> ## 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. # Get an eval sample trajectory > Returns one coding-agent trial's session — the steps the agent took, verbatim in the harness's interchange format (see `schema_version`, e.g. `ATIF-v1.7`). Deliberately not part of the samples list: a trajectory averages ~92 KB and that list pages up to 500 rows. Sample indices are unique per (task, model), not per run, so pass `task_id` and/or `model` when the run covers more than one; an index that matches several trials returns 400 rather than guessing, and never falls back to another trial's session. Returns 404 when the sample does not exist or recorded no trajectory. ## OpenAPI ````yaml https://apigw.mka1.com/speakeasy.json get /api/v1/llm/evals/runs/{run_id}/samples/{sample_index}/trajectory 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: Session x-displayName: Session - 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: schema-3_other x-displayName: other - 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 Volumes x-displayName: Compute Volumes - name: Compute Pricing x-displayName: Compute Pricing - 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/evals/runs/{run_id}/samples/{sample_index}/trajectory: get: tags: - Evals summary: Get an eval sample trajectory description: >- Returns one coding-agent trial's session — the steps the agent took, verbatim in the harness's interchange format (see `schema_version`, e.g. `ATIF-v1.7`). Deliberately not part of the samples list: a trajectory averages ~92 KB and that list pages up to 500 rows. Sample indices are unique per (task, model), not per run, so pass `task_id` and/or `model` when the run covers more than one; an index that matches several trials returns 400 rather than guessing, and never falls back to another trial's session. Returns 404 when the sample does not exist or recorded no trajectory. operationId: getEvalSampleTrajectory parameters: - name: run_id in: path required: true schema: type: string example: eval_run_aa87e2b1112a455b8deabed784372198 - name: sample_index in: path required: true schema: type: integer minimum: 0 maximum: 2147483647 example: 0 - name: task_id in: query schema: type: string description: >- Disambiguate the sample index, which is unique per (task, model) and not per run. Required when the index matches trials from more than one task. allowEmptyValue: true - name: model in: query schema: type: string description: >- Disambiguate the sample index when the run covers more than one model. allowEmptyValue: true - 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: type: object properties: object: const: eval.sample.trajectory run_id: type: string sample_index: type: integer minimum: -9007199254740991 maximum: 9007199254740991 task_id: type: string model: type: string schema_version: type: string description: >- Interchange format of `steps`, e.g. `ATIF-v1.7`. Read it before assuming a step shape. step_count: type: integer minimum: -9007199254740991 maximum: 9007199254740991 size_bytes: type: integer minimum: -9007199254740991 maximum: 9007199254740991 steps: type: array items: anyOf: - {} - type: 'null' description: >- Steps exactly as the harness wrote them — reasoning_content, tool_calls[{ function_name, arguments }], observation.results[{ source_call_id, content }]. Passed through unvalidated so a harness upgrade does not need a gateway release. logs: anyOf: - type: object propertyNames: type: string additionalProperties: type: string - type: 'null' description: >- Bounded tails of the trial's log files, keyed by their path in the trial dir (`trial.log`, `verifier/test-stdout.txt`, ...). Null for trials recorded before logs were captured. required: - object - run_id - sample_index - task_id - model - schema_version - step_count - size_bytes - steps - logs example: object: eval.sample.trajectory run_id: eval_run_aa87e2b1112a455b8deabed784372198 sample_index: 0 task_id: fix-permissions model: meetkai:functionary-urdu-mini-pak schema_version: ATIF-v1.7 step_count: 42 size_bytes: 94208 steps: - step_id: 1 source: agent reasoning_content: >- The test fails because the fixture directory is not writable. tool_calls: - function_name: bash arguments: command: ls -la /workdir security: - bearerAuth: [] x-codeSamples: - lang: python label: Python (SDK) source: |- from meetkai_mka1 import SDK with SDK( bearer_auth="", ) as sdk: res = sdk.llm.evals.get_sample_trajectory(run_id="eval_run_aa87e2b1112a455b8deabed784372198", sample_index=0) # 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.evals.getSampleTrajectory({ runId: "eval_run_aa87e2b1112a455b8deabed784372198", sampleIndex: 0, }); 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: ""); GetEvalSampleTrajectoryRequest req = new GetEvalSampleTrajectoryRequest() { RunId = "eval_run_aa87e2b1112a455b8deabed784372198", SampleIndex = 0, }; var res = await sdk.Llm.Evals.GetSampleTrajectoryAsync(req); // handle response components: 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: `. ````