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openapi: 3.0.0
info:
title: Mistral AI API
description: Chat Completion and Embeddings APIs
version: 0.0.1
servers:
- url: https://api.mistral.ai/v1
paths:
/chat/completions:
post:
operationId: createChatCompletion
summary: Create Chat Completions
requestBody:
required: true
content:
application/json:
schema:
$ref: '#/components/schemas/ChatCompletionRequest'
responses:
'200':
description: OK
content:
application/json:
schema:
$ref: '#/components/schemas/ChatCompletionResponse'
/embeddings:
post:
operationId: createEmbedding
summary: Create Embeddings
requestBody:
required: true
content:
application/json:
schema:
$ref: '#/components/schemas/EmbeddingRequest'
responses:
'200':
description: OK
content:
application/json:
schema:
$ref: '#/components/schemas/EmbeddingResponse'
/models:
get:
operationId: listModels
summary: List Available Models
responses:
'200':
description: OK
content:
application/json:
schema:
$ref: '#/components/schemas/ModelList'
components:
schemas:
Error:
type: object
properties:
type:
type: string
nullable: false
message:
type: string
nullable: false
param:
type: string
nullable: true
code:
type: string
nullable: true
required:
- type
- message
- param
- code
ErrorResponse:
type: object
properties:
error:
$ref: '#/components/schemas/Error'
required:
- error
ModelList:
type: object
properties:
object:
type: string
data:
type: array
items:
$ref: '#/components/schemas/Model'
required:
- object
- data
ChatCompletionRequest:
type: object
properties:
model:
description: >
ID of the model to use. You can use the [List Available
Models](/api#operation/listModels) API to see all of your available
models, or see our [Model overview](/models) for model descriptions.
type: string
example: mistral-tiny
messages:
description: >
The prompt(s) to generate completions for, encoded as a list of dict
with role and content. The first prompt role should be `user` or
`system`.
type: array
items:
type: object
properties:
role:
type: string
enum:
- system
- user
- assistant
content:
type: string
example:
- role: user
content: What is the best French cheese?
temperature:
type: number
minimum: 0
maximum: 1
default: 0.7
example: 0.7
nullable: true
description: >
What sampling temperature to use, between 0.0 and 1.0. 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: >
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.
max_tokens:
type: integer
minimum: 0
default: null
example: 16
nullable: true
description: >
The maximum number of tokens to generate in the completion.
The token count of your prompt plus `max_tokens` cannot exceed the
model's context length.
stream:
type: boolean
default: false
nullable: true
description: >
Whether to stream back partial progress. If set, tokens will be sent
as data-only server-sent events as they become available, with the
stream terminated by a data: [DONE] message. Otherwise, the server
will hold the request open until the timeout or until completion,
with the response containing the full result as JSON.
safe_mode:
type: boolean
default: false
description: |
Whether to inject a safety prompt before all conversations.
random_seed:
type: integer
default: null
description: >
The seed to use for random sampling. If set, different calls will
generate deterministic results.
required:
- model
- messages
ChatCompletionResponse:
type: object
properties:
id:
type: string
example: cmpl-e5cc70bb28c444948073e77776eb30ef
object:
type: string
example: chat.completion
created:
type: integer
example: 1702256327
model:
type: string
example: mistral-tiny
choices:
type: array
items:
type: object
required:
- index
- text
- finish_reason
properties:
index:
type: integer
example: 0
message:
type: object
properties:
role:
type: string
enum:
- user
- assistant
example: assistant
content:
type: string
example: >-
I don't have a favorite condiment as I don't consume food
or condiments. However, I can tell you that many people
enjoy using ketchup, mayonnaise, hot sauce, soy sauce, or
mustard as condiments to enhance the flavor of their
meals. Some people also enjoy using herbs, spices, or
vinegars as condiments. Ultimately, the best condiment is
a matter of personal preference.
finish_reason:
type: string
enum:
- stop
- length
- model_length
usage:
type: object
properties:
prompt_tokens:
type: integer
example: 14
completion_tokens:
type: integer
example: 93
total_tokens:
type: integer
example: 107
required:
- prompt_tokens
- completion_tokens
- total_tokens
EmbeddingRequest:
type: object
properties:
model:
type: string
example: mistral-embed
description: |
The ID of the model to use for this request.
input:
type: array
items:
type: string
example:
- Hello
- world
description: |
The list of strings to embed.
encoding_format:
type: string
enum:
- float
example: float
description: |
The format of the output data.
EmbeddingResponse:
type: object
properties:
id:
type: string
example: embd-aad6fc62b17349b192ef09225058bc45
object:
type: string
example: list
data:
type: array
items:
type: object
properties:
object:
type: string
example: embedding
embedding:
type: array
items:
type: number
example:
- 0.1
- 0.2
- 0.3
index:
type: int
example: 0
example:
- object: embedding
embedding:
- 0.1
- 0.2
- 0.3
index: 0
- object: embedding
embedding:
- 0.4
- 0.5
- 0.6
index: 1
model:
type: string
usage:
type: object
properties:
prompt_tokens:
type: integer
example: 9
total_tokens:
type: integer
example: 9
required:
- prompt_tokens
- total_tokens
required:
- id
- object
- data
- model
- usage
Model:
title: Model
properties:
id:
type: string
object:
type: string
created:
type: integer
owned_by:
type: string
required:
- id
- object
- created
- owned_by
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