AI Skill Hub 强烈推荐:opik Prompt模板 是一款优质的Prompt模板。在 GitHub 上收获超过 19.3k 颗 Star,AI 综合评分 8.5 分,在同类工具中表现稳健。如果你正在寻找可靠的Prompt模板解决方案,这是一个值得深入了解的选择。
opik Prompt模板 是经过精心设计和反复验证的专业 Prompt 模板集合。这些 Prompt 框架能够有效激活 Claude、ChatGPT 等大型语言模型的深层能力,让 AI 生成更准确、更有价值的输出结果。无需任何安装,直接复制模板内容到 AI 对话框即可使用。
opik Prompt模板 是经过精心设计和反复验证的专业 Prompt 模板集合。这些 Prompt 框架能够有效激活 Claude、ChatGPT 等大型语言模型的深层能力,让 AI 生成更准确、更有价值的输出结果。无需任何安装,直接复制模板内容到 AI 对话框即可使用。
# Prompt 无需安装,直接复制使用 # 支持:Claude / ChatGPT / Gemini / 通义千问 等主流模型 # 使用步骤 # 1. 复制 Prompt 模板内容 # 2. 粘贴到 AI 对话框 # 3. 替换 [占位符] 为实际内容 # 4. 发送后获取结构化输出 # 获取原始文件 git clone https://github.com/comet-ml/opik
# 粘贴到 Claude/ChatGPT 使用 # 示例 Prompt 结构: 你是一位 [角色],擅长 [领域]。 请根据以下要求完成任务: 任务背景:[描述背景] 具体要求:[详细说明] 输出格式:[期望格式] # 将 [] 内内容替换为实际需求
# opik 配置文件示例(config.yml) app: name: "opik" debug: false log_level: "INFO" # 运行时指定配置文件 opik --config config.yml # 或通过环境变量配置 export OPIK_API_KEY="your-key" export OPIK_OUTPUT_DIR="./output"
Opik is the open-source LLM observability and evaluation platform for AI agent tracing, LLM evaluation, prompt management, and production monitoring. Built by Comet. Apache-2.0 licensed, free to self-host the full platform, with 20,000+ GitHub stars.
</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>
<br>
<a id="-what-is-opik"></a>
Get your Opik server running in minutes. Choose the option that best suits your needs:
./opik.sh --build
pip install opik
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 for more configuration options.
You are now ready to start logging traces using the Python SDK.
<a id="-logging-traces-with-integrations"></a>
Install the Python SDK and configure it:
pip install opik
opik configure
Wrap any function with the @track decorator to start logging traces:
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 for the TypeScript SDK and other setup options.
<br>
<a id="-how-opik-compares"></a>
To get started with the Python SDK:
Install the package:
```bash
Access Opik instantly without any setup. Ideal for quick starts and hassle-free maintenance.
Deploy Opik in your own environment. Choose between Docker for local setups or Kubernetes for scalability.
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
./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 on your browser! For detailed instructions, see the Local Deployment Guide.
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.
<a id="-opik-client-sdk"></a>
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 support: any language with an OpenTelemetry SDK — including Java, Ruby, and .NET — can send traces to Opik. For detailed API and SDK references, see the Opik Client Reference Documentation.
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) |
| 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 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:
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>
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>
#### 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>
19.3k星高热度开源项目,功能完整覆盖LLM应用全生命周期,社区活跃维护好,是LLM工程化必备工具。
AI Skill Hub 为第三方内容聚合平台,本页面信息基于公开数据整理,不对工具功能和质量作任何法律背书。
建议在沙箱或测试环境中充分验证后,再部署至生产环境,并做好必要的安全评估。
✅ Apache 2.0 — 宽松开源协议,可商用,需保留版权声明和 NOTICE 文件,含专利授权条款。
总体来看,opik Prompt模板 是一款质量优秀的Prompt模板,在同类工具中具备一定竞争力。AI Skill Hub 将持续追踪其更新动态,建议收藏备用,结合自身场景选择合适时机引入使用。
| 原始名称 | opik |
| 原始描述 | 开源Prompt模板:Debug, evaluate, and monitor your LLM applications, RAG systems, and agentic wor。⭐19.3k · Python |
| Topics | LLM监控Prompt管理评估框架RAG系统Agent工具 |
| GitHub | https://github.com/comet-ml/opik |
| License | Apache-2.0 |
| 语言 | Python |
收录时间:2026-05-13 · 更新时间:2026-05-16 · License:Apache-2.0 · AI Skill Hub 不对第三方内容的准确性作法律背书。
选择 Agent 类型,复制安装指令后粘贴到对应客户端