Agent 开发框架

Opik|LLM与AI Agent可观测、评测及提示管理的开源平台

Opik

Opik 是 Apache-2.0 许可的开源 LLM 可观测与评测平台,支持 AI Agent 链路追踪、数据集实验、LLM-as-a-Judge 评测与生产监控,可云端或自托管部署。

获取与使用

需要部署

按官方资料自行安装或部署

使用难度待核验
国内可用性待核验

2026-11-09 更新 · 本站尚未实测

项目介绍

Agent 开发框架 · 2026-11-09 更新 · 本站尚未实测

Opik 由 Comet 开发,README 定位为“Open-Source LLM Observability, Evaluation & AI Agent Tracing”,即面向 LLM 应用与 AI Agent 的开源可观测、评测与链路追踪平台。仓库包含服务端后端、Web 应用、追踪、数据集、实验、评测、提示管理与在线评测等组件,README 声明这些均以 Apache-2.0 许可发布,可自托管完整平台。

需要区分:Opik 本身是一个可自托管部署的平台与 SDK 体系,并非单个可下载的 Agent 或工作流文件;它另外提供 opik-mcp 供编码助手接入。

核心能力

点击能力名称查看输入、输出和原文依据。

  • Agent 追踪与可观测:追踪 LLM 调用、会话日志与 Agent 活动,为多步 Agent 与工具调用提供完整链路树,并可通过 SDK 或 UI 为 trace/span 打反馈分。
  • LLM 评测:支持数据集、实验与 LLM-as-a-Judge 指标,用于幻觉检测、内容审核与 RAG 评估(Answer Relevance、Context Precision 等)。
  • 提示与 Agent 优化:README 提到 Opik Agent Optimizer SDK 及 Prompt Playground 用于尝试提示与模型。
  • 生产监控:仪表盘、在线评测规则,README 称设计上可承载每日 4000 万以上 trace 规模。
  • CI/CD 评测:提供 PyTest 集成,在每次提交时测试 LLM 流水线。
  • 集成与协议:官方 SDK 覆盖 Python 与 TypeScript,并提供 OpenTelemetry 支持;已列出大量框架集成(如 LangChain、LangGraph、LlamaIndex、CrewAI、AutoGen、Dify、Flowise、n8n、DeepSeek、Amazon Bedrock、Google Gemini 等,完整列表以 README 与文档为准)。
  • 编码助手接入:提供 MCP Server(opik-mcp),可由 Claude Code、Cursor、VS Code 等驱动查看 trace、打分与运行评测。

实际应用场景

适用场景

  • 构建 LLM Agent 或 RAG 应用的团队,需要调试多步调用与工具执行链路。
  • 需要把评测纳入 CI/CD、对每次提交做回归测试的工程团队。
  • 希望在自有基础设施内部署可观测平台、不希望数据外发或走企业销售流程的组织。
  • 在生产环境监控反馈分、trace 量与 token 使用,并用在线评测规则发现问题。

安装与接入

Python SDK 快速开始(README 原文命令):

pip install opik
opik configure

也可用 uv pip install opik。opik configure 会要求填写自托管服务地址,或 Comet.com 的 API Key 与工作区;也可在代码中调用 opik.configure(use_local=True) 连接本地自托管实例。随后用 @track 装饰器包裹函数即可记录 trace(含嵌套调用)。

编码助手 MCP 接入(README 原文,需 uv、无需 SDK):

uvx opik mcp configure

该命令同时处理自托管部署;README 给出的 Cursor / VS Code 徽章与 npx add-mcp 回退方式指向 Opik Cloud,例如 npx add-mcp https://www.comet.com/opik/api/v1/mcp --name opik-mcp。

自托管(Docker Compose,本地开发与测试):README 给出 Linux/Mac 使用 git clone https://github.com/comet-ml/opik.git、cd opik、./opik.sh;Windows 使用同样克隆步骤后执行 powershell -ExecutionPolicy ByPass -c ".\\opik.ps1"。脚本支持 --infra、--backend、--guardrails、--build、--verify、--stop、--clean 等参数,启动后访问 localhost:5173。生产规模可用 Kubernetes 与 Helm 部署,详见官方文档。

云端:可通过 Comet 账号直接使用 Opik Cloud,无需自建。

使用条件与限制

是否需要部署
需自行准备运行环境,具体要求见正文
是否需要注册
账号和认证要求见正文;未明确说明的项目仍待核验
是否需要 API Key
待核验
费用与额度
费用边界见正文,项目许可不代表模型或托管服务免费
所需权限
待核验
许可证与服务条款
待核验

权限费用与限制

  • README 声明完整平台(含后端)以 Apache-2.0 许可、可免费自托管,无需商业许可。
  • 云端服务与账号套餐的计费、额度与商业条款未在给定资料中说明,费用待向官方核验。
  • 使用云端时需要 Comet API Key 与工作区;自托管需要自行准备数据库、缓存等基础设施(Docker 或 Kubernetes 环境),具体资源要求待核验。
  • LLM-as-a-Judge 等评测需调用外部或自备模型,相关模型 API 费用、可用模型清单与地域可用性待核验。
  • README 提到 --clean 会删除全部 Opik 数据卷,属破坏性操作。
  • 资料未提供完整权限模型、数据驻留与合规认证信息,待核查。

国内使用情况

网友核验 用户经验分享

与站长实测独立,不代表官方认证或本站已实测。

我要核验
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最近核验:暂无有效核验。参与人数按当前项目有效身份去重;不同核验项分别统计,不合并成用户总结果。仅统计审核通过且未过期的记录。

分项统计、有效期与样本量
核验项目有效人数成功 / 部分 / 失败 / 无法判断成功率最近核验 / 有效期
官方网站访问00 / 0 / 0 / 0样本不足暂无 / 7 天
GitHub 仓库访问00 / 0 / 0 / 0样本不足暂无 / 7 天
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国内网络情况00 / 0 / 0 / 0样本不足暂无 / 7 天
国内模型兼容性00 / 0 / 0 / 0样本不足暂无 / 30 天
自定义 API00 / 0 / 0 / 0样本不足暂无 / 30 天
海外服务依赖
00 / 0 / 0 / 0样本不足暂无 / 30 天
海外账号要求
00 / 0 / 0 / 0样本不足暂无 / 30 天
中文界面
00 / 0 / 0 / 0样本不足暂无 / 30 天
客户端兼容性00 / 0 / 0 / 0样本不足暂无 / 30 天
账号及费用信息
00 / 0 / 0 / 0样本不足暂无 / 30 天

