> ## Documentation Index
> Fetch the complete documentation index at: https://docs.langdock.com/llms.txt
> Use this file to discover all available pages before exploring further.
# OpenAI Chat completion
> Creates a model response for the given chat conversation using an OpenAI model.
**⚠️ Using our API via a dedicated deployment?** Just replace `api.langdock.com` with your deployment's base URL: **`/api/public`**
Creates a model response for the given chat conversation. This endpoint follows the [OpenAI API specification](https://platform.openai.com/docs/api-reference/chat/create), and the requests are sent to the Azure OpenAI endpoint.
To use the API, you need an API key. Admins can create API keys in the settings.
All parameters from the [OpenAI Chat Completion endpoint](https://platform.openai.com/docs/api-reference/chat/create) are supported according to the OpenAI specifications, with the following exceptions:
* `model`: To see which models are available for your workspace, query the models endpoint: `GET /openai/{region}/v1/models`. The list of available models might differ if you are using your own API keys in Langdock ("Bring-your-own-keys / BYOK", see [here](/en/admin/byok/byok) for details).
* `reasoning_effort`: Constrains how much effort the model spends on reasoning before responding. Lower values produce faster, cheaper responses; higher values produce more thorough reasoning. Supported values: `none`, `minimal`, `low`, `medium`, `high`, `xhigh`. Not all values are supported by all models. See the [OpenAI reasoning guide](https://developers.openai.com/api/docs/guides/reasoning?api-mode=chat) for details.
- `n`: Not supported.
- `service_tier`: Not supported.
- `parallel_tool_calls`: Not supported.
- `stream_options`: Not supported.
## Rate limits
The rate limit for the Chat Completion endpoint is **500 RPM (requests per minute)** and **60,000 TPM (tokens per minute)**. Rate limits are defined at the workspace level - and not at an API key level. Each model has its own rate limit. If you exceed your rate limit, you will receive a `429 Too Many Requests` response.
Please note that the rate limits are subject to change, refer to this documentation for the most up-to-date information.
## Using OpenAI-compatible libraries
As the request and response format is the same as the OpenAI API, you can use popular libraries like the [OpenAI Python library](https://github.com/openai/openai-python) or the [Vercel AI SDK](https://ai-sdk.dev/docs/introduction) to use the Langdock API.
### Example using the OpenAI Python library
```python theme={null}
from openai import OpenAI
client = OpenAI(
base_url="https://api.langdock.com/openai/eu/v1",
api_key=""
)
completion = client.chat.completions.create(
model="gpt-5-mini",
messages=[
{"role": "user", "content": "Write a short poem about cats."}
]
)
print(completion.choices[0].message.content)
```
### Example using the Vercel AI SDK in Node.js
```typescript theme={null}
import { streamText } from "ai";
import { createOpenAI } from "@ai-sdk/openai";
const langdockProvider = createOpenAI({
baseURL: "https://api.langdock.com/openai/eu/v1",
apiKey: "",
});
const result = await streamText({
model: langdockProvider("gpt-5-mini"),
prompt: "Write a short poem about cats",
});
for await (const textPart of result.textStream) {
process.stdout.write(textPart);
}
```
Langdock intentionally blocks browser-origin requests to protect your API key and ensure your applications remain secure. For more information, please see our guide on [API Key Best Practices](/en/admin/ai-adoption-and-rollout/best-practices/api-key-best-practices).
## OpenAPI
````yaml POST /openai/{region}/v1/chat/completions
openapi: 3.0.0
info:
title: Langdock API
version: 3.0.0
servers:
- url: https://api.langdock.com
security:
- bearerAuth: []
paths:
/openai/{region}/v1/chat/completions:
post:
tags:
- Chat
summary: Creates a model response for the given chat conversation.
parameters:
- name: region
in: path
required: true
description: The region of the API to use.
schema:
type: string
enum:
- eu
- us
requestBody:
required: true
content:
application/json:
schema:
$ref: '#/components/schemas/CreateChatCompletionRequest'
example:
model: gpt-4o-mini
messages:
- role: system
content: You are a helpful agent.
