curl https://api.portkey.ai/v1/chat/completions \
-H "Content-Type: application/json" \
-H "x-portkey-api-key: $PORTKEY_API_KEY" \
-H "x-portkey-virtual-key: $PORTKEY_PROVIDER_VIRTUAL_KEY" \
-d '{
"model": "gpt-5",
"messages": [
{
"role": "system",
"content": "You are a helpful assistant."
},
{
"role": "user",
"content": "Hello!"
}
],
"max_completion_tokens": 250
}'{
"id": "<string>",
"choices": [
{
"finish_reason": "stop",
"index": 123,
"message": {
"content": "<string>",
"role": "assistant",
"tool_calls": [
{
"id": "<string>",
"type": "function",
"function": {
"name": "<string>",
"arguments": "<string>"
}
}
],
"function_call": {
"arguments": "<string>",
"name": "<string>"
},
"content_blocks": [
{
"type": "text",
"text": "<string>"
}
]
},
"logprobs": {
"content": [
{
"token": "<string>",
"logprob": 123,
"bytes": [
123
],
"top_logprobs": [
{
"token": "<string>",
"logprob": 123,
"bytes": [
123
]
}
]
}
]
}
}
],
"created": 123,
"model": "<string>",
"object": "chat.completion",
"system_fingerprint": "<string>",
"usage": {
"completion_tokens": 123,
"prompt_tokens": 123,
"total_tokens": 123,
"completion_tokens_details": {
"reasoning_tokens": 123,
"accepted_prediction_tokens": 123,
"rejected_prediction_tokens": 123
},
"prompt_tokens_details": {
"cached_tokens": 123
}
}
}Chat
curl https://api.portkey.ai/v1/chat/completions \
-H "Content-Type: application/json" \
-H "x-portkey-api-key: $PORTKEY_API_KEY" \
-H "x-portkey-virtual-key: $PORTKEY_PROVIDER_VIRTUAL_KEY" \
-d '{
"model": "gpt-5",
"messages": [
{
"role": "system",
"content": "You are a helpful assistant."
},
{
"role": "user",
"content": "Hello!"
}
],
"max_completion_tokens": 250
}'{
"id": "<string>",
"choices": [
{
"finish_reason": "stop",
"index": 123,
"message": {
"content": "<string>",
"role": "assistant",
"tool_calls": [
{
"id": "<string>",
"type": "function",
"function": {
"name": "<string>",
"arguments": "<string>"
}
}
],
"function_call": {
"arguments": "<string>",
"name": "<string>"
},
"content_blocks": [
{
"type": "text",
"text": "<string>"
}
]
},
"logprobs": {
"content": [
{
"token": "<string>",
"logprob": 123,
"bytes": [
123
],
"top_logprobs": [
{
"token": "<string>",
"logprob": 123,
"bytes": [
123
]
}
]
}
]
}
}
],
"created": 123,
"model": "<string>",
"object": "chat.completion",
"system_fingerprint": "<string>",
"usage": {
"completion_tokens": 123,
"prompt_tokens": 123,
"total_tokens": 123,
"completion_tokens_details": {
"reasoning_tokens": 123,
"accepted_prediction_tokens": 123,
"rejected_prediction_tokens": 123
},
"prompt_tokens_details": {
"cached_tokens": 123
}
}
}Portkey is now PRISMA AIRS AI Gateway. See it in action.
Authorizations
Headers
An ID you can pass to refer to a span under a trace.
Link a child span to a parent span
Name for the Span ID
Pass any arbitrary metadata along with your request
Partition your Portkey cache store based on custom strings, ignoring metadata and other headers
Forces a cache refresh for your request by making a new API call and storing the updated value
Body
A list of messages comprising the conversation so far. Example Python code.
1- System message
- Developer message
- User message
- Assistant message
- Tool message
- Function message
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ID of the model to use. See the model endpoint compatibility table for details on which models work with the Chat API.
"gpt-5"
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.
See more information about frequency and presence penalties.
-2 <= x <= 2Modify the likelihood of specified tokens appearing in the completion.
Accepts a JSON object that maps tokens (specified by their token ID in the tokenizer) to an associated bias value from -100 to 100. Mathematically, the bias is added to the logits generated by the model prior to sampling. The exact effect will vary per model, but values between -1 and 1 should decrease or increase likelihood of selection; values like -100 or 100 should result in a ban or exclusive selection of the relevant token.
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Whether 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.
0 <= x <= 20Deprecated in favor of max_completion_tokens.
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.
Supported models: GPT-4o, GPT-4o-mini, GPT-4, GPT-4 Turbo, GPT-3.5 Turbo.
Not supported: o-series reasoning models (o1, o3, o3-mini, o4-mini) and GPT-5 series — use max_completion_tokens instead.
An upper bound for the number of tokens that can be generated for a completion, including visible output tokens and reasoning tokens.
Supported models: GPT-5 series, o-series reasoning models (o1, o3, o3-mini, o4-mini) — required. Also supported on GPT-4o, GPT-4o-mini, GPT-4, GPT-4 Turbo, GPT-3.5 Turbo as a replacement for max_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.
1 <= x <= 1281
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.
See more information about frequency and presence penalties.
-2 <= x <= 2Default response format. Used to generate text responses.
- Text
- JSON schema
- JSON object
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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.
-9223372036854776000 <= x <= 9223372036854776000Up 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. Example Python code.
Options for streaming response. Only set this when you set stream: true.
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View the thinking/reasoning tokens as part of your response. Thinking models produce a long internal chain of thought before generating a response. Supported only for specific Claude models on Anthropic, Google Vertex AI, and AWS Bedrock. Requires setting strict_openai_compliance = false in your API call.
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{ "type": "enabled", "budget_tokens": 2030 }
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.
0 <= x <= 21
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.
0 <= x <= 11
A list of tools the model may call. Currently, only functions are supported as a tool. Use this to provide a list of functions the model may generate JSON inputs for. A max of 128 functions are supported.
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Controls 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, auto, required Whether to enable parallel function calling during tool use.
A unique identifier representing your end-user, which can help OpenAI to monitor and detect abuse. Learn more.
"user-1234"
Deprecated 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, auto Deprecated in favor of tools.
A list of functions the model may generate JSON inputs for.
1 - 128 elementsShow child attributes
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Response
OK
Represents a chat completion response returned by model, based on the provided input.
A unique identifier for the chat completion.
A list of chat completion choices. Can be more than one if n is greater than 1.
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The Unix timestamp (in seconds) of when the chat completion was created.
The model used for the chat completion.
The object type, which is always chat.completion.
chat.completion This fingerprint represents the backend configuration that the model runs with.
Can be used in conjunction with the seed request parameter to understand when backend changes have been made that might impact determinism.
Usage statistics for the completion request.
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