成功率 = 成功 ÷(成功 + 部分成功 + 失败);无法判断不计入分母。至少 5 份可判断结果才显示成功率。账号、费用、海外依赖与语言等事实项,成功表示核查结论与资料吻合,具体观察另行统计;不表示免费或没有海外依赖。不同网络、客户端和版本的结果不能直接等同。

最近有效核验

暂无审核通过且未过期的网友核验。欢迎提交真实使用记录。

查看全部有效核验 →

国内实测状态:国内可用性待核验。协议兼容和官方资料说明不等于国内网络可用。

官方网站访问
尚未实测 待核验
GitHub 仓库访问
尚未实测 待核验
官方服务国内连接
尚未实测 待核验
国内网络情况
尚未实测 待核验
国内模型兼容性
尚未实测 待核验
自定义 API
尚未实测 待核验
海外服务依赖
尚未实测 待核验
海外账号要求
尚未实测 待核验
中文界面
尚未实测 待核验
国内最后核验时间
尚未实测

许可与国内使用

仓库 LICENSE 为 Apache License 2.0(Copyright Comet ML, Inc),README 亦明确为 Apache-2.0。该许可覆盖仓库代码;Comet 托管云服务、第三方模型与框架集成各有其自身条款,需分别核验。资料未说明在华部署、网络可达性或国内模型/云服务的适配情况,相关结论待核验;README 列出 DeepSeek、字节 BytePlus 等集成,但不代表国内环境已验证可用。

项目资料与来源

官方网站 ↗

GitHub 仓库 ↗

官方文档 ↗

字段依据与待核验事项

access:来源确认 · pip install opik

project_type:来源确认 · Opik is the open-source LLM observability and evaluation platform for AI agent tracing, LLM evaluation, prompt management, and production monitoring.

原始 README(折叠技术参考)
<div align="center"><b><a href="README.md">English</a> | <a href="readme_CN.md">简体中文</a> | <a href="readme_ES.md">Español</a> | <a href="readme_FR.md">Français</a> | <a href="readme_DE.md">Deutsch</a> | <a href="readme_JA.md">日本語</a></b></div>


<h1 align="center" style="border-bottom: none">
    <div>
        <a href="https://www.comet.com/site/products/opik/?from=llm&utm_source=opik&utm_medium=github&utm_content=header_img&utm_campaign=opik"><picture>
            <source media="(prefers-color-scheme: dark)" srcset="https://raw.githubusercontent.com/comet-ml/opik/refs/heads/main/apps/opik-documentation/documentation/static/img/logo-dark-mode.svg">
            <source media="(prefers-color-scheme: light)" srcset="https://raw.githubusercontent.com/comet-ml/opik/refs/heads/main/apps/opik-documentation/documentation/static/img/opik-logo.svg">
            <img alt="Comet Opik logo" src="https://raw.githubusercontent.com/comet-ml/opik/refs/heads/main/apps/opik-documentation/documentation/static/img/opik-logo.svg" width="200" />
        </picture></a>
        <br>
        Opik: Open-Source LLM Observability, Evaluation & AI Agent Tracing
    </div>
</h1>
<p align="center">
<b>Opik is the open-source LLM observability and evaluation platform for AI agent tracing, LLM evaluation, prompt management, and production monitoring.</b> Built by <a href="https://www.comet.com?from=llm&utm_source=opik&utm_medium=github&utm_content=what_is_opik_link&utm_campaign=opik">Comet</a>. Apache-2.0 licensed, free to self-host the full platform, with 20,000+ GitHub stars.
</p>

<div align="center">

[![Python SDK](https://img.shields.io/pypi/v/opik)](https://pypi.org/project/opik/)
[![License](https://img.shields.io/github/license/comet-ml/opik)](https://github.com/comet-ml/opik/blob/main/LICENSE)
[![Build](https://github.com/comet-ml/opik/actions/workflows/build_apps.yml/badge.svg)](https://github.com/comet-ml/opik/actions/workflows/build_apps.yml)
<!-- [![Quick Start](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/comet-ml/opik/blob/main/apps/opik-documentation/documentation/docs/cookbook/opik_quickstart.ipynb) -->

</div>

<p align="center">
    <a href="https://www.comet.com/site/products/opik/?from=llm&utm_source=opik&utm_medium=github&utm_content=website_button&utm_campaign=opik"><b>Website</b></a> •
    <a href="https://chat.comet.com"><b>Slack Community</b></a> •
    <a href="https://x.com/Cometml"><b>Twitter</b></a> •
    <a href="https://www.comet.com/docs/opik/changelog"><b>Changelog</b></a> •
    <a href="https://www.comet.com/docs/opik/?from=llm&utm_source=opik&utm_medium=github&utm_content=docs_button&utm_campaign=opik"><b>Documentation</b></a>
</p>

<p align="center"><sub>Last updated: 2026-07-17</sub></p>

<div align="center" style="margin-top: 1em; margin-bottom: 1em;">
<a href="#-what-is-opik">🚀 What is Opik?</a> • <a href="#-quick-start">⚡ Quick Start</a> • <a href="#-how-opik-compares">📊 How Does Opik Compare?</a> • <a href="#-frequently-asked-questions">❓ FAQ</a> • <a href="#%EF%B8%8F-opik-server-installation">🛠️ Opik Server Installation</a> • <a href="#-opik-client-sdk">💻 Opik Client SDK</a> • <a href="#-logging-traces-with-integrations">📝 Logging Traces</a><br>
<a href="#-llm-as-a-judge-metrics">🧑‍⚖️ LLM as a Judge</a> • <a href="#-evaluating-your-llm-application">🔍 Evaluating your Application</a> • <a href="#-star-us-on-github">⭐ Star Us</a> • <a href="#-contributing">🤝 Contributing</a>
</div>

<br>

[![Opik platform screenshot (thumbnail)](readme-thumbnail-new.png)](https://www.comet.com/signup?from=llm&utm_source=opik&utm_medium=github&utm_content=readme_banner&utm_campaign=opik)

<a id="-what-is-opik"></a>
## 🚀 What is Opik?

