mlflow/mlflow

[FR] Support search_traces() API in TypeScript SDK

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#19,513 建立於 2025年12月19日

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area/tracingdomain/genaienhancementhelp wanted

描述

Proposal Summary

Currently, the mlflow.search_traces() API is only supported in the Python SDK. We should have equivalent in the TypeScript SDK that simply hits the same backend REST API.

What machine learning domain(s) is this feature request about?

  • domain/genai: LLMs, Agents, and other GenAI-related use cases
  • domain/classical-ml: Traditional machine learning, such as linear regression.
  • domain/deep-learning: Deep learning and neural networks.
  • domain/platform: MLflow platform foundation, not specific to a particular machine learning domain.

What area(s) of MLflow is this feature request about?

  • area/tracking: Tracking Service, tracking client APIs, autologging
  • area/model-registry: Model Registry service, APIs, and the fluent client calls for Model Registry
  • area/scoring: MLflow model serving, deployment tools, Spark UDFs
  • area/evaluation: MLflow model evaluation features, evaluation metrics, and evaluation workflows
  • area/prompt: MLflow prompt engineering features, prompt templates, and prompt management
  • area/tracing: MLflow Tracing features, tracing APIs, and LLM tracing functionality
  • area/gateway: MLflow AI Gateway client APIs, server, and third-party integrations
  • area/projects: MLproject format, project running backends
  • area/uiux: Front-end, user experience, plotting
  • area/docs: MLflow documentation pages

貢獻者指南

技術棧
typescript
領域
apiobservability
議題類型
feature
難度面向新貢獻者的預計實作難度，1 表示很小改動，5 表示專家級工作。
3
預計時間有經驗貢獻者完成調查、實作、測試並準備 pull request 的粗略時間範圍。
half day
活動狀態議題目前的可參與程度：新鮮、活躍、陳舊、阻塞或等待維護者輸入。
fresh
清晰度議題是否清楚說明預期改動、驗收標準和下一步。
clear
前置要求
Familiarity with mlflow TypeScript SDKUnderstanding of REST API basics
新手友善度1-100 的估計分數，表示該議題對首次貢獻者的友善程度。
60
研究方向
Examine the existing `search traces()` implementation in the Python SDK to understand the expected input parameters and output format. Then review the TypeScript SDK's existing API client structure, particularly how it makes HTTP requests to the MLflow backend. Look for similar search methods (e.g., search experiments) as a template. The issue states the TypeScript SDK should hit the same backend REST API, so identify the appropriate endpoint and payload from the Python client code or REST API documentation.