- role: user
content: Write a short poem about cats.
responses:
'200':
description: OK
content:
application/json:
schema:
$ref: '#/components/schemas/CreateChatCompletionResponse'
example:
choices:
- message:
content: |-
In moonlit shadows soft they prowl,
With eyes aglow in night's dark cowl.
role: assistant
index: 0
finish_reason: stop
logprobs: null
created: 1721722200
id: chatcmpl-8o4sq3sSzGVqS0aQyjlXuuEGVZnSj
model: gpt-4o-2024-05-13
object: chat.completion
system_fingerprint: fp_asd28019bf
usage:
completion_tokens: 34
prompt_tokens: 14
total_tokens: 48
security:
- bearerAuth: []
components:
schemas:
CreateChatCompletionRequest:
type: object
properties:
messages:
description: >-
A list of messages comprising the conversation so far. [Example
Python
code](https://cookbook.openai.com/examples/how_to_format_inputs_to_chatgpt_models).
type: array
minItems: 1
items:
$ref: '#/components/schemas/ChatCompletionRequestMessage'
model:
description: >-
ID of the model to use. See the [model endpoint
compatibility](https://platform.openai.com/docs/models/model-endpoint-compatibility)
table for details on which models work with the Chat API.
example: gpt-4-turbo
anyOf:
- type: string
- type: string
enum:
- gpt-4o
- gpt-4o-mini
- gpt-4
- gpt-3.5-turbo
x-oaiTypeLabel: string
frequency_penalty:
type: number
default: 0
minimum: -2
maximum: 2
nullable: true
description: >
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.](https://platform.openai.com/docs/guides/text-generation/parameter-details)
logit_bias:
type: object
x-oaiTypeLabel: map
default: null
nullable: true
additionalProperties:
type: integer
description: >
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:
description: >-
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`.
type: boolean
default: false
nullable: true
top_logprobs:
description: >-
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.
type: integer
minimum: 0
maximum: 20
nullable: true
max_tokens:
description: >
The maximum number of tokens that can be generated in the chat
completion.
The total length of input tokens and generated tokens is limited by
the model's context length. [Example Python
code](https://cookbook.openai.com/examples/how_to_count_tokens_with_tiktoken)
for counting tokens.
type: integer
nullable: true
presence_penalty:
type: number
default: 0
minimum: -2
maximum: 2
nullable: true
description: >
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.](https://platform.openai.com/docs/guides/text-generation/parameter-details)
response_format:
type: object
description: >
An object specifying the format that the model must output.
Compatible with GPT-4 Turbo and all GPT-3.5 Turbo models newer than
`gpt-3.5-turbo-1106`.
Setting to `{ "type": "json_object" }` enables JSON mode, which
guarantees 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.
properties:
type:
type: string
enum:
- text
- json_object
example: json_object
default: text
description: Must be one of `text` or `json_object`.
seed:
type: integer
minimum: -9223372036854776000
maximum: 9223372036854776000
nullable: true
description: >
This feature is in Beta.
If specified, OpenAI's 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.
x-oaiMeta:
beta: true
stop:
description: |
Up to 4 sequences where the API will stop generating further tokens.
default: null
oneOf:
- type: string
nullable: true
- type: array
minItems: 1
maxItems: 4
items:
type: string
stream:
description: >
If set, partial message deltas will be sent, like in ChatGPT. Tokens
will be sent as data-only [server-sent
events](https://developer.mozilla.org/en-US/docs/Web/API/Server-sent_events/Using_server-sent_events#Event_stream_format)
as they become available, with the stream terminated by a `data:
[DONE]` message. [Example Python
code](https://cookbook.openai.com/examples/how_to_stream_completions).
type: boolean
nullable: true
default: false
temperature:
type: number
minimum: 0
maximum: 2
default: 1
example: 1
nullable: true
description: >
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:
type: number
minimum: 0
maximum: 1
default: 1
example: 1
nullable: true
description: >
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:
type: array
description: >
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.
items:
$ref: '#/components/schemas/ChatCompletionTool'
tool_choice:
$ref: '#/components/schemas/ChatCompletionToolChoiceOption'
reasoning_effort:
type: string
nullable: true
description: >
Constrains how much effort the model spends on reasoning before
responding. Lower values produce faster, cheaper responses; higher
values produce more thorough reasoning. Supported values are `none`,
`minimal`, `low`, `medium`, `high`, and `xhigh`. Not all values are
supported by all models.
enum:
- none
- minimal
- low
- medium
- high
- xhigh
user:
type: string
example: user-1234
description: >
A unique identifier representing your end-user, which can help
OpenAI to monitor and detect abuse. [Learn
more](https://platform.openai.com/docs/guides/safety-best-practices/end-user-ids).
function_call:
deprecated: true
description: >
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.
oneOf:
- type: string
description: >
`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.
enum:
- none
- auto
- $ref: '#/components/schemas/ChatCompletionFunctionCallOption'
x-oaiExpandable: true
functions:
deprecated: true
description: |
Deprecated in favor of `tools`.