Opik covers the full LLM application lifecycle, from the first trace in development to production monitoring, for teams building LLM apps and AI agents. Key offerings include:

- **AI Agent Tracing & Observability**: Deep tracing of LLM calls, conversation logging, and agent activity, with full trace trees for multi-step agents and tool calls.
- **LLM Evaluation**: Datasets, experiments, and LLM-as-a-judge metrics for hallucination detection, moderation, and RAG assessment.
- **Prompt & Agent Optimization**: The Opik Agent Optimizer SDK to improve prompts and agents.
- **Production-Ready Monitoring**: Scalable dashboards and online evaluation rules.
- **Opik Guardrails**: Features to help you implement safe and responsible AI practices.
- **CI/CD Evaluation**: A PyTest integration to test LLM pipelines on every commit.

<br>

Key capabilities include:

- **Development & Tracing:**
  - Track all LLM calls and traces with detailed context during development and in production ([Quickstart](https://www.comet.com/docs/opik/quickstart/?from=llm&utm_source=opik&utm_medium=github&utm_content=quickstart_link&utm_campaign=opik)).
  - Extensive 3rd-party integrations for easy observability: Seamlessly integrate with a growing list of frameworks, supporting many of the largest and most popular ones natively (including recent additions like **Google ADK**, **Autogen**, and **Flowise AI**). ([Integrations](https://www.comet.com/docs/opik/integrations/overview/?from=llm&utm_source=opik&utm_medium=github&utm_content=integrations_link&utm_campaign=opik))
  - Annotate traces and spans with feedback scores via the [Python SDK](https://www.comet.com/docs/opik/tracing/advanced/annotate_traces/#annotating-traces-and-spans-using-the-sdk?from=llm&utm_source=opik&utm_medium=github&utm_content=sdk_link&utm_campaign=opik) or the [UI](https://www.comet.com/docs/opik/tracing/advanced/annotate_traces/#annotating-traces-through-the-ui?from=llm&utm_source=opik&utm_medium=github&utm_content=ui_link&utm_campaign=opik).
  - Experiment with prompts and models in the [Prompt Playground](https://www.comet.com/docs/opik/development/prompt-playground).

- **Evaluation & Testing**:
  - Automate your LLM application evaluation with [Datasets](https://www.comet.com/docs/opik/evaluation/advanced/manage_datasets/?from=llm&utm_source=opik&utm_medium=github&utm_content=datasets_link&utm_campaign=opik) and [Experiments](https://www.comet.com/docs/opik/evaluation/advanced/evaluate_your_llm/?from=llm&utm_source=opik&utm_medium=github&utm_content=eval_link&utm_campaign=opik).
  - Leverage powerful LLM-as-a-judge metrics for complex tasks like [hallucination detection](https://www.comet.com/docs/opik/evaluation/metrics/hallucination/?from=llm&utm_source=opik&utm_medium=github&utm_content=hallucination_link&utm_campaign=opik), [moderation](https://www.comet.com/docs/opik/evaluation/metrics/moderation/?from=llm&utm_source=opik&utm_medium=github&utm_content=moderation_link&utm_campaign=opik), and RAG assessment ([Answer Relevance](https://www.comet.com/docs/opik/evaluation/metrics/answer_relevance/?from=llm&utm_source=opik&utm_medium=github&utm_content=alex_link&utm_campaign=opik), [Context Precision](https://www.comet.com/docs/opik/evaluation/metrics/context_precision/?from=llm&utm_source=opik&utm_medium=github&utm_content=context_link&utm_campaign=opik)).
  - Integrate evaluations into your CI/CD pipeline with our [PyTest integration](https://www.comet.com/docs/opik/evaluation/overview/?from=llm&utm_source=opik&utm_medium=github&utm_content=pytest_link&utm_campaign=opik).

- **Production Monitoring & Optimization**:
  - Log high volumes of production traces: Opik is designed for scale (40M+ traces/day).
  - Monitor feedback scores, trace counts, and token usage over time in the [Opik Dashboard](https://www.comet.com/docs/opik/tracing/dashboards/production_monitoring/?from=llm&utm_source=opik&utm_medium=github&utm_content=dashboard_link&utm_campaign=opik).
  - Utilize [Online Evaluation Rules](https://www.comet.com/docs/opik/production/online-evaluation/rules/?from=llm&utm_source=opik&utm_medium=github&utm_content=dashboard_link&utm_campaign=opik) with LLM-as-a-Judge metrics to identify production issues.
  - Leverage **Opik Agent Optimizer** and **Opik Guardrails** to continuously improve and secure your LLM applications in production.

**Who it's for:** ML engineers building LLM-powered agents, AI teams moving from prototype to production, and engineering teams that need open-source, self-hostable observability they can run in their own environment.

> **Why open source matters here:** Opik is Apache-2.0 licensed and free to self-host: the full platform, backend included, not just a client SDK. The repository includes the server backend, web application, tracing, datasets, experiments, evaluations, prompt management, online evaluation, and agent optimization components, all under Apache-2.0. You can run LLM observability inside your own infrastructure with no data leaving your environment and no Enterprise sales conversation required.

> [!TIP]
> If you are looking for features that Opik doesn't have today, please raise a new [Feature request](https://github.com/comet-ml/opik/issues/new/choose) 🚀

<br>

<a id="-quick-start"></a>
## ⚡ Quick Start

Install the Python SDK and configure it:

```bash
pip install opik
opik configure
```

Wrap any function with the `@track` decorator to start logging traces:

```python
from opik import track

@track
def my_function(input: str) -> str:
    return input
```

Every call to `my_function` is now logged to Opik, including nested calls, so this works for full agent and pipeline traces, not just single LLM calls. See the [Quickstart guide](https://www.comet.com/docs/opik/quickstart?from=llm&utm_source=opik&utm_medium=github&utm_content=quickstart_hero_link&utm_campaign=opik) for the TypeScript SDK and other setup options.

