Migrating the Responses API from OpenRouter to Sarvam

Last updated: October 23, 2026

This guide covers moving OpenRouter Responses API calls to Sarvam’s POST /v2/responses. For Chat Completions, see Migrating Chat Completion.

Migration checklist

1. Change base_url to https://api.sarvam.ai/v2 and api_key to your Sarvam key.
2. Replace each model ID using the model ID table.
3. Remove OpenRouter-only fields: provider, models, plugins, and stop (list).
4. Replace OpenRouter server tools with function tools you run yourself (Tools).
5. On glm5.3 and glm5.3-flash, don’t send "max"; omitting reasoning.effort gives max on glm5.3 and high on glm5.3-flash (Reasoning).
6. Set max_output_tokens: it has no default cap on Sarvam.
7. If you use the sarvamai SDK, read the reply from the message item in output (quick start).

Quick start

from openai import OpenAI
client = OpenAI(
    api_key="YOUR_OPENROUTER_API_KEY",
    base_url="https://openrouter.ai/api/v1",
)
response = client.responses.create(
    model="deepseek/deepseek-v4-pro-0813",
    instructions="You are a helpful assistant.",
    input="Explain database indexing in three short points.",
    reasoning={"effort": "high"},
    max_output_tokens=3000,
    extra_body={"provider": {"sort": "throughput"}},
)
print(response.output_text)

Conversation history

Both APIs are stateless: send the whole conversation in input on every call. Code that already does this for OpenRouter works unchanged. previous_response_id, store: true, conversation, and background: true return 400 on Sarvam, as on OpenRouter.

Reasoning

Reasoning tokens count toward max_output_tokens, which has no default cap on Sarvam.

Tools

Sarvam’s Responses API supports function tools only, in the same flat Responses format: {"type": "function", "name": ..., "parameters": ...}. OpenRouter server tools, such as openrouter:web_search, return 400. Run those services from your own code and expose them as function tools.

The function call round trip is the same as on OpenRouter: the model returns a function_call item, you run the function, and you send back the call plus a function_call_output item in the next request’s input. See the full example.

Fields to remove

Sarvam returns 400 with the field named for request fields it doesn’t support.

Parameter concept map

Full example

A function-calling loop that sends the call and its result back in input:

import json
from openai import OpenAI
client = OpenAI(
    api_key="YOUR_SARVAM_API_KEY",
    base_url="https://api.sarvam.ai/v2",
)
tools = [{
    "type": "function",
    "name": "get_weather",
    "description": "Get the weather for a city",
    "parameters": {
        "type": "object",
        "properties": {"city": {"type": "string"}},
        "required": ["city"],
    },
}]
def get_weather(city: str) -> str:
    return f"31°C and sunny in {city}"  # call your real service here
history = [{"role": "user", "content": "What's the weather in Delhi?"}]
response = client.responses.create(model="kimi-k3", input=history, tools=tools, max_output_tokens=3000)
for item in response.output:
    if item.type == "function_call":
        result = get_weather(**json.loads(item.arguments))
        history += [
            {"type": "function_call", "call_id": item.call_id, "name": item.name, "arguments": item.arguments},
            {"type": "function_call_output", "call_id": item.call_id, "output": result},
        ]
final = client.responses.create(model="kimi-k3", input=history, tools=tools, max_output_tokens=3000)
print(final.output_text)

Common mistakes

See also

• Migration overview: base URL, auth, and model IDs
• Migrating Chat Completion from OpenRouter
• Responses API guide
• Responses API reference