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Create chat completion ​

POST https://api.fastapi.ai/v1/chat/completions

Creates a model response for the given chat conversation. Learn more in the text generation, vision, and audio guides.

Parameter support can differ depending on the model used to generate the response, particularly for newer reasoning models. Parameters that are only supported for reasoning models are noted below. For the current state of unsupported parameters in reasoning models, refer to the reasoning guide.

Request body ​

messages array Required
A list of messages comprising the conversation so far. Depending on the model you use, different message types (modalities) are supported, like text, images, and audio

Developer message object

Developer-provided instructions that the model should follow, regardless of messages sent by the user. With o1 models and newer, developer messages replace the previous system messages.

content string or array Required
The contents of the developer message.

role string Required
The role of the messages author, in this case developer.

name string Optional
An optional name for the participant. Provides the model information to differentiate between participants of the same role.

System message object

Developer-provided instructions that the model should follow, regardless of messages sent by the user. With o1 models and newer, use developer messages for this purpose instead.

content string or array Required
The contents of the system message.

role string Required
The role of the messages author, in this case system.

name string Optional
An optional name for the participant. Provides the model information to differentiate between participants of the same role.

User message object

Messages sent by an end user, containing prompts or additional context information.

content string or array Required
The contents of the user message.

Text content string
The text contents of the message.

Array of content parts array
An array of content parts with a defined type. Supported options differ based on the model being used to generate the response. Can contain text, image, or audio inputs.

Text content part object
Learn about text inputs.

type string Required
The type of the content part.

text string Required
The text content.

Image content part object
Learn about image inputs.

type string Required
The type of the content part.

image_url object Required

url string Required
Either a URL of the image or the base64 encoded image data.

detail string Optional Defaults to auto
Specifies the detail level of the image. Learn more in the Vision guide.

Audio content part object
Learn about audio inputs.

type string Required
The type of the content part. Always input_audio.

input_audio object Required

data string Required
Base64 encoded audio data.

format string Required
The format of the encoded audio data. Currently supports "wav" and "mp3".

role string Required
The role of the messages author, in this case user.

name string Optional
An optional name for the participant. Provides the model information to differentiate between participants of the same role.

Assistant message object

Messages sent by the model in response to user messages.

content string or array Optional
The contents of the assistant message. Required unless tool_calls or function_call is specified.

Text content string
The contents of the assistant message.

Array of content parts array
An array of content parts with a defined type. Can be one or more of type text, or exactly one of type refusal.

Text content part object Learn about text inputs.

type string Required
The type of the content part.

text string Required
The text content.

Refusal content part object

type string Required
The type of the content part.

refusal string Required
The refusal message generated by the model.

refusal string or null Optional The refusal message by the assistant.

role string Required
The role of the messages author, in this case assistant.

name string Optional
An optional name for the participant. Provides the model information to differentiate between participants of the same role.

audio object or null Optional
Data about a previous audio response from the model.Learn more.

id string Required
Unique identifier for a previous audio response from the model.

tool_calls array Optional
The tool calls generated by the model, such as function calls.

id string Required
The ID of the tool call.

type string Required
The type of the tool. Currently, only function is supported.

function object Required
The function that the model called.

name string Required
The name of the function to call.

arguments string Required
The arguments to call the function with, as generated by the model in JSON format. Note that the model does not always generate valid JSON, and may hallucinate parameters not defined by your function schema. Validate the arguments in your code before calling your function.

function_call Deprecated object or null Optional
Deprecated and replaced by tool_calls. The name and arguments of a function that should be called, as generated by the model.

arguments string Required
The arguments to call the function with, as generated by the model in JSON format. Note that the model does not always generate valid JSON, and may hallucinate parameters not defined by your function schema. Validate the arguments in your code before calling your function.

name string Required
The name of the function to call.

Tool message object

role string Required
The role of the messages author, in this case tool.

content string or array Required
The contents of the tool message.

tool_call_id string Required
Tool call that this message is responding to.