### Connect your coding agent

Let Claude Code, Cursor, VS Code Copilot, Codex or opencode read your traces, score outputs and run evaluations from chat. One command sets it up. It needs [`uv`](https://docs.astral.sh/uv/) and no SDK:

```bash
uvx opik mcp configure
```

[![Add to Cursor](https://cursor.com/deeplink/mcp-install-dark.svg)](https://cursor.com/en/install-mcp?name=opik-mcp&config=eyJ1cmwiOiJodHRwczovL3d3dy5jb21ldC5jb20vb3Bpay9hcGkvdjEvbWNwIn0%3D)
[![Install in VS Code](https://img.shields.io/badge/VS_Code-Install_Server-0098FF?style=flat-square&logo=visualstudiocode&logoColor=white)](https://insiders.vscode.dev/redirect/mcp/install?name=opik-mcp&config=%7B%22type%22%3A%22http%22%2C%22url%22%3A%22https%3A%2F%2Fwww.comet.com%2Fopik%2Fapi%2Fv1%2Fmcp%22%7D)

The badges and the `add-mcp` fallback below target Opik Cloud; the command above also handles self-hosted deployments. Other MCP clients on Opik Cloud: `npx add-mcp https://www.comet.com/opik/api/v1/mcp --name opik-mcp`. Details, troubleshooting and FAQ are in the [MCP server guide](https://www.comet.com/docs/opik/mcp-server?utm_source=opik&utm_medium=github&utm_content=mcp_quickstart_link&utm_campaign=opik).

<br>

<a id="-how-opik-compares"></a>
## 📊 How Does Opik Compare?

Opik competes in the **LLM observability / AI agent evaluation** category alongside **LangSmith, Arize (Phoenix and Arize AX), Weights & Biases (Weave), Langfuse, and Braintrust**.

| Capability | Opik | LangSmith | Phoenix | Arize AX | Weights & Biases (Weave) | Langfuse | Braintrust |
|---|---|---|---|---|---|---|---|
| Open source | Yes, Apache-2.0 (full platform) | No | Source-available (Elastic License 2.0, not OSI-approved) | No | Open-source SDK/toolkit; self-managed platform requires a commercial license | MIT-licensed core platform; commercial enterprise modules | No |
| Self-hosted deployment | Yes | Enterprise only | Yes | Enterprise only | Enterprise only for Weave itself | Yes, core | Enterprise only |
| Free tier available (cloud or self-hosted) | Yes, both | Yes, cloud | Yes, self-hosted | Yes, cloud | Yes, cloud | Yes, both | Yes, cloud |
| Agent / multi-step tracing | Yes | Yes | Yes | Yes | Yes | Yes | Yes |
| LLM-as-a-judge evaluation | Yes | Yes | Yes | Yes | Yes | Yes | Yes |
| Prompt management | Yes | Yes | Partly | Partly | Partly | Yes | Yes |
| Framework-agnostic | Yes | Partly, built around LangChain | Yes | Yes | Yes | Yes | Yes |

**When teams choose Opik:** Opik's full observability, evaluation, and optimization platform is Apache-2.0 licensed and free to self-host. Unlike closed platforms whose self-hosted deployment requires an Enterprise plan, Opik can be deployed without a commercial license, and it's framework-agnostic so it won't lock you into a single agent ecosystem. See the table above for where self-hosting and licensing differ across alternatives.

<br>

<a id="-frequently-asked-questions"></a>
## ❓ Frequently Asked Questions

#### Is Opik open source?
Opik is licensed under Apache 2.0. Its server, web application, and core observability and evaluation capabilities can be self-hosted without a commercial license.

#### Can I self-host Opik?
Yes. Opik can be deployed locally or in your own infrastructure using the documented self-hosting options.

#### Does Opik support AI agent tracing?
Yes. Opik captures multi-step traces containing LLM calls, tool executions, retrieval steps, and other agent activity.

#### Does Opik support LLM evaluation?
Yes. Opik supports datasets, experiments, code-based metrics, LLM-as-a-judge evaluation, and online evaluation.

#### Is Opik tied to a specific agent framework?
No. Opik is framework-agnostic and supports its SDK, OpenTelemetry, and framework-specific integrations.

<br>

<a id="%EF%B8%8F-opik-server-installation"></a>
## 🛠️ Opik Server Installation

Get your Opik server running in minutes. Choose the option that best suits your needs:

### Option 1: Comet.com Cloud (Easiest & Recommended)

Access Opik instantly without any setup. Ideal for quick starts and hassle-free maintenance.

👉 [Create your free Comet account](https://www.comet.com/signup?from=llm&utm_source=opik&utm_medium=github&utm_content=install_create_link&utm_campaign=opik)

### Option 2: Self-Host Opik for Full Control

Deploy Opik in your own environment. Choose between Docker for local setups or Kubernetes for scalability.

#### Self-Hosting with Docker Compose (for Local Development & Testing)

This is the simplest way to get a local Opik instance running. Note the new `./opik.sh` installation script:

On Linux or Mac Environment:

```bash
# Clone the Opik repository
git clone https://github.com/comet-ml/opik.git

# Navigate to the repository
cd opik

# Start the Opik platform
./opik.sh
```

On Windows Environment:

```powershell
# Clone the Opik repository
git clone https://github.com/comet-ml/opik.git

# Navigate to the repository
cd opik

# Start the Opik platform
powershell -ExecutionPolicy ByPass -c ".\\opik.ps1"
```

**Installation Script Options**

The `opik.sh` and `opik.ps1` scripts support the following options:

```bash
# Start full Opik suite (default behavior)
./opik.sh

# Start only infrastructure services (databases, caches etc.)
./opik.sh --infra

# Start infrastructure + backend services
./opik.sh --backend

# Enable guardrails with any profile
./opik.sh --guardrails # Guardrails with full Opik suite
./opik.sh --backend --guardrails # Guardrails with infrastructure + backend

# Build the containers from source before starting
./opik.sh --build

# Check that all containers are healthy
./opik.sh --verify

# Stop all containers
./opik.sh --stop

# Stop all containers and remove all Opik data volumes
# WARNING: ALL OPIK DATA WILL BE LOST
./opik.sh --clean

# Show all available options
./opik.sh --help
```

Use the `--help` or `--info` options to troubleshoot issues. Dockerfiles now ensure containers run as non-root users for enhanced security. Once all is up and running, you can now visit [localhost:5173](http://localhost:5173) on your browser! For detailed instructions, see the [Local Deployment Guide](https://www.comet.com/docs/opik/self-host/local_deployment?from=llm&utm_source=opik&utm_medium=github&utm_content=self_host_link&utm_campaign=opik).

