> ## 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. # List chat completion feedback > Retrieves a paginated list of feedback entries recorded on the caller's chat completions, ordered by the completion's creation date. Supports filtering by rating. An `after` cursor that no longer resolves to a completion visible to the caller returns 400; restart pagination from the first page. ## OpenAPI ````yaml https://apigw.mka1.com/speakeasy.json get /api/v1/llm/feedback/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. 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/feedback/completions: get: tags: - Feedback summary: List chat completion feedback description: >- Retrieves a paginated list of feedback entries recorded on the caller's chat completions, ordered by the completion's creation date. Supports filtering by rating. An `after` cursor that no longer resolves to a completion visible to the caller returns 400; restart pagination from the first page. operationId: listCompletionFeedback parameters: - name: after in: query schema: type: string description: >- A request ID to use as a cursor for pagination. Returns feedback entries that come after this ID in the list. If the ID no longer resolves to a request visible to the caller (for example, the underlying response was deleted), the request fails with 400; restart pagination from the first page. allowEmptyValue: true example: chatcmpl-abc123def456 - name: limit in: query schema: type: integer minimum: 1 maximum: 100 default: 20 description: >- The maximum number of feedback entries to return per page. Must be between 1 and 100. Defaults to 20 items. allowEmptyValue: true example: 25 - name: order in: query schema: enum: - asc - desc type: string default: desc description: >- The order to return feedback entries in by creation date of the underlying request. 'asc' returns oldest first, 'desc' returns newest first. Defaults to 'desc' (newest first). allowEmptyValue: true example: desc - name: rating in: query schema: enum: - thumbs_up - thumbs_down type: string description: >- Only return feedback entries with this rating. Omit to return entries with any rating. allowEmptyValue: true example: thumbs_up - 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': description: OK content: application/json: schema: $ref: '#/components/schemas/ListFeedbackResponse' example: object: list data: - id: chatcmpl-abc123def456 rating: thumbs_up description: The response was accurate and helpful. model: openai:gpt-4o-mini created_at: '2024-01-15T10:30:00Z' updated_at: '2024-01-15T10:30:00Z' first_id: chatcmpl-abc123def456 last_id: chatcmpl-abc123def456 has_more: false security: - bearerAuth: [] x-codeSamples: - lang: python label: Python (SDK) source: |- from meetkai_mka1 import SDK with SDK( bearer_auth="", ) as sdk: res = sdk.llm.feedback.list_completion_feedback(after="chatcmpl-abc123def456", limit=25, order="desc", rating="thumbs_up") # 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.feedback.listCompletionFeedback({ after: "chatcmpl-abc123def456", limit: 25, rating: "thumbs_up", }); console.log(result); } run(); - lang: csharp label: CSharp (SDK) source: >- using MeetKai.MKA1; using MeetKai.MKA1.Types.Components; using MeetKai.MKA1.Types.Requests; var sdk = new SDK(bearerAuth: ""); ListCompletionFeedbackRequest req = new ListCompletionFeedbackRequest() { After = "chatcmpl-abc123def456", Limit = 25, Rating = ListCompletionFeedbackRating.ThumbsUp, }; var res = await sdk.Llm.Feedback.ListCompletionFeedbackAsync(req); // handle response components: schemas: ListFeedbackResponse: type: object properties: object: const: list description: The object type, always 'list' for paginated list responses. data: type: array items: type: object properties: id: type: string description: The request ID that this feedback is associated with rating: enum: - thumbs_up - thumbs_down type: string description: The feedback rating indicating user satisfaction description: type: string description: >- Optional detailed feedback description providing additional context or explanation model: type: string description: The model that produced the rated output. created_at: type: string format: date-time x-native-type: date description: Timestamp when the underlying output was created updated_at: type: string format: date-time x-native-type: date description: Timestamp when the underlying output record was last updated required: - id - model - created_at - updated_at description: >- Feedback entry in a list, including the model that produced the rated output. description: >- Array of feedback entries ordered by creation date of the underlying request. first_id: type: string description: >- The ID of the first feedback entry in the current page. Used as a reference point for pagination. last_id: type: string description: >- The ID of the last feedback entry in the current page. Used as a cursor for fetching the next page. has_more: type: boolean description: >- Indicates whether there are more feedback entries available beyond the current page. True if additional pages exist. required: - object - data - has_more description: >- Paginated list object containing feedback entries with cursor-based pagination metadata. 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: `. ````