Function message object Deprecated

role string Required
The role of the messages author, in this case tool.

content string or array Required
The contents of the tool message.

name string Required
The name of the function to call.

model string Required
ID of the model to use. See the model endpoint compatibility table for details on which models work with the Chat API.

store boolean or null Optional Defaults to false
Whether or not to store the output of this chat completion request for use in our model distillation or evals products.

reasoning_effort string or null Optional Defaults to medium
o1 and o3-mini models only

Constrains effort on reasoning for reasoning models. Currently supported values are low, medium, and high. Reducing reasoning effort can result in faster responses and fewer tokens used on reasoning in a response.

metadata map Optional
Set of 16 key-value pairs that can be attached to an object. This can be useful for storing additional information about the object in a structured format, and querying for objects via API or the dashboard.

Keys are strings with a maximum length of 64 characters. Values are strings with a maximum length of 512 characters.

frequency_penalty number or null Optional Defaults to 0
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.

Keys are strings with a maximum length of 64 characters. Values are strings with a maximum length of 512 characters.

logit_bias map OptionalDefaults to null
Modify 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.

logprobs boolean or null Optional Defaults to false
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.

top_logprobs integer or null Optional
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.

max_tokens Deprecated integer or null Optional
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.

max_completion_tokens integer or null Optional
An upper bound for the number of tokens that can be generated for a completion, including visible output tokens and reasoning tokens.

n integer or null Optional Defaults to 1
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.

modalities array or null Optional
Output types that you would like the model to generate for this request. Most models are capable of generating text, which is the default:

["text"]

The gpt-4o-audio-preview model can also be used to generate audio. To request that this model generate both text and audio responses, you can use:

["text", "audio"]

prediction object Optional
Configuration 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.

Static Contentobject

Static predicted output content, such as the content of a text file that is being regenerated.

type string Required
The type of the predicted content you want to provide. This type is currently always content.

content string or array Required
The content that should be matched when generating a model response. If generated tokens would match this content, the entire model response can be returned much more quickly.

Text content string
The content used for a Predicted Output. This is often the text of a file you are regenerating with minor changes.

Array of content parts array
An array of content parts with a defined type. Supported options differ based on the model being used to generate the response. Can contain text inputs.

type string Required
The type of the content part.

text string Required
The text content.

audio object or null Optional
Parameters for audio output. Required when audio output is requested with modalities: ["audio"]. Learn more.

voice string Required

voice string Required
The voice the model uses to respond. Supported voices are ash, ballad, coral, sage, and verse (also supported but not recommended are alloy, echo, and shimmer; these voices are less expressive).

format string Required
Specifies the output audio format. Must be one of wav, mp3, flac, opus, or pcm16.

presence_penalty number or null Optional Defaults to 0
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.

response_format object Optional
An object specifying the format that the model must output.

Setting to { "type": "json_schema", "json_schema": {...} } enables Structured Outputs which ensures the model will match your supplied JSON schema. Learn more in the Structured Outputs guide.

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.

object

object

type string Required
The type of response format being defined: text

type string Required
The type of response format being defined: json_object

type string Required
The type of response format being defined: json_schema

json_schema string Required

descriptionstring Optional
A description of what the response format is for, used by the model to determine how to respond in the format.

name string Required
The name of the response format. Must be a-z, A-Z, 0-9, or contain underscores and dashes, with a maximum length of 64.

schema object Optional
The schema for the response format, described as a JSON Schema object.

strict boolean or null Optional Defaults to false
Whether to enable strict schema adherence when generating the output. If set to true, the model will always follow the exact schema defined in the schema field. Only a subset of JSON Schema is supported when strict is true. To learn more, read the Structured Outputs guide.

seed integer or null Optional
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.

service_tier string or null Optional Defaults to auto
Specifies the latency tier to use for processing the request. This parameter is relevant for customers subscribed to the scale tier service:

  • If set to 'auto', and the Project is Scale tier enabled, the system will utilize scale tier credits until they are exhausted.

