> ## 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. # [Deprecated] Chat completions for OpenAI SDK/client usage > **Deprecated: Use the Responses API (`/api/v1/llm/responses`) instead.** OpenAI-compatible chat completion endpoint designed for use with the official OpenAI client libraries (Python, Node.js, etc.). Supports both streaming and non-streaming requests by setting the `stream` parameter. This endpoint handles the request/response directly and returns standard OpenAI-formatted responses. Use this when integrating with existing OpenAI client code. Note: The actual handler is registered at the Bun server level for optimal performance with the OpenAI SDK streaming format. ## OpenAPI ````yaml https://apigw.mka1.com/speakeasy.json post /api/v1/llm/chat/completions 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: Compute Jobs x-displayName: Compute Jobs - name: Compute Services x-displayName: Compute Services - name: Compute Catalog x-displayName: Compute Catalog - name: Compute Secrets x-displayName: Compute Secrets - name: Compute Usage x-displayName: Compute Usage - name: Compute Tenants x-displayName: Compute Tenants - description: Create, list, read, update, and delete repositories. name: Repositories x-displayName: Repositories paths: /api/v1/llm/chat/completions: post: tags: - Chat Completions summary: '[Deprecated] Chat completions for OpenAI SDK/client usage' description: >- **Deprecated: Use the Responses API (`/api/v1/llm/responses`) instead.** OpenAI-compatible chat completion endpoint designed for use with the official OpenAI client libraries (Python, Node.js, etc.). Supports both streaming and non-streaming requests by setting the `stream` parameter. This endpoint handles the request/response directly and returns standard OpenAI-formatted responses. Use this when integrating with existing OpenAI client code. Note: The actual handler is registered at the Bun server level for optimal performance with the OpenAI SDK streaming format. operationId: createChatCompletion 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/OpenAIChatCompletionRequestParams' example: model: meetkai:functionary-urdu-mini-pak messages: - role: user content: What is the capital of France? temperature: 0.7 max_tokens: 100 responses: '200': description: >- Successful chat completion response. Returns JSON for non-streaming (stream=false) or Server-Sent Events for streaming (stream=true). content: application/json: schema: $ref: '#/components/schemas/OpenAIChatCompletion' example: id: chatcmpl-abc123 object: chat.completion created: 1704067200 model: meetkai:functionary-urdu-mini-pak choices: - index: 0 message: role: assistant content: The capital of France is Paris. finish_reason: stop usage: prompt_tokens: 15 completion_tokens: 8 total_tokens: 23 text/event-stream: schema: type: string example: |+ data: {"id":"chatcmpl-abc123"} deprecated: true security: - bearerAuth: [] components: schemas: OpenAIChatCompletionRequestParams: type: object properties: model: type: string minLength: 1 description: >- ID of the model to use. You can use provider:model format or just the model name with a default provider. messages: type: array minItems: 1 items: $ref: '#/components/schemas/OpenAIRequestMessage' description: >- A list of messages comprising the conversation so far. At least one message is required. tools: type: array items: $ref: '#/components/schemas/OpenAIToolDefinition' description: >- A list of tools the model may call. Use this to provide function definitions the model can invoke. tool_choice: anyOf: - const: none description: The model will not call any tool and instead generates a message - const: auto description: >- The model can pick between generating a message or calling one or more tools - const: required description: The model must call one or more tools - type: object properties: type: const: function description: >- The type of the tool. Currently only 'function' is supported. function: type: object properties: name: type: string minLength: 1 description: The name of the function to call required: - name description: The function to call required: - type - function description: Forces the model to call a specific function description: >- Controls which (if any) tool is called by the model. 'none' means the model will not call any tool. 'auto' means the model can pick. 'required' forces a tool call. stream: type: boolean description: >- If set, partial message deltas will be sent as server-sent events. Note: This field is ignored by the streaming endpoint, used only by OpenAI-compatible client endpoints. 'n': type: integer minimum: 1 maximum: 9007199254740991 description: >- How many chat completion choices to generate for each input message. Default is 1. max_tokens: type: integer minimum: 1 maximum: 9007199254740991 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. temperature: type: number minimum: 0 maximum: 2 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. top_p: type: number minimum: 0 maximum: 1 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. frequency_penalty: type: number 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. presence_penalty: type: number 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. seed: type: integer minimum: -9007199254740991 maximum: 9007199254740991 description: >- If specified, the system will make a best effort to sample deterministically. Determinism is not guaranteed, but the same seed should typically return similar results. stop: anyOf: - type: string - type: array maxItems: 4 items: type: string description: >- Up to 4 sequences where the API will stop generating further tokens. The returned text will not contain the stop sequence. response_format: type: object properties: type: anyOf: - type: string - enum: - text - json_object type: string description: >- The format type. Use 'json_object' to enable JSON mode, guaranteeing the message the model generates is valid JSON. json_schema: type: object properties: name: type: string schema: type: object propertyNames: type: string additionalProperties: {} strict: type: boolean required: - name - schema description: >- JSON Schema definition for structured output. Required when type is 'json_schema'. required: - type description: >- An object specifying