diff --git a/README.md b/README.md index d1f06ac..6de9b99 100644 --- a/README.md +++ b/README.md @@ -1,18 +1,24 @@ + +> [!NOTE] +> 本文档由 WeHub 基于上游 README 翻译整理，属于社区翻译，非官方中文文档。 +> [English](./README.en.md) · [原始项目](https://github.com/mlflow/mlflow) · [上游 README](https://github.com/mlflow/mlflow/blob/HEAD/README.md) +> 原作者、版权与许可证归属以原始项目及本仓库 LICENSE 文件为准。 +

MLflow logo

-

The Open Source AI Engineering Platform for Agents, LLMs & Models

+

面向智能体、LLM 与模型的开源 AI 工程平台

-MLflow is the largest open source **AI engineering platform for agents, LLMs, and ML models**. MLflow enables teams of all sizes to [debug](https://mlflow.org/llm-tracing), -[evaluate](https://mlflow.org/llm-evaluation), [monitor](https://mlflow.org/ai-monitoring), and [optimize](https://mlflow.org/prompt-optimization) production-quality AI applications while -controlling costs and managing access to models and data. With over **60 million monthly downloads**, -thousands of organizations rely on MLflow each day to ship AI to production with confidence. +MLflow 是规模最大的开源**面向智能体、LLM 和 ML 模型的 AI 工程平台**。MLflow 使各种规模的团队能够[调试](https://mlflow.org/llm-tracing), +[评估](https://mlflow.org/llm-evaluation), [监控](https://mlflow.org/ai-monitoring), 并[优化](https://mlflow.org/prompt-optimization) 生产级 AI 应用，同时 +控制成本并管理对模型和数据的访问。凭借每月超过 **6000 万次下载**， +每天有数千家组织依赖 MLflow 充满信心地将 AI 交付到生产环境。 -MLflow's comprehensive feature set for agents and LLM applications includes production-grade [observability](https://mlflow.org/docs/latest/genai/tracing), [evaluation](https://mlflow.org/docs/latest/genai/eval-monitor), -[prompt management](https://mlflow.org/docs/latest/genai/prompt-registry), [prompt optimization](https://mlflow.org/prompt-optimization) and an [AI Gateway](https://mlflow.org/docs/latest/genai/governance/ai-gateway) for managing costs and model access. -Learn more at [MLflow for LLMs and Agents](https://mlflow.org/docs/latest/genai). +MLflow 面向智能体和 LLM 应用的全面功能集包括生产级[可观测性](https://mlflow.org/docs/latest/genai/tracing), [评估](https://mlflow.org/docs/latest/genai/eval-monitor), +[提示词管理](https://mlflow.org/docs/latest/genai/prompt-registry), [提示词优化](https://mlflow.org/prompt-optimization) 以及用于管理成本和模型访问的 [AI 网关](https://mlflow.org/docs/latest/genai/governance/ai-gateway)。 +了解更多请参阅 [面向 LLM 与智能体的 MLflow](https://mlflow.org/docs/latest/genai).
@@ -21,45 +27,45 @@ Learn more at [MLflow for LLMs and Agents](https://mlflow.org/docs/latest/genai) [![License](https://img.shields.io/github/license/mlflow/mlflow)](https://github.com/mlflow/mlflow/blob/master/LICENSE.txt) follow on X(Twitter) + alt="在 X（Twitter）上关注"> follow on LinkedIn + alt="在 LinkedIn 上关注"> [![Ask DeepWiki](https://deepwiki.com/badge.svg)](https://deepwiki.com/mlflow/mlflow)
- Website · - Try Demo · - Docs · - News · - Events + 官网 · + 试用演示 · + 文档 · + 新闻 · + 活动

