Qubrid AI Chat Completions API

openapi: 3.2.0
info:
  title: Qubrid AI Inference Chat Completions API
  description: The Qubrid AI Inference API provides a single, OpenAI-compatible endpoint for orchestrating 40+ open-source models running on NVIDIA GPU infrastructure.
  version: 1.0.0
  contact:
    name: Qubrid AI Support
    url: https://www.qubrid.com/contact
  termsOfService: https://www.qubrid.com/terms-of-service
servers:
- url: https://platform.qubrid.com/v1
  description: Qubrid AI Production Server
security:
- bearerAuth: []
tags:
- name: Chat Completions
  description: Generate chat-based completions using open-source large language models hosted on NVIDIA GPU infrastructure. Compatible with the OpenAI chat completions request and response format.
paths:
  /chat/completions:
    post:
      operationId: createChatCompletion
      summary: Create a chat completion
      description: Generates a model response for the given chat conversation. This endpoint is compatible with the OpenAI chat completions format, accepting an array of messages and returning a generated assistant reply. Supports text generation, code generation, and vision-language models available on the Qubrid AI platform.
      tags:
      - Chat Completions
      requestBody:
        required: true
        content:
          application/json:
            schema:
              $ref: '#/components/schemas/ChatCompletionRequest'
      responses:
        '200':
          description: Successfully generated a chat completion response.
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/ChatCompletionResponse'
        '400':
          description: The request was malformed or contained invalid parameters.
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/ErrorResponse'
        '401':
          description: Authentication failed due to a missing or invalid bearer token.
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/ErrorResponse'
        '404':
          description: The specified model was not found or is not available.
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/ErrorResponse'
        '429':
          description: Rate limit exceeded. Too many requests were sent in a given time period.
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/ErrorResponse'
        '500':
          description: An internal server error occurred during inference.
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/ErrorResponse'
components:
  schemas:
    ChatCompletionChoice:
      type: object
      properties:
        index:
          type: integer
          description: The index of the choice in the list of choices.
        message:
          $ref: '#/components/schemas/ChatMessage'
        finish_reason:
          type: string
          enum:
          - stop
          - length
          - content_filter
          description: The reason the model stopped generating tokens. stop means the model hit a natural stop point or a provided stop sequence, length means the maximum number of tokens was reached, and content_filter means content was omitted due to a filter.
    Usage:
      type: object
      properties:
        prompt_tokens:
          type: integer
          description: The number of tokens in the prompt.
        completion_tokens:
          type: integer
          description: The number of tokens in the generated completion.
        total_tokens:
          type: integer
          description: The total number of tokens used in the request (prompt plus completion).
    ChatCompletionRequest:
      type: object
      required:
      - model
      - messages
      properties:
        model:
          type: string
          description: The identifier of the model to use for generating the chat completion. Must be one of the models available on the Qubrid AI platform.
          example: deepseek-ai/DeepSeek-R1-Distill-Llama-70B
        messages:
          type: array
          description: A list of messages comprising the conversation so far. Each message has a role (system, user, or assistant) and content.
          items:
            $ref: '#/components/schemas/ChatMessage'
          minItems: 1
        temperature:
          type: number
          description: Sampling temperature between 0 and 2. Higher values like 0.8 make the output more random, while lower values like 0.2 make it more focused and deterministic.
          minimum: 0
          maximum: 2
          default: 1.0
        top_p:
          type: number
          description: Nucleus sampling parameter. The model considers the results of the tokens with top_p probability mass. A value of 0.1 means only the tokens comprising the top 10% probability mass are considered.
          minimum: 0
          maximum: 1
          default: 1.0
        n:
          type: integer
          description: How many chat completion choices to generate for each input message.
          minimum: 1
          default: 1
        max_tokens:
          type: integer
          description: The maximum number of tokens to generate in the chat completion. The total length of input tokens and generated tokens is limited by the model's context length.
          minimum: 1
        stream:
          type: boolean
          description: 'If true, partial message deltas will be sent as server-sent events as they become available, with the stream terminated by a data: [DONE] message.'
          default: false
        stop:
          oneOf:
          - type: string
          - type: array
            items:
              type: string
            maxItems: 4
          description: Up to 4 sequences where the API will stop generating further tokens.
        presence_penalty:
          type: number
          description: Penalizes new tokens based on whether they appear in the text so far, increasing the model's likelihood to talk about new topics.
          minimum: -2
          maximum: 2
          default: 0
        frequency_penalty:
          type: number
          description: Penalizes new tokens based on their existing frequency in the text so far, decreasing the model's likelihood to repeat the same line verbatim.
          minimum: -2
          maximum: 2
          default: 0
    ErrorResponse:
      type: object
      properties:
        error:
          type: object
          properties:
            message:
              type: string
              description: A human-readable error message describing what went wrong.
            type:
              type: string
              description: The type of error that occurred.
            code:
              type: string
              description: A machine-readable error code.
    ContentPart:
      type: object
      required:
      - type
      properties:
        type:
          type: string
          enum:
          - text
          - image_url
          description: The type of content part. Use text for text content and image_url for image content in vision-language model requests.
        text:
          type: string
          description: The text content, used when the type is text.
        image_url:
          type: object
          description: The image URL object, used when the type is image_url.
          properties:
            url:
              type: string
              format: uri
              description: The URL of the image to include in the message.
    ChatCompletionResponse:
      type: object
      properties:
        id:
          type: string
          description: A unique identifier for the chat completion.
        object:
          type: string
          enum:
          - chat.completion
          description: The object type, always chat.completion.
        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.
        choices:
          type: array
          description: A list of chat completion choices. Can be more than one if n is greater than 1.
          items:
            $ref: '#/components/schemas/ChatCompletionChoice'
        usage:
          $ref: '#/components/schemas/Usage'
    ChatMessage:
      type: object
      required:
      - role
      - content
      properties:
        role:
          type: string
          enum:
          - system
          - user
          - assistant
          description: The role of the message author. Use system for setting the assistant's behavior, user for the human's input, and assistant for previously generated responses.
        content:
          oneOf:
          - type: string
          - type: array
            items:
              $ref: '#/components/schemas/ContentPart'
          description: The content of the message. Can be a string for text-only messages, or an array of content parts for multimodal messages that include images.
  securitySchemes:
    bearerAuth:
      type: http
      scheme: bearer
      bearerFormat: QUBRID_API_KEY
      description: Qubrid AI API key passed as a bearer token in the Authorization header. Obtain your API key from the Qubrid AI platform dashboard at https://platform.qubrid.com.
externalDocs:
  description: Qubrid AI Documentation
  url: https://docs.platform.qubrid.com