  • If set to 'auto', and the Project is not Scale tier enabled, the request will be processed using the default service tier with a lower uptime SLA and no latency guarantee.

  • If set to 'default', the request will be processed using the default service tier with a lower uptime SLA and no latency guarantee.

  • When not set, the default behavior is 'auto'.

stop string / array / null Optional Defaults to null
Up to 4 sequences where the API will stop generating further tokens.

stream boolean or null Optional Defaults to false
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.

stream_options object or null Optional Defaults to null
Options for streaming response. Only set this when you set stream: true.

include_usage boolean Optional

If set, an additional chunk will be streamed before the data: [DONE] message. The usage field on this chunk shows the token usage statistics for the entire request, and the choices field will always be an empty array. All other chunks will also include a usage field, but with a null value.

temperature number or null Optional Defaults to 1
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.

top_p number or null Optional Defaults to 1
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.

tools array Optional
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.

type string Required
The type of the tool. Currently, only function is supported.

function object Required

description string Optional
A description of what the function does, used by the model to choose when and how to call the function.

name string Required
The name of the function to be called. Must be a-z, A-Z, 0-9, or contain underscores and dashes, with a maximum length of 64.

parameters object Optional
The parameters the functions accepts, described as a JSON Schema object. See the guide for examples, and the JSON Schema reference for documentation about the format.

Omitting parameters defines a function with an empty parameter list.

strict boolean or null Optional Defaults to false
Whether to enable strict schema adherence when generating the function call. If set to true, the model will follow the exact schema defined in the parameters field. Only a subset of JSON Schema is supported when strict is true. Learn more about Structured Outputs in the function calling guide.

tool_choice string or object Optional
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.

string
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.

object

Specifies a tool the model should use. Use to force the model to call a specific function.

type string Required
The type of the tool. Currently, only function is supported.

function object Required

name string Required
The name of the function to call.

parallel_tool_calls boolean Optional Defaults to true
Whether to enable parallel function calling during tool use.

user string Optional
A unique identifier representing your end-user, which can help OpenAI to monitor and detect abuse. Learn more.

function_call Deprecated string or object Optional
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.

string
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.

object

Specifying a particular function via {"name": "my_function"} forces the model to call that function.

name string Required
The name of the function to call.

functions Deprecated array Optional
Deprecated in favor of tools.

A list of functions the model may generate JSON inputs for.

description string Optional
A description of what the function does, used by the model to choose when and how to call the function.

name string Required
The name of the function to be called. Must be a-z, A-Z, 0-9, or contain underscores and dashes, with a maximum length of 64.

parameters object Optional
The parameters the functions accepts, described as a JSON Schema object. See the guide for examples, and the JSON Schema reference for documentation about the format.

Omitting parameters defines a function with an empty parameter list.

Returns ​

Returns a chat completion object, or a streamed sequence of chat completion chunk objects if the request is streamed.

The chat completion object ​

Represents a chat completion response returned by model, based on the provided input.

id string
A unique identifier for the chat completion.

choices array

A list of chat completion choices. Can be more than one if n is greater than 1.

finish_reason string
The reason the model stopped generating tokens. This will be stop if the model hit a natural stop point or a provided stop sequence, length if the maximum number of tokens specified in the request was reached, content_filter if content was omitted due to a flag from our content filters, tool_calls if the model called a tool, or function_call (deprecated) if the model called a function.

index integer
The index of the choice in the list of choices.

message object
A chat completion message generated by the model.

content string or null
The contents of the message.

refusal string or null
The refusal message generated by the model.

tool_calls array
The tool calls generated by the model, such as function calls.

id string
The ID of the tool call.

type string
The type of the tool. Currently, only function is supported.

function object
The function that the model called.

name string
The name of the function to call.

arguments string
The arguments to call the function with, as generated by the model in JSON format. Note that the model does not always generate valid JSON, and may hallucinate parameters not defined by your function schema. Validate the arguments in your code before calling your function.

role string
The role of the author of this message.