#### Self-Hosting with Kubernetes & Helm (for Scalable Deployments)

For production or larger-scale self-hosted deployments, Opik can be installed on a Kubernetes cluster using our Helm chart. Click the badge for the full [Kubernetes Installation Guide using Helm](https://www.comet.com/docs/opik/self-host/kubernetes/#kubernetes-installation?from=llm&utm_source=opik&utm_medium=github&utm_content=kubernetes_link&utm_campaign=opik).

[![Kubernetes](https://img.shields.io/badge/Kubernetes-%23326ce5.svg?&logo=kubernetes&logoColor=white)](https://www.comet.com/docs/opik/self-host/kubernetes/#kubernetes-installation?from=llm&utm_source=opik&utm_medium=github&utm_content=kubernetes_link&utm_campaign=opik)

<a id="-opik-client-sdk"></a>
## 💻 Opik Client SDK

Opik provides a suite of client libraries and a REST API to interact with the Opik server. This includes SDKs for Python and TypeScript, plus first-party [OpenTelemetry](https://www.comet.com/docs/opik/tracing/opentelemetry/overview?from=llm&utm_source=opik&utm_medium=github&utm_content=otel_link&utm_campaign=opik) support: any language with an OpenTelemetry SDK — including [Java](https://www.comet.com/docs/opik/integrations/spring-ai?from=llm&utm_source=opik&utm_medium=github&utm_content=java_link&utm_campaign=opik), [Ruby](https://www.comet.com/docs/opik/integrations/opentelemetry-ruby-sdk?from=llm&utm_source=opik&utm_medium=github&utm_content=ruby_link&utm_campaign=opik), and .NET — can send traces to Opik. For detailed API and SDK references, see the [Opik Client Reference Documentation](https://www.comet.com/docs/opik/reference/overview?from=llm&utm_source=opik&utm_medium=github&utm_content=reference_link&utm_campaign=opik).

### Python SDK Quick Start

To get started with the Python SDK:

Install the package:

```bash
# install using pip
pip install opik

# or install with uv
uv pip install opik
```

Configure the python SDK by running the `opik configure` command, which will prompt you for your Opik server address (for self-hosted instances) or your API key and workspace (for Comet.com):

```bash
opik configure
```

> [!TIP]
> You can also call `opik.configure(use_local=True)` from your Python code to configure the SDK to run on a local self-hosted installation, or provide API key and workspace details directly for Comet.com. Refer to the [Python SDK documentation](https://www.comet.com/docs/opik/python-sdk-reference/?from=llm&utm_source=opik&utm_medium=github&utm_content=python_sdk_docs_link&utm_campaign=opik) for more configuration options.

You are now ready to start logging traces using the [Python SDK](https://www.comet.com/docs/opik/python-sdk-reference/?from=llm&utm_source=opik&utm_medium=github&utm_content=sdk_link2&utm_campaign=opik).

<a id="-logging-traces-with-integrations"></a>
### 📝 Logging Traces with Integrations

The easiest way to log traces is to use one of our direct integrations. Opik supports a wide array of frameworks, including recent additions like **Google ADK**, **Autogen**, **AG2**, and **Flowise AI**:

| Integration           | Description                                             | Documentation                                                                                                                                                                  |
| --------------------- | ------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ |
| ADK                   | Log traces for Google Agent Development Kit (ADK)       | [Documentation](https://www.comet.com/docs/opik/integrations/adk?utm_source=opik&utm_medium=github&utm_content=google_adk_link&utm_campaign=opik)                              |
| AG2                   | Log traces for AG2 LLM calls                            | [Documentation](https://www.comet.com/docs/opik/integrations/ag2?utm_source=opik&utm_medium=github&utm_content=ag2_link&utm_campaign=opik)                                     |
| Agent Spec            | Log traces for Agent Spec calls                         | [Documentation](https://www.comet.com/docs/opik/integrations/agentspec?utm_source=opik&utm_medium=github&utm_content=agentspec_link&utm_campaign=opik)                         |
| AIsuite               | Log traces for aisuite LLM calls                        | [Documentation](https://www.comet.com/docs/opik/integrations/aisuite?utm_source=opik&utm_medium=github&utm_content=aisuite_link&utm_campaign=opik)                             |
| Agno                  | Log traces for Agno agent orchestration framework calls | [Documentation](https://www.comet.com/docs/opik/integrations/agno?utm_source=opik&utm_medium=github&utm_content=agno_link&utm_campaign=opik)                                   |
| Anthropic             | Log traces for Anthropic LLM calls                      | [Documentation](https://www.comet.com/docs/opik/integrations/anthropic?utm_source=opik&utm_medium=github&utm_content=anthropic_link&utm_campaign=opik)                         |
| Autogen               | Log traces for Autogen agentic workflows                | [Documentation](https://www.comet.com/docs/opik/integrations/autogen?utm_source=opik&utm_medium=github&utm_content=autogen_link&utm_campaign=opik)                             |
| Bedrock               | Log traces for Amazon Bedrock LLM calls                 | [Documentation](https://www.comet.com/docs/opik/integrations/bedrock?utm_source=opik&utm_medium=github&utm_content=bedrock_link&utm_campaign=opik)                             |
| BeeAI (Python)        | Log traces for BeeAI Python agent framework calls       | [Documentation](https://www.comet.com/docs/opik/integrations/beeai?utm_source=opik&utm_medium=github&utm_content=beeai_link&utm_campaign=opik)                                 |
| BeeAI (TypeScript)    | Log traces for BeeAI TypeScript agent framework calls   | [Documentation](https://www.comet.com/docs/opik/integrations/beeai-typescript?utm_source=opik&utm_medium=github&utm_content=beeai_typescript_link&utm_campaign=opik)           |
| BytePlus              | Log traces for BytePlus LLM calls                       | [Documentation](https://www.comet.com/docs/opik/integrations/byteplus?utm_source=opik&utm_medium=github&utm_content=byteplus_link&utm_campaign=opik)                           |
| Claude Code           | Log traces for Claude Code sessions via the Opik plugin | [GitHub](https://github.com/comet-ml/opik-claude-code-plugin)                                                                                                                 |
| Cloudflare Workers AI | Log traces for Cloudflare Workers AI calls              | [Documentation](https://www.comet.com/docs/opik/integrations/cloudflare-workers-ai?utm_source=opik&utm_medium=github&utm_content=cloudflare_workers_ai_link&utm_campaign=opik) |
| Cohere                | Log traces for Cohere LLM calls                         | [Documentation](https://www.comet.com/docs/opik/integrations/cohere?utm_source=opik&utm_medium=github&utm_content=cohere_link&utm_campaign=opik)                               |
| CrewAI                | Log traces for CrewAI calls                             | [Documentation](https://www.comet.com/docs/opik/integrations/crewai?utm_source=opik&utm_medium=github&utm_content=crewai_link&utm_campaign=opik)                               |
| Cursor                | Log traces for Cursor conversations                     | [Documentation](https://www.comet.com/docs/opik/integrations/cursor?utm_source=opik&utm_medium=github&utm_content=cursor_link&utm_campaign=opik)                               |
| DeepSeek              | Log traces for DeepSeek LLM calls                       | [Documentation](https://www.comet.com/docs/opik/integrations/deepseek?utm_source=opik&utm_medium=github&utm_content=deepseek_link&utm_campaign=opik)                           |
| Dify                  | Log traces for Dify agent runs                          | [Documentation](https://www.comet.com/docs/opik/integrations/dify?utm_source=opik&utm_medium=github&utm_content=dify_link&utm_campaign=opik)                                   |
| DSPY                  | Log traces for DSPy runs                                | [Documentation](https://www.comet.com/docs/opik/integrations/dspy?utm_source=opik&utm_medium=github&utm_content=dspy_link&utm_campaign=opik)                                   |
| Fireworks AI          | Log traces for Fireworks AI LLM calls                   | [Documentation](https://www.comet.com/docs/opik/integrations/fireworks-ai?utm_source=opik&utm_medium=github&utm_content=fireworks_ai_link&utm_campaign=opik)                   |
| Flowise AI            | Log traces for Flowise AI visual LLM builder            | [Documentation](https://www.comet.com/docs/opik/integrations/flowise?utm_source=opik&utm_medium=github&utm_content=flowise_link&utm_campaign=opik)                             |
| Gemini (Python)       | Log traces for Google Gemini LLM calls                  | [Documentation](https://www.comet.com/docs/opik/integrations/gemini?utm_source=opik&utm_medium=github&utm_content=gemini_link&utm_campaign=opik)                               |
| Gemini (TypeScript)   | Log traces for Google Gemini TypeScript SDK calls       | [Documentation](https://www.comet.com/docs/opik/integrations/gemini-typescript?utm_source=opik&utm_medium=github&utm_content=gemini_typescript_link&utm_campaign=opik)         |
| Groq                  | Log traces for Groq LLM calls                           | [Documentation](https://www.comet.com/docs/opik/integrations/groq?utm_source=opik&utm_medium=github&utm_content=groq_link&utm_campaign=opik)                                   |
| Guardrails            | Log traces for Guardrails AI validations                | [Documentation](https://www.comet.com/docs/opik/integrations/guardrails-ai?utm_source=opik&utm_medium=github&utm_content=guardrails_link&utm_campaign=opik)                    |
| Haystack              | Log traces for Haystack calls                           | [Documentation](https://www.comet.com/docs/opik/integrations/haystack?utm_source=opik&utm_medium=github&utm_content=haystack_link&utm_campaign=opik)                           |
| Harbor                | Log traces for Harbor benchmark evaluation trials       | [Documentation](https://www.comet.com/docs/opik/integrations/harbor?utm_source=opik&utm_medium=github&utm_content=harbor_link&utm_campaign=opik)                               |
| Instructor            | Log traces for LLM calls made with Instructor           | [Documentation](https://www.comet.com/docs/opik/integrations/instructor?utm_source=opik&utm_medium=github&utm_content=instructor_link&utm_campaign=opik)                       |
| LangChain (Python)    | Log traces for LangChain LLM calls                      | [Documentation](https://www.comet.com/docs/opik/integrations/langchain?utm_source=opik&utm_medium=github&utm_content=langchain_link&utm_campaign=opik)                         |
| LangChain (JS/TS)     | Log traces for LangChain JavaScript/TypeScript calls    | [Documentation](https://www.comet.com/docs/opik/integrations/langchainjs?utm_source=opik&utm_medium=github&utm_content=langchainjs_link&utm_campaign=opik)                     |
| LangGraph             | Log traces for LangGraph executions                     | [Documentation](https://www.comet.com/docs/opik/integrations/langgraph?utm_source=opik&utm_medium=github&utm_content=langgraph_link&utm_campaign=opik)                         |
| Langflow              | Log traces for Langflow visual AI builder               | [Documentation](https://www.comet.com/docs/opik/integrations/langflow?utm_source=opik&utm_medium=github&utm_content=langflow_link&utm_campaign=opik)                           |
