Chat
To use or not fallbacks in chat completion request
Model name, UUID, or agent UUID.
GPT 5.6 SolWhether or not to store the output of this chat completion request
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.
0Whether to return log probabilities of the output tokens or not. If true, returns the log probabilities of each output token returned in the content of message.
An integer between 0 and 20 specifying the number of most likely tokens to return at each token position, each with an associated log probability. logprobs must be set to true if this parameter is used.
The maximum number of tokens that can be generated in the chat completion. This value can be used to control costs for text generated via API.
This value is now deprecated in favor of max_completion_tokens, and is not compatible with o1 series models.
An upper bound for the number of tokens that can be generated for a completion, including visible output tokens and reasoning tokens.
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.
1Example: 1Configuration for a Predicted Output, which can greatly improve response times when large parts of the model response are known ahead of time. This is most common when you are regenerating a file with only minor changes to most of the content.
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.
0An object specifying the format that the model must output. Compatible with GPT-4o, GPT-4o mini, GPT-4 Turbo and all GPT-3.5 Turbo models newer than gpt-3.5-turbo-1106.
Setting to { "type": "json_schema", "json_schema": {...} } enables Structured Outputs which ensures the model will match your supplied JSON schema.
Setting to { "type": "json_object" } enables JSON mode, which ensures the message the model generates is valid JSON.
Important: when using JSON mode, you must also instruct the model to produce JSON yourself via a system or user message. Without this, the model may generate an unending stream of whitespace until the generation reaches the token limit, resulting in a long-running and seemingly "stuck" request. Also note that the message content may be partially cut off if finish_reason="length", which indicates the generation exceeded max_tokens or the conversation exceeded the max context length.
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.
Specifies the processing type used for serving the request.
If set to 'default' or 'auto', then the request will be processed with the standard pricing and performance for the selected model.
If set to 'flex' or 'priority', then the request will be processed with the corresponding service tier.
When not set, the default behavior is 'auto'.
When the service_tier parameter is set, the response body will include the service_tier value based on the processing mode actually used to serve the request. This response value may be different from the value set in the parameter.
autoPossible values: Up to 4 sequences where the API will stop generating further tokens.
If set, partial message deltas will be sent, like in ChatGPT. Tokens will be sent as data-only server-sent events as they become available, with the stream terminated by a data: [DONE] message. Chunks follow the OpenAI chat.completion.chunk format; the final chunk additionally carries usage (with nexos_credits_cost), and some providers include a nexos latency_checkpoint object with detailed timing metrics. Note: Gemini-backed streams currently end without the data: [DONE] terminator.
What sampling temperature to use, between 0 and 2. Higher values like 0.8 will make the output more random, while lower values like 0.2 will make it more focused and deterministic.
We generally recommend altering this or top_p but not both.
1Example: 1An 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.
1Example: 1Controls which (if any) tool is called by the model.
none means the model will not call any tool and instead generates a message.
auto means the model can pick between generating a message or calling one or more tools.
required means the model must call one or more tools.
Specifying a particular tool via {"type": "function", "function": {"name": "my_function"}} forces the model to call that tool.
none is the default when no tools are present. auto is the default if tools are present.
none means the model will not call any tool and instead generates a message. auto means the model can pick between generating a message or calling one or more tools. required means the model must call one or more tools.
Whether to enable parallel function calling during tool use.
trueDeprecated in favor of tool_choice.
Controls which (if any) function is called by the model.
none means the model will not call a function and instead generates a message.
auto means the model can pick between generating a message or calling a function.
Specifying a particular function via {"name": "my_function"} forces the model to call that function.
none is the default when no functions are present. auto is the default if functions are present.
none means the model will not call a function and instead generates a message. auto means the model can pick between generating a message or calling a function.
Reasoning effort for models that support reasoning.
Constrains the verbosity of the model's response.
Represents a chat completion response returned by model, based on the provided input.
Invalid request data.
The company has run out of AI credits. Returned when the company's budget limit has been reached.
Server error.
POST /v1/chat/completions HTTP/1.1
Host: api.nexos.ai
Authorization: Bearer YOUR_SECRET_TOKEN
Content-Type: application/json
Accept: */*
Content-Length: 115
{
"model": "GPT 5.6 Sol",
"messages": [
{
"role": "user",
"content": "how many letters 'r' are in the word 'strawberry'?"
}
]
}{
"id": "text",
"choices": [
{
"finish_reason": "stop",
"index": 1,
"message": {
"content": "text",
"refusal": "text",
"tool_calls": [
{
"id": "text",
"type": "function",
"function": {
"name": "text",
"arguments": "text"
}
}
],
"role": "assistant",
"audio": {
"id": "text",
"expires_at": 1,
"data": "text",
"transcript": "text"
},
"annotations": [
{
"type": "url_citation",
"url_citation": {
"end_index": 1,
"start_index": 1,
"title": "text",
"url": "text"
}
}
]
},
"content_filter_results": {},
"logprobs": {
"content": [
{
"token": "text",
"logprob": 1,
"bytes": [
1
],
"top_logprobs": [
{
"token": "text",
"logprob": 1,
"bytes": [
1
]
}
]
}
],
"refusal": [
{
"token": "text",
"logprob": 1,
"bytes": [
1
],
"top_logprobs": [
{
"token": "text",
"logprob": 1,
"bytes": [
1
]
}
]
}
]
}
}
],
"created": 1,
"model": "text",
"service_tier": "default",
"system_fingerprint": "text",
"object": "chat.completion",
"usage": {
"completion_tokens": 1,
"prompt_tokens": 1,
"total_tokens": 1,
"nexos_credits_cost": 1,
"completion_tokens_details": {
"accepted_prediction_tokens": 1,
"audio_tokens": 1,
"reasoning_tokens": 1,
"rejected_prediction_tokens": 1,
"image_tokens": 1
},
"prompt_tokens_details": {
"audio_tokens": 1,
"cached_tokens": 1,
"cache_write_tokens": 1,
"image_tokens": 1
},
"cache_creation_input_tokens": 1,
"cache_read_input_tokens": 1,
"cache_creation": {
"ephemeral_5m_input_tokens": 1,
"ephemeral_1h_input_tokens": 1
}
},
"provider": "text",
"prompt_filter_results": [
{
"prompt_index": 1,
"content_filter_results": {}
}
],
"guardrails": {
"validation_passed": true,
"reask": "text",
"error": "text",
"results": [
{
"type": "text",
"result": "text",
"target": "text"
}
]
}
}Last updated