How to control response randomness with `temperature`

The temperature parameter controls how random or deterministic the model’s responses will be.

Range: 0 to 2
Default: 0.2

Lower temperature → more focused, predictable answers (e.g. 0.2)
Higher temperature → more creative, varied responses (e.g. 0.8 or 1.0)

👉 Tip: For most use cases, values between 0.2 and 0.8 give good results.

How it works:

Mode	Recommended `temperature`	Behavior
Non-thinking mode	`0.2` (default)	Straightforward, factual responses
Thinking mode	`0.5` or higher	Deeper reasoning, more exploration
Highly creative	`0.8` - `1.0`	Storytelling, brainstorming, poetry
Very random / playful	`> 1.0`	Unexpected, experimental output

First, install the SDK:

$ pip install -Uqq sarvamai

Then use the following Python code:

1 from sarvamai import SarvamAI
2 
3 # Initialize the SarvamAI client with your API key
4 client = SarvamAI(api_subscription_key="YOUR_SARVAM_API_KEY")
5 
6 # Example 1: Using default temperature (0.2) — straightforward, factual response
7 response = client.chat.completions(
8     model="sarvam-105b",
9     messages=[
10         {"role": "system", "content": "You are a helpful assistant."},
11         {"role": "user", "content": "Explain the concept of gravity."}
12     ],
13     # temperature is not specified → uses default 0.2
14 )
15 
16 print(response.choices[0].message.content)

1 from sarvamai import SarvamAI
2 
3 client = SarvamAI(api_subscription_key="YOUR_SARVAM_API_KEY")
4 
5 # Example 2: Using temperature = 0.9 — more creative, varied response
6 response = client.chat.completions(
7     model="sarvam-105b",
8     messages=[
9         {"role": "system", "content": "You are a creative storyteller."},
10         {"role": "user", "content": "Tell me a story about a magical tiger."}
11     ],
12     temperature=0.9  # More creative storytelling
13 )
14 
15 # Receive assistant's reply as output
16 print(response.choices[0].message.content)

1	from sarvamai import SarvamAI
2
3	# Initialize the SarvamAI client with your API key
4	client = SarvamAI(api_subscription_key="YOUR_SARVAM_API_KEY")
5
6	# Example 1: Using default temperature (0.2) — straightforward, factual response
7	response = client.chat.completions(
8	model="sarvam-105b",
9	messages=[
10	{"role": "system", "content": "You are a helpful assistant."},
11	{"role": "user", "content": "Explain the concept of gravity."}
12	],
13	# temperature is not specified → uses default 0.2
14	)
15
16	print(response.choices[0].message.content)

1	from sarvamai import SarvamAI
2
3	client = SarvamAI(api_subscription_key="YOUR_SARVAM_API_KEY")
4
5	# Example 2: Using temperature = 0.9 — more creative, varied response
6	response = client.chat.completions(
7	model="sarvam-105b",
8	messages=[
9	{"role": "system", "content": "You are a creative storyteller."},
10	{"role": "user", "content": "Tell me a story about a magical tiger."}
11	],
12	temperature=0.9 # More creative storytelling
13	)
14
15	# Receive assistant's reply as output
16	print(response.choices[0].message.content)