openlit
Open source platform for AI Engineering: OpenTelemetry-native LLM Observability, GPU Monitoring, Guardrails, Evaluations, Prompt Management, Vault, Playground. 🚀💻 Integrates with 50+ LLM Providers,
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Overview
OpenLIT 是一个开源的 AI 工程平台，专为生成式 AI 和大语言模型(LLM)开发而设计。该平台基于 OpenTelemetry 标准，提供原生的可观测性能力，支持 LLM、向量数据库和 GPU 的全栈监控。通过一行代码即可启用完整的监控功能，帮助开发者从测试环境平滑过渡到生产环境。平台集成了 50+ LLM 提供商，包含分析仪表板、提示词管理、API 密钥保管库、实验场地等功能。OpenLIT 遵循并维护 OpenTelemetry 社区的语义约定，提供厂商中立的 SDK（支持 Python、TypeScript、Go），内置 11 种评估类型，支持护栏、评估和规则引擎等高级功能，为 AI 应用的开发、监控和优化提供一站式解决方案。
Deep Analysis
Key Differentiator
Most comprehensive open-source AI engineering platform — combines observability, 11 evaluation types, rule engine, prompt hub, secret vault, playground, and fleet management in one tool
⚡ Capabilities
- • OpenTelemetry-native LLM observability
- • 11 built-in LLM-as-judge evaluation types
- • Rule engine with AND/OR logic for trace matching
- • Prompt management and versioning (Prompt Hub)
- • API key and secrets management (Vault)
- • LLM playground (OpenGround)
- • Fleet management via OpAMP protocol
- • GPU monitoring
🔗 Integrations
OpenAIAnthropicCohereMistralGroqLangChainLlamaIndexCrewAIHaystackChromaPineconeQdrantClickHouse
✓ Best For
- ✓ Teams wanting all-in-one LLM platform (observability + eval + prompts + secrets)
- ✓ Organizations needing self-hosted AI engineering platform
- ✓ Multi-language teams (Python/TS/Go SDK support)
✗ Not Ideal For
- ✗ Teams only needing simple logging
- ✗ Projects without infrastructure for self-hosting ClickHouse
Languages
PythonTypeScriptGo
Deployment
Docker ComposeKubernetes (Helm)pip/npm install SDK
Pricing Detail
Free: Fully open-source, self-hosted
Paid: N/A
⚠ Known Limitations
- ⚠ Self-hosted requires ClickHouse and OTel Collector
- ⚠ Newer project — smaller community than alternatives
- ⚠ Evaluation types focused on text (limited multimodal)
- ⚠ Fleet management requires OpAMP setup
Pros
- + OpenTelemetry 原生支持，厂商中立，可与现有可观测性工具无缝集成
- + 一行代码集成，提供从 LLM 到 GPU 的全栈监控能力
- + 功能丰富的一体化平台，包含监控、评估、提示词管理、实验场地等完整工具链
Cons
- - 作为综合性平台，对于简单用例可能过于复杂
- - 开源项目需要自行部署和维护基础设施
Use Cases
- • LLM 应用的性能监控和成本跟踪
- • 多 LLM 提供商的实验和对比测试
- • AI 开发工作流的统一管理和版本控制
Getting Started
安装对应语言的 SDK（pip install openlit 或 npm install openlit），在代码中添加一行初始化代码启用监控，访问仪表板查看应用性能指标和分析数据