Chat Completion V1
Creates a model response for the given chat conversation. This endpoint serves only sarvam-105b and sarvam-105b-conversations.
Authentication
Bearer authentication of the form Bearer <token>, where token is your auth token.
Headers
Request
Chat model ID. Use sarvam-105b (128K context) for complex reasoning and agentic tasks, or sarvam-105b-conversations (32K context) for real-time conversational and voice-agent workloads.
Sampling temperature between 0 and 2. Higher values such as 0.8 increase variation; lower values such as 0.2 make output more focused. Output is not bit-reproducible, even at 0. Prefer changing either temperature or top_p, not both.
An alternative to sampling with temperature, called nucleus sampling, where the model considers the results of the tokens with top_p probability mass. So 0.1 means only the tokens comprising the top 10% probability mass are considered.
We generally recommend altering this or temperature but not both.
If set to true, the model response data will be streamed to the client as it is generated using server-sent events.
Up to 4 stop sequences (string or array). Generated text excludes the matched sequence. On glm5.3, more than four entries may return 503 model_overloaded rather than 400.
How many chat completion choices to generate for each input message. Note that you will be charged based on the number of generated tokens across all of the choices. Keep n as 1 to minimize costs.
This feature is in Beta.
If specified, our system will make a best effort to sample deterministically, such that repeated requests with the same seed and parameters should return the same result.
Determinism is not guaranteed, and you should refer to the system_fingerprint response parameter to monitor changes in the backend.
Number between -2.0 and 2.0. Positive values penalize new tokens based on their existing frequency in the text so far, decreasing the model’s likelihood to repeat the same line verbatim.
Number between -2.0 and 2.0. Positive values penalize new tokens based on whether they appear in the text so far, increasing the model’s likelihood to talk about new topics.
Controls which (if any) tool is called by the model.
An object specifying the format that the model must output. Setting { "type": "json_schema", "json_schema": {...} } enables Structured Outputs which guarantees the model generates output matching the supplied JSON Schema. Setting { "type": "json_object" } enables the older JSON mode, which guarantees valid JSON but not a specific schema.
Response
A list of chat completion choices. Can be more than one if n is greater than 1.
The Unix timestamp (in seconds) of when the chat completion was created.
The object type, which is always chat.completion.