> ## Documentation Index > Fetch the complete documentation index at: https://docs.mka1.com/llms.txt > Use this file to discover all available pages before exploring further. # Generate images from text descriptions > Creates AI-generated images from text descriptions. ## OpenAPI ````yaml https://apigw.mka1.com/speakeasy.json post /api/v1/llm/images/generations openapi: 3.1.1 info: title: MKA1 API version: 1.1.0 description: >- The MKA1 API is a RESTful API that provides access to the MKA1 platform. Learn how to get started with the API and the TypeScript SDK [here](https://mka1.apidocumentation.com/guides/getting-started). license: name: Proprietary servers: - url: https://apigw.mka1.com description: MKA1 API Gateway - url: / description: Relative server URL (configurable via SDK constructor) security: [] tags: - name: Resource Authorization description: >- Manage permissions for LLM resources. Create resources, grant/revoke permissions, and delete resources. Only resource owners can grant, revoke, or delete permissions. x-displayName: Resource Authorization - name: Embeddings description: >- Text embedding API endpoints for generating vector representations of text. Create semantic embeddings for search, clustering, and similarity matching using various embedding models. x-displayName: Embeddings - name: Feedback description: >- User feedback API for rating and commenting on chat completions. Collect thumbs up/down ratings and detailed feedback to improve model responses and track user satisfaction. x-displayName: Feedback - name: Images description: >- Image generation API endpoints for creating images from text descriptions. Generate images with control over size, quality, and style. x-displayName: Images - name: MCP Vault description: >- MCP vault API for storing user-owned MCP server configurations and encrypted credentials. Agents reference vault IDs so secrets are resolved only at tool execution time. x-displayName: MCP Vault - name: Speech description: >- Speech API endpoints for audio processing. Convert text to natural-sounding speech (TTS) or transcribe speech to text (STT) in different languages. x-displayName: Speech - name: Usage description: >- Usage tracking and analytics API for monitoring token consumption, request counts, and cost analysis. View detailed statistics per user, model, and time period. x-displayName: Usage - name: Extract description: >- Structured data extraction API for extracting information from files. Define JSON schemas to extract structured data from images, PDFs, and documents. Supports reusable schema templates. x-displayName: Extract - name: Text Classification description: >- Text classification API for categorizing text into predefined labels. Use AI models to classify text content for sentiment analysis, topic categorization, and content moderation. x-displayName: Text Classification - name: Responses description: >- Agent-powered responses API for creating AI agents with autonomous tool usage. Build conversational assistants that can use web search, file operations, image generation, code execution, computer use simulation, and MCP integrations. Supports background processing, streaming, and real-time status tracking. x-displayName: Responses - name: Files description: >- File management API for uploading, storing, and managing files with automatic expiration and S3 integration. Upload files that can be used with Assistants, Vector Stores, and other features. Files are stored in S3 with metadata tracked in PostgreSQL. Supports automatic cleanup of expired files. x-displayName: Files - name: Vector Stores description: >- Vector store API for storing and searching documents using embeddings. Create vector stores, upload files with automatic chunking and embedding generation, and perform semantic search. Files are processed asynchronously using Temporal workflows for durability. Supports automatic cleanup of expired stores and LanceDB for efficient vector storage. x-displayName: Vector Stores - name: Conversations description: >- Conversation management API for storing and retrieving conversation state across Response API calls. Create conversations, add items (user messages, assistant messages, system messages), and maintain conversation history. Supports metadata tracking and multi-turn dialogue state management. x-displayName: Conversations - name: Guardrails description: >- AI safety guardrails API for configuring content moderation and security policies. Set up ban word lists, prompt injection detection, and system prompt leakage prevention. Guardrails apply to all requests from an account and can be tested before deployment. x-displayName: Guardrails - name: Models description: >- Model listing API for discovering available models. Returns model IDs, ownership, and metadata for all registered models in the gateway. x-displayName: Models - name: Skills description: >- Skills API for managing versioned bundles of instructions and files following the Agent Skills standard. Create, version, and download reusable skill packages that include SKILL.md manifests for agent environments. x-displayName: Skills - name: Chat Completions description: >- **Deprecated: Use the Responses API (`/api/v1/llm/responses`) instead.** Chat completion endpoints with support for streaming, tool calls, and multiple providers. x-deprecated: true x-displayName: Chat Completions - name: Batches x-displayName: Batches - name: Evals x-displayName: Evals - name: Fine-Tuning x-displayName: Fine-Tuning - name: Memory Stores x-displayName: Memory Stores - name: Prompts x-displayName: Prompts - name: API Key x-displayName: API Key - name: Organization x-displayName: Organization - name: Cluster Admin x-displayName: Cluster Admin - name: Sessions description: Create, inspect, access, and terminate sandbox sessions. x-displayName: Sessions - name: Browser description: >- Connect to browser sessions through the gateway port proxy. Browser sessions expose a Chrome DevTools Protocol endpoint on port 9222. x-displayName: Browser - name: Execution description: Run shell commands and code inside an existing sandbox session. x-displayName: Execution - name: Workspace description: >- Inspect the workspace manifest, transfer files or archives, and download generated artifacts. x-displayName: Workspace - name: Sandbox Usage description: >- Aggregate sandbox usage statistics across sessions, execution, and workspace operations. x-displayName: Sandbox Usage - name: Sandbox Pricing description: >- Cluster-admin management of the sandbox compute rate card used for budgeted spend. x-displayName: Sandbox Pricing - name: Agents description: Create and manage reusable