the format that the model must output. Setting to { 'type': 'json_object' } enables JSON mode. logprobs: type: boolean description: >- Whether to return log probabilities of the output tokens. If true, returns the log probabilities of each output token returned in the content of message. top_logprobs: type: integer minimum: 0 maximum: 20 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. user: type: string description: >- A unique identifier representing your end-user, which can help monitor and detect abuse. Also used for usage tracking and analytics. stream_options: type: object properties: include_usage: type: boolean description: >- If set, an additional chunk with token usage statistics will be streamed before the data: [DONE] message. The usage field shows total token usage for the entire request. description: >- Options for streaming response. Only set this when you set stream: true. parallel_tool_calls: type: boolean default: true description: Whether to enable parallel function calling during tool use. reasoning_effort: anyOf: - enum: - none - minimal - low - medium - high - xhigh type: string - type: 'null' description: >- Constrains effort on reasoning for reasoning models. Lower effort results in faster responses and fewer reasoning tokens. Supported values: 'none', 'minimal', 'low', 'medium', 'high', 'xhigh', or null. auto_routing: type: boolean description: >- When true, the gateway analyzes request complexity and automatically routes between quantized, MoE, and dense variants of the requested model family. required: - model - messages additionalProperties: false description: >- Request parameters for creating a chat completion. Based on the OpenAI Chat Completions API. examples: - model: meetkai:functionary-urdu-mini-pak messages: - role: user content: What is the capital of France? temperature: 0.7 max_tokens: 100 OpenAIChatCompletion: type: object properties: id: type: string description: A unique identifier for the chat completion object: const: chat.completion description: The object type, always 'chat.completion' created: type: integer minimum: -9007199254740991 maximum: 9007199254740991 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 items: $ref: '#/components/schemas/OpenAIChatCompletionChoice' description: >- A list of chat completion choices. Can be more than one if n is greater than 1. usage: type: object properties: prompt_tokens: type: integer minimum: -9007199254740991 maximum: 9007199254740991 description: Number of tokens in the prompt completion_tokens: type: integer minimum: -9007199254740991 maximum: 9007199254740991 description: Number of tokens in the generated completion total_tokens: type: integer minimum: -9007199254740991 maximum: 9007199254740991 description: Total number of tokens used in the request (prompt + completion) completion_tokens_details: type: object properties: reasoning_tokens: type: integer minimum: -9007199254740991 maximum: 9007199254740991 description: Number of tokens used for reasoning audio_tokens: type: integer minimum: -9007199254740991 maximum: 9007199254740991 description: Number of tokens used for audio description: Breakdown of completion tokens by type required: - prompt_tokens - completion_tokens - total_tokens description: Usage statistics for the completion request 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. required: - id - object - created - model - choices - usage description: Represents a chat completion response from the API examples: - id: chatcmpl-abc123 object: chat.completion created: 1704067200 model: meetkai:functionary-urdu-mini-pak choices: - index: 0 message: role: assistant content: The capital of France is Paris. finish_reason: stop usage: prompt_tokens: 15 completion_tokens: 8 total_tokens: 23 example: id: chatcmpl-abc123 object: chat.completion created: 1704067200 model: meetkai:functionary-urdu-mini-pak choices: - index: 0 message: role: assistant content: The capital of France is Paris. finish_reason: stop usage: prompt_tokens: 15 completion_tokens: 8 total_tokens: 23 OpenAIRequestMessage: type: object properties: role: enum: - system - user - assistant - tool - developer type: string description: >- The role of the message author. Determines how the message is interpreted by the model. name: type: string description: >- An optional name for the participant. For tool role messages, this is the name of the function called. tool_call_id: type: string description: >- Tool call that this message is responding to. Required when role is 'tool'. content: anyOf: - type: string - type: array items: anyOf: - type: object properties: type: const: text description: Content type identifier for text content text: type: string description: The text content to include in the message required: - type - text - type: object properties: type: const: image_url description: Content type identifier for image URL content image_url: type: object properties: url: type: string description: >- The URL of the image, or a base64-encoded image data URL detail: enum: - auto - low - high type: string description: >- The detail level of the image analysis. 'low' disables high-res mode, 'high' enables it, 'auto' lets the model decide. required: - url required: - type - image_url - type: object properties: type: const: input_audio description: Content type identifier for audio input content input_audio: type: object properties: data: type: string description: Base64-encoded audio data format: enum: - wav - mp3 type: string description: The format of the encoded audio data required: - data - format required: - type - input_audio - type: object properties: type: const: file description: Content type identifier for file content file: anyOf: - type: object properties: filename: type: string description: The name of the file file_data: type: string description: Base64-encoded file data required: - filename - file_data - type: object properties: file_id: type: string description: >- The unique identifier of a previously uploaded file filename: type: string description: Optional filename override required: - file_id description: >- The file to include in the message, either as raw data or by reference required: - type - file description: >- A content part that can be included in a message. Supports