-## Get Started in 3 Simple Steps +## 三步即可上手 -From zero to full-stack LLMOps in minutes. No complex setup or major code changes required. [Get Started →](https://mlflow.org/docs/latest/genai/tracing/quickstart/) +几分钟内从零搭建完整 LLMOps 技术栈。无需复杂配置或大规模代码改动。[立即上手 →](https://mlflow.org/docs/latest/genai/tracing/quickstart/) -> **Fastest start — set up tracing with our CLI** +> **最快上手 — 使用 CLI 设置追踪（tracing）** > > ```bash > uvx mlflow@latest agent setup > ``` > -> One command installs the MLflow skills and launches your coding agent of choice to add tracing to your app. Prefer to wire it up yourself? Follow the three steps below. +> 一条命令即可安装 MLflow 技能，并启动你选择的编程智能体，为应用添加追踪。想自己动手接入？请按照以下三个步骤操作。 -**1. Start MLflow Server** +**1. 启动 MLflow Server** ```bash uvx mlflow server ``` -**2. Enable Logging** +**2. 启用日志记录** ```python import mlflow @@ -68,7 +74,7 @@ mlflow.set_tracking_uri("http://localhost:5000") mlflow.openai.autolog() ``` -**3. Run Your Code** +**3. 运行你的代码** ```python from openai import OpenAI @@ -80,11 +86,11 @@ client.responses.create( ) ``` -Explore traces and metrics in the MLflow UI at `http://localhost:5000`. +在 `http://localhost:5000` 的 MLflow UI 中探索追踪和指标。 -## LLMs & Agents +## LLM 与智能体 -MLflow provides everything you need to build, debug, evaluate, and deploy production-quality LLM applications and AI agents. Supports Python, TypeScript/JavaScript, Java and any other programming language. MLflow also natively integrates with [OpenTelemetry](https://opentelemetry.io/) and MCP. +MLflow 提供构建、调试、评估和部署生产级 LLM 应用与 AI 智能体所需的一切。支持 Python、TypeScript/JavaScript、Java 及任何其他编程语言。MLflow 还与 [OpenTelemetry](https://opentelemetry.io/) 和 MCP 原生集成。 @@ -94,10 +100,10 @@ MLflow provides everything you need to build, debug, evaluate, and deploy produc
Observability

-
Capture complete traces of your LLM applications and agents for deep behavioral insights. Built on OpenTelemetry, supporting any LLM provider and agent framework. Monitor production quality, costs, and safety.

- Getting Started → +
捕获 LLM 应用和智能体的完整追踪，以深入洞察行为。基于 OpenTelemetry 构建，支持任何 LLM 提供商和智能体框架。监控生产质量、成本与安全性。

+ 入门指南 →
- Try Demo → + 试用演示 →

@@ -107,10 +113,10 @@ MLflow provides everything you need to build, debug, evaluate, and deploy produc
Evaluation

-
Run systematic evaluations, track quality metrics over time, and catch regressions before they reach production. Choose from 50+ built-in metrics and LLM judges, or define your own.

- Getting Started → +
运行系统化评估，随时间跟踪质量指标，在回归进入生产环境之前及时发现。可从 50 多种内置指标和 LLM 评判器中选择，或自定义指标。

+ 入门指南 →
- Try Demo → + 试用演示 →

@@ -122,10 +128,10 @@ MLflow provides everything you need to build, debug, evaluate, and deploy produc
Prompts & Optimization

-
Version, test, and deploy prompts with full lineage tracking. Automatically optimize prompts with state-of-the-art algorithms to improve performance.

- Getting Started → +
对提示词进行版本管理、测试和部署，并完整追踪血缘关系。自动优化提示词，采用前沿算法提升性能。

+ 入门指南 →
- Try Demo → + 试用演示 →

@@ -135,28 +141,28 @@ MLflow provides everything you need to build, debug, evaluate, and deploy produc
AI Gateway

-
Unified API gateway for all LLM providers. Route requests, manage rate limits, handle fallbacks, and control costs through an OpenAI-compatible interface with built-in credential management, guardrails and traffic splitting for A/B testing.