| LiteLLM               | Log traces for LiteLLM model calls                      | [Documentation](https://www.comet.com/docs/opik/integrations/litellm?utm_source=opik&utm_medium=github&utm_content=litellm_link&utm_campaign=opik)                             |
| LiveKit Agents        | Log traces for LiveKit Agents AI agent framework calls  | [Documentation](https://www.comet.com/docs/opik/integrations/livekit?utm_source=opik&utm_medium=github&utm_content=livekit_link&utm_campaign=opik)                             |
| LlamaIndex            | Log traces for LlamaIndex LLM calls                     | [Documentation](https://www.comet.com/docs/opik/integrations/llama_index?utm_source=opik&utm_medium=github&utm_content=llama_index_link&utm_campaign=opik)                     |
| Mastra                | Log traces for Mastra AI workflow framework calls       | [Documentation](https://www.comet.com/docs/opik/integrations/mastra?utm_source=opik&utm_medium=github&utm_content=mastra_link&utm_campaign=opik)                               |
| MCP Server (opik-mcp) | Drive Opik from Claude Code, Cursor, or VS Code via Model Context Protocol | [Documentation](https://www.comet.com/docs/opik/integrations/mcp-server?utm_source=opik&utm_medium=github&utm_content=mcp_server_link&utm_campaign=opik) |
| Microsoft Agent Framework (Python) | Log traces for Microsoft Agent Framework calls | [Documentation](https://www.comet.com/docs/opik/integrations/microsoft-agent-framework?utm_source=opik&utm_medium=github&utm_content=agent_framework_link&utm_campaign=opik)              |
| Microsoft Agent Framework (.NET) | Log traces for Microsoft Agent Framework .NET calls | [Documentation](https://www.comet.com/docs/opik/integrations/microsoft-agent-framework-dotnet?utm_source=opik&utm_medium=github&utm_content=agent_framework_dotnet_link&utm_campaign=opik) |
| Mistral AI            | Log traces for Mistral AI LLM calls                     | [Documentation](https://www.comet.com/docs/opik/integrations/mistral?utm_source=opik&utm_medium=github&utm_content=mistral_link&utm_campaign=opik)                             |
| n8n                   | Log traces for n8n workflow executions                  | [Documentation](https://www.comet.com/docs/opik/integrations/n8n?utm_source=opik&utm_medium=github&utm_content=n8n_link&utm_campaign=opik)                                     |
| Novita AI             | Log traces for Novita AI LLM calls                      | [Documentation](https://www.comet.com/docs/opik/integrations/novita-ai?utm_source=opik&utm_medium=github&utm_content=novita_ai_link&utm_campaign=opik)                         |
| Ollama                | Log traces for Ollama LLM calls                         | [Documentation](https://www.comet.com/docs/opik/integrations/ollama?utm_source=opik&utm_medium=github&utm_content=ollama_link&utm_campaign=opik)                               |
| OpenAI (Python)       | Log traces for OpenAI LLM calls                         | [Documentation](https://www.comet.com/docs/opik/integrations/openai?utm_source=opik&utm_medium=github&utm_content=openai_link&utm_campaign=opik)                               |
| OpenAI (JS/TS)        | Log traces for OpenAI JavaScript/TypeScript calls       | [Documentation](https://www.comet.com/docs/opik/integrations/openai-typescript?utm_source=opik&utm_medium=github&utm_content=openai_typescript_link&utm_campaign=opik)         |
| OpenAI Agents         | Log traces for OpenAI Agents SDK calls                  | [Documentation](https://www.comet.com/docs/opik/integrations/openai_agents?utm_source=opik&utm_medium=github&utm_content=openai_agents_link&utm_campaign=opik)                 |
| OpenClaw              | Log traces for OpenClaw agent runs                  | [Documentation](https://www.comet.com/docs/opik/integrations/openclaw?utm_source=opik&utm_medium=github&utm_content=openclaw_link&utm_campaign=opik) |
| OpenRouter            | Log traces for OpenRouter LLM calls                     | [Documentation](https://www.comet.com/docs/opik/integrations/openrouter?utm_source=opik&utm_medium=github&utm_content=openrouter_link&utm_campaign=opik)                       |
| OpenTelemetry         | Log traces for OpenTelemetry supported calls            | [Documentation](https://www.comet.com/docs/opik/tracing/opentelemetry/overview?utm_source=opik&utm_medium=github&utm_content=opentelemetry_link&utm_campaign=opik)             |
| OpenWebUI             | Log traces for OpenWebUI conversations                  | [Documentation](https://www.comet.com/docs/opik/integrations/openwebui?utm_source=opik&utm_medium=github&utm_content=openwebui_link&utm_campaign=opik)                         |
| Pipecat               | Log traces for Pipecat real-time voice agent calls      | [Documentation](https://www.comet.com/docs/opik/integrations/pipecat?utm_source=opik&utm_medium=github&utm_content=pipecat_link&utm_campaign=opik)                             |
| Predibase             | Log traces for Predibase LLM calls                      | [Documentation](https://www.comet.com/docs/opik/integrations/predibase?utm_source=opik&utm_medium=github&utm_content=predibase_link&utm_campaign=opik)                         |
| Pydantic AI           | Log traces for PydanticAI agent calls                   | [Documentation](https://www.comet.com/docs/opik/integrations/pydantic-ai?utm_source=opik&utm_medium=github&utm_content=pydantic_ai_link&utm_campaign=opik)                     |
| Ragas                 | Log traces for Ragas evaluations                        | [Documentation](https://www.comet.com/docs/opik/integrations/ragas?utm_source=opik&utm_medium=github&utm_content=ragas_link&utm_campaign=opik)                                 |
| Semantic Kernel       | Log traces for Microsoft Semantic Kernel calls          | [Documentation](https://www.comet.com/docs/opik/integrations/semantic-kernel?utm_source=opik&utm_medium=github&utm_content=semantic_kernel_link&utm_campaign=opik)             |
| Smolagents            | Log traces for Smolagents agents                        | [Documentation](https://www.comet.com/docs/opik/integrations/smolagents?utm_source=opik&utm_medium=github&utm_content=smolagents_link&utm_campaign=opik)                       |
| Spring AI             | Log traces for Spring AI framework calls                | [Documentation](https://www.comet.com/docs/opik/integrations/spring-ai?utm_source=opik&utm_medium=github&utm_content=spring_ai_link&utm_campaign=opik)                         |
| Strands Agents        | Log traces for Strands agents calls                     | [Documentation](https://www.comet.com/docs/opik/integrations/strands-agents?utm_source=opik&utm_medium=github&utm_content=strands_agents_link&utm_campaign=opik)               |
| Together AI           | Log traces for Together AI LLM calls                    | [Documentation](https://www.comet.com/docs/opik/integrations/together-ai?utm_source=opik&utm_medium=github&utm_content=together_ai_link&utm_campaign=opik)                     |
| TrueFoundry           | Log traces for TrueFoundry AI Gateway LLM calls         | [Documentation](https://www.comet.com/docs/opik/integrations/truefoundry?utm_source=opik&utm_medium=github&utm_content=truefoundry_link&utm_campaign=opik)                     |
| TypeSafe AI           | Log traces for TypeSafe AI (Jev) System One calls       | [Documentation](https://www.comet.com/docs/opik/integrations/typesafe?utm_source=opik&utm_medium=github&utm_content=typesafe_link&utm_campaign=opik)                           |
| Vercel AI SDK         | Log traces for Vercel AI SDK calls                      | [Documentation](https://www.comet.com/docs/opik/integrations/vercel-ai-sdk?utm_source=opik&utm_medium=github&utm_content=vercel_ai_sdk_link&utm_campaign=opik)                 |
| VoltAgent             | Log traces for VoltAgent agent framework calls          | [Documentation](https://www.comet.com/docs/opik/integrations/voltagent?utm_source=opik&utm_medium=github&utm_content=voltagent_link&utm_campaign=opik)                         |
| WatsonX               | Log traces for IBM watsonx LLM calls                    | [Documentation](https://www.comet.com/docs/opik/integrations/watsonx?utm_source=opik&utm_medium=github&utm_content=watsonx_link&utm_campaign=opik)                             |
| xAI Grok              | Log traces for xAI Grok LLM calls                       | [Documentation](https://www.comet.com/docs/opik/integrations/xai-grok?utm_source=opik&utm_medium=github&utm_content=xai_grok_link&utm_campaign=opik)                           |