A list of functions the model may generate JSON inputs for.
type: array
minItems: 1
maxItems: 128
items:
$ref: '#/components/schemas/ChatCompletionFunctions'
required:
- model
- messages
CreateChatCompletionResponse:
type: object
description: >-
Represents a chat completion response returned by model, based on the
provided input.
properties:
id:
type: string
description: A unique identifier for the chat completion.
choices:
type: array
description: >-
A list of chat completion choices. Can be more than one if `n` is
greater than 1.
items:
type: object
required:
- finish_reason
- index
- message
- logprobs
properties:
finish_reason:
type: string
description: >
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
OpenAI's content filters,
`tool_calls` if the model called a tool, or `function_call`
(deprecated) if the model called a function.
enum:
- stop
- length
- tool_calls
- content_filter
- function_call
index:
type: integer
description: The index of the choice in the list of choices.
message:
$ref: '#/components/schemas/ChatCompletionResponseMessage'
logprobs:
description: Log probability information for the choice.
type: object
nullable: true
properties:
content:
description: >-
A list of message content tokens with log probability
information.
type: array
items:
$ref: '#/components/schemas/ChatCompletionTokenLogprob'
nullable: true
required:
- content
created:
type: integer
description: >-
The Unix timestamp (in seconds) of when the chat completion was
created.
model:
type: string
description: The model used for the chat completion.
system_fingerprint:
type: string
description: >
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:
type: string
description: The object type, which is always `chat.completion`.
enum:
- chat.completion
usage:
$ref: '#/components/schemas/CompletionUsage'
required:
- choices
- created
- id
- model
- object
x-oaiMeta:
name: The chat completion object
group: chat
example: |
{
"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
}
ChatCompletionRequestMessage:
oneOf:
- $ref: '#/components/schemas/ChatCompletionRequestSystemMessage'
- $ref: '#/components/schemas/ChatCompletionRequestUserMessage'
- $ref: '#/components/schemas/ChatCompletionRequestAssistantMessage'
- $ref: '#/components/schemas/ChatCompletionRequestToolMessage'
- $ref: '#/components/schemas/ChatCompletionRequestFunctionMessage'
x-oaiExpandable: true
ChatCompletionTool:
type: object
properties:
type:
type: string
enum:
- function
description: The type of the tool. Currently, only `function` is supported.
function:
$ref: '#/components/schemas/FunctionObject'
required:
- type
- function
ChatCompletionToolChoiceOption:
description: >
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.
oneOf:
- type: string
description: >
`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.
enum:
- none
- auto
- required
- $ref: '#/components/schemas/ChatCompletionNamedToolChoice'
x-oaiExpandable: true
ChatCompletionFunctionCallOption:
type: object
description: >
Specifying a particular function via `{"name": "my_function"}` forces
the model to call that function.
properties:
name:
type: string
description: The name of the function to call.
required:
- name
ChatCompletionFunctions:
type: object
deprecated: true
properties:
description:
type: string
description: >-
A description of what the function does, used by the model to choose
when and how to call the function.
name:
type: string
description: >-
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:
$ref: '#/components/schemas/FunctionParameters'
required:
- name
ChatCompletionResponseMessage:
type: object
description: A chat completion message generated by the model.
properties:
content:
type: string
description: The contents of the message.
nullable: true
tool_calls:
$ref: '#/components/schemas/ChatCompletionMessageToolCalls'
role:
type: string
enum:
- assistant
description: The role of the author of this message.
function_call:
type: object
deprecated: true
description: >-
Deprecated and replaced by `tool_calls`. The name and arguments of a
function that should be called, as generated by the model.
properties:
arguments:
type: string
description: >-
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:
type: string
description: The name of the function to call.
required:
- name
- arguments
required:
- role
- content
ChatCompletionTokenLogprob:
type: object
properties:
token:
description: The token.
type: string
logprob:
description: >-
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.
type: number
bytes:
description: >-
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.
type: array
items:
type: integer
nullable: true
top_logprobs:
description: >-
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.
type: array
items:
type: object
properties:
token:
description: The token.
type: string
logprob:
description: >-
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.
type: number
bytes:
description: >-
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.
type: array
items:
type: integer
nullable: true
required:
- token
- logprob
- bytes
required:
- token
- logprob
- bytes
- top_logprobs
CompletionUsage:
type: object
description: Usage statistics for the completion request.
properties:
completion_tokens:
type: integer
description: Number of tokens in the generated completion.
prompt_tokens:
type: integer
description: Number of tokens in the prompt.
total_tokens:
type: integer
description: Total number of tokens used in the request (prompt + completion).
required:
- prompt_tokens
- completion_tokens
- total_tokens
ChatCompletionRequestSystemMessage:
type: object
title: System message
properties:
content:
description: The contents of the system message.
type: string
role:
type: string
enum:
- system
description: The role of the messages author, in this case `system`.
name:
type: string
description: >-
An optional name for the participant. Provides the model information
to differentiate between participants of the same role.
required:
- content
- role
ChatCompletionRequestUserMessage:
type: object
title: User message
properties:
content:
description: |
The contents of the user message.
oneOf:
- type: string
description: The text contents of the message.
title: Text content
- type: array
description: >-
An array of content parts with a defined type, each can be of
type `text` or `image_url` when passing in images. You can pass
multiple images by adding multiple `image_url` content parts.