- Getting Started → +
面向所有 LLM 提供商的统一 API 网关。通过兼容 OpenAI 的接口路由请求、管理速率限制、处理故障转移并控制成本，内置凭据管理、防护栏（guardrails）以及用于 A/B 测试的流量分流。

+ 入门指南 →

-## Model Training +## 模型训练 -For machine learning and deep learning model development, MLflow provides a full suite of tools to manage the ML lifecycle: +对于机器学习和深度学习模型开发，MLflow 提供全套工具来管理 ML 生命周期： -- [**Experiment Tracking**](https://mlflow.org/docs/latest/ml/tracking/) — Track models, parameters, metrics, and evaluation results across experiments -- [**Model Evaluation**](https://mlflow.org/docs/latest/ml/evaluation/) — Automated evaluation tools integrated with experiment tracking -- [**Model Registry**](https://mlflow.org/docs/latest/ml/model-registry/) — Collaboratively manage the full lifecycle of ML models -- [**Deployment**](https://mlflow.org/docs/latest/ml/deployment/) — Deploy models to batch and real-time scoring on Docker, Kubernetes, Azure ML, AWS SageMaker, and more +- [**实验跟踪（Experiment Tracking）**](https://mlflow.org/docs/latest/ml/tracking/) — 跨实验跟踪模型、参数、指标和评估结果 +- [**模型评估（Model Evaluation）**](https://mlflow.org/docs/latest/ml/evaluation/) — 与实验跟踪集成的自动化评估工具 +- [**模型注册表（Model Registry）**](https://mlflow.org/docs/latest/ml/model-registry/) — 协作管理 ML 模型的完整生命周期 +- [**部署（Deployment）**](https://mlflow.org/docs/latest/ml/deployment/) — 将模型部署到 Docker、Kubernetes、Azure ML、AWS SageMaker 等平台，支持批处理和实时评分 -Learn more at [MLflow for Model Training](https://mlflow.org/docs/latest/ml). +了解更多请参阅 [面向模型训练的 MLflow](https://mlflow.org/docs/latest/ml). -## Integrations +## 集成 -MLflow supports all agent frameworks, LLM providers, tools, and programming languages. We offer one-line automatic tracing for more than 60 frameworks. See the [full integrations list](https://mlflow.org/docs/latest/genai/tracing/integrations/). +MLflow 支持所有智能体（agent）框架、大语言模型（LLM）提供商、工具和编程语言。我们为 60 多个框架提供一行代码即可启用的自动追踪（tracing）。请参阅[完整集成列表](https://mlflow.org/docs/latest/genai/tracing/integrations/). ### OpenTelemetry @@ -166,7 +172,7 @@ MLflow supports all agent frameworks, LLM providers, tools, and programming lang -### Agent Frameworks (Python) +### 智能体框架（Python） @@ -202,7 +208,7 @@ MLflow supports all agent frameworks, LLM providers, tools, and programming lang
-### Agent Frameworks (TypeScript) +### 智能体框架（TypeScript） @@ -214,7 +220,7 @@ MLflow supports all agent frameworks, LLM providers, tools, and programming lang
-### Agent Frameworks (Java) +### 智能体框架（Java） @@ -223,7 +229,7 @@ MLflow supports all agent frameworks, LLM providers, tools, and programming lang
-### Model Providers +### 模型提供商 @@ -252,7 +258,7 @@ MLflow supports all agent frameworks, LLM providers, tools, and programming lang
-### Gateways +### 网关 @@ -270,7 +276,7 @@ MLflow supports all agent frameworks, LLM providers, tools, and programming lang
-### Tools & No-Code +### 工具与无代码（No-Code） @@ -286,9 +292,9 @@ MLflow supports all agent frameworks, LLM providers, tools, and programming lang
-## Hosting MLflow +## 托管 MLflow -MLflow can be used in a variety of environments, including your local environment, on-premises clusters, cloud platforms, and managed services. Being an open-source platform, MLflow is **vendor-neutral** — whether you're building AI agents, LLM applications, or ML models, you have access to MLflow's core capabilities. +MLflow 可用于多种环境，包括本地环境、本地部署（on-premises）集群、云平台以及托管服务。作为一款开源平台，MLflow **厂商中立（vendor-neutral）**——无论你是在构建 AI 智能体、LLM 应用还是 ML 模型，都能使用 MLflow 的核心能力。 @@ -300,42 +306,41 @@ MLflow can be used in a variety of environments, including your local environmen