> [!TIP]
> If the framework you are using is not listed above, feel free to [open an issue](https://github.com/comet-ml/opik/issues) or submit a PR with the integration.

If you are not using any of the frameworks above, you can also use the `track` function decorator to [log traces](https://www.comet.com/docs/opik/tracing/advanced/log_traces/?from=llm&utm_source=opik&utm_medium=github&utm_content=traces_link&utm_campaign=opik):

```python
import opik

opik.configure(use_local=True) # Run locally

@opik.track
def my_llm_function(user_question: str) -> str:
    # Your LLM code here

    return "Hello"
```

> [!TIP]
> The track decorator can be used in conjunction with any of our integrations and can also be used to track nested function calls.

<a id="-llm-as-a-judge-metrics"></a>
### 🧑‍⚖️ LLM as a Judge metrics

The Python Opik SDK includes a number of LLM as a judge metrics to help you evaluate your LLM application. Learn more about it in the [metrics documentation](https://www.comet.com/docs/opik/evaluation/metrics/overview/?from=llm&utm_source=opik&utm_medium=github&utm_content=metrics_2_link&utm_campaign=opik).

To use them, simply import the relevant metric and use the `score` function:

```python
from opik.evaluation.metrics import Hallucination

metric = Hallucination()
score = metric.score(
    input="What is the capital of France?",
    output="Paris",
    context=["France is a country in Europe."]
)
print(score)
```

Opik also includes a number of pre-built heuristic metrics as well as the ability to create your own. Learn more about it in the [metrics documentation](https://www.comet.com/docs/opik/evaluation/metrics/overview?from=llm&utm_source=opik&utm_medium=github&utm_content=metrics_3_link&utm_campaign=opik).

<a id="-evaluating-your-llm-application"></a>
### 🔍 Evaluating your LLM Applications

Opik allows you to evaluate your LLM application during development through [Datasets](https://www.comet.com/docs/opik/evaluation/advanced/manage_datasets/?from=llm&utm_source=opik&utm_medium=github&utm_content=datasets_2_link&utm_campaign=opik) and [Experiments](https://www.comet.com/docs/opik/evaluation/advanced/evaluate_your_llm/?from=llm&utm_source=opik&utm_medium=github&utm_content=experiments_link&utm_campaign=opik). The Opik Dashboard offers enhanced charts for experiments and better handling of large traces. You can also run evaluations as part of your CI/CD pipeline using our [PyTest integration](https://www.comet.com/docs/opik/evaluation/overview/?from=llm&utm_source=opik&utm_medium=github&utm_content=pytest_2_link&utm_campaign=opik).

<a id="-star-us-on-github"></a>
## ⭐ Star Us on GitHub

If you find Opik useful, please consider giving us a star! Your support helps us grow our community and continue improving the product.

<a href="https://github.com/comet-ml/opik">
  <picture>
    <source media="(prefers-color-scheme: dark)" srcset="https://cdn.comet.com/opik/star-history/star-history-dark.svg" />
    <img alt="Star History Chart" src="https://cdn.comet.com/opik/star-history/star-history-light.svg" />
  </picture>
</a>

<a id="-contributing"></a>
## 🤝 Contributing

There are many ways to contribute to Opik:

- Submit [bug reports](https://github.com/comet-ml/opik/issues) and [feature requests](https://github.com/comet-ml/opik/issues)
- Review the documentation and submit [Pull Requests](https://github.com/comet-ml/opik/pulls) to improve it
- Speaking or writing about Opik and [letting us know](https://chat.comet.com)
- Upvoting [popular feature requests](https://github.com/comet-ml/opik/issues?q=is%3Aissue+is%3Aopen+label%3A%22enhancement%22) to show your support

To learn more about how to contribute to Opik, please see our [contributing guidelines](CONTRIBUTING.md).
历史前置条件说明(补充参考)

Python 环境与 pip/uv(安装 Python SDK);自托管需 Docker Compose 或 Kubernetes/Helm 及数据库、缓存等基础设施;云端需 Comet 账号、API Key 与工作区;评测与 LLM-as-a-Judge 需自备模型或 API Key,费用与模型范围待核验;MCP 接入需 uv 及兼容客户端(Claude Code、Cursor、VS Code 等),客户端具体配置待核验。

项目来源与清单版权许可

https://github.com/comet-ml/opik

整理来源:https://github.com/slavakurilyak/awesome-ai-agents

清单版权与许可:

MIT License

Copyright (c) 2024 Slava Kurilyak

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.