SDK 初始化必须放在任何 LLM 模块导入之前;云端使用需先注册并在项目内生成 API key;自托管需同时启动 Postgres 与 Clickhouse,默认访问 http://localhost:3000。
langtrace
Scale3-LabsAGPL-3.0更新放缓基于 OpenTelemetry 的 LLM 应用全链路可观测性工具,提供实时追踪、评估和指标,支持主流大模型、框架与向量数据库,可用 TypeScript 和 Python 接入。
Langtrace 🔍 is an open-source, Open Telemetry based end-to-end observability tool for LLM applications, providing real-time tracing, evaluations and metrics for popular LLMs, LLM frameworks, vectorDBs and more.. Integrate using Typescript, Python. 🚀💻📊
pip install langtrace-python-sdk
from langtrace_python_sdk import langtrace
langtrace.init(api_key='<your_api_key>')README 未说明显存或 GPU 要求;自托管需 Docker 与 Docker Compose,运行 Next.js 应用、Postgres 和 Clickhouse 三个服务。
基于 OpenTelemetry 的开源 LLM 应用可观测性工具,实时追踪调用、评估与指标
基于 OpenTelemetry 的 LLM 应用全链路可观测性工具,提供实时追踪、评估和指标,支持主流大模型、框架与向量数据库,可用 TypeScript 和 Python 接入。
核心能力
- 基于 OTEL 标准生成并采集链路追踪数据
- 实时监控 LLM API 调用与向量库操作
- 分析延迟、成本与用量等性能指标
- 提供追踪调试工具定位 LLM 工作流问题
- 支持自托管部署,数据不出自有服务器
容易踩的坑
- 4.0.11最新正式版2025-04-17 · 2025-04-17 23:33 UTC
What's Changed
- Added support for displaying Cleanlab trustworthiness score on the traces tab
- Cleanlab span shows additional metadata such as the explanation logs on the span attributes
- 4.0.102025-04-17 · 2025-04-17 14:28 UTC
查看更新说明
What's Changed
- Fixed the setup instructions for the typescript sdk by @kanlanc
- fix selfhosting missing team issue + add proper timeout to clickhouse by @alizenhom
New Contributors
- @kanlanc made their first contribution
- 4.0.92025-04-15 · 2025-04-15 12:53 UTC
查看更新说明
What's Changed
- Bugfixes and query performance improvement
- 4.0.82025-04-14 · 2025-04-14 16:22 UTC
查看更新说明
What's Changed
- add flexibility for get project endpoint by @alizenhom in https://github.com/Scale3-Labs/langtrace/pull/421
Full Changelog: https://github.com/Scale3-Labs/langtrace/compare/4.0.7...4.0.8
- 4.0.72025-04-10 · 2025-04-10 16:07 UTC
查看更新说明
What's Changed
- adjust gemini pricings by @alizenhom in https://github.com/Scale3-Labs/langtrace/pull/418
- Ali/sync dev main by @alizenhom in https://github.com/Scale3-Labs/langtrace/pull/419
Full Changelog: https://github.com/Scale3-Labs/langtrace/compare/4.0.6...4.0.7
用户点评
登录用户的真实使用记录,可按版本和硬件筛选还没有人点评。第一个说出真实体验的人最有价值。
📚 Table of Contents
- ✨ Features
- 🚀 Quick Start
- 🔗 Integrations
- 🌐 Getting Started
- 🏠 Self Hosting
- 📐 Architecture
- 🤝 Contributing
- 🔒 Security
- ❓ FAQ
- 👥 Contributors
- 📜 License
Langtrace is an open source observability software which lets you capture, debug and analyze traces and metrics from all your applications that leverages LLM APIs, Vector Databases and LLM based Frameworks.

✨ Features
- 📊 Open Telemetry Support: Built on OTEL standards for comprehensive tracing
- 🔄 Real-time Monitoring: Track LLM API calls, vector operations, and framework usage
- 🎯 Performance Insights: Analyze latency, costs, and usage patterns
- 🔍 Debug Tools: Trace and debug your LLM application workflows
- 📈 Analytics: Get detailed metrics and visualizations
- 🏠 Self-hosting Option: Deploy on your own infrastructure
🚀 Quick Start
# For TypeScript/JavaScript
npm i @langtrase/typescript-sdk
# For Python
pip install langtrace-python-sdk
Initialize in your code:
// TypeScript
import * as Langtrace from '@langtrase/typescript-sdk'
Langtrace.init({ api_key: '<your_api_key>' }) // Get your API key at langtrace.ai
# Python
from langtrace_python_sdk import langtrace
langtrace.init(api_key='<your_api_key>') # Get your API key at langtrace.ai
For detailed setup instructions, see Getting Started.
📊 Open Telemetry Support
The traces generated by Langtrace adhere to Open Telemetry Standards(OTEL). We are developing semantic conventions for the traces generated by this project. You can checkout the current definitions in this repository. Note: This is an ongoing development and we encourage you to get involved and welcome your feedback.
📦 SDK Repositories
🚀 Getting Started
Langtrace Cloud ☁️
To use the managed SaaS version of Langtrace, follow the steps below:
- Sign up by going to this link.