function_call Deprecated object
Deprecated and replaced by tool_calls. The name and arguments of a function that should be called, as generated by the model.

arguments string
The arguments to call the function with, as generated by the model in JSON format. Note that the model does not always generate valid JSON, and may hallucinate parameters not defined by your function schema. Validate the arguments in your code before calling your function.

name string
The name of the function to call.

audio object or null
If the audio output modality is requested, this object contains data about the audio response from the model. Learn more.

id string
Unique identifier for this audio response.

expires_at integer
The Unix timestamp (in seconds) for when this audio response will no longer be accessible on the server for use in multi-turn conversations.

data string
Base64 encoded audio bytes generated by the model, in the format specified in the request.

transcript string
Transcript of the audio generated by the model.

id string
The identifier of the chat message.

logprobs object or null
Log probability information for the choice.

content array or null
A list of message content tokens with log probability information.

token string
The token.

logprob number
The log probability of this token, if it is within the top 20 most likely tokens. Otherwise, the value -9999.0 is used to signify that the token is very unlikely.

bytes array or null
A list of integers representing the UTF-8 bytes representation of the token. Useful in instances where characters are represented by multiple tokens and their byte representations must be combined to generate the correct text representation. Can be null if there is no bytes representation for the token.

top_logprobs array
List of the most likely tokens and their log probability, at this token position. In rare cases, there may be fewer than the number of requested top_logprobs returned.

token string
The token.

logprob number
The log probability of this token, if it is within the top 20 most likely tokens. Otherwise, the value -9999.0 is used to signify that the token is very unlikely.

bytes array or null
A list of integers representing the UTF-8 bytes representation of the token. Useful in instances where characters are represented by multiple tokens and their byte representations must be combined to generate the correct text representation. Can be null if there is no bytes representation for the token.

refusal array or null
A list of message refusal tokens with log probability information.

token string
The token.

logprob number
The log probability of this token, if it is within the top 20 most likely tokens. Otherwise, the value -9999.0 is used to signify that the token is very unlikely.

bytes array or null
A list of integers representing the UTF-8 bytes representation of the token. Useful in instances where characters are represented by multiple tokens and their byte representations must be combined to generate the correct text representation. Can be null if there is no bytes representation for the token.

top_logprobs array
List of the most likely tokens and their log probability, at this token position. In rare cases, there may be fewer than the number of requested top_logprobs returned.

token string
The token.

logprob number
The log probability of this token, if it is within the top 20 most likely tokens. Otherwise, the value -9999.0 is used to signify that the token is very unlikely.

bytes array or null
A list of integers representing the UTF-8 bytes representation of the token. Useful in instances where characters are represented by multiple tokens and their byte representations must be combined to generate the correct text representation. Can be null if there is no bytes representation for the token.

created integer
The Unix timestamp (in seconds) of when the chat completion was created.

model string
The model used for the chat completion.

service_tier string or null
The service tier used for processing the request.

system_fingerprint string
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.

object string
The object type, which is always chat.completion.

usage object

Usage statistics for the completion request.

completion_tokens integer
Number of tokens in the generated completion.

prompt_tokens integer
Number of tokens in the prompt.

total_tokens integer
Total number of tokens used in the request (prompt + completion).

completion_tokens_details object
Breakdown of tokens used in a completion.

accepted_prediction_tokens integer
When using Predicted Outputs, the number of tokens in the prediction that appeared in the completion.

audio_tokens integer
Audio input tokens generated by the model.

reasoning_tokens integer
Tokens generated by the model for reasoning.

rejected_prediction_tokens integer
When using Predicted Outputs, the number of tokens in the prediction that did not appear in the completion. However, like reasoning tokens, these tokens are still counted in the total completion tokens for purposes of billing, output, and context window limits.

prompt_tokens_details object
Breakdown of tokens used in the prompt.

audio_tokens integer
Audio input tokens present in the prompt.

cached_tokens integer
Cached tokens present in the prompt.