Image input is only supported when using the
`gpt-4-visual-preview` model.
title: Array of content parts
items:
$ref: '#/components/schemas/ChatCompletionRequestMessageContentPart'
minItems: 1
x-oaiExpandable: true
role:
type: string
enum:
- user
description: The role of the messages author, in this case `user`.
name:
type: string
description: >-
An optional name for the participant. Provides the model information
to differentiate between participants of the same role.
required:
- content
- role
ChatCompletionRequestAssistantMessage:
type: object
title: Assistant message
properties:
content:
nullable: true
type: string
description: >
The contents of the assistant message. Required unless `tool_calls`
or `function_call` is specified.
role:
type: string
enum:
- assistant
description: The role of the messages author, in this case `assistant`.
name:
type: string
description: >-
An optional name for the participant. Provides the model information
to differentiate between participants of the same role.
tool_calls:
$ref: '#/components/schemas/ChatCompletionMessageToolCalls'
function_call:
type: object
deprecated: true
description: >-
Deprecated and replaced by `tool_calls`. The name and arguments of a
function that should be called, as generated by the model.
nullable: true
properties:
arguments:
type: string
description: >-
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:
type: string
description: The name of the function to call.
required:
- arguments
- name
required:
- role
ChatCompletionRequestToolMessage:
type: object
title: Tool message
properties:
role:
type: string
enum:
- tool
description: The role of the messages author, in this case `tool`.
content:
type: string
description: The contents of the tool message.
tool_call_id:
type: string
description: Tool call that this message is responding to.
required:
- role
- content
- tool_call_id
ChatCompletionRequestFunctionMessage:
type: object
title: Function message
deprecated: true
properties:
role:
type: string
enum:
- function
description: The role of the messages author, in this case `function`.
content:
nullable: true
type: string
description: The contents of the function message.
name:
type: string
description: The name of the function to call.
required:
- role
- content
- name
FunctionObject:
type: object
properties:
description:
type: string
description: >-
A description of what the function does, used by the model to choose
when and how to call the function.
name:
type: string
description: >-
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:
$ref: '#/components/schemas/FunctionParameters'
required:
- name
ChatCompletionNamedToolChoice:
type: object
description: >-
Specifies a tool the model should use. Use to force the model to call a
specific function.
properties:
type:
type: string
enum:
- function
description: The type of the tool. Currently, only `function` is supported.
function:
type: object
properties:
name:
type: string
description: The name of the function to call.
required:
- name
required:
- type
- function
FunctionParameters:
type: object
description: >-
The parameters the functions accepts, described as a JSON Schema object.
See the
[guide](https://platform.openai.com/docs/guides/function-calling) for
examples, and the [JSON Schema
reference](https://json-schema.org/understanding-json-schema/reference)
for documentation about the format.
Omitting `parameters` defines a function with an empty parameter list.
additionalProperties: true
ChatCompletionMessageToolCalls:
type: array
description: The tool calls generated by the model, such as function calls.
items:
$ref: '#/components/schemas/ChatCompletionMessageToolCall'
ChatCompletionRequestMessageContentPart:
oneOf:
- $ref: '#/components/schemas/ChatCompletionRequestMessageContentPartText'
- $ref: '#/components/schemas/ChatCompletionRequestMessageContentPartImage'
x-oaiExpandable: true
ChatCompletionMessageToolCall:
type: object
properties:
id:
type: string
description: The ID of the tool call.
type:
type: string
enum:
- function
description: The type of the tool. Currently, only `function` is supported.
function:
type: object
description: The function that the model called.
properties:
name:
type: string
description: The name of the function to call.
arguments:
type: string
description: >-
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.
required:
- name
- arguments
required:
- id
- type
- function
ChatCompletionRequestMessageContentPartText:
type: object
title: Text content part
properties:
type:
type: string
enum:
- text
description: The type of the content part.
text:
type: string
description: The text content.
required:
- type
- text
ChatCompletionRequestMessageContentPartImage:
type: object
title: Image content part
properties:
type:
type: string
enum:
- image_url
description: The type of the content part.
image_url:
type: object
properties:
url:
type: string
description: Either a URL of the image or the base64 encoded image data.
format: uri
detail:
type: string
description: >-
Specifies the detail level of the image. Learn more in the
[Vision
guide](https://platform.openai.com/docs/guides/vision/low-or-high-fidelity-image-understanding).
enum:
- auto
- low
- high
default: auto
required:
- url
required:
- type
- image_url
securitySchemes:
bearerAuth:
type: http
scheme: bearer
bearerFormat: API Key
description: API key as Bearer token. Format "Bearer YOUR_API_KEY"
````