> ## 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. # Search a vector store > Performs semantic search within a vector store to find the most relevant document chunks for a query. ## OpenAPI ````yaml https://apigw.mka1.com/speakeasy.json post /api/v1/llm/vector_stores/{vector_store_id}/search 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/vector_stores/{vector_store_id}/search: post: tags: - Vector Stores summary: Search a vector store description: >- Performs semantic search within a vector store to find the most relevant document chunks for a query. operationId: searchVectorStore parameters: - name: vector_store_id in: path required: true schema: type: string description: The ID of the vector store to search. example: vs_abc123 - 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/SearchVectorStoreRequest' example: query: How do I reset my password? max_num_results: 5 responses: '200': description: OK content: application/json: schema: $ref: '#/components/schemas/VectorStoreSearchResults' example: object: vector_store.search_results.page search_query: How do I reset my password? data: - file_id: file-abc123 filename: user-guide.pdf score: 0.92 content: - type: text text: >- To reset your password, navigate to Settings > Security > Reset Password... has_more: false next_page: null security: - bearerAuth: [] x-codeSamples: - lang: python label: Python (SDK) source: |- from meetkai_mka1 import SDK with SDK( bearer_auth="", ) as sdk: res = sdk.llm.vector_stores.search(vector_store_id="vs_abc123", query="How do I reset my password?", max_num_results=5, rewrite_query=False) # 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.vectorStores.search({ vectorStoreId: "vs_abc123", searchVectorStoreRequest: { query: "How do I reset my password?", maxNumResults: 5, }, }); 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.VectorStores.SearchAsync( vectorStoreId: "vs_abc123", body: new MeetKai.MKA1.Types.Components.SearchVectorStoreRequest() { Query = Query.CreateStr( "How do I reset my password?" ), MaxNumResults = 5, } ); // handle response components: schemas: SearchVectorStoreRequest: type: object properties: query: anyOf: - type: string - type: array items: type: string description: A query string for a search, or an array of query strings. filters: $ref: '#/components/schemas/Filter' description: >- A filter to apply based on file attributes (evaluated against each file's current attributes). A missing attribute key fails every comparison, including ne/nin; gt/gte/lt/lte are numeric-only; in/nin take an array value. max_num_results: type: integer minimum: 1 maximum: 50 default: 10 description: >- The maximum number of results to return. This number should be between 1 and 50 inclusive. ranking_options: type: object properties: ranker: enum: - auto - none type: string default: auto description: >- Enable re-ranking; set to 'none' to disable, which can help reduce latency. score_threshold: type: number default: 0 description: Minimum score threshold for search results. description: Ranking options for search. rewrite_query: type: boolean default: false description: Whether to rewrite the natural language query for vector search. required: - query description: Request body for searching a vector store. examples: - query: How do I reset my password? max_num_results: 5 VectorStoreSearchResults: type: object properties: object: const: vector_store.search_results.page description: The object type, which is always 'vector_store.search_results.page'. search_query: type: string description: The query that was used for the search. data: type: array items: $ref: '#/components/schemas/VectorSearchResult' description: Array of search results. has_more: type: boolean description: Whether there are more results available. next_page: anyOf: - type: string - type: 'null' description: Cursor for the next page of results, or null if no more results. required: - object - search_query - data - has_more - next_page description: A page of search results from the vector store. examples: - object: vector_store.search_results.page search_query: How do I reset my password? data: - file_id: file-abc123 filename: user-guide.pdf score: 0.92 content: - type: text text: >- To reset your password, navigate to Settings > Security > Reset Password... has_more: false next_page: null Filter: anyOf: - type: object properties: type: enum: - eq - ne - gt - gte - lt - lte - in - nin type: string description: >- Comparison operator: eq (equals), ne (not equal), gt (greater than), gte (greater than or equal), lt (less than), lte (less than or equal), in (in), nin (not in). key: type: string description: The key to compare against the value. value: anyOf: - type: string - type: number - type: boolean - type: array items: anyOf: - type: string - type: number - type: boolean description: >- The value to compare against the attribute key; supports string, number, boolean, or array types. required: - type - key - value description: >- A filter used to compare a specified attribute key to a given value using a defined comparison operation. - type: object properties: type: enum: - and - or type: string description: 'Type of operation: ''and'' or ''or''.' filters: type: array items: anyOf: - type: object properties: type: enum: - eq - ne - gt - gte - lt - lte - in - nin type: string description: >- Comparison operator: eq (equals), ne (not equal), gt (greater than), gte (greater than or equal), lt (less than), lte (less than or equal), in (in), nin (not in). key: type: string description: The key to compare against the value. value: anyOf: - type: string - type: number - type: boolean - type: array items: anyOf: - type: string - type: number - type: boolean description: >- The value to compare against the attribute key; supports string, number, boolean, or array types. required: - type - key - value description: >- A filter used to compare a specified attribute key to a given value using a defined comparison operation. - type: object properties: type: enum: - and - or type: string description: 'Type of operation: ''and'' or ''or''.' filters: type: array items: anyOf: - type: object properties: type: enum: - eq - ne - gt - gte - lt - lte - in - nin type: string description: >- Comparison operator: eq (equals), ne (not equal), gt (greater than), gte (greater than or equal), lt (less than), lte (less than or equal), in (in), nin (not in). key: type: string description: The key to compare against the value. value: anyOf: - type: string - type: number - type: boolean - type: array items: anyOf: - type: string - type: number - type: boolean description: >- The value to compare against the attribute key; supports string, number, boolean, or array types. required: - type - key - value description: >- A filter used to compare a specified attribute key to a given value using a defined comparison operation. - {} description: >- Array of filters to combine. Items can be ComparisonFilter or CompoundFilter. required: - type - filters description: Combine multiple filters using 'and' or 'or'. description: >- Array of filters to combine. Items can be ComparisonFilter or CompoundFilter. required: - type - filters description: Combine multiple filters using 'and' or 'or'. VectorSearchResult: type: object properties: file_id: type: string description: The ID of the file containing this result. filename: type: string description: The name of the file. score: type: number description: The relevance score of this result. attributes: type: object propertyNames: type: string additionalProperties: anyOf: - type: string - type: boolean - type: number description: File attributes. content: type: array items: $ref: '#/components/schemas/VectorSearchResultContent' description: Array of content items. required: - file_id - filename - score - content description: A single search result from a vector store search. VectorSearchResultContent: type: object properties: type: const: text description: The content type identifier for text content. text: type: string description: The text content of the search result. required: - type - text description: Content item in a search result. 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: `. ````