OBJECT The chat completion object
bash
{
  "id": "chatcmpl-123456",
  "object": "chat.completion",
  "created": 1728933352,
  "model": "gpt-4o-2024-08-06",
  "choices": [
    {
      "index": 0,
      "message": {
        "role": "assistant",
        "content": "Hi there! How can I assist you today?",
        "refusal": null
      },
      "logprobs": null,
      "finish_reason": "stop"
    }
  ],
  "usage": {
    "prompt_tokens": 19,
    "completion_tokens": 10,
    "total_tokens": 29,
    "prompt_tokens_details": {
      "cached_tokens": 0
    },
    "completion_tokens_details": {
      "reasoning_tokens": 0,
      "accepted_prediction_tokens": 0,
      "rejected_prediction_tokens": 0
    }
  },
  "system_fingerprint": "fp_6b68a8204b"
}

The chat completion chunk object ​

Represents a streamed chunk of a chat completion response returned by model, based on the provided input.

id string
A unique identifier for the chat completion. Each chunk has the same ID.

choices array

A list of chat completion choices. Can contain more than one elements if n is greater than 1. Can also be empty for the last chunk if you set stream_options: {"include_usage": true}.

delta object
A chat completion delta generated by streamed model responses.

content string or null
The contents of the chunk message.

function_call Deprecated object
Deprecated and replaced by tool_calls. The name and arguments of a function that should be called, as generated by the model.

arguments string
The arguments to call the function with, as generated by the model in JSON format. Note that the model does not always generate valid JSON, and may hallucinate parameters not defined by your function schema. Validate the arguments in your code before calling your function.

name string
The name of the function to call.

tool_calls array

index integer

id string
The ID of the tool call.

type string
The type of the tool. Currently, only function is supported.

function object

name string
The name of the function to call.

arguments string
The arguments to call the function with, as generated by the model in JSON format. Note that the model does not always generate valid JSON, and may hallucinate parameters not defined by your function schema. Validate the arguments in your code before calling your function.

role string
The role of the author of this message.

refusal string or null
The refusal message generated by the model.

logprobs object or null
Log probability information for the choice.

content array or null A list of message content tokens with log probability information.

token string
The token.

logprob number
The log probability of this token, if it is within the top 20 most likely tokens. Otherwise, the value -9999.0 is used to signify that the token is very unlikely.

bytes array or null
A list of integers representing the UTF-8 bytes representation of the token. Useful in instances where characters are represented by multiple tokens and their byte representations must be combined to generate the correct text representation. Can be null if there is no bytes representation for the token.

top_logprobs array
List of the most likely tokens and their log probability, at this token position. In rare cases, there may be fewer than the number of requested top_logprobs returned.

token string
The token.

logprob number
The log probability of this token, if it is within the top 20 most likely tokens. Otherwise, the value -9999.0 is used to signify that the token is very unlikely.

bytes array or null
A list of integers representing the UTF-8 bytes representation of the token. Useful in instances where characters are represented by multiple tokens and their byte representations must be combined to generate the correct text representation. Can be null if there is no bytes representation for the token.

refusal array or null
A list of message refusal tokens with log probability information.

token string
The token.

logprob number
The log probability of this token, if it is within the top 20 most likely tokens. Otherwise, the value -9999.0 is used to signify that the token is very unlikely.

bytes array or null
A list of integers representing the UTF-8 bytes representation of the token. Useful in instances where characters are represented by multiple tokens and their byte representations must be combined to generate the correct text representation. Can be null if there is no bytes representation for the token.

top_logprobs array
List of the most likely tokens and their log probability, at this token position. In rare cases, there may be fewer than the number of requested top_logprobs returned.

token string
The token.

logprob number
The log probability of this token, if it is within the top 20 most likely tokens. Otherwise, the value -9999.0 is used to signify that the token is very unlikely.

bytes array or null
A list of integers representing the UTF-8 bytes representation of the token. Useful in instances where characters are represented by multiple tokens and their byte representations must be combined to generate the correct text representation. Can be null if there is no bytes representation for the token.

