> ## 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. # Register the model with the LLM gateway > Make the deployment's model available for inference: registers it in the LLM gateway's model registry under the deployment's name. Deployment must be ready. Registration is deliberately decoupled from deployment so pricing, budgets, and rate limits can be configured before the model becomes callable. ## OpenAPI ````yaml https://apigw.mka1.com/speakeasy.json post /api/v1/serving/deployments/{deployment_id}/registration 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 - description: Long-lived inference servers. name: Deployments x-displayName: Deployments - description: Submit, monitor, and cancel fine-tune jobs. name: Fine-Tune Jobs x-displayName: Fine-Tune Jobs - description: Custom container images for deployments and jobs. name: Container Images x-displayName: Container Images - description: Models registered for deployment and fine-tuning. name: Serving Models x-displayName: Serving Models - description: Persistent storage for weights and checkpoints. name: Volumes x-displayName: Volumes - description: Credentials injected into your workloads. name: Secrets x-displayName: Secrets - description: Available accelerator types (GPU, NPU, TPU). name: Accelerators x-displayName: Accelerators - description: Cluster-admin organization provisioning for serving. name: Serving Tenants x-displayName: Serving Tenants paths: /api/v1/serving/deployments/{deployment_id}/registration: post: tags: - Deployments summary: Register the model with the LLM gateway description: >- Make the deployment's model available for inference: registers it in the LLM gateway's model registry under the deployment's name. Deployment must be ready. Registration is deliberately decoupled from deployment so pricing, budgets, and rate limits can be configured before the model becomes callable. operationId: registerDeployment parameters: - in: path name: deployment_id required: true schema: title: Deployment Id type: string - name: X-On-Behalf-Of in: header required: false schema: type: string description: Optional external end-user identifier forwarded by the API gateway. responses: '200': content: application/json: schema: $ref: '#/components/schemas/Deployment' description: Successful Response '401': description: Missing or invalid bearer token. '403': content: application/json: schema: $ref: '#/components/schemas/ServingError' description: Serving is not enabled for your tenant. '404': content: application/json: schema: $ref: '#/components/schemas/ServingError' description: Resource not found. '409': content: application/json: schema: $ref: '#/components/schemas/ServingError' description: >- Deployment not ready, or the model name is already taken in the registry. '422': content: application/json: schema: $ref: '#/components/schemas/ServingHTTPValidationError' description: Validation Error '500': content: application/json: schema: $ref: '#/components/schemas/ServingError' description: Gateway registration failed unexpectedly. '503': content: application/json: schema: $ref: '#/components/schemas/ServingError' description: Gateway registration is unavailable or not configured. security: - bearerAuth: [] x-codeSamples: - lang: python label: Python (SDK) source: |- from meetkai_mka1 import SDK with SDK( bearer_auth="", ) as sdk: res = sdk.serving.deployments.register(deployment_id="") # 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.serving.deployments.register({ deploymentId: "", }); 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.Serving.Deployments.RegisterAsync(deploymentId: ""); // handle response components: schemas: Deployment: description: A deployed inference server. properties: accelerator: $ref: '#/components/schemas/AcceleratorSpec' created_at: type: string format: date-time title: Created At endpoint: anyOf: - $ref: '#/components/schemas/DeploymentEndpoint' - type: 'null' description: >- Where and how to call the model; set while registered with the gateway engine: $ref: '#/components/schemas/Engine' id: title: Id type: string image: anyOf: - type: string - type: 'null' title: Image model: title: Model type: string name: title: Name type: string revision: description: Current config revision title: Revision type: integer scaling: $ref: '#/components/schemas/Scaling' served_model_id: anyOf: - type: string - type: 'null' description: >- Model ID consumers pass to the gateway's inference endpoints; set while the deployment is registered with the gateway (see Register), null when unregistered title: Served Model Id status: enum: - pending - provisioning - ready - scaling - updating - degraded - failed - stopped - deleted title: Status type: string updated_at: type: string format: date-time title: Updated At required: - id - name - status - model - engine - accelerator - scaling - image - revision - created_at - updated_at title: Deployment type: object ServingError: description: Standard error envelope. properties: error: $ref: '#/components/schemas/ErrorDetail' required: - error title: ServingError type: object ServingHTTPValidationError: properties: detail: items: $ref: '#/components/schemas/ServingValidationError' title: Detail type: array title: ServingHTTPValidationError type: object AcceleratorSpec: description: |- A hardware accelerator request — GPU, NPU, TPU, or similar. Request an accelerator by type and count, with optional fallback types. properties: count: default: 1 description: Accelerators per replica maximum: 8 minimum: 1 title: Count type: integer fallback: description: Ordered fallback types if the primary is unavailable examples: - - H100 - MI300X items: type: string title: Fallback type: array type: examples: - H100 - MI300X - gaudi3 - trn2 title: Type type: string required: - type title: AcceleratorSpec type: object DeploymentEndpoint: description: >- How consumers reach the deployed model. Inference always flows through the MKA1 LLM gateway: the deployment registers its model there, and callers use their normal MKA1 API key. Provider URLs and credentials never leave the control plane. properties: base_url: description: Gateway base URL to send inference requests to examples: - https://apigw.mka1.com/api/v1/llm title: Base Url type: string openai_compatible: default: true title: Openai Compatible type: boolean via: const: gateway default: gateway title: Via type: string required: - base_url title: DeploymentEndpoint type: object Engine: description: Inference engine that backs a deployment. enum: - vllm - sglang title: Engine type: string Scaling: description: Autoscaling configuration for a deployment. properties: buffer_containers: default: 0 description: Idle replicas kept ready for bursts minimum: 0 title: Buffer Containers type: integer max_concurrent_inputs: default: 100 description: In-flight requests a single replica accepts at once minimum: 1 title: Max Concurrent Inputs type: integer max_containers: default: 1 description: Replica ceiling minimum: 1 title: Max Containers type: integer min_containers: default: 0 description: Warm replicas to always keep minimum: 0 title: Min Containers type: integer scaledown_window_s: default: 300 description: Idle seconds before a replica is killed maximum: 1200 minimum: 2 title: Scaledown Window S type: integer title: Scaling type: object ErrorDetail: description: The body of an error response. properties: code: examples: - tenant_not_provisioned title: Code type: string message: type: string title: Message type: examples: - authorization_error title: Type type: string required: - code - message - type title: ErrorDetail type: object ServingValidationError: properties: ctx: title: Context type: object input: title: Input loc: items: anyOf: - type: string - type: integer type: array title: Location msg: type: string title: Message type: type: string title: Error Type required: - loc - msg - type title: ServingValidationError type: object 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: `. ````