- Create a new Project after signing up. Projects are containers for storing traces and metrics generated by your application. If you have only one application, creating 1 project will do.
- Generate an API key by going inside the project.
- In your application, install the Langtrace SDK and initialize it with the API key you generated in the step 3.
- The code for installing and setting up the SDK is shown below:
If your application is built using typescript/javascript
npm i @langtrase/typescript-sdk
import * as Langtrace from '@langtrase/typescript-sdk' // Must precede any llm module imports
Langtrace.init({ api_key: <your_api_key> })
OR
import * as Langtrace from "@langtrase/typescript-sdk"; // Must precede any llm module imports
LangTrace.init(); // LANGTRACE_API_KEY as an ENVIRONMENT variable
If your application is built using python
pip install langtrace-python-sdk
from langtrace_python_sdk import langtrace
langtrace.init(api_key=<your_api_key>)
OR
from langtrace_python_sdk import langtrace
langtrace.init() # LANGTRACE_API_KEY as an ENVIRONMENT variable
🏠 Langtrace self hosted
To run the Langtrace locally, you have to run three services:
- Next.js app
- Postgres database
- Clickhouse database
[!IMPORTANT] Checkout our documentation for various deployment options and configurations.
Requirements:
- Docker
- Docker Compose
The .env file
Feel free to modify the .env file to suit your needs.
Starting the servers
docker compose up
The application will be available at http://localhost:3000.
Take down the setup
To delete containers and volumes
docker compose down -v
-v flag is used to delete volumes
Telemetry
Langtrace does NOT collect any Telemetry if you are self hosting the OSS client. None of your data leaves your servers.
🔗 Supported Integrations
Langtrace automatically captures traces from the following vendors and frameworks:
LLM Providers
| Provider | TypeScript SDK | Python SDK |
|---|---|---|
| OpenAI | ✅ | ✅ |
| Anthropic | ✅ | ✅ |
| Azure OpenAI | ✅ | ✅ |
| Cohere | ✅ | ✅ |
| DeepSeek | ✅ | ✅ |
| xAI | ✅ | ✅ |
| Groq | ✅ | ✅ |
| Perplexity | ✅ | ✅ |
| Gemini | ✅ | ✅ |
| AWS Bedrock | ✅ | ✅ |
| Mistral | ❌ | ✅ |
LLM Frameworks
| Framework | TypeScript SDK | Python SDK |
|---|---|---|
| Langchain | ❌ | ✅ |
| LlamaIndex | ✅ | ✅ |
| Langgraph | ❌ | ✅ |
| LiteLLM | ❌ | ✅ |
| DSPy | ❌ | ✅ |
| CrewAI | ❌ | ✅ |
| Ollama | ❌ | ✅ |
| VertexAI | ✅ | ✅ |
| Vercel AI | ✅ | ❌ |
| GuardrailsAI | ❌ | ✅ |
| Arch | ❌ | ✅ |
| Graphlit | ❌ | ✅ |
| Agno | ❌ | ✅ |
| Phidata | ❌ | ✅ |
| Cleanlab | ❌ | ✅ |
Vector Databases
| Database | TypeScript SDK | Python SDK |
|---|---|---|
| Pinecone | ✅ | ✅ |
| ChromaDB | ✅ | ✅ |
| QDrant | ✅ | ✅ |
| Weaviate | ✅ | ✅ |
| PGVector | ✅ | ✅ (SQLAlchemy) |
| MongoDB | ❌ | ✅ |
| Milvus | ❌ | ✅ |
📐 Langtrace System Architecture
💡 Feature Requests and Issues
- To request for features, head over here to start a discussion.
- To raise an issue, head over here and create an issue.
🤝 Contributions
We welcome contributions to this project. To get started, fork this repository and start developing. To get involved, join our Slack workspace.
🌟 Langtrace Star History
🔒Security
To report security vulnerabilities, email us at [email protected]. You can read more on security here.
📜 License
- Langtrace application(this repository) is licensed under the AGPL 3.0 License. You can read about this license here.
- Langtrace SDKs are licensed under the Apache 2.0 License. You can read about this license here.
👥 Contributors
❓Frequently Asked Questions
1. Can I self host and run Langtrace in my own cloud? Yes, you can absolutely do that. Follow the self hosting setup instructions in our documentation.
2. What is the pricing for Langtrace cloud? Currently, we are not charging anything for Langtrace cloud and we are primarily looking for feedback so we can continue to improve the project. We will inform our users when we decide to monetize it.
3. What is the tech stack of Langtrace? Langtrace uses NextJS for the frontend and APIs. It uses PostgresDB as a metadata store and Clickhouse DB for storing spans, metrics, logs and traces.
4. Can I contribute to this project? Absolutely! We love developers and welcome contributions. Get involved early by joining our Discord Community.
5. What skillset is required to contribute to this project? Programming Languages: Typescript and Python. Framework knowledge: NextJS. Database: Postgres and Prisma ORM. Nice to haves: Opentelemetry instrumentation framework, experience with distributed tracing.