finish_reason string or null
The reason the model stopped generating tokens. This will be stop if the model hit a natural stop point or a provided stop sequence, length if the maximum number of tokens specified in the request was reached, content_filter if content was omitted due to a flag from our content filters, tool_calls if the model called a tool, or function_call (deprecated) if the model called a function.

index integer
The index of the choice in the list of choices.

created integer
The Unix timestamp (in seconds) of when the chat completion was created. Each chunk has the same timestamp.

model string
The model to generate the completion.

service_tier string or null
The service tier used for processing the request.

system_fingerprint string
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.

object string
The object type, which is always chat.completion.chunk.

usage object or null
An optional field that will only be present when you set stream_options: {"include_usage": true} in your request. When present, it contains a null value except for the last chunk which contains the token usage statistics for the entire request.

completion_tokens integer
Number of tokens in the generated completion.

prompt_tokens integer
Number of tokens in the prompt.

total_tokens integer
Total number of tokens used in the request (prompt + completion).

OBJECT The chat completion chunk object
bash
{"id":"chatcmpl-123","object":"chat.completion.chunk","created":1694268190,"model":"gpt-4o-mini", "system_fingerprint": "fp_44709d6fcb", "choices":[{"index":0,"delta":{"role":"assistant","content":""},"logprobs":null,"finish_reason":null}]}

{"id":"chatcmpl-123","object":"chat.completion.chunk","created":1694268190,"model":"gpt-4o-mini", "system_fingerprint": "fp_44709d6fcb", "choices":[{"index":0,"delta":{"content":"Hello"},"logprobs":null,"finish_reason":null}]}

....

{"id":"chatcmpl-123","object":"chat.completion.chunk","created":1694268190,"model":"gpt-4o-mini", "system_fingerprint": "fp_44709d6fcb", "choices":[{"index":0,"delta":{},"logprobs":null,"finish_reason":"stop"}]}

Example ​

Request ​

bash
curl https://api.fastapi.ai/v1/chat/completions \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $FAST_API_KEY" \
  -d '{
    "model": "gpt-4o",
    "messages": [
      {
        "role": "system", // With o1 models and newer, `developer` messages replace the previous `system` messages.
        "content": "You are a helpful assistant."
      },
      {
        "role": "user",
        "content": "Hello!"
      }
    ]
  }'
bash
curl https://api.fastapi.ai/v1/chat/completions \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $FAST_API_KEY" \
  -d '{
    "model": "gpt-4o",
    "messages": [
      {
        "role": "user",
        "content": [
          {
            "type": "text",
            "text": "What's in this image?"
          },
          {
            "type": "image_url",
            "image_url": {
              "url": "https://upload.wikimedia.org/wikipedia/commons/thumb/d/dd/Gfp-wisconsin-madison-the-nature-boardwalk.jpg"
            }
          }
        ]
      }
    ],
    "max_tokens": 300
  }'
bash
curl https://api.fastapi.ai/v1/chat/completions \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $FAST_API_KEY" \
  -d '{
    "model": "gpt-4o",
    "messages": [
      {
        "role": "developer",
        "content": "You are a helpful assistant."
      },
      {
        "role": "user",
        "content": "Hello!"
      }
    ],
    "stream": true
  }'
bash
curl https://api.fastapi.ai/v1/chat/completions \
-H "Content-Type: application/json" \
-H "Authorization: Bearer $FAST_API_KEY" \
-d '{
  "model": "gpt-4o",
  "messages": [
    {
      "role": "user",
      "content": "What's the weather like in Boston today?"
    }
  ],
  "tools": [
    {
      "type": "function",
      "function": {
        "name": "get_current_weather",
        "description": "Get the current weather in a given location",
        "parameters": {
          "type": "object",
          "properties": {
            "location": {
              "type": "string",
              "description": "The city and state, e.g. San Francisco, CA"
            },
            "unit": {
              "type": "string",
              "enum": ["celsius", "fahrenheit"]
            }
          },
          "required": ["location"]
        }
      }
    }
  ],
  "tool_choice": "auto"
}'
bash
curl https://api.fastapi.ai/v1/chat/completions \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $FAST_API_KEY" \
  -d '{
    "model": "gpt-4o",
    "messages": [
      {
        "role": "user",
        "content": "Hello!"
      }
    ],
    "logprobs": true,
    "top_logprobs": 2
  }'