agent definitions. x-displayName: Agents - name: Agent Versions description: Inspect an agent's configuration history and roll back to a prior version. x-displayName: Agent Versions - name: Agent Runs description: Execute saved agents and inspect persisted run results. x-displayName: Agent Runs - name: Agent Connectors description: >- Connect saved agents to external messaging channels such as Telegram, including text, photo, and supported document exchange. x-displayName: Agent Connectors - name: Agent Schedules description: Create and manage scheduled or recurring saved agent runs. x-displayName: Agent Schedules - name: schema-4_other x-displayName: other - name: Budgets x-displayName: Budgets - name: Settings x-displayName: Settings - name: Deployments description: Long-lived inference servers. x-displayName: Deployments - name: Fine-Tune Jobs description: Submit, monitor, and cancel fine-tune jobs. x-displayName: Fine-Tune Jobs - name: Container Images description: Custom container images for deployments and jobs. x-displayName: Container Images - name: Serving Models description: Models registered for deployment and fine-tuning. x-displayName: Serving Models - name: Volumes description: Persistent storage for weights and checkpoints. x-displayName: Volumes - name: Secrets description: Credentials injected into your workloads. x-displayName: Secrets - name: Accelerators description: Available accelerator types (GPU, NPU, TPU). x-displayName: Accelerators paths: /api/v1/llm/images/generations: post: tags: - Images summary: Generate images from text descriptions description: Creates AI-generated images from text descriptions. operationId: createImage parameters: - name: X-On-Behalf-Of in: header required: false schema: type: string description: Optional external end-user identifier forwarded by the API gateway. requestBody: required: true content: application/json: schema: $ref: '#/components/schemas/ImageGenerationRequest' example: model: auto prompt: A serene mountain landscape at sunset with a lake reflection size: 1024x1024 quality: hd responses: '200': description: OK content: application/json: schema: $ref: '#/components/schemas/ImageGenerationResponse' example: created: 1704067200 data: - url: https://example.com/generated-image.png revised_prompt: >- A serene mountain landscape at sunset with a calm lake reflection, digital art style security: - bearerAuth: [] x-codeSamples: - lang: python label: Python (SDK) source: |- from meetkai_mka1 import SDK with SDK( bearer_auth="", ) as sdk: res = sdk.llm.images.create(prompt="A serene mountain landscape at sunset with a lake reflection", model="auto", n=1, quality="hd", response_format="url", size="1024x1024", style="vivid") # Handle response print(res) - lang: typescript label: Typescript (SDK) source: |- import { SDK } from "@meetkai/mka1"; const sdk = new SDK({ bearerAuth: "", }); async function run() { const result = await sdk.llm.images.create({ imageGenerationRequest: { prompt: "A serene mountain landscape at sunset with a lake reflection", quality: "hd", }, }); console.log(result); } run(); - lang: csharp label: CSharp (SDK) source: >- using MeetKai.MKA1; using MeetKai.MKA1.Types.Components; var sdk = new SDK(bearerAuth: ""); var res = await sdk.Llm.Images.CreateAsync(body: new ImageGenerationRequest() { Prompt = "A serene mountain landscape at sunset with a lake reflection", Quality = ImageGenerationRequestQuality.Hd, }); // handle response components: schemas: ImageGenerationRequest: type: object properties: model: type: string default: auto description: The model to use for image generation. Defaults to 'auto'. prompt: type: string minLength: 1 maxLength: 1000 description: >- A text description of the desired image(s). The maximum length is 1000 characters. 'n': type: integer minimum: 1 maximum: 10 default: 1 description: >- The number of images to generate. Must be between 1 and 10. Defaults to 1. quality: enum: - low - medium - high - auto - standard - hd type: string default: auto description: >- The quality tier of the generated image. Higher tiers may incur higher latency or cost. 'auto' lets the gateway pick a sensible value per model. 'standard' and 'hd' are accepted as legacy aliases. response_format: enum: - url - b64_json type: string default: url description: >- The format in which the generated images are returned. 'url' returns a URL to the image, 'b64_json' returns the image as a base64-encoded JSON string. Defaults to 'url'. size: enum: - 256x256 - 512x512 - 1024x1024 - 1024x1536 - 1536x1024 - 1792x1024 - 1024x1792 - auto type: string default: 1024x1024 description: >- The size of the generated image. 'auto' defers to the model's default. style: enum: - vivid - natural type: string default: vivid description: >- The style of the generated image. 'vivid' leans toward hyper-real and dramatic. 'natural' produces more naturalistic results. Conditionally supported. output_format: enum: - png - webp - jpeg type: string description: Output file format. Conditionally supported. user: type: string description: >- A unique identifier representing your end-user, which can help monitor and detect abuse. required: - prompt description: >- Request parameters for generating images. Creates one or more images from a text prompt. examples: - model: auto prompt: A serene mountain landscape at sunset with a lake reflection size: 1024x1024 quality: high ImageGenerationResponse: type: object properties: created: type: number description: >- The Unix timestamp (in seconds) of when the image generation was completed. data: type: array items: type: object properties: url: type: string description: >- The URL of the generated image, if response_format is 'url' (default). The URL is valid for 1 hour. b64_json: type: string description: >- The base64-encoded JSON of the generated image, if response_format is 'b64_json'. revised_prompt: type: string description: >- The prompt that was used to generate the image, if there was any revision to the prompt. description: An individual image object in the response. description: A list of image objects containing the generated image data. required: - created - data description: >- Response from the image generation endpoint containing the generated images and metadata. examples: - created: 1704067200 data: - url: https://example.com/generated-image.png revised_prompt: >- A serene mountain landscape at sunset with a calm lake reflection, digital art style securitySchemes: bearerAuth: type: http scheme: bearer bearerFormat: API Key description: >- Gateway auth: send `Authorization: Bearer `. For multi-user server-side integrations, you can also send `X-On-Behalf-Of: `. ````