         "content": "The capital of India is New Delhi. It has been the capital since 1931."
12       },
13       "finish_reason": "stop"
14     }
15   ],
16   "usage": {
17     "prompt_tokens": 15,
18     "completion_tokens": 25,
19     "total_tokens": 40
20   }
21 }

Response Fields

Field	Type	Description
`id`	string	Unique identifier for the completion request
`object`	string	Always `"chat.completion"`
`created`	integer	Unix timestamp when the completion was created
`model`	string	The model used for completion
`choices[].index`	integer	Index of the choice in the list
`choices[].message.role`	string	Always `"assistant"`
`choices[].message.content`	string	The generated text response
`choices[].message.reasoning_content`	string	Thinking steps (only when `reasoning_effort` is set)
`choices[].finish_reason`	string	Why generation stopped: `"stop"`, `"length"`, `"content_filter"`
`usage.prompt_tokens`	integer	Tokens in the input prompt
`usage.completion_tokens`	integer	Tokens in the generated response
`usage.total_tokens`	integer	Total tokens used (prompt + completion)

Error Responses

All errors return a JSON object with an error field containing details about what went wrong.

Error Response Structure

1 {
2   "error": {
3     "message": "Human-readable error description",
4     "code": "error_code_for_programmatic_handling",
5     "request_id": "unique_request_identifier"
6   }
7 }

Error Codes Reference

HTTP Status	Error Code	When This Happens	What To Do
`400`	`invalid_request_error`	Missing `messages` array or malformed request	Include valid `messages` array with role/content
`403`	`invalid_api_key_error`	API key is invalid, missing, or expired	Verify your API key in the dashboard
`422`	`unprocessable_entity_error`	Invalid model name or parameter values	Check temperature (0-2), model name, etc.
`429`	`insufficient_quota_error`	API quota or rate limit exceeded	Wait for reset or upgrade your plan
`500`	`internal_server_error`	Unexpected server error	Retry the request; contact support if persistent

Example Error Response

1 {
2   "error": {
3     "message": "Invalid value for parameter 'temperature': must be between 0 and 2",
4     "code": "unprocessable_entity_error",
5     "request_id": "20241115_abc12345"
6   }
7 }

Error Handling Code Example

1 from sarvamai import SarvamAI
2 from sarvamai.core.api_error import ApiError
3 
4 client = SarvamAI(api_subscription_key="YOUR_SARVAM_API_KEY")
5 
6 try:
7     response = client.chat.completions(
8         messages=[
9             {"role": "user", "content": "What is the capital of India?"}
10         ]
11     )
12     print(response.choices[0].message.content)
13 except ApiError as e:
14     if e.status_code == 400:
15         print(f"Bad request: {e.body}")
16     elif e.status_code == 403:
17         print("Invalid API key. Check your credentials.")
18     elif e.status_code == 422:
19         print(f"Invalid parameters: {e.body}")
20     elif e.status_code == 429:
21         print("Rate limit exceeded. Wait and retry.")
22     else:
23         print(f"Error {e.status_code}: {e.body}")

Check out our detailed API Reference to explore Chat Completion and all available options.