Response ​

bash
{
  "id": "chatcmpl-123",
  "object": "chat.completion",
  "created": 1677652288,
  "model": "gpt-4o-mini",
  "system_fingerprint": "fp_44709d6fcb",
  "choices": [{
    "index": 0,
    "message": {
      "role": "assistant",
      "content": "\n\nHello there, how may I assist you today?",
    },
    "logprobs": null,
    "finish_reason": "stop"
  }],
  "usage": {
    "prompt_tokens": 9,
    "completion_tokens": 12,
    "total_tokens": 21,
    "completion_tokens_details": {
      "reasoning_tokens": 0,
      "accepted_prediction_tokens": 0,
      "rejected_prediction_tokens": 0
    }
  }
}
bash
{
  "id": "chatcmpl-123",
  "object": "chat.completion",
  "created": 1677652288,
  "model": "gpt-4o-mini",
  "system_fingerprint": "fp_44709d6fcb",
  "choices": [{
    "index": 0,
    "message": {
      "role": "assistant",
      "content": "\n\nThis image shows a wooden boardwalk extending through a lush green marshland.",
    },
    "logprobs": null,
    "finish_reason": "stop"
  }],
  "usage": {
    "prompt_tokens": 9,
    "completion_tokens": 12,
    "total_tokens": 21,
    "completion_tokens_details": {
      "reasoning_tokens": 0,
      "accepted_prediction_tokens": 0,
      "rejected_prediction_tokens": 0
    }
  }
}
bash
{"id":"chatcmpl-123","object":"chat.completion.chunk","created":1694268190,"model":"gpt-4o-mini", "system_fingerprint": "fp_44709d6fcb", "choices":[{"index":0,"delta":{"role":"assistant","content":""},"logprobs":null,"finish_reason":null}]}

{"id":"chatcmpl-123","object":"chat.completion.chunk","created":1694268190,"model":"gpt-4o-mini", "system_fingerprint": "fp_44709d6fcb", "choices":[{"index":0,"delta":{"content":"Hello"},"logprobs":null,"finish_reason":null}]}

....