text, images, audio, and files. - type: 'null' description: >- The contents of the message. Can be a string, an array of content parts (for multimodal inputs), or null for assistant messages with tool calls. tool_calls: type: array items: type: object properties: id: type: string description: The ID of the tool call type: const: 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 arguments: type: string description: The arguments to call the function with, as a JSON string required: - name - arguments description: The function to be called required: - id - type - function description: >- The tool calls generated by the model, such as function calls. Only present for assistant messages with tool calls. required: - role - content description: >- A message in the chat completion request. Represents a conversation turn from the user, assistant, system, or tool. OpenAIToolDefinition: type: object properties: type: const: function description: The type of the tool. Currently only 'function' is supported. function: type: object properties: name: type: string minLength: 1 description: >- The name of the function to be called. Must be a-z, A-Z, 0-9, underscores and dashes, with a maximum length of 64 characters. description: type: string description: >- A description of what the function does. Used by the model to choose when and how to call the function. parameters: description: >- The parameters the function accepts, described as a JSON Schema object. Omit to accept no parameters. required: - name description: The function definition required: - type - function description: A tool the model may call while generating a response. OpenAIChatCompletionChoice: type: object properties: index: type: integer minimum: -9007199254740991 maximum: 9007199254740991 description: The index of this choice in the list of choices message: type: object properties: role: const: assistant description: >- The role of the message author, must be 'assistant' for assistant messages name: type: string description: >- An optional name for the participant. For tool role messages, this is the name of the function called. tool_call_id: type: string description: >- Tool call that this message is responding to. Required when role is 'tool'. content: anyOf: - type: string - type: array items: anyOf: - type: object properties: type: const: text description: Content type identifier for text content text: type: string description: The text content to include in the message required: - type - text - type: object properties: type: const: image_url description: Content type identifier for image URL content image_url: type: object properties: url: type: string description: >- The URL of the image, or a base64-encoded image data URL detail: enum: - auto - low - high type: string description: >- The detail level of the image analysis. 'low' disables high-res mode, 'high' enables it, 'auto' lets the model decide. required: - url required: - type - image_url - type: object properties: type: const: input_audio description: Content type identifier for audio input content input_audio: type: object properties: data: type: string description: Base64-encoded audio data format: enum: - wav - mp3 type: string description: The format of the encoded audio data required: - data - format required: - type - input_audio - type: object properties: type: const: file description: Content type identifier for file content file: anyOf: - type: object properties: filename: type: string description: The name of the file file_data: type: string description: Base64-encoded file data required: - filename - file_data - type: object properties: file_id: type: string description: >- The unique identifier of a previously uploaded file filename: type: string description: Optional filename override required: - file_id description: >- The file to include in the message, either as raw data or by reference required: - type - file description: >- A content part that can be included in a message. Supports text, images, audio, and files. - type: 'null' description: >- The contents of the assistant message. Can be null when the message contains tool calls only. reasoning: anyOf: - type: string - type: 'null' description: >- The reasoning content generated by the model before producing the final response. Present for models that support chain-of-thought reasoning. tool_calls: type: array items: type: object properties: id: type: string description: The ID of the tool call type: const: 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 arguments: type: string description: >- The arguments to call the function with, as a JSON string required: - name - arguments description: The function that the model called required: - id - type - function description: The tool calls generated by the model, such as function calls. required: - role - content description: The message generated by the model finish_reason: anyOf: - anyOf: - enum: - stop - length - tool_calls - content_filter type: string description: The reason why the model stopped generating tokens. - type: string - type: 'null' description: >- The reason the model stopped generating tokens. 'stop' means natural stop point or provided stop sequence, 'length' means max_tokens limit reached, 'tool_calls' means the model called a tool, 'content_filter' means content was filtered due to policy violations. logprobs: anyOf: - type: object properties: tokens: type: array items: type: string description: The list of tokens token_logprobs: type: array items: type: number description: The log probability of each token top_logprobs: type: array items: type: object propertyNames: type: string additionalProperties: type: number description: The top log probabilities for each token position text_offset: type: array items: type: integer minimum: -9007199254740991 maximum: 9007199254740991 description: >- The character offset from the beginning of the returned text for each token required: - tokens - token_logprobs - top_logprobs - text_offset description: Log probability information for the choice - type: 'null' description: Log probability information for the choice required: - index - message - finish_reason description: A chat completion choice generated by the model 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: `. ````