-## 💭 Support +## 💭 支持 -- For help or questions about MLflow usage (e.g. "how do I do X?") visit the [documentation](https://mlflow.org/docs/latest). -- In the documentation, you can ask the question to our AI-powered chat bot. Click on the **"Ask AI"** button at the right bottom. -- Join the [virtual events](https://lu.ma/mlflow?k=c) like office hours and meetups. -- To report a bug, file a documentation issue, or submit a feature request, please [open a GitHub issue](https://github.com/mlflow/mlflow/issues/new/choose). -- For release announcements and other discussions, please subscribe to our mailing list (mlflow-users@googlegroups.com) - or join us on [Slack](https://mlflow.org/slack). +- 如需 MLflow 使用方面的帮助或提问（例如「如何做 X？」），请访问[文档](https://mlflow.org/docs/latest). +- 在文档中，你可以向我们的 AI 聊天机器人提问。点击右下角的 **"Ask AI"** 按钮。 +- 参加[线上活动](https://lu.ma/mlflow?k=c)，例如 Office Hours 和聚会（meetup）。 +- 如需报告 bug、提交文档问题或提出功能请求，请[在 GitHub 上提交 issue](https://github.com/mlflow/mlflow/issues/new/choose). +- 如需接收版本发布公告并参与其他讨论，请订阅我们的邮件列表（mlflow-users@googlegroups.com），或在 [Slack](https://mlflow.org/slack). 上加入我们。 -## 🤝 Contributing +## 🤝 贡献 -We happily welcome contributions to MLflow! +我们诚挚欢迎为 MLflow 做出贡献！ -- Submit [bug reports](https://github.com/mlflow/mlflow/issues/new?template=bug_report_template.yaml) and [feature requests](https://github.com/mlflow/mlflow/issues/new?template=feature_request_template.yaml) -- Contribute for [good-first-issues](https://github.com/mlflow/mlflow/issues?q=is%3Aissue+is%3Aopen+label%3A%22good+first+issue%22) and [help-wanted](https://github.com/mlflow/mlflow/issues?q=is%3Aissue+is%3Aopen+label%3A%22help+wanted%22) -- Writing about MLflow and sharing your experience +- 提交 [bug 报告](https://github.com/mlflow/mlflow/issues/new?template=bug_report_template.yaml) 和 [功能请求](https://github.com/mlflow/mlflow/issues/new?template=feature_request_template.yaml) +- 参与 [good-first-issues](https://github.com/mlflow/mlflow/issues?q=is%3Aissue+is%3Aopen+label%3A%22good+first+issue%22) 和 [help-wanted](https://github.com/mlflow/mlflow/issues?q=is%3Aissue+is%3Aopen+label%3A%22help+wanted%22) +- 撰写关于 MLflow 的文章并分享你的使用经验 -Please see our [contribution guide](CONTRIBUTING.md) to learn more about contributing to MLflow. +请参阅我们的[贡献指南](CONTRIBUTING.md)，了解更多关于为 MLflow 做出贡献的信息。 -## ⭐️ Star History +## ⭐️ Star 历史 - Star History Chart + Star 历史图表 -## ✏️ Citation +## ✏️ 引用 -If you use MLflow in your research, please cite it using the "Cite this repository" button at the top of the [GitHub repository page](https://github.com/mlflow/mlflow), which will provide you with citation formats including APA and BibTeX. +如果你在研究中使用 MLflow，请通过 [GitHub 仓库页面](https://github.com/mlflow/mlflow), 顶部的 "Cite this repository" 按钮进行引用，该按钮会提供包括 APA 和 BibTeX 在内的引用格式。 -## 👥 Core Members +## 👥 核心成员 -MLflow is currently maintained by the following core members with significant contributions from hundreds of exceptionally talented community members. +MLflow 目前由以下核心成员维护，并得到了数百位才华横溢的社区成员的重要贡献。 - [Ben Wilson](https://github.com/BenWilson2) - [Corey Zumar](https://github.com/dbczumar)