{"id":"chatcmpl-123","object":"chat.completion.chunk","created":1694268190,"model":"gpt-4o-mini", "system_fingerprint": "fp_44709d6fcb", "choices":[{"index":0,"delta":{},"logprobs":null,"finish_reason":"stop"}]}
bash
{
  "id": "chatcmpl-abc123",
  "object": "chat.completion",
  "created": 1699896916,
  "model": "gpt-4o-mini",
  "choices": [
    {
      "index": 0,
      "message": {
        "role": "assistant",
        "content": null,
        "tool_calls": [
          {
            "id": "call_abc123",
            "type": "function",
            "function": {
              "name": "get_current_weather",
              "arguments": "{\n\"location\": \"Boston, MA\"\n}"
            }
          }
        ]
      },
      "logprobs": null,
      "finish_reason": "tool_calls"
    }
  ],
  "usage": {
    "prompt_tokens": 82,
    "completion_tokens": 17,
    "total_tokens": 99,
    "completion_tokens_details": {
      "reasoning_tokens": 0,
      "accepted_prediction_tokens": 0,
      "rejected_prediction_tokens": 0
    }
  }
}
bash
{
  "id": "chatcmpl-123",
  "object": "chat.completion",
  "created": 1702685778,
  "model": "gpt-4o-mini",
  "choices": [
    {
      "index": 0,
      "message": {
        "role": "assistant",
        "content": "Hello! How can I assist you today?"
      },
      "logprobs": {
        "content": [
          {
            "token": "Hello",
            "logprob": -0.31725305,
            "bytes": [72, 101, 108, 108, 111],
            "top_logprobs": [
              {
                "token": "Hello",
                "logprob": -0.31725305,
                "bytes": [72, 101, 108, 108, 111]
              },
              {
                "token": "Hi",
                "logprob": -1.3190403,
                "bytes": [72, 105]
              }
            ]
          },
          {
            "token": "!",
            "logprob": -0.02380986,
            "bytes": [
              33
            ],
            "top_logprobs": [
              {
                "token": "!",
                "logprob": -0.02380986,
                "bytes": [33]
              },
              {
                "token": " there",
                "logprob": -3.787621,
                "bytes": [32, 116, 104, 101, 114, 101]
              }
            ]
          },
          {
            "token": " How",
            "logprob": -0.000054669687,
            "bytes": [32, 72, 111, 119],
            "top_logprobs": [
              {
                "token": " How",
                "logprob": -0.000054669687,
                "bytes": [32, 72, 111, 119]
              },
              {
                "token": "<|end|>",
                "logprob": -10.953937,
                "bytes": null
              }
            ]
          },
          {
            "token": " can",
            "logprob": -0.015801601,
            "bytes": [32, 99, 97, 110],
            "top_logprobs": [
              {
                "token": " can",
                "logprob": -0.015801601,
                "bytes": [32, 99, 97, 110]
              },
              {
                "token": " may",
                "logprob": -4.161023,
                "bytes": [32, 109, 97, 121]
              }
            ]
          },
          {
            "token": " I",
            "logprob": -3.7697225e-6,
            "bytes": [
              32,
              73
            ],
            "top_logprobs": [
              {
                "token": " I",
                "logprob": -3.7697225e-6,
                "bytes": [32, 73]
              },
              {
                "token": " assist",
                "logprob": -13.596657,
                "bytes": [32, 97, 115, 115, 105, 115, 116]
              }
            ]
          },
          {
            "token": " assist",
            "logprob": -0.04571125,
            "bytes": [32, 97, 115, 115, 105, 115, 116],
            "top_logprobs": [
              {
                "token": " assist",
                "logprob": -0.04571125,
                "bytes": [32, 97, 115, 115, 105, 115, 116]
              },
              {
                "token": " help",
                "logprob": -3.1089056,
                "bytes": [32, 104, 101, 108, 112]
              }
            ]
          },
          {
            "token": " you",
            "logprob": -5.4385737e-6,
            "bytes": [32, 121, 111, 117],
            "top_logprobs": [
              {
                "token": " you",
                "logprob": -5.4385737e-6,
                "bytes": [32, 121, 111, 117]
              },
              {
                "token": " today",
                "logprob": -12.807695,
                "bytes": [32, 116, 111, 100, 97, 121]
              }
            ]
          },
          {
            "token": " today",
            "logprob": -0.0040071653,
            "bytes": [32, 116, 111, 100, 97, 121],
            "top_logprobs": [
              {
                "token": " today",
                "logprob": -0.0040071653,
                "bytes": [32, 116, 111, 100, 97, 121]
              },
              {
                "token": "?",
                "logprob": -5.5247097,
                "bytes": [63]
              }
            ]
          },
          {
            "token": "?",
            "logprob": -0.0008108172,
            "bytes": [63],
            "top_logprobs": [
              {
                "token": "?",
                "logprob": -0.0008108172,
                "bytes": [63]
              },
              {
                "token": "?\n",
                "logprob": -7.184561,
                "bytes": [63, 10]
              }
            ]
          }
        ]
      },
      "finish_reason": "stop"
    }
  ],
  "usage": {
    "prompt_tokens": 9,
    "completion_tokens": 9,
    "total_tokens": 18,
    "completion_tokens_details": {
      "reasoning_tokens": 0,
      "accepted_prediction_tokens": 0,
      "rejected_prediction_tokens": 0
    }
  },
  "system_fingerprint": null
}

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